Applied Science and Precision Engineering Innovation 9783038263289, 3038263281

Table of contents :
Applied Science and Precision Engineering Innovation
Preface, Welcome Address and Committees
Table of Contents
Chapter 1: Materials Engineering and Processing Technologies of Materials
Effect of Bi2O3 Addition on the Microstructure and Electrical Properties of Lead-Free (Na0.5K0.5)NbO3-Bi0.5(Na0.93K0.07)0.5TiO3 Ceramics
Effects of Grain Size and Lubricating Conditions on Micro Forward and Backward Hollow Extrusion of Brass
Effect on Vibroengineering of Material Deterioration in a Scale-Down Reinforced Concrete Containment Vessel Specimen
Preparation and Investigation of Co-Dispersed MWCNT Buckypaper for the Microwave Absorption
Direct Heating Billet within Die during Hot Forging Process
Using Soft Material as Die during Hot Forging
The Characterization of Alumina Reinforced with CNT by the Mechanical Alloying Method
Transparent Conductive Oxide GZO Thin Films by Sol-Gel Process
Nonlinear Evolution of the Travelling Waves in Roll Coating Flows of Thin Viscoelastic Polymer Falling Films
Photo-Electronic Properties of Titanium Dioxide Nano Thin Films
Step-Stress Accelerated Degradation Testing of NBR Sealing Ring
The Friction Characteristics and Microscopic Properties of Composite Electroplating Thin Films
Preparation and Characterization of Cubic and Rod-Shaped Indium Tin Oxide Powders Using the Hydrothermal Process
Effect of ZnO Seed Layer and TiO2 Coating Treatments on Aligned TiO2/ZnO Nanostructures for Dye-Sensitized Solar Cells
Tuning the Torsion Mechanical Properties of Carbon Nanotube by Feeding H2 Molecules
Atomic Layer Deposited Al2O3 Barrier Layers on Flexible PET Substrates
Study the Rheological Property of Gel Abrasives in Magnetic Abrasive Finishing
Experiment on Intermittent Gas Jet Assisted Modulated Fiber Laser Drilling
Temperature Effect on Mechanical Properties of Aluminum Film
Artificial Photosynthesis of Formic Acid Using Iron Doped TiO2
Graded Silicon Nanostructure Arrays for Tailoring Antireflection Performances
Thermoelectric Properties of Transition Metal Deposited MWCNT Buckypaper
Morphology and Microstructure of Aggregates and Gelation Behaviour of Poly(3-hexylthiophene) in Xylene Solution
Small Scale Effect on Nonlinear Vibration of Fluid-Loaded Double-Walled Carbon Nanotubes with Uncertainty
Determination of the Optimal Locations for Injection Molding Gates with Higher Order Response Surface Approximations
Chapter 2: Optoelectronics and Optical Systems
Simulation of Broadband Transmission Photonic Crystal Waveguide Crossing with Linear Taper
A Study on Measurement of Photoplethysmograph Using a Smartphone Camera
A Simulation Study of the Treatment Effects for the 1064 nm Nd:YAG Laser under Various Fluence and Pulse Durations
Assessment of the UVB Transmittance Measurement Uncertainty in Conformity with ISO/IEC 17025
Compound Optical Film Using Gray Scale Mask Embedded with Micro-Voids
Design of Secondary Optical Element for a Two-Reflector Solar Concentrator
Integrated Multi-Object Taguchi Method with Optical Design for Contact Lenses
Improvement on Zhang's Camera Calibration
Video Matching by One-Dimensional PSNR Profile
Chapter 3: Machine Parts and Mechanisms, Design and Manufacturing
An Investigation into Optimized Ti-6Al-4V Titanium Alloy Equal Channel Angular Extrusion Process
Design of a Magnetic Gear Set with Low Torque Ripple
Heat Transfer of Oscillating Fluid through Finned Heat Sink with Top Bypass Clearance
Reducing Cogging Force of a Permanent Magnet Transverse Flux Linear Synchronous Motor
Design and Optimization on Active Engine Mounting Systems for Vibration Isolation
Harmonic Analysis and Filter Design for the Light Rail Transit Systems
Modeling of a Shape Memory Alloy Beam and its Stochastic Chaos
Parametric Study of a Micromixer with Convergent-Divergent Sinusoidal Walls
Design and Manufacturing of Drug Eluting Depot Stents with Micro-Sized Drug Reservoirs
Finite-Element Analysis of the Magnetic Field in a Magnetic Gear Mechanism
Kinematic Analysis of an 8-Speed Bicycle Transmission Hub
Ground Vibration Characteristics for High-Speed Trains on Embankments
Dynamic Response of a Viscoelastic Damping Isolator under High Cyclic Loading
Thermal Performances in Ribbed Rectangular Convergent and Divergent Channels
Finite Element Analysis of Bridge-Vehicle System with Randomness
Design of Geneva Mechanism with Curved Slots
The Study and Fabrication of Electron Field Emission Module for Next-Generation Multi-Beams Lithography Applications
An Adaptive Parameter Tuning Method with On-Machine Weight Identification Function for CNC Machine Tools
Heat Transfer of Oscillating-Move Pin-Fin Heat Sinks with Circular Impinging Jets
Performance Improvement of a Hidden Ceiling Fan
The Design of Heat Pipe Heat Exchanger for CO2 EGS
Optimization of Circular Diamond Saw Blades with Annular Slots
Effects of Metal Hydride Absorption in Reactor with Annular Finned Tube Heat Exchanger
Magnetic Assisted Laser Percussion Drilling
An Electric Wheelchair with Function of Climbing up and down a Step
The Meshing Efficiency Analysis of Coupled Planetary Gear Reducer
A Study on the Optimization Design of BOP Gantry Crane by ANSYS
Stress Distribution Analysis of Different Types of Blade for a Fermentation System
Optimal Design of the Single-Mode Piezoelectric Actuator
The Design of Multiple Function Acoustic Horns for Ultrasonic Welding of Plastic
Five-Axis NC Program Conversion for Inclined Plane Machining
The Impact of Bicycle Suspension on Pedaling Forces
Development of a Virtual Milling Machining Center Simulation System with Switchable Modular Components
Hysteretic Nonlinear Characteristics and Stochastic Bifurcation of Cantilevered Piezoelectric Energy Harvester
Optimal Yield Rate in ACF Cutting Process of TFT-LCD Module Using Orthogonal Particle Swarm Optimization
An Optimal Design for New Electromagnetic Valve in Camless Engines
The Dynamic Analysis and Simulation of Electric Scooter
Study on Bevel Gear Worm Forging by Finite Element Analysis
The Characteristic Analysis of Interrupted Flow Pulsation on Ultrafiltration System
Pressure Distribution in the Air Film and the Porous Conveyor Air Bearing
Dynamics of a Quadruped Walking Machine
Magnetostatic Field Analysis of Disk-Type Permanent-Magnet Motors
Using ADAMS Application on Mechanism Simulation of New Multiaxis Machines
An Integrated CFD and Experimental Study of the In-Line Fan
The Characteristic Comparison of the Accelerometer and the Gyroscope Using the Pendulum Model of Body Sway
Heat Transfer of a Double Layer Microchannel Heat Sink
The Analysis of Magnetorheological Brake Structure with Multiple Poles
Seismic Response for a One-Third Scale-Down Vertical Cylindrical Cask Specimen Using Cyclic Loading Testing
Microstructure Design of Surface Permanent Magnet and Tooth Surface Stator in Brushless DC Motor with Low Rare Earth Material
Stability and Dynamic Analysis of the Electrostatic MEMS Actuators
A Compact Planar Inverted-F Antenna for Octa-Band Operations of Smart Handsets
Chapter 4: Medical Machinery and Technologies, Innovative Developments
Application of Artificial Neural Networks for Diagnosing Acute Appendicitis
Study on Biohydrogen Production of Dark Fermentation with the Stimulation of Ultrasonic
Implementation and Validation of ECG-Derived Respiration with QRS Characteristics
A Newly Developed Polyurethane Prosthetic Heart Valve
The Measurement of Anesthesia Depth Using Biomedical Signal during General Anesthesia
The Effects of Application Site and Time of Vibration Stimulation: Changes in Gait Pattern and Muscle Activity
Different Frequency Bands of Electromagnetic Wave on Age-Related Developmental Changes
L2-EMD Filter Design for Photoplethysmography Signal
Supervised Neural Networks for the Automatic Classification of Leukocytes in Blood Microscope Images
Analysis of Non-Fourier Thermal Behavior in Layered Tissue with Pulse Train Heating
Chapter 5: Electronics, Electrical Engineering and Power Electronics
Contour Data Acquisition System for Electric Vehicle Distance Estimation Method
FPGA Implementation of a High-Speed Two Dimensional Discrete Wavelet Transform
Low Phase Noise Voltage Controlled Oscillator Using Cascode and Current-Reuse Techniques for Radio Frequency Circuits
Time-Frequency Bands of Electromagnetic Wave from ERPCOH on Developmental Changes
In-Plane Electromagnetic Generator Fabricated on Printed Circuit Board Technology
Wide Area Input Stabilizer for Damping of Power System Inter-Area Oscillation
Development of Serial-Connected High Step-Up DC-DC Converter with Single Switch
Chapter 6: Energy and Power Engineering
Application of TRACE and FRAPTRAN in the Spent Fuel Pool of Chinshan Nuclear Power Plant
LAPUR6 Stability Analysis on Power/Flow Map of Lungmen ABWR
Potential of Solar Farm Development at UTM Campus for Generating Green Energy
Impact of a Large Scale PV Generation System on the Distribution System
Development of Intelligent Solar Panel Cleaning System with Fuzzy Logic Theorem
Elman Neural Network for Dynamic Control of Wind Power Systems
Design and Analysis of a Novel Hybrid Solar/Gas Dish Stirling System (HS/GDSS)
An Active Islanding Detection Method for Grid-Connected Renewable Energy Generation System
Comparison of Three Short Term Photovoltaic System Power Generation Forecasting Methods
Optimal Penetration of Photovoltaic Systems in Distribution Networks
HCPV Module Temperature Prediction: A Case Study Based on Measurements at NPUST
Effect of Geometry on Energy Absorption of Reduction Tubes Using a Die - A Numerical Study
Chapter 7: Automation and Control
An Integrated Realization of Motion Control and Motor Drives with FPGA
Direct Adaptive CMAC PI Control for Uncertain Nonlinear Systems with Measurable Output Feedback
Whole-Body Human-to-Humanoid Motion Imitation
The Development of a Hybrid Antilock Braking System Using Magnetorheological Brake
Optimization of the Neural Muscular Drive and Respiratory Signals under Dead Space Loading and CO2 Inhalation
Development of an Automatic Optical Inspection System and its Application to Defect Examination
Design of Flight Control System Bus Controller of UAV Based on Double CAN-Bus
A Wireless Sensor Network Deployment Planning Tool to Support Building Automation
Cryptanalysis and Improvement of Secure Key Distribution for the Smart Grid
Study and Design of Smart Embedded Home System Based on Wireless Electric Power Measurement Monitoring System
Home Security Service and Condition Control
Chapter 8: Sensors, Mechatronics and Robotics
Hysteretic Nonlinear Characteristics of Giant Magnetostrictive Sensors
Safety Assessments for Wearable Robot Suits
Calibration of RGB-D Sensors for Robot SLAM
Experimental Evaluation of a Small-Displacement Sensing System Based on the Surface Plasmon Resonance Technology in Heterodyne Interferometry
A Study on FBG Vehicle Loading Sensing System
Structure Design of the Biaxial Piezoelectric Actuated Stage Using a Novel Disk Piezoelectric Actuator
Stepping Experiment and Characteristics Analysis of a Novel Biaxial Piezoelectric Actuated Stage
High Performance CO Sensors Utilizing Sprayed Distributed Toluene-Based Gold Nanoparticles
Development of a Laser Measuring Method for Small Displacement of a Thin Plastic String
The Design of Multi-Parameter Bio-Signal Sensor for Applying a Smartphone m-Health Service
Interpretation of the Oscillating Signals of the Smart NOx Sensors Used in Urea Selective Catalyst Reduction Systems via Spectral Analysis
Design of Photo Diode Sensors for Measuring Solar Light Orientation
Singularity Avoidance for a Redundant Robot Using Fuzzy Motion Planning
An Output Based Adaptive Iterative Learning Control with Particle Swarm Optimization for Robotic Systems
Distributed Control Intelligent Robotic Gripper
A Laboratory-Based Smart Grid Sensor Network Testbed
Discoid and Asymmetrical Micro-Satellite Propulsion Mode Attitude Control with Great Mass Change and without Angular Rate Sensor
A Fuzzy-Based Management for Power-Aware Wireless Sensor Network
A Centre Clustering Mechanism of Wireless Sensor Network
Motion Control of a Robot Arm
Enhance A* Searching Algorithm Applying in Multiple Robot System
A Cyclostationarity-Based Spectrum Sensing Scheme for Dynamic Traffic Circumstances
Distributed Tree Routing Scheme for Large-Scale Wireless Sensor Networks
A N-Hop Concentric Clustering Algorithm with Sub-Clusters in a Wireless Sensor Network
Chapter 9: Methods and Algorithms for Processing and Analysis of Data
Development of Causal Model of Four Parameters upon Statistical and Mathematical Analysis and Management
Using Maple to Study the Partial Differential Problems
Efficient Computational Workload Distribution on Heterogeneous GPUs
Fingerprint Identification Based on Mopso in SVM
Accelerometry-Based Motion Pattern Analysis for Physical Activity Recognition and Activity Level Assessment
Application of Maple on Evaluation of Definite Integrals
A Study on the Multiple Improper Integral Problems with Maple
Facial Expression Generated Automatically Using Triangular Segmentation
Refinement of Depth Estimation Method via Energy Minimization
Modeling and Simulation of the Optical Properties of Low-Speed Target in Near Space
Application of Maple on the Integral Problems
Application of Maple on Solving the Differential Problem of Rational Functions
An Artificial Evolutionary Approach for Solving the Nonlinear Constrained Optimization Problems
A Novel Unambiguous Correlation Function with a High and Sharp Main-Peak for BOC Signal Tracking
Image Contrast Enhancement by Hybrid 3SAIHT and CLAHE Algorithm
A Low Complexity Integer Frequency Offset Estimation Scheme Based on Coherence Phase Bandwidth for OFDM Systems
Face Recognition by Geometrical Feature-Point Bilateral Matching
Robust Observer-Based Output Feedback Control for Time-Varying Systems
Chapter 10: Computer and Information Technologies
Volumetric Model Body Outline Computation for an Object Tracking in a Video Stream
Efficient Scheduling for Real-Time Pinwheel Tasks on DVS Processors
A Method of Handling Missing Data in the Context of Learning Bayesian Network Structure
A Automatic Vehicle License Plate Location Based on Sobel Edge Method
Detecting Phishing Sites Using URLs Collected from Emails
Serum System: An Automatic Curing System for Worms and Buffer Overflow-Based Botnets
Impacts of Langauge Learning Based on Computer-Assisted Language Learning Instruction
A Novel Fuel Cell System Design by Using Ziegler-Nichols-Based Intelligent Fuzzy Controller
A Gesture Recognition Based on Accelerometer and Hidden Markov Model for Human Computer Communication
Optical Music Recognition for Numbered Music Notation with Multimodal Reconstruction
Color 3D Image Encryption Technique by Combined Use of Computational Integral Imaging Joint Image Scrambling Technique
A Cloud-Based Test Architecture for IPv6 SNMPv3 Agent
3D Integral Imaging Encryption Using a Depth-Converted Elemental Image Array
On the Security of the Discrete Logarithm Based Remote Authentication Scheme Using Smart Cards
A Secure Hybrid P2P Network Mobile Communication Device Design
An Enhanced Vehicular Information Dissemination Based on Back-Off Time Mechanism
Threshold-Based Privacy-Preserving Key Management Scheme for Vehicle-to-Grid Networks
Robust Exponential Stability for Uncertain Discrete-Time Switched Systems with Interval Time-Varying Delay via a Switching Signal
The Hybrid Differential Evolution with Dynamic Scaling Mutation and Wrapper Local Search for Optimization Problems
Implementation and Experiments of TDOA Monitoring Techniques for Broadcasting Interferences
Development of an Equipment Failure Identification Expert System with Multiple Reasoning Approaches
Classification of Chinese Popular Songs Using a Fusion Scheme of GMM Model Estimate and Formant Feature Analysis
Low Phase Noise and Low Power Voltage-Controlled-Oscillator Using Current-Reuse Techniques for Wireless Communication Circuits
Design of 3.1-10.6GHz CMOS LNA Based on Input Matching Technique of Common-Gate Topology
A Source Routing Protocol for Bluetooth-Based Sensor Networks
Development of Software-as-a-Service Cloud Computing Architecture for Manufacturing Management Systems Based on Virtual COM Port Driver Technology
Performance Analysis of Hybrid Fusion in Cognitive Radio Networks
Design of a Smart Green Energy Management System Based on DMX512 Protocol
An Innovative but Low-Cost Mechanism for E-Payment, E-Ticketing, and E-Identity Document: A Case Study of Multiple Perspectives in Innovation Management
Chapter 11: Environmental Sciences and Engineering, GIS
Frequency Analysis of the Motor Control Centers in a Nuclear Power Plant Using Testing and Simulating Methods
Seismic Testing and Verification for 30 Tons Scaled-Down Model of Reinforced Concrete Containment Vessel
Application of GIS on Rapid Evaluation for Potential Portal Areas of Tunnels
Preliminary Volcanic Seismic Hazard Analysis for Tatun Volcano Group in Northern Taiwan
Weibull Component Reliability Prediction with Masked Data
Life Cycle Carbon Dioxide Emission Assessment of Housing in Taiwan
Site Response Analysis for a Site with the Dipping Bedrock and Liquefiable Layers Using FLAC 3D
A Multi-Agent System for Multi-Level Based Environmental and Physiological Signal Monitoring and Analysis
Promoting Usage of Effective Rainfall in Pond Irrigation System
Chapter 12: Architecture, Civil and Industrial Engineering
Corrosion Risk of Stainless Steel Facilities in the Coastal Regions of Taiwan
Corrosion Risk of Welded Steel Frames in the Urban Areas of Taiwan
A Study on the Deterioration of External Wall Tiles on RC Buildings in Taiwan
The Interaction between Adjacent Structures with Different Foundation Levels under Earthquake Loading
Novel Pile-to-Pilecap Connection Under Lateral Load
Improvement of Accelerated Weathering Test through Physicochemical Analysis for Polymeric Materials in Building Construction
A Study on the Deterioration Condition and Renovation Work for High-Rise Reinforced Concrete Apartment in Japan - The Practice Project Kajima Corporation Minaminagasaki Dormitory
The Construction Protest Management Study with NIMBY Conflict
Experimental and Analytical Investigation of Lateral-Torsional Buckling of RC Beams with Geometric Imperfections
Centrifuge Modeling on Seismic Behavior of Pile in Liquefiable Soil Ground
Influence of Angle Thickness towards Stiffness and Strength Prediction for Cold-Formed Steel Top-Seat Flange Cleat Connection
Development of Physical-Parameter Identification Procedure for Energy-Dissipated Buildings with Symmetric Ductile Braces
Modal Identification of Structures from Seismic Response Data via Amplitude-Dependent Time Series Model
Model for Evaluating Uncertain Project Duration Considering Construction Interface Problems
Seismic Rehabilitation of Beam-Column Joints Using FRP Sheets and Buckling Restrained Braces
Structural Behavior of a Steel Grid Shear Wall Subjected to Combined Axial and Cyclic Lateral Loads
Enhancing Collapse Detection and Alarms in Bridge Management
A New Damage Detection Method for Aging Offshore Platform Using Two Measurements
Chapter 13: Related Topics
Item Relational Structure Theory Based on Liu’s Improved Nonparametric IRT Theory
An Extensive Evaluation Design Approach to Quality Function Deployment
A Framework of Fit Status of Organizational Innovation: Based on the Typology of Organizational Lag
Research on Human Resource Strategy under Customer Demand Using System Dynamics for the Thin Film Sputtering Target Material Industry
Using RSSI Simple Localization Method to Implement the Context-Aware and Social Recommendation System
Keywords Index
Authors Index

Citation preview

Applied Science and Precision Engineering Innovation

Edited by Chien-Hung Liu

Applied Science and Precision Engineering Innovation

Selected, peer reviewed papers from the International Applied Science and Precision Engineering Conference 2013, October 18-22, 2013, Nan Tou, Taiwan

Edited by

Chien-Hung Liu

Copyright  2014 Trans Tech Publications Ltd, Switzerland All rights reserved. No part of the contents of this publication may be reproduced or transmitted in any form or by any means without the written permission of the publisher. Trans Tech Publications Ltd Kreuzstrasse 10 CH-8635 Durnten-Zurich Switzerland http://www.ttp.net

Volumes 479-480 of Applied Mechanics and Materials ISSN print 1660-9336 ISSN cd 1660-9336 ISSN web 1662-7482

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Preface The Proceedings Applied Science and Precision Engineering Innovation includes 232 papers presented in the first International Applied Science and Precision Engineering Conference 2013 held in Sun Moon Lake, NanTou, Taiwan on October 18th – October 22th, 2013. The ASPEC2013 conference covers a wide range of fields in science and engineering innovation and aims to bring together engineering technology expertise. The professionals from the industry, academia and government to discourse on research and development, professional practice, business and management in the science and engineering fields are welcome to the ASPEC2013. This conference enables interdisciplinary collaboration between science and engineering technologists in the academic and industrial fields as well as networking internationally. During the conference, there should be substantial time for presentation and discussion. Attendees will find various activities useful in bringing together a diverse group of engineers and technologists from across disciplines for the generation of new ideas, collaboration potential and business opportunities. To meet the need of the growth of the technology, contributor from the world, especially for Asia, will be welcomed to provide new developments on this area. The objective of the conference is to facilitate close dialogues among experts on issues relating to research and technological development in advanced science and engineering innovation technology. Over two hundred of attendees all over the world from the industry, academia and government to discourse on research and development, professional practice, business and management in the science and engineering fields will present at the ASPEC2013 conference. All the submitted papers were reviewed by at least two of the members of the technical committee and the accessory review team. The papers accepted for publication have been considered to be sufficiently original and to contain new developed data or technologies that deserve to be published in the Proceedings. Authors from all over the world are included in the Proceedings, proving our international orientation. Two hundred and thirty two papers selected by the Editors for inclusion in this volume and the Editors would like to thank heartily to all members of the Technical and Organizing Committees for their efforts to organize the conference successfully, and to perform their duties as Chairman and reviewers. We would like to appreciate the authors for submitting their work to the conference and contributing to the quality of the conference Proceedings. We also acknowledge our profound gratitude to the reviewers for their time, efforts and expert comments in evaluating the papers, and the distinguished keynote speakers for accepting our invitation. Our gratitude to Taiwan Association of Engineering and Technology Innovation for their support in organizing ASPEC2013 Conference and publishing the Proceedings. Chien-Hung Liu & Editorial Board Taichung, Taiwan, R.O.C. October, 2013

Welcome Address Distinguished Guests, Ladies and Gentlemen: On behalf of the organizing committees, I would like to welcome all of you to Nantou, Taiwan for 2013 International Applied Science and Precision Engineering Conference. It is my great pleasure in declaring this conference open. The conference is organized by Taiwan Association of Engineering and Technology Innovation, Chiuan Yan Technology Co., Ltd, and National Chung Hsing University in the beautiful setting of Taichung. We would like to express our sincere appreciation for their supports to the conference. The theme of the conference is set as “Applied Science and Precision Engineering Innovation.” This is a great opportunity for the engineering and technology community to present their new research results, exchange ideas and become familiar with new trends and directions in the fields of Science and Engineering Innovation. In addition, it is also a unique opportunity for us to form an international collaboration framework for promoting engineering and technology innovation. We have with us today representatives from research funding organizations, universities, as well as other research agencies. I hope that this five-day conference － a platform for thought-leaders, academics and researchers to share their ideas and views on common engineering and technology innovation issues – will challenge all delegates, in particular the heads of institutions, to think more about the technology challenges and responses in engineering innovation which may in turn inspire new and practicable standards in the field. The conference has received 326 submitted papers, whereby 232 papers have been selected by the committees to be included within the ASPEC2013 proceeding. These papers on various topics are divided into 35 sessions and presented in several parallel sessions in the conference. To all members of the Technical and Organizing Committees, we would like to take this opportunity to thank all of them for their tremendous efforts to organize this conference successfully. At last, I would like to thank all of you for your participation. The program committee not only organizes keynote speeches and technical sessions, but also a special banquet to give the warm welcome to our guests. We look forward to having a successful conference, and we hope that all the attendees will have an enjoyable stay in Taiwan. Chien-Hung Liu Program Chairman of ASPEC2013

Committees Program Chairman: Chien-Hung Liu Te-Hua Fang Yu-Ying Chiu Hau-Wei Lee

Program Co-Chairman: Yu-Fen Chen Yi-Chang Wu Van-Tsai Liu Ming-Tsang Lee

Technical Committee Chairman: Wen-Hsiang Hsieh Young-Long Chen Yunn-Lin Hwang G.Y. Tzou H.T. Yau S.C. Tzeng Artde D.K.T. Lam Chang-Tzuoh Wu

Invited Session Chairman: Young-Long Chen Wei-Ting Lin Zong-Yu Chang Chia-Chin Chiang Cheng-Chi Wang Chia-Lung Kuo Heui-Yung Chang Yao-Tang Chang Chung-Chi Huang Sung Min Kim

International Scientific Committee: A. Gottscheber (Germany) A. Walton (UK) R. S. Beniwal (India) C. Warwick (UK) E. Manske (Germany) G. Jäger (Germany) G.Y. Tzou (Taiwan) J. Wood (UK) J. Carlos (Portugal)

J.S. Dai (UK) M. Woolley (UK) M. Bradley (UK) P.F. Savanna (USA) R.X. Du (HK) S.G. Hanson (Denmark) S.D. Prior (UK)

Table of Contents Preface, Welcome Address and Committees

Chapter 1: Materials Engineering and Processing Technologies of Materials Effect of Bi2O3 Addition on the Microstructure and Electrical Properties of Lead-Free (Na0.5K0.5)NbO3-Bi0.5(Na0.93K0.07)0.5TiO3 Ceramics C.H. Wang Effects of Grain Size and Lubricating Conditions on Micro Forward and Backward Hollow Extrusion of Brass C.C. Chang, C.H. Hsu and J.C. Lai Effect on Vibroengineering of Material Deterioration in a Scale-Down Reinforced Concrete Containment Vessel Specimen W.T. Lin, Y.C. Wu, T.L. Chu and A. Cheng Preparation and Investigation of Co-Dispersed MWCNT Buckypaper for the Microwave Absorption L. Saravanan, J.H. Liu, H.Y. Miao and L.C. Wang Direct Heating Billet within Die during Hot Forging Process F.S. Cheng and Y.S. Cheng Using Soft Material as Die during Hot Forging F.S. Cheng and Y.S. Chen The Characterization of Alumina Reinforced with CNT by the Mechanical Alloying Method G.N. Kim, G.T. Bae, J.S. Park, B.Y. Choi and S.C. Huh Transparent Conductive Oxide GZO Thin Films by Sol-Gel Process C.C. Wang and C.Y. Yen Nonlinear Evolution of the Travelling Waves in Roll Coating Flows of Thin Viscoelastic Polymer Falling Films P.J. Cheng, K.C. Liu and C.C. Wang Photo-Electronic Properties of Titanium Dioxide Nano Thin Films S.L. Tu, Y.H. Su, Y.H. Shen, D.T. Ray, Y.C. Wu and T.H. Chen Step-Stress Accelerated Degradation Testing of NBR Sealing Ring X.H. Wang, L.Z. Wang, X. Zhang and Q.X. Li The Friction Characteristics and Microscopic Properties of Composite Electroplating Thin Films S.H. Wang, C.C. Chiang, L. Tsai, W.C. Fang and J.L. Huang Preparation and Characterization of Cubic and Rod-Shaped Indium Tin Oxide Powders Using the Hydrothermal Process K.C. Hsu, J.D. Liao, Z.Z. Xie and Y.S. Fu Effect of ZnO Seed Layer and TiO2 Coating Treatments on Aligned TiO2/ZnO Nanostructures for Dye-Sensitized Solar Cells L.C. Chen, J.H. Chen, S.F. Tsai and G.W. Wang Tuning the Torsion Mechanical Properties of Carbon Nanotube by Feeding H2 Molecules B.H. Chen, Y.W. Chao and C.C. Wang Atomic Layer Deposited Al2O3 Barrier Layers on Flexible PET Substrates R.C. Chang, H.T. Hou, F.T. Tsai and P.S. Jhu Study the Rheological Property of Gel Abrasives in Magnetic Abrasive Finishing A.C. Wang, L. Tsai and Y.C. Lin Experiment on Intermittent Gas Jet Assisted Modulated Fiber Laser Drilling J.C. Hsu, C.Y. Liao, C.C. Ho, Y.J. Chang and C.L. Kuo Temperature Effect on Mechanical Properties of Aluminum Film S.C. Her and Y.H. Wang Artificial Photosynthesis of Formic Acid Using Iron Doped TiO2 A. Abidov and S.J. Kim

3 8 13 20 25 30 35 40 45 50 55 60 64 69 75 80 86 91 96 100

b

Applied Science and Precision Engineering Innovation

Graded Silicon Nanostructure Arrays for Tailoring Antireflection Performances C.C. Wang, C.Y. Chen and Y.C. Chou Thermoelectric Properties of Transition Metal Deposited MWCNT Buckypaper J.H. Liu, L. Saravanan, H.Y. Miao and L.C. Wang Morphology and Microstructure of Aggregates and Gelation Behaviour of Poly(3hexylthiophene) in Xylene Solution J.H. Chen, J.Y. Li, L.C. Chen and C.I. Su Small Scale Effect on Nonlinear Vibration of Fluid-Loaded Double-Walled Carbon Nanotubes with Uncertainty T.P. Chang Determination of the Optimal Locations for Injection Molding Gates with Higher Order Response Surface Approximations K.N. Chen and W.D. Ueng

105 110 115 121 126

Chapter 2: Optoelectronics and Optical Systems Simulation of Broadband Transmission Photonic Crystal Waveguide Crossing with Linear Taper Y.B. Lin, R.S. Chen, T.C. Yu and J.F. Liu A Study on Measurement of Photoplethysmograph Using a Smartphone Camera J.H. Jeong, S.M. Kim, S.Y. Park and S. Lee A Simulation Study of the Treatment Effects for the 1064 nm Nd:YAG Laser under Various Fluence and Pulse Durations M.J. Seo, S.Y. Park, J.H. Lee and S.M. Kim Assessment of the UVB Transmittance Measurement Uncertainty in Conformity with ISO/IEC 17025 J.Y. Shieh, S.Y. Huang, S.C. Huang, K.H. Lin and W.C. Huang Compound Optical Film Using Gray Scale Mask Embedded with Micro-Voids Y.C. Chen, C.T. Pan, H.C. Wu, Y.J. Chen and H.C. Yang Design of Secondary Optical Element for a Two-Reflector Solar Concentrator Y.C. Chen and C.C. You Integrated Multi-Object Taguchi Method with Optical Design for Contact Lenses C.T. Yen, I.J. Ding, H.C. Cheng, J.W. Ye and J.M. Shih Improvement on Zhang's Camera Calibration J.H. Park and S.H. Park Video Matching by One-Dimensional PSNR Profile S.W. Lo

133 137 143 149 155 161 166 170 174

Chapter 3: Machine Parts and Mechanisms, Design and Manufacturing An Investigation into Optimized Ti-6Al-4V Titanium Alloy Equal Channel Angular Extrusion Process D.C. Chen, Y.J. Li and G.Y. Tzou Design of a Magnetic Gear Set with Low Torque Ripple Y.C. Wu, W.T. Tseng and Y.D. Chen Heat Transfer of Oscillating Fluid through Finned Heat Sink with Top Bypass Clearance T.M. Jeng, S.C. Tzeng, W.T. Hsu and G.W. Xu Reducing Cogging Force of a Permanent Magnet Transverse Flux Linear Synchronous Motor W.T. Tseng and C.N. Kuo Design and Optimization on Active Engine Mounting Systems for Vibration Isolation P.K. Wong, Z.C. Xie, Y.C. Cao and M. Li Harmonic Analysis and Filter Design for the Light Rail Transit Systems C.T. Hsu, H.M. Huang, T.J. Cheng and L.J. Tsai Modeling of a Shape Memory Alloy Beam and its Stochastic Chaos G. Ge and J. Xu

181 187 192 197 202 210 215

Applied Mechanics and Materials Vols. 479-480

Parametric Study of a Micromixer with Convergent-Divergent Sinusoidal Walls A. Afzal and K.Y. Kim Design and Manufacturing of Drug Eluting Depot Stents with Micro-Sized Drug Reservoirs H.M. Hsiao, C.T. Yeh, T.Y. Wu, L.W. Wu, B.H. Huang and H.N. Yang Finite-Element Analysis of the Magnetic Field in a Magnetic Gear Mechanism Y.C. Wu and B.S. Jian Kinematic Analysis of an 8-Speed Bicycle Transmission Hub Y.C. Wu, P.W. Ren and L.A. Chen Ground Vibration Characteristics for High-Speed Trains on Embankments Y.J. Chen, S.W. Lin and Y.J. Shen Dynamic Response of a Viscoelastic Damping Isolator under High Cyclic Loading B.W. Huang, J.G. Tseng and Y.L. Ke Thermal Performances in Ribbed Rectangular Convergent and Divergent Channels M.S. Lee, S.S. Jeong and S.W. Ahn Finite Element Analysis of Bridge-Vehicle System with Randomness T.P. Chang Design of Geneva Mechanism with Curved Slots J.F. Hsieh and F.S. Wang The Study and Fabrication of Electron Field Emission Module for Next-Generation MultiBeams Lithography Applications W.S. Lin, T.H. Chen and T.C. Cheng An Adaptive Parameter Tuning Method with On-Machine Weight Identification Function for CNC Machine Tools S.M. Wang, S.C. Ouh and C.T. Yen Heat Transfer of Oscillating-Move Pin-Fin Heat Sinks with Circular Impinging Jets T.M. Jeng, S.C. Tzeng, C.H. Liu and Y.X. Huang Performance Improvement of a Hidden Ceiling Fan S.C. Lin, M.Y. Hsieh and C.J. Chang The Design of Heat Pipe Heat Exchanger for CO2 EGS J.C. Hsieh, D.T.W. Lin, W.M. Yan and L.D. Shin Optimization of Circular Diamond Saw Blades with Annular Slots W.H. Gau, K.N. Chen and Y.L. Hwang Effects of Metal Hydride Absorption in Reactor with Annular Finned Tube Heat Exchanger Y.S. Yap, C.H. Peng and C.C. Wang Magnetic Assisted Laser Percussion Drilling C.C. Ho, G.R. Tseng, Y.J. Chang, J.C. Hsu and C.L. Kuo An Electric Wheelchair with Function of Climbing up and down a Step R.C. Soong, S.L. Wu and J.M. Lee The Meshing Efficiency Analysis of Coupled Planetary Gear Reducer L.C. Hsieh and H.C. Tang A Study on the Optimization Design of BOP Gantry Crane by ANSYS H.J. Kim, C.K. Jeong, Y.G. Jung and S.C. Huh Stress Distribution Analysis of Different Types of Blade for a Fermentation System C.C. Wang, P.J. Cheng and K.C. Liu Optimal Design of the Single-Mode Piezoelectric Actuator S.J. Chang and J. Chen The Design of Multiple Function Acoustic Horns for Ultrasonic Welding of Plastic K.M. Shu, Y.J. Wang and C.W. Chi Five-Axis NC Program Conversion for Inclined Plane Machining H.Y. Cheng and Y.C. Kao The Impact of Bicycle Suspension on Pedaling Forces Y.S. Liu, T.S. Tsay, T.C. Wang and C.F. Liu Development of a Virtual Milling Machining Center Simulation System with Switchable Modular Components C.L. Wei, H.Y. Cheng, C.Y. Yu and Y.C. Kao Hysteretic Nonlinear Characteristics and Stochastic Bifurcation of Cantilevered Piezoelectric Energy Harvester J. Xu and Z.W. Zhu

c

220 225 230 234 239 244 249 254 259 264 268 274 279 284 289 294 299 304 309 314 319 324 329 333 338 343 348

d

Applied Science and Precision Engineering Innovation

Optimal Yield Rate in ACF Cutting Process of TFT-LCD Module Using Orthogonal Particle Swarm Optimization J.L. Kuo and C.H. Hsieh An Optimal Design for New Electromagnetic Valve in Camless Engines L.V. Dat, Y.J. Shiao and T.P. Le The Dynamic Analysis and Simulation of Electric Scooter Y.L. Hwang and J.K. Cheng Study on Bevel Gear Worm Forging by Finite Element Analysis T.S. Yang, L.H. Lai and J.H. Deng The Characteristic Analysis of Interrupted Flow Pulsation on Ultrafiltration System C. Huang and H.S. Chen Pressure Distribution in the Air Film and the Porous Conveyor Air Bearing T.Y. Huang, S.C. Shen, S.C. Lin and S.Y. Hsu Dynamics of a Quadruped Walking Machine F.C. Chen, S.C. Wu and Y.C. Chen Magnetostatic Field Analysis of Disk-Type Permanent-Magnet Motors Y.C. Wu and Y.C. Hong Using ADAMS Application on Mechanism Simulation of New Multiaxis Machines Y.M. Lee, K.S. Hsu and S.B. Chang An Integrated CFD and Experimental Study of the In-Line Fan H.C. Yen, W.S. Hsu, Y.J. Cheng, S.C. Lin and Y.C. Wu The Characteristic Comparison of the Accelerometer and the Gyroscope Using the Pendulum Model of Body Sway K. Kaewkannate, G. Han, S.M. Kim and S. Kim Heat Transfer of a Double Layer Microchannel Heat Sink W.K. Cheong and F.N. bin Ahmad Muezzin The Analysis of Magnetorheological Brake Structure with Multiple Poles Y.J. Shiao, Q.A. Nguyen and G.D. Huang Seismic Response for a One-Third Scale-Down Vertical Cylindrical Cask Specimen Using Cyclic Loading Testing W.T. Lin, T.C. Fu, Y.C. Wu and C.C. Huang Microstructure Design of Surface Permanent Magnet and Tooth Surface Stator in Brushless DC Motor with Low Rare Earth Material H.C. Yu and B.S. Yu Stability and Dynamic Analysis of the Electrostatic MEMS Actuators C.C. Liu A Compact Planar Inverted-F Antenna for Octa-Band Operations of Smart Handsets S.C. Li, I.T. Tang, Y.L. Shih, H.Y. Cheng and W.F. Chang

353 360 365 369 373 380 385 390 396 401 406 411 416 421 427 431 436

Chapter 4: Medical Machinery and Technologies, Innovative Developments Application of Artificial Neural Networks for Diagnosing Acute Appendicitis S.Y. Park, S. Lee, J.H. Jeong and S.M. Kim Study on Biohydrogen Production of Dark Fermentation with the Stimulation of Ultrasonic S.Y. Hsia, C.H. Wang and Y.T. Chou Implementation and Validation of ECG-Derived Respiration with QRS Characteristics S.L. Lin, C.K. Chen and C.S. Chien A Newly Developed Polyurethane Prosthetic Heart Valve Y.H. Kang, H.H. Vu, C.H. Hsu, K.W. Yang and W.C. Shih The Measurement of Anesthesia Depth Using Biomedical Signal during General Anesthesia B.C. Choi, S.Y. Ye, S.J. Kim and S.M. Kim The Effects of Application Site and Time of Vibration Stimulation: Changes in Gait Pattern and Muscle Activity H.J. So, S.H. Kim and D.W. Kim

445 451 457 463 468 475

Applied Mechanics and Materials Vols. 479-480

Different Frequency Bands of Electromagnetic Wave on Age-Related Developmental Changes M.C. Ho, C.F. Huang, C.Y. Chou, M.C. Lu, C. Hsieh and C.J. Liu L2-EMD Filter Design for Photoplethysmography Signal Y.W. Tang and Y.D. Lin Supervised Neural Networks for the Automatic Classification of Leukocytes in Blood Microscope Images S.F. Lin, C.H. Tseng and C.I. Huang Analysis of Non-Fourier Thermal Behavior in Layered Tissue with Pulse Train Heating K.C. Liu, C.C. Wang and P.J. Cheng

e

480 486 491 496

Chapter 5: Electronics, Electrical Engineering and Power Electronics Contour Data Acquisition System for Electric Vehicle Distance Estimation Method K.W. Chew, C.K. Leong and B.M. Goi FPGA Implementation of a High-Speed Two Dimensional Discrete Wavelet Transform C.F. Hsieh and T.H. Tsai Low Phase Noise Voltage Controlled Oscillator Using Cascode and Current-Reuse Techniques for Radio Frequency Circuits S.C. Hsu, M.T. Hsu and Y.T. Hsu Time-Frequency Bands of Electromagnetic Wave from ERPCOH on Developmental Changes M.C. Ho, C.F. Huang, C.Y. Chou, M.C. Lu, Y.Y. Chang and C.J. Liu In-Plane Electromagnetic Generator Fabricated on Printed Circuit Board Technology C.T. Pan, F.T. Hsu, C.C. Nien, Z.H. Liu, Y.J. Chen and P.H. Chen Wide Area Input Stabilizer for Damping of Power System Inter-Area Oscillation V.D. Doan, T.H. Tseng and P.H. Huang Development of Serial-Connected High Step-Up DC-DC Converter with Single Switch V.T. Liu and C.H. Hsu

503 508 513 517 524 530 535

Chapter 6: Energy and Power Engineering Application of TRACE and FRAPTRAN in the Spent Fuel Pool of Chinshan Nuclear Power Plant J.R. Wang, H.T. Lin, W.Y. Li, S.W. Chen and C.K. Shih LAPUR6 Stability Analysis on Power/Flow Map of Lungmen ABWR H.T. Lin, J.R. Wang, K.Y. Chen, S.H. Chen and C.K. Shih Potential of Solar Farm Development at UTM Campus for Generating Green Energy S.N. Mohammad, R. Zakaria, W. Omar, M.Z. Abd Majid, A.L. Saleh, M. Mustaffar, R. Mohamad Zin and N.A. Jainudin Impact of a Large Scale PV Generation System on the Distribution System C.T. Hsu, C.S. Chen, C.H. Lin and T.J. Cheng Development of Intelligent Solar Panel Cleaning System with Fuzzy Logic Theorem C.H. Huang, M.R. Lee, Y.F. Su, C.C. Huang, Y.T. Su, W.H. Su and F.Z. Cai Elman Neural Network for Dynamic Control of Wind Power Systems C.H. Huang, C.M. Hong, Y.F. Su, S.M. Lee, C.S. Jhuang, B.Y. Shi and B.R. Shi Design and Analysis of a Novel Hybrid Solar/Gas Dish Stirling System (HS/GDSS) W.B. Zhan, G.Q. Xu, Y.K. Quan, X. Luo and T.T. Li An Active Islanding Detection Method for Grid-Connected Renewable Energy Generation System W.Y. Chang Comparison of Three Short Term Photovoltaic System Power Generation Forecasting Methods W.Y. Chang Optimal Penetration of Photovoltaic Systems in Distribution Networks W.L. Hsieh, C.H. Lin, C.S. Chen, C.T. Hsu, C.Y. Ho and H.J. Chuang

543 548 553 559 565 570 575 580 585 590

f

Applied Science and Precision Engineering Innovation

HCPV Module Temperature Prediction: A Case Study Based on Measurements at NPUST Y.N. Wang, L.M. Fu, C.H. Tsai, Y.T. Hsu, T.T. Lin and J.C. Leong Effect of Geometry on Energy Absorption of Reduction Tubes Using a Die - A Numerical Study H. Mao, C.J. Luo, K. He and R.X. Du

595 599

Chapter 7: Automation and Control An Integrated Realization of Motion Control and Motor Drives with FPGA C.K. Lai, Y.T. Tsao, S.L. Tsai and W.N. Chen Direct Adaptive CMAC PI Control for Uncertain Nonlinear Systems with Measurable Output Feedback C.S. Chen Whole-Body Human-to-Humanoid Motion Imitation H.I. Lin and Z.S. Chen The Development of a Hybrid Antilock Braking System Using Magnetorheological Brake Y.J. Shiao, Q.A. Nguyen and J.W. Lin Optimization of the Neural Muscular Drive and Respiratory Signals under Dead Space Loading and CO2 Inhalation S.L. Lin, T.C. Chen and H.C. Chang Development of an Automatic Optical Inspection System and its Application to Defect Examination J.H. Jean, C.H. Chen, T.B. Huang and S.H. Tsai Design of Flight Control System Bus Controller of UAV Based on Double CAN-Bus J.H. Pan, S.B. Zhang and H. Ma A Wireless Sensor Network Deployment Planning Tool to Support Building Automation R.S. Hsiao, D.B. Lin, H.P. Lin and C.H. Chung Cryptanalysis and Improvement of Secure Key Distribution for the Smart Grid H.R. Tseng and T.H. Chueh Study and Design of Smart Embedded Home System Based on Wireless Electric Power Measurement Monitoring System W.H. Choi and M.S. Jie Home Security Service and Condition Control S.C. Tung, W.J. Li and S.M. Huang

607 612 617 622 627 636 641 646 651 656 661

Chapter 8: Sensors, Mechatronics and Robotics Hysteretic Nonlinear Characteristics of Giant Magnetostrictive Sensors Z.W. Zhu, Q.X. Zhang and J. Xu Safety Assessments for Wearable Robot Suits K.H. Yen and C. Wang Calibration of RGB-D Sensors for Robot SLAM C.T. Chi, S.C. Yang and Y.T. Wang Experimental Evaluation of a Small-Displacement Sensing System Based on the Surface Plasmon Resonance Technology in Heterodyne Interferometry S.F. Wang, C.T. Chen, F.H. Kao, Y. Chu, S.R. Lay, Y.P. Liao, L.C. Lin and A.L. Liu A Study on FBG Vehicle Loading Sensing System T.S. Hsieh, S.K. Liaw, C.H. Lin, L.R. Tasi and C.C. Chiang Structure Design of the Biaxial Piezoelectric Actuated Stage Using a Novel Disk Piezoelectric Actuator S.C. Mou Stepping Experiment and Characteristics Analysis of a Novel Biaxial Piezoelectric Actuated Stage S.C. Mou and Y.R. Zhuang High Performance CO Sensors Utilizing Sprayed Distributed Toluene-Based Gold Nanoparticles C.Y. Wang, H.C. Lee, Y.C. Wu and C.H. Lin

667 672 677 682 687 692 697 702

Applied Mechanics and Materials Vols. 479-480

Development of a Laser Measuring Method for Small Displacement of a Thin Plastic String C.F. Liu The Design of Multi-Parameter Bio-Signal Sensor for Applying a Smartphone m-Health Service S.J. Kim, S. Lee, J.H. Jeong, S.Y. Park and S.M. Kim Interpretation of the Oscillating Signals of the Smart NOx Sensors Used in Urea Selective Catalyst Reduction Systems via Spectral Analysis C.C. Chou, C.J. Chiang, Y.H. Su and Y.Y. Ku Design of Photo Diode Sensors for Measuring Solar Light Orientation Y.N. Chang, H.L. Cheng, S.Y. Chan and Y.S. Shen Singularity Avoidance for a Redundant Robot Using Fuzzy Motion Planning C.J. Lin, C.R. Lin, S.K. Yu and C.C. Han An Output Based Adaptive Iterative Learning Control with Particle Swarm Optimization for Robotic Systems Y.C. Wang, C.J. Chien and C.N. Chuang Distributed Control Intelligent Robotic Gripper S.J. Huang, W.H. Chang, J.Y. Su and Y.C. Liu A Laboratory-Based Smart Grid Sensor Network Testbed L.F. Cheung, K.S. Lui, K.K.Y. Wong, W.K. Lee and P.W.T. Pong Discoid and Asymmetrical Micro-Satellite Propulsion Mode Attitude Control with Great Mass Change and without Angular Rate Sensor H.N. Shou A Fuzzy-Based Management for Power-Aware Wireless Sensor Network S.C. Wang, S.S. Wang, C.W. Chen and K.Q. Yan A Centre Clustering Mechanism of Wireless Sensor Network K.Q. Yan, S.C. Wang, C.S. Peng and S.S. Wang Motion Control of a Robot Arm K.L. Su, B.Y. Li, J.H. Guo and H.H.K. Chau Enhance A* Searching Algorithm Applying in Multiple Robot System K.L. Su, B.Y. Li and C.Y. Chung A Cyclostationarity-Based Spectrum Sensing Scheme for Dynamic Traffic Circumstances Y. Lee, S.R. Lee, S. Yoo, J. Lee, J. Shim and S. Yoon Distributed Tree Routing Scheme for Large-Scale Wireless Sensor Networks Y.C. Lin and J.H. Zhong A N-Hop Concentric Clustering Algorithm with Sub-Clusters in a Wireless Sensor Network Y.L. Chen, Y.N. Shih and S.J. Shih

g

708 713 719 724 729 737 742 747 753 758 763 768 773 778 783 788

Chapter 9: Methods and Algorithms for Processing and Analysis of Data Development of Causal Model of Four Parameters upon Statistical and Mathematical Analysis and Management H.M. Shih, S.L. Chen and C.H. Wang Using Maple to Study the Partial Differential Problems C.H. Yu Efficient Computational Workload Distribution on Heterogeneous GPUs C.S. Lin, P.T. Liu, C.W. Hsieh, H.Y. Chang and P.A. Hsiung Fingerprint Identification Based on Mopso in SVM C.S. Hu and C.S. Hu Accelerometry-Based Motion Pattern Analysis for Physical Activity Recognition and Activity Level Assessment K.C. Liu, C.T. Liu, C.W. Chen, C.C. Lin and C.T. Chan Application of Maple on Evaluation of Definite Integrals C.H. Yu A Study on the Multiple Improper Integral Problems with Maple C.H. Yu

795 800 805 810 818 823 828

h

Applied Science and Precision Engineering Innovation

Facial Expression Generated Automatically Using Triangular Segmentation J.S. Sheu, T.S. Hsieh and H.N. Shou Refinement of Depth Estimation Method via Energy Minimization F.H. Cheng and Y.P. Chang Modeling and Simulation of the Optical Properties of Low-Speed Target in Near Space X.P. Du, H. Chen, Z.J. Liu and X.Z. Cheng Application of Maple on the Integral Problems C.H. Yu Application of Maple on Solving the Differential Problem of Rational Functions C.H. Yu An Artificial Evolutionary Approach for Solving the Nonlinear Constrained Optimization Problems Y.C. Hsieh and P.S. You A Novel Unambiguous Correlation Function with a High and Sharp Main-Peak for BOC Signal Tracking Y. Lee, S.R. Lee, S. Yoo, J. Lee, J. Shim and S. Yoon Image Contrast Enhancement by Hybrid 3SAIHT and CLAHE Algorithm C.Y. Yu, H.Y. Lin and C.J. Lin A Low Complexity Integer Frequency Offset Estimation Scheme Based on Coherence Phase Bandwidth for OFDM Systems Y. Lee, S.R. Lee, S. Yoo, J. Shim, J. Lee and S. Yoon Face Recognition by Geometrical Feature-Point Bilateral Matching Y.S. Huang and G.D. Peng Robust Observer-Based Output Feedback Control for Time-Varying Systems C.C. Feng

834 839 844 849 855 861 865 870 878 883 889

Chapter 10: Computer and Information Technologies Volumetric Model Body Outline Computation for an Object Tracking in a Video Stream J.H. Park Efficient Scheduling for Real-Time Pinwheel Tasks on DVS Processors D.R. Chen and Y.S. Chen A Method of Handling Missing Data in the Context of Learning Bayesian Network Structure C. Chen, H. Yu and J.Y. Wang A Automatic Vehicle License Plate Location Based on Sobel Edge Method R.C. Lee, K.C. Hung and H.S. Wang Detecting Phishing Sites Using URLs Collected from Emails C.S. Wang, F.H. Hsu, S.J. Chen, Y.L. Hwang and M.H. Wu Serum System: An Automatic Curing System for Worms and Buffer Overflow-Based Botnets L.H. Chen, F.H. Hsu, S.J. Chen, C.J. Lin and Y.L. Hwang Impacts of Langauge Learning Based on Computer-Assisted Language Learning Instruction Y.L. Hwang, P.W. Huang and L.P. Hsu A Novel Fuel Cell System Design by Using Ziegler-Nichols-Based Intelligent Fuzzy Controller J.M. Lin and C.H. Lin A Gesture Recognition Based on Accelerometer and Hidden Markov Model for Human Computer Communication S.L. Wang, Z.G. Zhang and Y.G. Guo Optical Music Recognition for Numbered Music Notation with Multimodal Reconstruction F.H.F. Wu and J.S.R. Jang Color 3D Image Encryption Technique by Combined Use of Computational Integral Imaging Joint Image Scrambling Technique X.W. Li, S.J. Cho and S.T. Kim A Cloud-Based Test Architecture for IPv6 SNMPv3 Agent C.I. Chang and C.C. Tsao

897 901 906 911 916 923 928 934 938 943 948 953

Applied Mechanics and Materials Vols. 479-480

3D Integral Imaging Encryption Using a Depth-Converted Elemental Image Array X.W. Li, S.K. Lee, S.J. Cho and S.T. Kim On the Security of the Discrete Logarithm Based Remote Authentication Scheme Using Smart Cards Y.C. Lee and P.J. Lee A Secure Hybrid P2P Network Mobile Communication Device Design W.H. Kuo, P.C. Su and J.L. Liu An Enhanced Vehicular Information Dissemination Based on Back-Off Time Mechanism J.M. Hsu and W.T. Wang Threshold-Based Privacy-Preserving Key Management Scheme for Vehicle-to-Grid Networks H.R. Tseng Robust Exponential Stability for Uncertain Discrete-Time Switched Systems with Interval Time-Varying Delay via a Switching Signal J.D. Chen, C.H. Lien, K.W. Yu, C.T. Lee, R.S. Chen and C.D. Yang The Hybrid Differential Evolution with Dynamic Scaling Mutation and Wrapper Local Search for Optimization Problems C.L. Lu, S.Y. Chiu, C.H. Hsu and S.J. Yen Implementation and Experiments of TDOA Monitoring Techniques for Broadcasting Interferences Y.T. Chang and Y.C. Lin Development of an Equipment Failure Identification Expert System with Multiple Reasoning Approaches Y.H. Ho, H.S. Wang and H.C. Wang Classification of Chinese Popular Songs Using a Fusion Scheme of GMM Model Estimate and Formant Feature Analysis I.J. Ding, C.T. Yen and C.W. Chang Low Phase Noise and Low Power Voltage-Controlled-Oscillator Using Current-Reuse Techniques for Wireless Communication Circuits T.H. Han, M.T. Hsu and C.C. Chung Design of 3.1-10.6GHz CMOS LNA Based on Input Matching Technique of Common-Gate Topology Y.C. Chang, M.T. Hsu and Y.C. Hsieh A Source Routing Protocol for Bluetooth-Based Sensor Networks C.M. Yu and Y.B. Yu Development of Software-as-a-Service Cloud Computing Architecture for Manufacturing Management Systems Based on Virtual COM Port Driver Technology S.L. Chen, H.P. Wang, Y.Y. Chen and C. Hsu Performance Analysis of Hybrid Fusion in Cognitive Radio Networks M.M. Guo, Y.X. Liu and W.Q. Fan Design of a Smart Green Energy Management System Based on DMX512 Protocol S.F. Wang, Y.Z. Su, Y. Chu, Y.F. Chau, J.H. Wei, W. Yang, A.L. Liu and F.H. Kao An Innovative but Low-Cost Mechanism for E-Payment, E-Ticketing, and E-Identity Document: A Case Study of Multiple Perspectives in Innovation Management V.K.Y. Chan

i

958 963 968 973 978 983 989 996 1001 1006 1010 1014 1018 1023 1027 1032 1038

Chapter 11: Environmental Sciences and Engineering, GIS Frequency Analysis of the Motor Control Centers in a Nuclear Power Plant Using Testing and Simulating Methods W.T. Lin, Y.C. Wu and C.C. Huang Seismic Testing and Verification for 30 Tons Scaled-Down Model of Reinforced Concrete Containment Vessel Y.C. Chen, W.T. Lin, T.L. Chu and Y.C. Wu Application of GIS on Rapid Evaluation for Potential Portal Areas of Tunnels I.T. Wang Preliminary Volcanic Seismic Hazard Analysis for Tatun Volcano Group in Northern Taiwan C.Y. Pan, Y.C. Wu and C.W. Chang

1045 1051 1056 1061

j

Applied Science and Precision Engineering Innovation

Weibull Component Reliability Prediction with Masked Data X.G. Li and K. Yuan Life Cycle Carbon Dioxide Emission Assessment of Housing in Taiwan Y.S. Chang and K.P. Lee Site Response Analysis for a Site with the Dipping Bedrock and Liquefiable Layers Using FLAC 3D Y.C. Wu and M.H. Hsieh A Multi-Agent System for Multi-Level Based Environmental and Physiological Signal Monitoring and Analysis Y.C. Chou, W.C. Liao and Y.L. Chen Promoting Usage of Effective Rainfall in Pond Irrigation System R.S. Wu, S.F. Yu and S.W. Chen

1066 1071 1076 1081 1086

Chapter 12: Architecture, Civil and Industrial Engineering Corrosion Risk of Stainless Steel Facilities in the Coastal Regions of Taiwan T. Huang and H.Y. Chang Corrosion Risk of Welded Steel Frames in the Urban Areas of Taiwan K.C. Lin, K.T. Liou and H.Y. Chang A Study on the Deterioration of External Wall Tiles on RC Buildings in Taiwan C.Y. Chen and K.Y. Huang The Interaction between Adjacent Structures with Different Foundation Levels under Earthquake Loading K. Han and D. Cho Novel Pile-to-Pilecap Connection Under Lateral Load J.H. Lee, W.S. Kim, Y.W. Seo and K.J. Kim Improvement of Accelerated Weathering Test through Physicochemical Analysis for Polymeric Materials in Building Construction T.C. Yang A Study on the Deterioration Condition and Renovation Work for High-Rise Reinforced Concrete Apartment in Japan - The Practice Project Kajima Corporation Minaminagasaki Dormitory C.T. Liao, H.Y. Chang and Y.J. Juan The Construction Protest Management Study with NIMBY Conflict L.K. Lin, Y.R. Zhou and J.W. Lin Experimental and Analytical Investigation of Lateral-Torsional Buckling of RC Beams with Geometric Imperfections J.H. Lee and I. Kalkan Centrifuge Modeling on Seismic Behavior of Pile in Liquefiable Soil Ground W.Y. Hung, C.J. Lee, W.Y. Chung, C.H. Tsai, T. Chen, C.C. Huang and Y.C. Wu Influence of Angle Thickness towards Stiffness and Strength Prediction for Cold-Formed Steel Top-Seat Flange Cleat Connection Y.H. Lee, C.S. Tan, M.M. Tahir, S. Mohammad, P.N. Shek and Y.L. Lee Development of Physical-Parameter Identification Procedure for Energy-Dissipated Buildings with Symmetric Ductile Braces M.C. Huang, Y.P. Wang, T.K. Lin and J.F. Wang Modal Identification of Structures from Seismic Response Data via Amplitude-Dependent Time Series Model W.C. Su, C.S. Huang and C.Y. Liu Model for Evaluating Uncertain Project Duration Considering Construction Interface Problems S.H. Wang, Y.T. Lai, J.J. Liu and W.C. Wang Seismic Rehabilitation of Beam-Column Joints Using FRP Sheets and Buckling Restrained Braces H. Kim, D.J. Kim, M.S. Kim and Y.H. Lee Structural Behavior of a Steel Grid Shear Wall Subjected to Combined Axial and Cyclic Lateral Loads H. Kim, J.W. Park, J.Y. Park, Y.H. Lee and D.J. Kim

1097 1101 1105 1109 1115 1119

1124 1128 1133 1139 1144 1149 1155 1160 1170 1175

Applied Mechanics and Materials Vols. 479-480

Enhancing Collapse Detection and Alarms in Bridge Management M.K. Tsai and N.J. Yau A New Damage Detection Method for Aging Offshore Platform Using Two Measurements F.S. Liu, W.W. Chen, D.P. Yang, J.F. Qin, Z.G. Yue, H.C. Lu and L. Xu

k

1180 1185

Chapter 13: Related Topics Item Relational Structure Theory Based on Liu’s Improved Nonparametric IRT Theory H.C. Liu, Y.K. Yu and H.C. Tsai An Extensive Evaluation Design Approach to Quality Function Deployment C.T. Wu and N.T. Liu A Framework of Fit Status of Organizational Innovation: Based on the Typology of Organizational Lag J. Li and C.S. Shi Research on Human Resource Strategy under Customer Demand Using System Dynamics for the Thin Film Sputtering Target Material Industry T.S. Lan, C.H. Lan, P.C. Chen and K.C. Chuang Using RSSI Simple Localization Method to Implement the Context-Aware and Social Recommendation System M.Y. Chen, M.N. Wu and H.E. Lin

1193 1197 1202 1207 1213

CHAPTER 1: Materials Engineering and Processing Technologies of Materials

Applied Mechanics and Materials Vols. 479-480 (2014) pp 3-7 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.3

Effect of Bi2O3 Addition on the Microstructure and Electrical Properties of Lead-Free (Na0.5K0.5)NbO3- Bi0.5(Na0.93K0.07)0.5TiO3 Ceramics Chun-Huy Wang Department of Electronic Engineering, Nan-Jeon Institute of Technology, Tainan, Taiwan, R.O.C email: [email protected] Keywords: sintering, poling, dielectric property, piezoelectric property, lead-free piezoceramic.

Abstract. In the present study, various quantities of Bi2O3 were added into 0.98(Na0.5K0.5)NbO3-0.02Bi0.5(Na0.93K0.07)0.5TiO3 (0.98NKN-0.02BNKT) ceramics. It was found that 0.98NKN-0.02BNKT with the addition of 0~0.5 wt.% Bi2O3 exhibit relatively good piezoelectric properties. For 0.98NKN-0.02BNKT ceramics, the electromechanical coupling coefficients of the planar mode kp and the thickness mode kt reach 0.40 and 0.47, respectively. For 0.98NKN-0.02BNKT ceramics with the addition of 0.3 wt.% Bi2O3, the electromechanical coupling coefficients of the planar mode kp and the thickness mode kt reach 0.50 and 0.53, respectively. It is obvious that 0.98NKN-0.02BNKT solid solution ceramics by adding low quantities of Bi2O3 is one of the promising lead-free ceramics for electromechanical transducer applications. Introduction (Na0.5K0.5)NbO3 (NKN) ceramics have been considered a good candidate for lead-free piezoelectric ceramics because of its high piezoelectricity and ferroelectricity. The hot pressed NKN ceramics (~99% of theoretical density) have been reported to possess large piezoelectric longitudinal response (d33~160 pC/N), high planar coupling coefficient (kp~45%) and high phase transition temperature (Tc = 420oC) [1]. NKN ceramics sintered by ordinary sintering show relatively lower values (kp=29.5%) due to difficulty in the processing of dense ceramics by ordinary sintering. It has received a lot of attention and been thoroughly investigated [2]. Recently, an efficient solution to improve these problems has been realized by using some additives in NKN ceramics, such as BaTiO3 [3], LiNbO3 [4], LiTaO3 [5], SrTiO3 [6], CaTiO3 [7], Ba(Sn,Ti)O3 [8], and Ba(Zr,Ti)O3 [9], etc. A comparison of the properties of (Na0.5K0.5)NbO3 ceramics based on the previous reports of various groups is shown in Table I. Thus, the addition of some perovskite compounds to form solid solutions with NKN or synthesizing by Spark Plasma Sintering (SPS) has been made to obtain lead-free materials suitable for industrial applications. Perovskite structure (Bi1/2Na1/2)TiO3 [abbreviated as BNT] ceramics are considered as one of the candidates for lead-free piezoelectric ceramics because of its high ferroelectric properties and high Curie temperature (Tc = 320 oC). Some modifications of BNT ceramics have proved to be helpful by forming solid solution with other perovskite oxides [10]. Bi0.5(Na0.93K0.07)0.5TiO3 is well-known lead-free piezoelectric materials, which has a rhombohedral symmetry at room temperature and show better piezoelectric response [11]. However, there have been few studies on the properties of NKN ceramics modified with Bi0.5(Na0.93K0.07)0.5TiO3 [abbreviated as BNKT]. Therefore, it is desirable to expect that the solid mixtures of NKN and BNKT have better piezoelectric properties. For the most important perovskite BNT family, Bi2O3 has been common used as an additive to improve their physical and elect ic properties [12]. Despite of these investigations, the role of Bi on the structure and electrical properties of NKN-based ceramics remains somewhat ambiguous. Therefore, further investigation on this subject is necessary. The aim of this study is to investigate the physical and electrical properties of (1-x)(Na0.5K0.5)NbO3-xBi0.5(Na0.93K0.07)0.5TiO3 system. The effects of the dielectric and piezoelectric properties of 0.98NKN-0.02BNKT ceramics added with various amounts of Bi2O3 were discussed in this work, and the influence of the Bi2O3 addition on the microstructure and electrical properties was examined.

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Table I. Comparison of properties of NKN ceramics based on the previous reports of various groups. kp kt kt /kp Ref Composition Density Relative Ko . (g/cm3) density (%) NKN 4.34 96.4 ----- 0.295 0.41 1.39 3 0.98NKN-0.02BaTiO3 4.44 98.4 ----- 0.29 0.38 1.31 3 0.94NKN-0.06LiNbO3 4.35 96.5 ----- 0.42 0.48 1.14 4 0.94NKN-0.06LiTaO3 ----570 0.36 ----- ------ 5 0.995NKN-0.005SrTiO3 4.44 98.4 412 0.325 0.44 1.35 6 0.995NKN-0.005CaTiO3 4.4 97.6 553 0.42 0.38 1.1 7 0.98NKN-0.02 Ba(Sn0.02Ti0.98)O3 4.15 92.2 365 0.31 0.39 1.26 8 0.98NKN-0.02Ba(Zr0.04Ti0.96) O3 4.28 95.1 875 0.30 0.55 1.83 9 Methods and Procedures The (1-x)(Na0.5K0.5)NbO3-xBi0.5(Na0.93K0.07)0.5TiO3 [abbreviated as (1-x)NKN-xBNKT] ceramics were prepared by solid-state reaction method. Additive amounts of Bi2O3 were added to the 0.98(Na0.5K0.5)NbO3-0.02Bi0.5(Na0.93K0.07)0.5TiO3 ceramics powders in concentration varying from 0 to 0.5 wt.%. Starting materials were K2CO3, Na2CO3, Bi2O3, Nb2O5, TiO2 with purities of at least 99.5% and weighted according to the stoichiometric composition (x= 0, 0.01, 0.02, 0.03, 0.04 and 0.05). Additive amounts of Bi2O3 were added after the calcination at 900 oC for 10 h. The calcined powders were pressed (CIP) at 180 MPa into pellets with 15 mm in diameter. The disc samples were sintered in alumina crucible at 1100 oC for 3 h in air atmosphere. To measure relevant piezoelectric properties, the prepared ceramic samples were polarized in silicone oil at 120~160 oC under the electric field of 4 kV/mm for 30 min. An X-ray diffractometer (Seimens D5000) using Cu Kα radiation was used to evaluate the crystal structure of the sintered ceramics. The room temperature dielectric constant was measured by LCR meter (Angilent 4284A) at 1 kHz. The temperature dependence of the electrical permittivity of an unpoled specimen was automatically measured at 1 kHz using an HP4192A LF impedance analyzer under computer control from 30oC to 510 oC. The Curie temperature Tc and the maximum dielectric constant at Tc were determined from this measurement. The piezoelectric properties were measured by a resonance-antiresonance method based on IEEE standards [13] using an impedance/gain-phase analyzer (Angilent 4194). The samples for observation of the microstructure were polished and thermally etched. The microstructures were observed using a scanning electron microscope (SEM). The mean grain size was calculated by the line intercept method [14]. The density was measured by Archimedes method. Results and Discussion Figure 1 shows the X-ray diffraction (XRD) patterns of (1-x)NKN-xBNKT ceramics for x=0.01, 0.02, 0.03, 0.04 and 0.05. The orthorhombic symmetry of (1-x)NKN-xBNKT ceramics at room temperature is characterized in the XRD patterns in the 2θ range of 44-48°. The XRD analysis of sintered samples shows that (1-x)NKN-xBNKT has a single phase with a perovskite structure and forms a solid solution. The BNKT appears to have diffused into the NKN lattice to form a solid solution, in which Bi occupies (Na,K) lattice and Ti enters Nb sites of NKN. It can be concluded that the (1-x)NKN-xBNKT ceramics have orthorhombic structures in this case. The temperature dependence of the dielectric constant at 1 kHz for (1-x)NKN -xBNKT ceramics is shown in Fig. 2. For pure NKN, two sharp phase transitions are reported at 420 oC and 200 oC, corresponding to the phase transitions of paraelectric (cubic)–ferroelectric (tetragonal; Tc) and tetragonal– orthorhombic(TT–O), respectively [8]. With increasing BNKT content, the paraelectric (cubic) ferroelectric (tetragonal) and tetragonal-orthorhombic transition temperatures all shift to lower temperatures. Table II shows the physical and electrical properties of (1-x)(Na0.5K0.5)NbO3 -xBi0.5(Na0.93K0.07)0.5TiO3 ceramics under different x compositions. For 0.98(Na0.5K0.5)NbO3 -0.02Bi0.5(Na0.93K0.07)0.5TiO3 [abbreviated as 0.98NKN-0.02BNKT] ceramics, the electromechanical coupling coefficients of the planar mode kp and the thickness mode kt reach 0.40 and 0.47, respectively. The dielectric constant (Ko= 1020) is found for 0.98NKN-0.02BNKT ceramics.

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Table II. Physical and electrical properties of(1-x)(Na0.5K0.5)NbO3-xBi0.5(Na0.93K0.07)0.5TiO3 ceramics under different compositions. x Ko kp kt 0.01 840 0.38 0.42 0.02 1020 0.40 0.47 0.03 950 0.32 0.38 0.04 780 0.26 0.32 0.05 620 0.18 0.25

Fig. 1. X-ray diffraction (XRD) patterns of (1-x) Fig. 2. Temperature dependence of dielectric NKN-xBNKT ceramics system for different x constant of (1-x)NKN-xBNKT ceramics at 1 kHz. compositions.

Fig. 3. XRD patterns of 0.98NKN-0.02BNKT Fig. 4. Measured density and dielectric loss ceramics with addition of different Bi2O3 doping. tangent of 0.98NKN-0.02BNKT ceramics with addition of different Bi2O3 doping. Figure 3 shows the XRD patterns of 0.98NKN-0.02BNKT ceramics with different Bi2O3 addition. All the compositions were sintered in air at 1100 oC for 3 h. The orthorhombic symmetry of 0.98NKN-0.02BNKT ceramics at room temperature is characterized in the XRD patterns in the 2θ range of 44-48°. Only an orthorhombic phase with a perovskite structure was observed. It indicates that the addition of small amounts of Bi2O3 did not give rise to an obvious change in crystal structure. Figure 4 shows the measured density and dielectric loss tangent of 0.98NKN-0.02BNKT ceramics with various Bi2O3 contents. The measured density of the sintered samples is 93–98% of the theoretical density. The measured density increases with an increase of Bi2O3 contents until they reach

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a maximum value at 0.3 wt.%, then decrease for higher Bi2O3 contents. The variation trend of dielectric loss tangent with Bi2O3 contents is inverse to that of the measured density. The microstructure of 0.98NKN-0.02BNKT ceramics with different Bi2O3 addition is shown in Fig.5. It can be seen that the 0.98NKN-0.02BNKT ceramics consist of small grains, with a loose structure, and a high porosity. The SEM images of 0.98NKN-0.02BNKT with 0.3 wt% Bi2O3 addition are denser, with low porosity, and exhibit a larger grain size of ~3 µm in Fig. 5(d). It seems that Bi2O3 addition at amount less than 0.3 wt% enhances the grain growth. However, at the addition more than 0.3 wt%, the grain size is decreased.

Fig. 5(a)

Fig. 5(b)

Fig. 5(c)

Fig. 5(d) Fig. 5(e) Fig. 5(f) Fig. 5. SEM images of 0.98NKN-0.02BNKT ceramics with addition of different Bi2O3 doping: (a) 0 wt.% (b) 0.1 wt.% (c) 0.2 wt.% (d) 0.3 wt.% (e) 0.4 wt.% (f) 0.5 wt.%. Bar=10 µm

Fig. 6. Electromechanical coupling factor of 0.98NKN-0.02BNKT ceramics with addition of different Bi2O3 doping.

Fig. 7. Dielectric constant of 0.98NKN-0.02BNKT ceramics with addition of different Bi2O3 doping.

The planar coupling factor (kp) and thickness coupling factor (kt) of 0.98NKN-0.02BNKT ceramics with various Bi2O3 contents in Fig. 6. The electromechanical coupling factor has been used extensively as a measure of the piezoelectric response of PZT type ceramics. It was found that the electromechanical coupling factor depended on the material parameters such as grain size, porosity, and chemical composition. Usually, the piezoelectric activity increases with the value of the electromechanical coupling factor in radial mode kp and in thickness mode kt. For

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0.98NKN-0.02BNKT ceramics, the kp and the kt reach 0.40 and 0.47, respectively. The kp and kt increases with an increase of Bi2O3 contents until it reaches a maximum value at 0.3 wt.%, then decreases for higher Bi2O3 contents. Figure 7 shows the dielectric constant of 0.98NKN-0.02BNKT ceramics with various Bi2O3 contents. The addition of small amounts of Bi2O3 (≤ 0.3 wt.%) did not give rise to an obvious change in the variation trend of the dielectric constant. But, there is a deep fall of dielectric constant in the high Bi2O3 content region (> 0.3 wt.%). The 0.98NKN-0.02BNKT ceramics with 0.3 wt.% Bi2O3 addition have better properties than without the addition of excess Bi2O3. The relative density was raised to 98% and the grain size was increased to 3 um for the 0.98NKN-0.02BNKT ceramic with 0.3 wt.% Bi2O3 addition as shown in Fig. 5(d). In this research, Bi was introduced into 0.98NKN-0.02BNKT composition in the form of Na+ or K+. Bi3+ has cationic radii of 1. 4 Å close to that of Na+ (1.39 Å) and K+ (1.64 Å). Thus, Bi3+ can enter into the octahedral site of the perovskite structure to substitute for Na+ and K+ because of radius matching. Similar to the case of PZT-based piezoelectric ceramics, the incorporation of Bi into the perovskite structure as a donor can generate a soft effect on the electrical properties. The variation of the electrical properties with the addition of Bi2O3 can be tentatively interpreted with respect to the doping effect and microstructural evolution. When the addition amount of Bi2O3 is relatively low (≤ 0.3 wt.%), the soft doping effect on the electrical properties appears to be predominant. In the low Bi2O3 content region (≤ 0.3 wt.%), the slight increase of the electromechanical coupling factor together correspond well to the feature of a soft doping effect on the electrical properties. In the case of low Bi2O3 content (≤ 0.3 wt.%), the grain growth became remarkable. The increase of grain size favors improving the electromechanical coupling factor and the dielectric constant, which is known as grain size effect. The degradation of the dielectric constant and the electromechanical coupling factor in the high Bi2O3 content region (> 0.3 wt.%) may be attributed to the decrease of the grain size in the microstructure. Therefore, it is likely that the doping and microstructural effects contribute to the electrical properties of the ceramics in a cooperative way. Conclusion The specimens of 0.98NKN-0.02BNKT ceramics added with Bi2O3 maintain an orthorhombic phase. It indicates that the addition of small amounts of Bi2O3 did not give rise to an obvious change in crystal structure. The electromechanical coupling coefficients of the planar mode kp and kt of 0.98NKN-0.02BNKT ceramics reach 0.40 and 0.47, respectively. For 0.98NKN-0.02BNKT ceramics by doping 0.3 wt% Bi2O3 the electromechanical coupling coefficients of the planar mode kp and the dielectric constant reach 0.50 and 0.53, respectively. References [1] G. Shirane, R. Newnham, and R. Pepinsky: Phys. Rev. Vol.96, (1954), p.581. [2] H. Birol, D. Damjanovic, and N. Setter: J. Eur. Ceram. Soc. Vol.26, (2006), p.861. [3] Y. Guo, K. Kakimoto, and H. Ohsato: Jpn. J. Appl. Phys. Vol.43, (2004), p.6662. [4] Y. Guo, K. Kakimoto, and H. Ohsato: Appl. Phys. Lett.Vol. 85, (2004), p.4121. [5] Y. Guo, K. Kakimoto, H. Ohsato: Mater. Lett. Vol.59, (2005), p.241. [6] Y. Guo, K. Kakimoto, and H. Ohsato: Solid State Commun. Vol.129, (2004), p.279. [7] R. C. Chang, S. Y. Chu, Y. F. Lin, and Y. P. Wong: J. Eur. Ceram. Soc. Vol.27, (2007), p.4453. [8] C. H. Wang: Jpn. J. Appl. Phys. Vol.48, (2009), p.041403. [9] C. H. Wang: J. Ceram. Soc. Jpn. Vol.117, (2009), p.680 [10]. C. H. Wang: J. Ceram. Soc. Jpn. Vol.116, (2008), p.632. [11] C. H. Wang: Advanced Materials Research, Vol.239-242, (2011), p.3240. [12] C. H. Wang: J. Ceram. Soc. Jpn Vol.117, (2009), p.693. [13] Anon.: Proc. IRE. Vol.49, (1961), p.1161. [14] T. Senda, and R. C. Bradt: J. Am. Ceram. Soc. Vol.73, (1990), p.106.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 8-12 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.8

Effects of Grain Size and Lubricating Conditions on Micro Forward and Backward Hollow Extrusion of Brass Chao-Cheng Changa, Cheung-Hwa Hsub and Jian-Cheng Laic Department of Mold and Engineering, National Kaohsiung University of Applied Sciences, 415 Chien Kung Road, Kaohsiung 807, Taiwan a

[email protected], [email protected], [email protected]

Keywords: Micro metal forming, Grain size, Friction.

Abstract. Grain size and lubricating conditions influence material flow behaviours in micro metal forming processes. In this study, the brass (JIS C2700) tubes with 1.1 mm outer diameter and 0.5 mm inner diameter were treated by annealing at 400 ºC, 500 ºC and 600 ºC to obtain various microstructures with the grain sizes of 20 µm, 34 µm and 80 µm, respectively. The treated tubes were machined and grounded to be 0.6 mm length specimens for the experiments of micro forward and backward hollow extrusion. Three lubricating conditions, which were dry, full and punch lubricated conditions, were carried out in the experiments. By comparing the upper cup height and rod length of the extruded specimens with the calibration curves established by finite element simulations, it is possible to estimate the friction factors in the processes. The results show that the dry conditions lead to stronger friction effects and thus larger friction factors. Moreover, the friction factor increased with grain size and stroke for all conditions. Introduction A trend of product miniaturization and functional integration significantly increases the demands of micro metal parts over the past few years. Metal parts may be produced by a metal forming process since its high productivity, high material utilization and good mechanical properties makes the technology suitable for mass production. However, the knowledge of conventional metal forming cannot be simply transferred to micro scale processes since the material behaviours and process are strongly affected by so-called size effects [1]. The size effects influence not only material flow but also friction. Engel [2] reported that the friction can be increased significantly when the metal forming process is scaled down to micro dimensions. The phenomenon is probably caused by an increase in the area of the open lubricant pockets in which the lubricant escapes as pressure increases at contact interface. A study of size effect on micro deformation using the simple compression and ring tests at micro scale also revealed the area fraction of open lubricant pocket were increased with the decrease of specimen size. In addition, inhomogeneous material flow clearly occurred with miniaturization [3, 4]. One of the critical factors influencing the material flow in the micro metal forming process is the ratio of grain size to the specimen dimensions. Only a few grains might be located in the region of deformation at micro scale. Therefore, the orientation, size or position of a single grain could significantly affect the process and result in inhomogeneous flow behaviour. Rosochowski et al. [5] used the equal channel angular extrusion (ECAE) to prepare pure aluminium with refine-grained microstructure for backward extrusion experiments at micro scale. The results showed that the grain refinement led to a more uniform structure and better shape representation. Chang and Lin [6] also reported that a grain refinement of copper resulted in a more homogeneous flow which had a similar effect to an increase in forming temperature. Grain size clearly affects material flow in micro metal forming processes and the area fraction of open lubricant pocket is increased with miniaturization. However, the effect of grain size on friction has not been fully understood. To investigate the effect of grain size on friction in the micro metal forming process, this study used annealing techniques to prepare brass specimens with various grain sizes for the experiments of micro forward and backward hollow extrusion. Three lubricating conditions, namely dry, full and punch lubricated conditions, were taken into account in the experiments. By comparing results of simulations and experiments, the friction factors for each condition were estimated.

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Grain Size The brass (JIS C2700) tubes with 1.1 mm outer diameter and 0.5 mm inner diameter were used as the billets for the experiments of micro forward and backward hollow extrusion. The tubes were treated by annealing at 400 ºC, 500 ºC and 600 ºC in vacuumed conditions to obtain various microstructures with grain sizes, 20 µm, 34 µm and 80 µm, respectively. Table 1 shows the micrographs and mean grain sizes of the treated tubes. Simulations of the extrusion processes require the true stress-strain curves. However, it is difficult to obtain the curves from the tubes. The study employed the same annealing conditions as those for the tubes to treat cylindrical specimens of brass. The cylindrical specimens were then used in simple upsetting tests to obtain the stress-strain curves as presented in Fig. 1. A comparison of the hardness between the tube and cylindrical specimens (see Fig. 2) shows the above approach was able to provide a good correlation in strength. Table 1 Micrograph and grain size of the tube Annealing temperature (ºC) Grain size (µm)

400

500

600

20

34

80

Micrograph

Fig. 1 Stress-strain curves

Fig. 2 Hardness comparison

Experimental Setup The annealed tubes with 1.1 mm outer diameter and 0.5 mm inner diameter were machined as rings with 0.6 mm length for experiments of the micro forward and backward hollow extrusion. The punch and die components are presented in Fig. 3. The experiments were carried out using a precision press and the punch speed was 0.01 mm/s for all lubricating conditions. The main dimensions of the extruded specimens are given in Fig. 4. Three lubricating conditions, namely dry, full and punch lubricated conditions, were taken into account in the experiments. For lubricated conditions, molybdenum disulphide was used. Three strokes of the punch were performed to produce various deformations of the specimens. By comparing the cup height (Hc) and rod length (Lr) with the calibration curves established by simulations, friction factors can be estimated.

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Fig. 3 Die components

Fig. 4 Main dimensions of extruded specimen

Calibration Curves The study employed a finite element software DEFORM 3D to simulate the micro forward and backward hollow extrusion of brass. The specimen and die were treated as plastic and rigid, respectively. The friction at the contact interface was considered by Tresca friction law, τf = mk, in which τf is friction stress, k is the strength in shear and m is friction factor. Two friction factors for the workpiece-die interface, 0.02 and 0.5, and five friction factors for the workpiece-punch interface, 0.02, 0.1, 0.2, 0.3, 0.4 and 0.5, were tested in simulations. By using the Hc /Lr against Lr, a set of calibration curves for different friction factors was established. Results and Discussions Deformation. A worse lubricating condition results in a longer rod as shown in Fig. 5(a). The rod length decreased as the lubricating conditions became better from dry, partial lubricated (punch lubricated) and fully lubricated conditions. The phenomena also occurred in the cases of 34 µm and 80 µm as shown in Figs. 5(b) and (c). The rod length (Lr) of the extruded specimens was affected by lubricating conditions. In addition, the rod length slightly increased with grain size. An increase in grain size has a similar influence to a decrease in lubrication. The reason could be that larger grains cause less homogeneous flow and form more areas with the open pocket conditions in which the lubricant is difficult to remain at the contact interface. Friction Factor. By measuring the cup height (Hc) and rod length (Lr) of the extruded specimens and compare with the calibration curves, estimated friction factors were in a range from 0.1 to 0.35 as presented in Fig. 6. Table 2 lists the estimated friction factors at different strokes for each lubricating condition. The dry conditions led to stronger friction effects and thus larger friction factors. Moreover, the friction factor increased with grain size and stroke for all lubricating conditions. Conclusions This study investigated the effects of grain size and lubricating conditions on the micro forward and backward hollow extrusion of brass. The study used the brass tubes treated by annealing at different temperatures to obtain various microstructures with different grain sizes. The treated tubes were then used in the experiments under dry, full and punch lubricated conditions. By comparing the upper cup height and rod length of the extruded specimens with the calibration curves, the friction factors were estimated. The results show that the dry conditions lead to stronger friction effects and thus larger friction factors. The friction factor increased with grain size and stroke for all lubricating conditions.

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Stroke (mm)

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Lubricating condition Dry

Punch Lubricated

Full

0.5 Aa

Ab

Ac

Ba

Bb

Bc

Ca

Cb

Cc

0.6

0.7

(a) 20µm Stroke (mm)

(a) 20µm

Lubricating condition Dry

Punch Lubricated

Full

0.5 Da

Db

Dc

Ea

Eb

Ec

Fa

Fb

Fc

0.6

0.7

(b) 34µm

(b) 34µm Stroke (mm)

Lubricating condition Dry

Punch Lubricated

Full

0.5 Ga

Gb

Gc

Ha

Hb

Hc

0.6

(c) 80µm

0.7 Ia

Ib

(c) 80µm

Fig. 5 Extruded specimens

Ic

Fig. 6 Calibration curves (line types for various die friction factors, line colors for various punch friction factors)

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Table 2 Estimated friction factors at different strokes 20 34 80 Grain Size(µm) Stroke(mm) 0.5 0.6 0.7 0.5 0.6 0.7 0.5 0.6 Picture in Fig. 5 Aa Ba Ca Da Ea Fa Ga Ha Dry p 0.2 0.3 0.3 0.2 0.3 0.35 0.2 0.3 m 0.1 0.1 0.2 0.15 0.2 0.3 0.2 0.2 Picture in Fig. 5 Ab Bb Cb Db Eb Fb Gb Hb p 0.1 0.1 0.2 0.1 0.1 0.2 0.1 0.2 Full m 0.02 0.02 0.1 0.02 0.1 0.2 0.1 0.1 Picture in Fig. 5 Ac Bc Cc Dc Ea Fc Gc Hc Punch p 0.1 0.1 0.2 0.1 0.2 0.25 0.1 0.2 Lubricated m 0.1 0.1 0.15 0.1 0.15 0.25 0.15 0.15 Note: p for punch friction factor. m for die friction factor

0.7 Ia 0.35 0.3 Ib 0.25 0.25 Ic 0.25 0.3

References [1] M. Geiger, M. Kleiner, R. Eckstein, N. Tiesler, U. Engel: CIRP Annals-Manufacturing Technology Vol. 50 (2001), p. 445 [2] U. Engel: Wear Vol. 260 (2006), p. 265 [3] W. Chan, M. Fu, J. Lu: Materials & Design Vol. 32 (2011), p. 198 [4] J. Deng, M. Fu, W. Chan: Materials Science and Engineering: A Vol. 528 (2011), p. 4799 [5] A. Rosochowski, W. Presz, L. Olejnik, M. Richert: The International Journal of Advanced Manufacturing Technology Vol. 33 (2007), p. 137 [6] C.C. Chang, J.C. Lin: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture Vol. 226 (2012), p. 183

Applied Mechanics and Materials Vols. 479-480 (2014) pp 13-19 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.13

Effect on Vibroengineering of Material Deterioration in a Scale-down Reinforced Concrete Containment Vessel Specimen Wei-Ting Lin1,2,a, Yuan-Chieh Wu1,b, Tung-Liang Chu1,c and An Cheng2,d 1

Institute of Nuclear Energy Research, Atomic Energy Council, Executive Yuan, Taoyuan 325, Taiwan 2

Department of Civil Engineering, National Ilan University, Ilan 260, Taiwan

a

b

c

d

[email protected], [email protected], [email protected], [email protected]

Keywords: Natural Frequency Spectra, Accelerated Corrosion Test, Resistivity.

Abstract. This study is aim to evaluate the natural frequency variation of the scale-down reinforced concrete containment vessel specimen under accelerated corrosion conditions. A plastic ring was sealed around the perimeter of the cylindrical vessel bottom with the 3.5 % NaCl solution to achieve the accelerated corrosion test. Concrete resistivity, open circuit potential, corrosion rate and natural frequencies were tested and discussed in this study. Test results presented that the accelerated corrosion method with a direct 60 voltage applied was a suitable method for estimating and accelerating the concrete vessel specimen. Therefore, the changes in natural frequencies were consistent with the material degradation of the concrete vessel specimen. The natural frequencies decreased with the increasing corrosion rate or decreasing resistivities for the specimen at higher mode, but would be no change for the specimen at the natural frequency of 1st mode. Introduction Concrete is one of the most widely used building materials in civil and architecture structures for many years. However, the reinforced concrete structures subject to severe environment are liable to rebar corrosion. It led to numerous serious problems throughout the world by the corrosion of metals in concrete. Corrosion is the degradation of the material properties over time due to environmental effects [1]. Therefore, the degradation of concrete is considered a key factor in the durability of reinforced concrete structures and a major concern for civil engineers [2]. Inspection, monitoring, repair and strengthening for reinforced concrete structures are also an important discussion in civil and structural engineering field. The reinforced concrete containment vessel (RCCV) is seismic category I structures in nuclear power plant with advanced boiling water reactor (ABWR). The primary containment vessel contains the reactor primary systems (reactor pressure vessel, etc.) and prevents the spread of radioactivity released. In addition, the RCCV is used a cylindrical vessel made of reinforced concrete wall and steel liner to prevent unclear leaks and it is an important structural element for resisting the seismic loading. In 2011, the Tohoku earthquake and subsequent tsunami struck northern Japan and caused crucial damages to the structures of nuclear power plants and nuclear disaster triggered immediately [3,4]. Therefore, the safety of these nuclear power plants is a matter of grave concern to authorities and the general public. In Taiwan, the nuclear power stations are situated near the sea due to the requirement of cooling capacity. Nuclear power plants in marine environment caused reinforced concrete deterioration and its long-term performance was dominated by structural deterioration [5,6]. The long-term performance of the plants is largely a function of its deterioration level. In addition, many previous researchers have studied on the elevation of either seismic capacity or structural safety in concrete containment structure individually; however, few studies have evaluated the effect of material degradation in nuclear related structures. This study is aim to clarify the variation of natural frequency in a deteriorated scale-down RCCV specimen with rebar corrosion. Corrosion test, concrete resistivity test and frequency measurement were used and compared in this study.

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Experiment Specimens. The scaled-down RCCV specimen consisted of a square basemat and cylindrical vessel with a hollow. The dimension of the basemat was 1760 mm length and 250 mm depth, the cylindrical vessel had an outer diameter of 1000 mm, a thickness of 100 mm and a height of 2400 mm. Also, the net weight of the RCCV specimen was approximately 6000 kg. In addition, the normal concrete of 210 kg/cm2 was used in accordance with ASTM C211.1 and the embedded #3 rebar was made of medium carbon steel following the specification of ASTM A615. The appearance and details of RCCV specimen are shown in Figs.1 to 2, respectively.

Fig. 1. Appearance of the RCCV Specimens

Fig. 2. Drawing of the RCCV Specimens

Testing methods. The concrete resistivity of specimens was measured using a four-probe device and tests were carried out on saturated surface-dry specimens. For accelerated corrosion test, the corrosion cell was connected so that #3 rebar acted as working electrode, saturated calomel electrode as reference electrode, and the titanium mesh as counter electrode. A direct voltage with a potential of 60 V was applied and the open circuit potential (OCP) and corrosion rate was measured using a Nichia NP-G100/ED potentiostat at a 24-hour interval. The specimen was immersed in 3.5 % NaCl solution to achieve the accelerated corrosion test. The polarization resistance (Rp) is generally related to a uniform corrosion rate and the polarization resistance measurements are accurate and rapid. The polarization resistance of the reinforcing steel is defined as the slope of the potential-current density curve at the zero current point when the rate of polarization is close to zero: ∂ ( ∆E ) Rp = [ ]i =0,dE dt →0 ∂i (1) 2 where Rp is the polarization resistance (KΩ-cm ), ∆E is the applied potential (mV) and i is the current density (mA/cm2). In this study, the applied external potential was increased or decreased gradually within ±10 mV at an interval of 20 mV and the corresponding currents were measured. The polarization resistances were then calculated using the slope of the potential-current density curve. In addition, the corrosion current density (icorr) can be estimated from Stern-Geary equation.   1 βaβc B icorr =  × =   2.303(β a + β c ) R p R p (2) where icorr is the corrosion current density, and βa, βc are the anodic and cathodic Tafel slopes, respectively. Rp is the polarization resistance. For iron, the constant, B, is assumed to be 26 mV in evaluating corrosion rate of steel for actively corroding system and 52 mV for passively system. After the corrosion current density is obtained, the instantaneous corrosion rate (r) can be calculated from Faraday’s law as follows: i a r = corr × n F (3)

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where F is Faraday’s constant (96500 coulombs/equivalent), n is the number of equivalent exchange, and a is the atomic weight. The natural frequency of RCCV specimen before and after accelerated corrosion test was measured using a Piezotronics Model 086D20 impact hammer kits. The impact hammer kits used in this study were included one impact hammer, three accelerometers with 1 degree of freedom, one displayer and one dynamic signal analyzer, as shown in Fig. 3. Three accelerometers were attached on the surface of the RCCV specimen at the elevation of 150 cm, which was marked in red point and shown in Fig. 4. The hammer was hit on the RCCV specimen at the elevation of 120 cm (blue point no. 1), 60 cm (blue point no. 2), 30 cm (blue point no. 3) and 90 cm (blue point no. 4), respectively. In addition, the natural frequencies of modes at the frequency range from 0 to 500 Hz were obtained from the peak values of the recorded natural frequency spectra (Fig. 5).

(a) impact hammer (b) accelerometer (c) dynamic signal analyzer Fig. 3. Appearance of the impact hammer kits

Fig. 4. Illustration of the frequency measurement

Fig. 5. Intercepting image under frequency measuring

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For cylindrical vessel, all data from the resistivity and OCP testing were measured at various elevations (0 cm, 30 cm, 60 cm, 90 cm, 120 cm and 150 cm) and those were the average of eleven values at each elevation as shown in Fig. 4. In addition, the basemat, divided into inner ponding zone (immersed in 3.5 % NaCl solution) and outer ponting zone, was also measured the resistivity and OCP in this study.

Results and Discussion Resistivity measurement. The concrete resistivities of RCCV basemat and vessel are illustrated in Fig. 6, in which the resistivity of the basemat at the inner ponding zone was lower than that at the outer ponding zone. The basemat with a resistivity between 10 and 20 kΩ-cm was like to be a high corrosion rate [7]. A plastic ring was sealed around the perimeter of the cylindrical vessel bottom, an inner ponding zone. The accelerated method led the chloride ions migration effectively. As shown in Fig. 6 (b), the resistivity of the vessel specimen decreased with the measuring elevation decreased significantly due to the immersion of NaCl solution. The vessel specimen above 30 cm elevation had a higher resistivity exceeded 20 kΩ-cm, which indicated the lower corrosion rate occurred in those zones. 100

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(a) basemat (b) cylindrical vessel Fig. 7. OCP versus Immersion time curves

OCP measurement. According to ASTM C876, when the OCP is between 0 and -127mV (SCE), the probability ere is less than 10 % that reinforcing may corrode. When the potential ranges from -127 mV to -276 mV (SCE), corrosion probability is uncertain and corrosion probability may be higher than 90 % for OCPs higher than -276 mV (SCE). For the 24 hours accelerated immersion in Fig. 7 (a), the OCP curves of the RCCV basemet dropped rapidly over -450 mV and hightend the

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corrosion probability of reinforcing steel. The OCP curves of the cylindrical vessel specimens are illustrated in Fig. 7 (b). It indicated that the OCP of the measuring point at 0 cm elevation dropped rapidly from -300 mV to -600 mV and cracks on the surface of the concrete can be found. In addition, the OCP of the vessel specimen above 60 cm elevation kept the potential ranges between -150 mV and -250 mV and the potential reached steady value. Therefore, the superstructure of the cylindrical vessel specimen had lower corrosion probability and was consistency with the results of concrete resistivity. Corrosion rate measurement. The relationship between corrosion rate and immersion time is shown in Fig. 8. After 24 hours of accelerated corrosion test, the corrosion rate of the scale-down RCCV specimen was up to 42 µm/yr with a 60 V potential voltage. The corrosion rate increased significantly with an increase in accelerated immersion time and reached steady value up to 70 µm/yr. It also indicated that the RCCV specimen was like to be a high corrosion rate [7] in this accelerated method. The amount of chloride ions had reached to the critical value. This means that the passive protective film on the rebar had been totally spoiled, and thus the corrosion rate of the rebar increased abruptly. Therefore, the accelerated corrosion method is suitable for carrying out the corrosion evaluation of the scale-down RCCV specimen. 80

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Fig. 8. Corrosion rate versus Immersion time curves

Natural frequency measurement. The natural frequencies generated by impact hammer method and natural frequency spectra for three directions are shown in Figs. 9 to 12, respectively. Comparing to the specimen before accelerated corrosion, the natural frequency of 1st mode became steadily in those measuring points (point 1 to point 4) for the corroded specimen. For the natural frequency of 2nd mode to higher mode, this was apparent in the changes in the natural frequencies of the corroded specimen. It was also observed in general the trend of the magnitude of the percentage change in natural frequencies increased with the higher modes. Similar trends were also reported in the previous study [8]. In addition, the variations of the natural frequency spectra at the measuring point 3 and 4 in Y direction became more obvious. It might due to the greater loss in structural stiffness or more serious corroded rebar debonding. In conclusion, the rebar corrosion of the scale-down RCCV specimen caused slight changes to the natural frequencies and structural capacity.

(a) X-direction (b) Y-direction (c) Z-direction Fig. 9. Natural frequency spectra of RCCV specimen at point 1

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(a) X-direction (b) Y-direction (c) Z-direction Fig. 10. Natural frequency spectra of RCCV specimen at point 2

(a) X-direction (b) Y-direction (c) Z-direction Fig. 11. Natural frequency spectra of RCCV specimen at point 3

(a) X-direction (b) Y-direction (c) Z-direction Fig. 12. Natural frequency spectra of RCCV specimen at point 4

Conclusions The corrosion measurements and an impact hammer test were performed for evaluation the effect on the modal properties of the degraded scale-down RCCV specimen. Test results indicated that the specimen in ponding zones with NaCl solution had lower resistivity, greater corrosion probability and higher corrosion rate compared to the specimen without corrosion. The accelerated corrosion method described here is suitable for evaluating the corrosion behavior of the scale-down RCCV specimens. Generally, the results also presented that rebar corrosion caused slight charges in natural frequencies and the variations of the natural frequencies increased with the higher modes.

Acknowledgement This support of the National Science Council (NSC) under the Grant NSC102-3113-P042A-009 is gratefully acknowledged.

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References [1] E. Güneyisi, M. Gesoğlu, F. Karaboğa, K. Mermerdaş: Compos. Pt. B. Eng. Vol. 45 (2013), p. 1288. [2] R.J. Flatt, N. Roussel, C. R. Cheeseman: J. Euro. Ceram. Soc. Vol. 32 (2012), p. 2787. [3] F. Tajima, J. Mori, B. L.N. Kennett: Tectonophysics Vol. 586 (2013), p. 15. [4] I. Takewaki, K. Fujita, S. Yoshitomi: Eng. Struct. Vol. 19 (2013), p. 119. [5] B.A. Emilio, B. Philippe, C. Alaa, S.S. Mauricio: Struct. Saf. Vol. 31 (2009), p. 54. [6] C.L. Lee, R. Huang, W.T. Lin, T.L. Weng: Mater. Des. Vol. 37 (2012), p. 28. [7] J.P. Broomfield: Corrosion of Steel in Concrete: Understanding, Investigation and Repair (Spoon Press 2003). [8] H.A. Razak, F.C. Choi: Eng. Struct. Vol. 23 (2001), p. 1126.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 20-24 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.20

Preparation and Investigation of Co-dispersed MWCNT Buckypaper for the Microwave Absorption Lakshmanan Saravanan1,a, Jih-Hsin Liu1,2,b, Hsin-Yuan Miao1,2,c,* and Li-Chih Wang1,3,d 1

Tunghai Green Energy Development and Management Institute, Tunghai University, Taichung, 40704 Taiwan 2

Department of Electrical Engineering, Tunghai University, Taichung, 40704 Taiwan

3

Department of Industrial Engineering and Enterprise Information, Tunghai University, Taichung, 40704 Taiwan

a

[email protected], [email protected], *[email protected], [email protected]

Keywords: MWCNT, Buckypaper, XRD, Transmission coefficient, Microwave absorption

Abstract. The paper deals with the preparation of cobalt nanoparticles dispersed multi walled carbon nanotube buckypaper by the dispersion and filtration method to study the electromagnetic (microwave) absorption properties. From the X-ray diffraction the crystallite size of the cobalt nanoparticles of 33.04 nm was calculated. FESEM image clearly indicates the presence of cobalt nanoparticles in the buckypaper. Microwave-absorbing properties were investigated in terms of measuring the transmission coefficient (S21) with MWCNT-buckypaper as the absorber using microstrip line in a frequency range of 2–20 GHz. Compared to the pure buckypaper the absorption peak of the Co-CNT composites move to the lower frequency by dispersing the Co nanoparticles into the MWCNT-BP. Introduction There has been a growing and widespread interest in microwave-absorbing material technology because of their civil and military applications. The development of radar-absorbing materials (RAM) that work in the radar frequency (i.e. GHz) had obtained a big momentum due to their potential applications in the stealth technology of aircrafts and microwave dark-room and protection [1]. Microwave absorbing material (MAM) is a kind of functional material that can absorb electromagnetic (EM) wave effectively and convert this energy into heat or make EM wave disappear by interference. It is worth noting that compared to conventional metal-based EMI shielding materials, using carbon-based conducting composites is advantageous for satellite applications because of their light weight, small thickness, and flexibility [2]. As a lightweight MW absorber, the MWCNTs have been considerably studied for their good compatibility and small density [3]. For the lightweight EMI shielding performance and corrosion resistance, purified CNTs with less metal impurity are desired. In the earlier, CNTs filled with ferromagnetic metals have potential applications in anisotropic magnetic responses as high density magnetic recording media [4], microwave absorption [5,6] and so on. Energy absorption into materials from microwave fields occurs by three main methods: dipolar, magnetic and conductive losses. However, most of the materials used as microwave absorbers, only exhibit dielectric losses, while a few display both dielectric and magnetic losses. The way these properties change with frequency reflects the performance of the absorber [7]. It has been reported earlier that the enhancement of MW-absorbing properties of CNTs by the incorporation of magnetic metal particles such as Co [8,9], Fe [10] and Ni [11]. Buckypaper (BP) an entangled mat of CNTs which is a highly porous structure is reported to be an interesting material composite in several domains of application. In this work, we present the doping of magnetic metal cobalt in the flexible MWCNT buckypaper, by the direct dispersion and filtration method. The structural, morphological and microwave (MW) absorption characteristics for the prepared Co-BP composites were evaluated. The transmission coefficient (S21) studies were

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carried out in the frequency range of 1–18 GHz. The observed minimal transmission coefficient indicated that the Co doped BP displays good microwave absorption properties for potential application as wide-band electromagnetic wave absorbers. Experimental Techniques Synthesis of Cobalt Nanoparticles. Cobalt (Co) nanoparticles prepared by the thermal evaporation method, was deposited inside the chamber under a relative pressure of 5 x 10-5 torr in the Ar atmosphere (180-220 mtorr). The cobalt granules (99.995 %) were purchased and used as a metal source. The deposited cobalt nanoparticles (NPs) were collected from the walls of chamber. Preparation of Cobalt Doped Buckypaper. The cobalt doped MWCNT-buckypaper was prepared by the direct dispersion and filtration method. The modified procedure for the fabrication of BP was followed from the earlier reports [12,13]. The Co NPs and CNTs were dispersed in DI water in separate beakers by the ultrasonication (20 KHz, 63 W). Both the suspension was added together slowly to form mixed suspension. This suspension then stabilized by a water soluble, non-ionic surfactant Triton-X-100 via ultrasonication and was vacuum filtered by a nylon membrane, to form Co doped buckypaper (Co-BP). The sample was placed in the bath of isopropyl alcohol (IPA) to get the surfactant free sample. After filtering and drying process, the paper was peeled carefully from the membrane resulting in a thin sheet network of flexible Co doped BP with the film thickness of ~100 µm. The similar procedure followed for different weight percentage (20 % and 40 %) of Co. The pure MWCNT buckypaper was also made for comparison. Measurement Techniques. The surface morphology was analyzed by field emission scanning electron microscope (FE-SEM) with JEOL JSM-7000F. The Low temperature electrical resistivity measurement was carried out by the standard programmable DC voltage/current detector four-point probe method in the temperature range from 50 to 300 K. The MW absorption measurement was carried out in the frequency range of 1–20 GHz with the apparatus of ANRITSU 37347A vector network analyzer and the two port waveguide to find the value of transmission coefficient (S21) with the use of microstrip line. Results and Discussion Structural and Morphological Analysis. The X-ray diffraction pattern for the synthesized cobalt nanoparticles was shown in Fig. 1. The crystallite size of cobalt nanoparticles with the diameter of 33.04 nm is calculated using the Scherer’s formula with the high intense peak (111) shown in the inset of Fig. 1. The FE-SEM images of the pure and cobalt doped buckypaper were shown in Fig. 2 (a) and (b) respectively. The morphology of the pure MWCNT buckypaper in the Fig. 2 (a) illustrates the porous and random entanglement of carbon nanotubes network structures. It can also be clear from the surface structure of Co-BP in Fig. 2 (b), compared to pure BP that cobalt nanoparticles homogeneously dispersed in the thin sheet of CNT network and some agglomerated NPs appears on the surface of the BP. Electrical Resistivity. The low temperature (LT) electrical resistivity measurement was shown in Fig. 3 (a). It was observed that, the resistivity for all the samples found increases at low temperature and decreases at high temperature which confirms the semiconducting behavior of multiwalled CNT buckypaper. It was also observed that, after inclusion of cobalt nanoparticles into the buckypaper the electrical resistivity decreases both for 20 % and 40 % cobalt concentrations, compared to the pure BP. At 50 K the resistivity value reaches from 6.54 x 10-4 for pure BP to 5.62 x 10-4 Ω-m for 40 wt. % of Co doping.

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Fig. 1 X-ray diffraction pattern for cobalt nanoparticles

Fig. 2 FE-SEM images of (a) Pure buckypaper (b) Co doped buckypaper Transmission Coefficient (S21) Measurement. When the electromagnetic waves travel into a material they can be either reflected, absorbed by the material or can travel through the material. The materials used as MW absorbers, mostly exhibit dielectric losses, while a few materials display both dielectric and magnetic losses. The manufacture of microwave absorbing materials involves the use of compounds capable of generating dielectric and/or magnetic losses when impinged by an electromagnetic wave. If we restrict the measurement to only the complex reflection coefficient (S11) and the transmission coefficient (S21) of a two-port network, the architecture and the calibration task can be drastically simplified. The use of microstrip is a convenient and versatile transmission-line technology for fabricating compact band-pass filters for wireless communications applications. The transmission coefficient (S21) plot for all the samples was shown in Fig. 3 (b). From the Fig. 3 (b), we reveal the maximum value of absorption (> 90%) for 40 wt. % of Co/BP composite and the observed S21 value is about -9.57 dB at 9.79 GHz and for 20 % the S21 value is -9.38 dB at 9.79 GHz. At low frequency the observed transmission coefficient value is -6.66 dB at 4.38 GHz for 20 % and for 40 % it is -6.59 dB at 4.25 GHz. At higher frequency the S21 value is -6.34 dB and -7.07 dB respectively for 20 % and 40 % at 17.89 GHz. In the microwave absorbing material which contains an electromagnetic loss substance and dipoles, these dipoles acts as electron couples to generate an inductive current in the electromagnetic field. The induced current then causes a loss current and energy dissipation. This is the main mechanism in microwave attenuation. Either only

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the magnetic loss or only the dielectric loss may induce weak microwave absorption due to the imbalance of the electromagnetic match [14]. Zhao and co-workers reported that the microwave enhancement absorption of the Co-filled CNT composites was attributed to both dielectric and magnetic losses [9]. It was also reported that for CNTs/Co nanocomposites, the microwave absorption is improved by the better match between the dielectric loss and magnetic loss, originates from the combination of paramagnetic CNTs and ferromagnetic Co nanoparticles [8]. Dispersing Co NPs on the CNTs surface is also beneficial to improve microwave absorption due to interface polarization between the Co NPs and CNTs.

Fig. 3 (a) Low temperature resistivity (b) Transmission coefficient (S21) for the pure and cobalt doped buckypapers Summary The cobalt NPs synthesized by thermal evaporation method were successfully doped into the buckypaper via direct dispersion and filtration method for two different wt. % of Co. XRD pattern confirms the Co nanoparticles with the crystallite size of 33.04 nm calculated by Scherer’s equation. Low temperature resistivity analysis reveals the semiconducting behavior of CNT networks for all the samples. Increasing the cobalt composition to 40 wt.% in the BP illustrates decrease in the resistivity compared to pure BP. We demonstrate the transmission coefficient (S21) measurement by the two-port network analyzer for all the samples of Co/BP composites in the microstrip line with BP as the absorber. It was found that the Co doped MWCNT-BP exhibit good microwave absorption than the pure CNTs and Co NPs. The enhancement in the microwave absorption is attributed to the better match between dielectric loss and magnetic loss. The experiment results indicate that CNTs mixed Co nanoparticles are good candidates for preparing efficient microwave absorbents with thin thickness and light weight. Acknowledgments This work is supported by the program of Global Research and Education on Environment and Society (GREEnS), Tunghai University, Taiwan and by the National Science Council, Republic of China (NSC101-2221-E-029-006 and NSC101-2221-E-029-010).

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References [1] Horvath, M.P. Microwave applications of soft ferrites (2000) J. Magn. Magn. Mater., 215, pp. 171-183. [2] Chung, D.D.L. Carbon materials for structural self-sensing, electromagnetic shielding and thermal interfacing (2012) Carbon, 50 (9), pp. 3342-3353. [3] Deng, L.J., Han, M.G. Microwave absorbing performances of multiwalled carbon nanotube composites with negative permeability (2007) Appl. Phys. Lett., 91 (2), pp. 023119-023121. [4] Chou, S.Y., Wei, M.S., Kraus, P.R., Fisher, P.B. Single‐domain magnetic pillar array of 35 nm diameter and 65 Gbits/in.2 density for ultrahigh density quantum magnetic storage (1994) J. Appl. Phys., 76 (10), pp. 6673-6675. [5] Zou, T., Li, H., Zhao, N., Shi, C. Electromagnetic and microwave absorbing properties of multiwalled carbon nanotubes filled with Ni nanowire (2010) J. Alloys Compd., 496 (1-2), pp. L22L24. [6] Che, R.C, Peng, L-M., Duan, X.F., Chen, Q., Liang, X.L. Microwave Absorption Enhancement and Complex Permittivity and Permeability of Fe Encapsulated within Carbon Nanotubes (2004) Adv. Mater., 16 (5), pp. 401-405. [7] Bigg, D.M. Conductive polymeric compositions (1977) Polym. Eng. Sci., 17 (12), pp. 842-847. [8] Sui, J., Zhang, C., Li, J., Yu, Z., Cai, W. Microwave absorption and catalytic activity of carbon nanotubes decorated with cobalt nanoparticles (2012) Mater. Lett., 75, pp. 158-160. [9] Zhao, D.L., Zhang, J.M., Li, X., Shen, Z.M. Electromagnetic and microwave absorbing properties of Co-filled carbon nanotubes (2010) J. Alloy. Compd., 505 (2), pp. 712-716. [10] Vovchenko, L., Matzui, L., Oliynyk, V., Launetz, V., Normand, F.L. Anomalous microwave absorption in multi-walled carbon nanotubes filled with iron (2012) Physica E, 44 (6), pp. 928931. [11] Wen, F., Zhang, F., Liu, Z.Y. Investigation on Microwave Absorption Properties for Multiwalled Carbon Nanotubes/Fe/Co/Ni Nanopowders as Lightweight Absorbers (2011) J. Phys. Chem. C, 115 (29), pp. 14025-14030. [12] Wang, Z., Liang, Z., Wang, B., Zhang, C., Kramer, L. Processing and property investigation of single-walled carbon nanotube (SWNT) buckypaper/epoxy resin matrix nanocomposites (2004) Composites Part A, 35 (10), pp. 1225-1232. [13] Chen, Y.W., Miao, H.Y., Zhang, M., Liang, R., Zhang, C., Wang, B. Analysis of a laser postprocess on a buckypaper field emitter for high and uniform electron emission (2009) Nanotechnology, 20 (32), pp. 325302-325309. [14] Che, R.C., Peng, L.M., Duan, X.F., Chen, Q., Liang, X.L. Microwave Absorption Enhancement and Complex Permittivity and Permeability of Fe Encapsulated within Carbon Nanotubes (2004) Adv. Mater., 16 (5), pp. 401-405.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 25-29 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.25

Direct Heating Billet within Die during Hot Forging Process Fang-Sung Cheng a and Yu-Shun Cheng b Department of Mechanical and Computer Aided Engineering, National Formosa University, 64 Wen-Hua Road, Huwei, Yunlin 632, TAIWAN a

b

[email protected], [email protected]

Keywords: hot forging, resistance heating, direct heating within die

Abstract. This paper reports a simple and effective method to increase heating efficiency and decrease heating time that renders direct heating billet within die using resistance heating system during hot forging process. The apparatus employs resistance equipment set into the forging die, and the billet was directly resistance heating by the forging die. Base on the approach, the die as a forming condition on direct heating and forging was also researched. The result of experiments shows that the billet could be heated quickly to 1000oC in about 5 seconds and the high strength material (AISI4140) was successfully formed to the shape of bolt head. With this mechanism, the rapidly heating and isothermal deformation during the hot forging process can be achieved. Introduction For aerospace and automobile industry, to reduce the weight of the transport and thus energy consumption, the proportion of high specific strength materials used is gradually increasing. Recently, to forming high specific strength materials have become the most important issues in hot forging process, such as Ti-base, Ni-base and high strength steel (HSS) etc, [1]. The forming of those materials is possible at elevated temperatures with less heat dissipation. However, these metals may be very sensitive to the forming temperature. Some alloys exhibit better formability at elevated temperature but limited to a narrow temperature range [2]. In general, most high-alloy metals have poor workability. To address this tendency, the investment of manufacturing industry on the development and research of the ability for rapid heating rates and isothermal deformation during forming process also increases. Recently, the induction heating method is widely applied in precise forming of high-alloy metal. The advantages of induction heating include rapid heating rates due to minimal warm-up and hold time and less scale formation [3]. Those procedures consists in loading billets into the heating mechanism, raising their temperature up to the recommended forging temperature, removing the heated billet out, and then using the forming die to carry out forged. On the contradictory, there are three main disadvantages of the induction heating. Firstly, the heat source is still needed to remove before the forging operations that leading to the heat transfer occur before metal deformation in press. Secondly, the geometry of induction is more limitation in the dies shapes. Finally, the surface temperature is higher than the internal temperature due to the eddy current effect caused. For now, the use of resistance heating method has been developed in many fields for rapidly heating process such as high strength sheet (HSS) stamping [4], mushy state forging [5], powder forming [6] and rolling forming [7]. With this method, the raw material is clamped to copper electrodes and charged with electric currents. Heat is created via dissipation of the electrical current within the billet. From this heating method, the heating rate is fast and the distribution of temperature is uniform. Notice that the copper is usually used as an electrode. As the working temperature of raw materials is achieved, the heating of raw material is stopped and then a next step of forming is performed by separate die. However, it will cause a major problem that the forming force is increasing when the working temperature is down. Up to date, there is a limited study carried out an investigation for temperature-sensitive materials by using the direct resistance heating forming [8]. However, few

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Applied Science and Precision Engineering Innovation

investigations have been made in developing a system in the forging field which can directly heat the billet within die during the forming process. The objective in this study is to research a direct heating billet within die during hot forging process that can achieve the rapidly heating and isothermal forming. It becomes one of the most promising techniques to forming the hard and temperature-sensitive materials. In this paper, a modified spot welding machine with the temperature control was developed as a hot forging apparatus. With this apparatus, the billet was rapidly heated within die by the electrifying to increase the formability and to decrease the flow stress during the forging process. The applicability of the material of die and the temperature uniformity of billets were experimental and discussion. A series of experiments of bolt-head forming processes were also performed by using this researched system. Experimental Setup Experimental apparatus. Fig. 1 show a schematic of the direct heating billet within die using resistance method during hot forging process. The set-up of the prototype system with a resistance heating apparatus is suitable for heating billets to working temperature for a forging operation. A press machine is used as a pressure source. In this study, the voltage of the electric source used in the experiment is 12V. The forming temperatures are controlled by using a PID feedback (type: TempScan 1100), and the temperature distribution of billet were measured by using a thermocouple system (type: TempScan 1100) and an infrared thermograph. All K type thermocouples were welded directly onto the billet to guarantee a short response time.

Fig. 1 Schematic of the hot forging apparatus for direct heating billet within die using resistance method. The proposed direct heating billet within die during hot forging process includes four steps: (a) placing the billet onto the die to form a billet–die stack, which is then placed among plates of machine. A pre-pressure of 8MPa was applied by the press to obtain sufficient contact between the billet and dies for the electrifying; (b) the billet temperature is raised by the resistance heating to the desired temperature. The electric source generates the low-voltage direct current. The voltage of the electric source used in the experiment is 12V; (c) kept the electrifying to heat billet at set points and forge the billet; (d) opening the die to retrieve the forged billet. It is a simple and effective method to increase heating efficiency and decrease heating time during hot forging process. Materials and experiment parameters. In this paper, the practical applicability of the direct resistance heating billet within die was primarily presented. In order to investigate the effects of the current intensity, the geometry and material of billet on the heating temperature, the heating process prior to forming was researched at first. The die having 30 mm in diameter with 20 mm in height is made of SKD61. There are three geometries of billet and three materials of billet were used for comparing the effects of the heating temperature. Two different voltage intensities (12V and 18V) were also experimented to compare the heating rates with a pre-pressure of 8MPa. The experiment

Applied Mechanics and Materials Vols. 479-480

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temperature was 1000oC. Since the thermocouple was placed at intermediate position of the billet, and at surface position of the dies from the billet at the position of 2mm. Experiments of bolt-head forging. Final, the bolt-head forging was performed to evaluate the feasibility of the new method, in which the billet was heated in the dies and subsequently forming. In order to achieve optimal results, a die was designed as shown in Fig. 2. Heating resisters were fixed in the die to heat up the billet directly, and greatly improved the heat efficiency. In address, the die was designed to achieve the resistance equation R = ρ ⋅ l / A to provides the die to heating the billet directly because of the resistance of billet is larger than the forming die, where R is the resistance of material, ρ is the resistive of material, l is the length of the material along the direction of current and A is the cross sectional area normal to the current flow.

(a) Heating state (b) Forging state Fig. 2 Schematic of the bolt-head forging process using resistance heating method. (1) ceramic bushing, (2) upper plate, (3) bushing, (4) upper die, (5) billet, (6) guides,(7) lower die,(8) bottom plate.

Results and Discussions Verification of direct resistance heating billet within die. In this study, the die was designed to heating the billet directly. Therefore, the practical applicability of the direct resistance heating billet within die was primarily experimented. Fig. 3(a) shows the curves of the temperature of billet and dies by the electrifying. The result show the heating time of billet up to 1000oC is only 5 s, and the temperature of dies is up to 250oC after 5 s. This proves that the presented mechanism can achieve the rapidly heating demonstrated and the temperature elevated of the die was by the heat transfer from the billet. The rise in temperature with different current intensity during resistance heating process is shown in Fig. 3(b). The result shown that the temperature increased of billet was faster at the higher input current intensity by experiment and simulation.

(a) (b) Fig. 3 (a) The results of the direct heating billet within die using resistance method; (b) Effect of current intensity on temperature of billet by experiment and simulation

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Applied Science and Precision Engineering Innovation

The experiment results of the billet temperature. Here in this section, the process parameter of the proposed system is discussed. Fig. 4(a) shows the effect of temperature of billet with different geometric shapes during resistance heating process. The results shown the billet with larger length/diameter ratio has faster heating rate. The rise in temperature for the with different billet materials during resistance heating process is shown in Fig. 4(b). The results shown the billet with larger resistance ratio has faster heating rate.

(a) different billet shapes (b) different billet materials Fig. 4 Effect of temperature of billet during resistance heating process 1s

3s

5s

Fig. 5 The photo images of the heating state of C276 billet during resistance heating process

The experiment of bolt-head forging using the apparatus. Fig. 5 shows the photo images of the heating state of AISI4140. The experiment result proved that the billet could be direct heating within die quickly by resistance heating method. Fig.6 shows the simulation images and photograph images of the formed head of twelve point shoulder bolt by using the proposal method. The forging temperature is 1000oC, and the billet diameter is 8mm. The result shows that the billet could be heated quickly to forging temperature and the billet was successfully formed to the shape of bolt head.

Fig. 6 The simulation images and photograph images of the formed head of twelve point shoulder bolt by using the proposal method.

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Summary This paper presents a novel prototype system for the hot forging process using the electric resistance system to heat the billet directly within die. The result shown the billet could be heated quickly to 1000℃ within about 5 seconds and the high strength material AISI4140 was successfully formed into desired product geometries. With this mechanism, the high fidelity of feature replication implies that the new process has its potential as a low-cost one-step direct local area forming for enhanced productivity. It also can be applied on the other forming processes significantly for the advantages of high forming ability and high efficiency of heating. In addition, the rapidly heating and isothermal deformation during the hot forging process can be achieved. The accuracy of the bolt head has been experimentally verified. Furthermore, it was clarified that the rapid forming of high alloys with poor workability could be realized by using the proposal system.

Acknowledgements The financial support of the National Science Council of the Republic of China under contact number NSC 101-2622-E-150 -002 -CC3 is gratefully acknowledged.

References [1] K. Shi, D.B. Shan, W.C. Xu and Y. Lu, Near net shape forming process of a titanium alloy impeller, Journal of Materials Processing Technology 187/188 (2007) 582-.585. [2] Hu Yamin, Lai Zhouyi and Zhang Yucheng, The study of cup-rod combined extrusion processes of magnesium alloy (AZ61A), Journal of Materials Processing Technology 187/188 (2007) 649-.652. [3] Katsuyoshi Ikeuchi and Jun Yanagimoto, Valuation method for effects of hot stamping process parameters on product properties using hot forming simulator, Journal of Materials Processing Technology 211 (2011) 1441-1447. [4] K. Zhao, B. Wietbrock and G. Hirt, Numerical and experimental analysis of electric conductive heating for micro warm coining of stainless steel, Prod. Eng. Res. Devel 5 (2011) 629-639. [5] Malek Naderi, Mostafa Ketabchi, Mahmoud Abbasi and Wolfgang Bleck, Semi-hot Stamping as an Improved Process of Hot Stamping, J. Mater. Sci. Technol. 27 (2011) 369-376. [6] S. Maki, Y. Harada and K. Mori, Sinter-joining of different metal powder compacts using resistance heating, Journal of Materials Processing Technology 143 (2003) 561-566. [7] Jun Yanagimoto and Ryo Izumi, Continuous electric resistance heating—Hot forming system for high-alloy metals with poor workability, Journal of Materials Processing Technology 209 (2009) 3060-3068. [8] Men Zheng-xing, Zhou Jie and Xu Zhi-min, Sinter-joining of different metal powder compacts using resistance heating, Materials Science Forum 704 (2012) 252-260.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 30-34 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.30

Using Soft Material as Die during Hot Forging Fang-Sung Cheng a and Yi-Sheng Chen b Department of Mechanical and Computer Aided Engineering, National Formosa University, 64 Wen-Hua Road, Huwei, Yunlin 632, TAIWAN a

[email protected], b [email protected]

Keywords: Soft die, hot forging, resistance heating, direct heating within die

Abstract. This study introduces a new forming concept for hot forging by using soft die. The soft die (AISI1050) was employed not only to heating the billet, but also to forming the billet. In this proposed method, the soft die can be used as the electrode to raise the temperature of billet directly by resistance heating. The temperature of the billet is higher; the flow stress of the billet is become lower. Then the billet is easier to press into the cavity of the soft die. In addition, the soft die itself could not be heated by the electrifying and the temperature raise of soft die was occurred by the heat transfer from the heated billet. Therefore, the soft die can be carried out on hot forging process, and to achieve the purpose of forming. The result of experiments shows that the billet could be heated quickly to 1000oC in about 5 seconds, and a spur gear was successfully formed. With the proposed method, it was simple enough to hot forging high-alloy metals with poor workability. Introduction Forging has traditionally enjoyed an eminent position among the various methods of manufacturing because forged products have been looked upon as offering maximum reliability and superior properties. In some cases significant improvements in fatigue life are also a result. In addition, forged parts with near-net shape offer considerable advantages over machined parts because this method not only substantially reduces material usage and machining costs, but it also having good flow lines following their contours to improve greatly their load-bearing capacity00MPT04MPT. Recently, the most important issues in hot forging process is to forming high specific strength metals for aerospace and automobile industry, such as Ti-base, Ni-base and high strength steel (HSS) etc, [1]. However, these metals may be very sensitive to the forming temperature. Some alloys exhibit better formability at elevated temperature but limited to a narrow temperature range [2]. Therefore, a good temperature control for high-alloy metals during the forging process is important. The induction heating method is widely applied in precise forming of high-alloy metal for good heating effect [3]. But there are three main disadvantages: Firstly, the heat source is needed to remove before the forging operations that leading to the heat transfer occur before metal deformation in press. Secondly, the geometry of induction is more limitation in the dies shapes. Finally, the surface temperature is higher than the internal temperature due to the eddy current effect caused. For now, the use of resistance heating method has been developed in many fields for rapidly heating process and isothermal deformation during the hot forming process such as high strength sheet stamping [4,5], mushy state forging [6], powder forming [7] and rolling forming [8]. With this method, heat is created via dissipation of the electrical current within the billet. The heating rate is fast and the distribution of temperature is uniform. In general, the used of die materials in the hot forging process typically have a relatively higher hardness than billet to ensure the forming accuracy and die life. It is well known that the temperature of the billet is higher; the flow stress of the billet is become lower. Then the billet is easily pressed into the cavity of the die. According to the resistance heating method, the billet is heated via the electrifying, and the electrode itself could not be heated during the electrifying process. Therefore the temperature increase of the electrode is occurred only via the heat transfer of the heated billet. Up to date, there is a limited study carried out an investigation for the bulk materials of temperature-

Applied Mechanics and Materials Vols. 479-480

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sensitive using the direct resistance heating forming [9]. However, few investigations have been made in developing a system in the forging field which can directly heat the billet within die during the forming process. In this study, a new forming concept is introduced for hot forging of high-alloy metals using direct resistance heating billet within soft die. The soft die can be used as the electrode to raise the temperature of billet directly by resistance heating, and the strength of the billet is become lower than the soft die. Then the billet is formed by pressed into the cavity of the soft die. With the proposed method, it was simple enough to obtain near-net shape on the billets and to be mass-produced in local hot forging process. Additionally, the rapidly heating and isothermal deformation during the hot forging process was examined. Even for high-alloy metals forming, were experimentally verified. Experimental Setup Experimental apparatus. Fig. 1 show a schematic of the direct heating billet within die using resistance method during hot forging process. The set-up of the prototype system with a resistance heating apparatus is suitable for heating billets to working temperature for a forging operation. A press machine is used as a pressure source. In this study, the voltage of the electric source used in the experiment is 12V. The forming temperatures are controlled by using a PID feedback (type: TempScan 1100), and the temperature distribution of billet were measured by using a thermocouple system (type: TempScan 1100) and an infrared thermograph. All K type thermocouples were welded directly onto the billet to guarantee a short response time.

Fig. 1 Schematic of the hot forging apparatus for direct heating billet within die using resistance method. The proposed direct heating billet within die during hot forging process includes four steps: (a) placing the billet onto the die to form a billet–die stack, which is then placed among plates of machine. A pre-pressure of 8MPa was applied by the press to obtain sufficient contact between the billet and dies for the electrifying; (b) the billet temperature is raised by the resistance heating to the desired temperature. The voltage of the electric source used in the experiment is 12V; (c) kept the electrifying to heat billet at set points and forge the billet; (d) opening the die to retrieve the forged billet. It is a simple and effective method to increase heating efficiency and decrease heating time during hot forging process. Materials and experiment parameters. The practical applicability of the direct resistance heating billet within soft die was primarily presented. In order to investigate the effects of the material strength, the forging temperature and the geometry of billet on the heating temperature, the heating process prior to forming was researched at first. In this paper, the die material is AISI1050. The billet material is AISI4140 with 30 mm in diameter and 20 mm in height. The forging temperature is

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1000oC. Since the thermocouple was placed at intermediate position of the billet, and at surface position of the dies from the billet at the position of 2mm, Fig.2 shows the flow stress values of different materials at different temperatures. It can be found that the flow stresses of AISI4140 at room temperature was higher than AISI1050 at room temperature, but the flow stresses were lower than AISI1050 at high temperature. With the proposed method, the die material is AISI1050, the die was used as the electrode to raise the temperature of billet directly by resistance heating and the strength of the billet is become lower than the die. Therefore, the die can be carried out on hot forging process, and to achieve the purpose of forming.

Fig. 2 The flow stress of different materials at different temperatures. 1 2 3 4 5 6 7 8

7

Fig. 3 Schematic of the spur gear forging die: (1) punch; (2) ceramic bushings; (3) upper plate; (4) bakelite; (5) forming die; (6) pins; (7) bottom plate; (8) billet Experiments of spur gear forging. In order to achieve optimal results, a die was designed as shown in Fig. 3. Heating resisters were fixed in the die to heat up the billet directly, and greatly improved the heat efficiency. Since the thermocouple was near to the working area of the billet, it could accurately measure the temperature of the billet, which was located in the working area of the die. In address, the die was designed to achieve the resistance equation R = ρ ⋅ l / A to provides the die to heating the billet directly because of the resistance of billet is larger than the forming die, where R is the resistance of material, ρ is the resistive of material, l is the length of the material along the direction of current and A is the cross sectional area normal to the current flow. Results and Discussions Verification of direct resistance heating billet within soft die. In this study, the die was designed to heating the billet directly by the electrifying. According to the resistance equation, it is important to ensure that the resistance of billet is larger than the forming die. Therefore, the practical applicability

Applied Mechanics and Materials Vols. 479-480

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of the direct resistance heating billet within die was primarily experimented. Fig. 4 shows the temperature of billet and dies by the electrifying. The result show the heating time of billet up to 1000oC is only 5s by using SKD61 die, about 5.5s by using AISI1050 die, and the temperature of dies is up to about 170oC after 5 s. This proves that the presented mechanism can achieve the rapidly heating demonstrated for direct resistance heating billet within die. The reason for the temperature elevated of the die was by the heat transfer from the billet. Accordingly, the geometry of die was designed properly; the billet can be heating with rapidly heating rate by the die.

Fig. 4 The experiment of the temperature of billet and dies by the electrifying 1s

3s

5s

(a) Punch heated (b) Billet heated (without upper die) Fig. 5 The direct resistance heating billet within die was primarily experimented. The billet size is (a) φ 8 × 25l ; (b) φ 7 × 30l

The experiment of spur gear forging. The practical applicability of the proposal method was primarily experimented as shown in Fig. 5. The results show the punch is heated in Fig. 5(a) and the billet is heated in Fig. 5(b). There is only a different parameter in billet size. It is important to ensure that the resistance of billet is larger than the forming die. Fig. 6 shows the simulation images and photograph images of the forming of spur gear with forming load. The results show the shape of spur gear was successfully formed. With the proposed method, it was simple enough to obtain near-net shape on the billet by using the soft die, even for high-alloy metals forming.

Fig. 6 The simulation images and photograph images of the forming of spur gear with forming load

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Summary This paper presents a novel prototype system for the hot forging process by using the electric resistance system to heat the billet directly within soft die. The result shown the billet could be heated quickly to 1000℃ within about 5.5s, and the high strength AISI4140 was successfully formed into desired product geometries. It is a very promising technique for simple processing of hard forming material. With this mechanism, the high fidelity of feature replication implies that the new process has its potential as a low-cost one-step direct forming for enhanced productivity. In addition, the rapidly heating and isothermal deformation during the hot forging process can be achieved.

Acknowledgements The financial support of the National Science Council of the Republic of China under contact number NSC 101-2622-E-150 -002 -CC3 is gratefully acknowledged.

References [1] K. Shi, D.B. Shan, W.C. Xu and Y. Lu, Near net shape forming process of a titanium alloy impeller, Journal of Materials Processing Technology 187/188 (2007) 582-.585. [2] Hu Yamin, Lai Zhouyi and Zhang Yucheng, The study of cup-rod combined extrusion processes of magnesium alloy (AZ61A), Journal of Materials Processing Technology 187/188 (2007) 649-.652. [3] Katsuyoshi Ikeuchi and Jun Yanagimoto, Valuation method for effects of hot stamping process parameters on product properties using hot forming simulator, Journal of Materials Processing Technology 211 (2011) 1441-1447. [4] K. Zhao, B. Wietbrock and G. Hirt, Numerical and experimental analysis of electric conductive heating for micro warm coining of stainless steel, Prod. Eng. Res. Devel 5 (2011) 629-639. [5] K. Mori, S. Saito and S. Maki, Warm and hot punching of ultra high strength steel sheet, CIRP Annals - Manufacturing Technology 57 (2008) 321-324. [6] Malek Naderi, Mostafa Ketabchi, Mahmoud Abbasi and Wolfgang Bleck, Semi-hot Stamping as an Improved Process of Hot Stamping, J. Mater. Sci. Technol 27 (2011) 369-376. [7] S. Maki, Y. Harada and K. Mori, Sinter-joining of different metal powder compacts using resistance heating, Journal of Materials Processing Technology 143 (2003) 561-566. [8] Peijie Yan, Jingtao Han, Zhengyi Jiang, Heijie Li and Danyang Li, Warm and hot punching of ultra high strength steel sheet, Advanced Materials Research 472 (2012) 2783-2787. [9] Men Zheng-xing, Zhou Jie and Xu Zhi-min, Sinter-joining of different metal powder compacts using resistance heating, Materials Science Forum 704 (2012) 252-260.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 35-39 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.35

The Characterization of Alumina Reinforced with CNT by the Mechanical Alloying Method Gwi-Nam Kim1, a, Gyung-Tae Bae1,b, Joun-Sung Park1,c, Boo-Young Choi1,d and Sun-Chul Huh2,e 1

Graduate School of Department of Mechanical and Precision Engineering, Gyeongsang National University, Tongyeong, Korea

2

Department of Mechanical and Energy Engineering , Gyeongsang National University, Tongyeong, Korea a

[email protected], [email protected], [email protected], [email protected], e [email protected]

Keywords: Planetary Ball Mill, Al2O3, Carbon nanotube, Sintering

Abstract. Carbon nano tube(CNT) possesses excellent electrical, mechanical and thermal properties. Therefore, it has been applied in a variety of fields. In this study, we added CNT in Al2O3 to improve the characteristics. The composite of CNT(1.5 wt%), Al2O3( ∅ = 20nm), zirconia(90g) and ethanol(20ml) is deconcentrated with planetary ball mill for 1hr, 3hr, 5hr under 200rpm, 300rpm, respectively. The prepared powder was pressed under 14MPa uniaxialy after the composite was dried in the oven at 90℃, and then the powder is pressed again by Cold Isostatic Press(CIP) with 200MPa. Then reinforced alumina matrix composites with CNT was sintered by high temperature furnace at 1525 ℃ Introduction Ceramic materials, due to superior wear resistance, high temperature properties and corrosion resistance than metals, have been used in wear-resistance products and insulation products in many different fields. However, the fabrication is difficult due to poor machineability and the use is limited due to brittleness. Since the development of ceramic matrix composite materials with micron-size fiber added aiming to improve the toughness, the study to improve the toughness through the use of carbon nanotubes (CNTs) as the reinforcing matrix for ceramics is being conducted Recently, XiRu Zheng et al.(1) used a method wherre the additives are added during the production stage of the specimen and subjected to ultrasonication for deconcentration to comparatively study various deconcentration agents. Ke Chu et al.(3) researched effective deconcentration of CNT where CNT was added to Cu powder and particle composite system (PCS) was used. Sung-wan Kim et al. reinforced aluminum matrix composite with CNT, added zirconia balls, and deconcentrated it by ball milling for various CNT fractions(2). Among these studies, the deconcentration method by ball milling uses a physical mechanism, and is one of the fields that are actively studied. However, there is a relatively smaller number of studies of adjusting the CNT fraction through ball milling or of varying the conditions of ball milling. Thus, to study the deconcentration characteristics according to the conditions of ball milling, this study conducted ball milling to Al2O3 (diameter 20 nm) particles with CNT 1.5 wt% added. As for the test conditions, after each speed of 200 rpm and 300 rpm was run for 1 hour, 3 hours, and 5 hours, the specimen was fabricated through pressureless sintering using an electric furnace after preforming the prepared composite powder. The mechanical characteristics were compared by measuring the hardness of the ceramic specimens. Changes in the characteristics according to the deconcentration conditions were observed through surface observation using a scanning electron microscope, as a basic research for development of novel composite materials.

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Experiment Equipment & Method As for the CNT, the experimented material, Multiwall CNT with 90% purity produced by Carbonnano-material Technology, which has a diameter of 20 nm and a length of 5µm. As for the Al2O3, the nano powder of 99% purity produced by Nanostructured & Amorphous Materials was used for the experiment, and the particle diameter was 20 nm. As for the test method, after the test port was filled with 90 g of zirconia balls with 3 mm diameter, 0.06g (1.5 wt%) of CNT was added to 3.94 g of Al2O3 powder, and 20 ml of ethanol was added for wet ball milling. The experiment was conducted with rotational speeds of 200 rpm and 300 rpm and the test durations of 1 hour, 3hour, and 5 hour. It was then dried at 90℃ and fabricated into nano powder. The fabricated powder was examined using a TEM to observe the degrees of synthesis and deconcentration. After sintering the powder, differences depending on the conditions were examined by comparing the contraction rate and the hardness. After the prepared Al2O3-CNT powder was placed in the mold of 25.5 mm diameter, a uniaxial press was used to press at 14 MPa. Cold Isostatic Press (CIP) was used to press at 200 MPa and form the specimen to increase the true density of the specimen. After placing the disk-shaped formed specimens which have the density increased by preforming in a high temperature electronic furnace, the temperature was increased at the rate of 10℃/min up to 1525℃and kept there for 4 hours before furnace cooling. 2 Experiment Results & Consideration Observation Result of Composite Powder Fig. 1 shows the results of the observation of powders for each dispersion condition using a TEM. (a) shows the result of 1-hour ball milling at 200 rpm and (b) and (c) show the results of increasing the duration of ball milling to 3 hour and 5 hour, respectively. It was found that the longer the duration of ball mill is, the smaller the particle size of Al2O3 is and the greater the amount of Al2O3 combined with CNT is. (d), (e), and (f) show the results of ball milling at the rotational speed of 300 rpm for the durations of 1 hour, 3 hour, and 5 hour, respectively. Similarly to the above results, as the duration of ball milling gets longer, the size of Al2O3 is reduced little by little and the density of Al2O3 combined with CNT increases. Comparing by the ball milling speed, the density of Al2O3 combined with CNT was a little higher at 300 rpm than at 200 rpm. (a) (b) (c)

(d)

(e)

(f)

Fig. 1 TEM micrographs of (a)200rpm for 1hr, (b)200rpm, 3hr, (c)200rpm, 5hr, (d)300rpm, 1hr, (e)300rpm, 3hr, and (f)200rpm, 5hr

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Results of Sintering The grey composite powder changed the color to white when it was sintered, and the size of 25.5 mm was reduced due to shrinkage by heat. Table. 1 shows the diameter and the contraction percentage of each specimen after the shrinkage. The contraction percentage was increased from 37.8% to 38.12% and the diameter was reduced from 15.85 mm to 15.78 mm as the speed was increased from 200 rpm to 300 rpm and the duration was increased from 1 hour to 5 hour. For a same duration, the contraction percentage was increased when the rotational speed was faster, and the average contraction percentage was high at approximately 37.8%. We infer from these results that, the friction between the brittle materials and the balls reduced the particle size, leading to the increased surface area for the smaller particles being more affected by heat, thus increasing the contraction percentage when sintering. Table 1 Diameter and shrinkage of sintered specimen diameter Shrinkage specimen (mm) (%) A

15.85

37.84

B

15.91

37.60

C

15.72

38.35

D

16.09

36.90

E

15.65

38.63

F

15.59

38.86

Fig. 2 Result of X-ray Diffraction

Fig. 2 shows the results of measuring the crystal structure of the sintered specimen using an XRD. (a) is the crystal structure of pure Al2O3 and (b) is the crystal structure of the sintered Al2O3+CNT composite. Comparison of these results shows that the peak value resulted from the pure Al2O3 and that from the Al2O3+CNT composite were similar. Although it was difficult to identify the crystal structure of CNT with an XRD but it was inferred from the particle structure forming after sintering at 1525℃ with an electric sintering furnace that the sintering was conducted well. Fig. 3 shows the results of the surface observation of the composite after etching through heat treatment at 1425℃. (a), (b), and (c) are the results of maintaining the speed at 200 rpm for 1 hour, 3 hour, and 5 hour, respectively, and (d), (e), and (f) are the results maintaining the speed at 300 rpm for 1 hour, 3 hour, and 5 hour, respectively. In the result of (a), Al2O3 particles are observed and many gas pockets are observed between particles. Also, as the duration of ball milling is increased, the gas pockets can be observed to be reduced in (b) with the particle size growing larger and the inter-particle density getting higher, and the inter-particle density appears greater in (c). (d) shows the result of ball milling at 300 rpm for 1 hour where the particle size is much smaller than in the result for 200 rpm. It also shows that the remaining gas pockets are more reduced than (a). (e) and (f) show that, as the duration is increased, the density is increased and the gas pockets are reduced. In case of ceramics, the degree of formation of the crystal lattice is normally identified by destroying the crystal lattice after it is formed.

(a)

(b)

(c)

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(d)

(e)

(f)

Fig. 3 Optical micrographs of (a)200rpm for 1hr, (b)200rpm, 3hr, (c)200rpm, 5hr, (d)300rpm, 1hr, (e)300rpm, 3hr, and (f)200rpm, 5hr Fig. 4 shows the result of the observation of the fractured surface using a SEM after destroying the specimen. In (a) and (b), the fracture surfaces of the specimen after ball milling at 200 rpm for 5 hour and at 300 rpm for 5 hour were observed at x5000 magnification to compare the remaining gas pockets inside the specimens; and in (c) and (d), each specimen was observed at x25000 magnification to examine the state of CNT.

(a) (b) (c) (d) Fig. 4 Optical micrographs of (a)200rpm for 1hr, (b)200rpm, 3hr, (c)200rpm, 5hr, (d)300rpm, 1hr, (e)300rpm, 3hr, and (f)200rpm, 5hr Comparing (a) and (b), it is found that, as the speed is increased from 200 rpm, the internal gas pockets are reduced. Also, the observation at x5000 magnification shows considerable agglomeration of CNT at 200 rpm, but CNT appears more evenly distributed at 300 rpm. Measurement Results of Hardness Fig. 5 shows the results of hardness. We measured the hardness for each specimen 10 times and averaged the values except for the maximum and the minimum values. At 200 rpm, the hardness was increased from 14.36 GPa to 23.57 Gpa as the duration was increased. It was increased also at 300 rpm from 22.75 GPa to 28.24 GPa. Comparison by the rotational speed showed that the hardness at 300 rpm was measured to be higher than the hardness at 200 rpm. Compared to the established hardness of ceramic of 15 GPa (Heon-jin Lim, 1995), hardness was generally increased. It is inferred that, the addition of CNT acted as a reinforcement agent among the alumina particles. The density of the specimen was increased with the increased in the contraction percentage caused by heat, thus yielding a higher hardness for the specimen.

Fig. 5 The results of Vikers hardness values on time

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Summary In this study, we fabricated Al2O3/CNT composite powder with the speed and the duration of ball milling as variables and we fabricated the composite materials through forming and sintering. After analyzing their contraction percentage and hardness, we concluded as follows: (1) According to the results of the SEM examination, when the duration of ball milling is increased and the speed of ball milling is increased, the particle size is decreased and the density is increased, leading to the internal gas pockets also being reduced. (2) According to the result of examination of the fractured surface, agglomeration of CNT is observed when the ball milling speed is at 200 rpm but appears reduced at 300 rpm, and thus it is inferred that the speed affects the degree of CNT disconcentration more than the duration does. (3) The contract percentage of the sintered specimen was approximately 37.93% at 200 rpm and approximately 38.13% at 300 rpm. It is inferred from this that, as the speed increases, the particle size is decreased and the heat contact area is increased, resulting in the contract percentage being increased affected by heat. (4) According to the result of the hardness measurement, with the addition of CNT, the hardness was increased by 7~13 GPa compared to the hardness of the existing sintered alumina. In addition, the hardness at 300 rpm was increased by 4~8 GPa from the hardness at 200 rpm, and the hardness was increased by 2~6 GPa as the duration of ball milling was increased. Acknowledgement This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(2012R1A1A4A01002052) References [1] XiRu Zheng, E.J.Pialago, D.Y You and C.W Park: A study on the pool boiling heat transfer of CNT/Cu composite coated surface by sintering. SAREK, pp 218-223. (2011) [2] S.W Kim, W.S Chung, K.S Sohn, C.Y Son and S.H Lee: Fabrication and Fracture Properties of Alumina Matrix Composites Reinforced with Carbon Nanotubes. Vol. 47 of J.Kor.Inst. Met&Mater, 1, pp50-58 (2009) [3] Ke Chu, Hong Guo, Chengchang Jia, Fazhang Yin, Ximin Zhang, Xuebing Liang and Hui Chen: Thermal Properties of Carbon Nanotube-Copper Composites for Thermal Management Applicaations. Nanoscale Res Lett, 5, pp 868~874 (2010). [4] A. Esawi and K. Morsi: Dispersion of carbon nanotubes (CNTs) in aluminum powder. Vol. 38 of ScienceDirect Part A. pp 646~650 (2007). [5] Y.G kim, Munkhbayar batmunkh, H.G Jung, H.M Jung and H.S Jung: Study of Grinding Charcteristic of MWCNT and Al2O3 by Uising Planetary Ball Mill Unit. SAREK, pp 948~951 (2011). [6] S.H Jo, I.Y Ko, J.M Doh, J.K Yoon and I.J Shon: Rapid Sintering of FeAl by Pulsed Current Activated Heating and its Mechanical Properties. Vol.48 of KJMM,7, pp 639~643 (2010). [7] S.C Huh, M.B Bat, Y.G Kim, H.C Chung, H.M. jeong and H.K Choi: The Ball Milling with Various Rotation Speeds Assisted to Dispersion of the Multi-Walled Carbon Nanotubes. Vol.4 of Nanoscience and nanotechnology Letters. pp 20~29 (2012).

Applied Mechanics and Materials Vols. 479-480 (2014) pp 40-44 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.40

Transparent Conductive Oxide GZO Thin Films by Sol-gel Process Cheng-Chuan Wang1,a, Chia-Ying Yen1,b 1

Industrial Technology Research Institute (ITRI), Material and Chemical Research Laboratories (MCL), Hsinchu, Taiwan, 31040, R.O.C. a

b

[email protected], [email protected]

Keywords: Ga-doped zinc oxide (GZO), Sol-gel, Conductivity, transmittance

Abstract. In this work, GZO thin films were prepared by sol-gel process and spin coating technique. The XRD results showed the preferential c-axis orientation of the crystallites and the presence of the wurite phase of ZnO and it were suggested that the presence of Ga might be changed the d-spacing of ZnO to formation the Ga-doped zinc oxide. The effects of Ga amount on the conductivity and transparency were studied. The electrical resistivity for the GZO film doped 2 at% of Ga could be lowered to be 7.5×10-3Ω-cm with the calcination temperature was 550°C and hydrogen treatment was conducted in the Ar/H2 (97/3) atmosphere at 500°C. In addition, the optical transmittances of GZO thin films were higher than 90% in visible wavelength region. Introduction Transparent conducting oxide (TCO) thin films have received considerable attention of many researches because of their wide applications in optoelectronic devices such as display panel, solar cell, and photovoltaic devices, owing to their high conductivity and transparency in the visible wavelength region [1-3]. Tin-doped indium oxide (ITO) is the TCO material mostly used to date. However, its excellent electrical and optical properties are degraded while being exposed to a hydrogen plasma atmosphere [3]. ZnO is one of the metal oxide semiconductors suitable for use as TCO thin films because of higher thermal stability, good resistance against hydrogen plasma processing damage, and relatively low cost compared with tin-doped indium oxide (ITO) [2-3]. Since its conductivity is due to intrinsic defects such as zinc excess at the interstitial position and the lack of oxidation, pure ZnO thin films are sensitive to oxidation which will decrease the conductivity [4]. To improve the conductivity, ZnO thin films are usually thermally treated in a reducing atmosphere and doped with various dopants, e.g. B, Al, Ga, In, Zr, F, etc. The use of dopants not only enhances the conductivity of ZnO thin films by extrinsic defects but also improves the thermal stability [4,7-10]. Furthermore, the optical properties of ZnO thin films are mainly affected by the surface morphology and the dopant-induced change of energy band gap. The thermal treatment and doping process also can lead to the modification of surface morphology [4,8-13]. Although Al-doped ZnO (AZO) is an attractive electrode material alternative to ITO, Ga-doped ZnO (GZO) is more stable with respect to oxidation due to gallium’s greater electronegativity in comparison with aluminum [14]. It has also been reported that heavily Ga-doped ZnO is more stable when subjected to moisture than Al-doped ZnO. [15]. Several approaches have been proposed and developed for the preparation of Ga-doped ZnO thin films such as magnetron sputtering [16], spray pyrolysis [17], metal-organic chemical vapor deposition (MOCVD) [18], pulsed laser deposition (PLD) [19] and dip-coating [20]. In this work, we report the structural, optical and electrical properties of the transparent conducting GZO thin films prepared by sol–gel process. By varying the Ga content and heat treatment conditions, the electrical resistivity of Ga doped ZnO thin films were minimized. Experimental details The GZO thin films were prepared using the sol-gel method by dissolving an appropriate amount of zinc acetate dehydrate and gallium nitrate were dissolved in a mixture of 2-methoxyethanol and monoethanolamine (MEA) which served as the solvent and stabilizer, respectively. The concentration

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of gallium was varied from 0 to 9 at%. The molar ratio of MEA to zinc acetate was maintained at 1.0. The solution was stirred at 60°C for 5 h to yield a form a clear and transparent homogeneous mixture solution. After cooling to room temperature and aging for 2 days, the solutions were deposited on the glass substrates by a spin coater at a rate of 3000 rpm for 30 s. The as-deposited films were then dried in a furnace at 350°C for 10 min to evaporate the solvent and remove organic residuals. The spin coating and drying procedures were repeated 10 times to obtain an appropriate thickness. Finally, the films were put into a furnace and fired in air at 550°C for 1 h (first heat treatment: calcination) and annealed in Ar/H2 (97/3) atmosphere at 500°C and the gauge pressures of 0.1 kg/cm2 for 2 h (second heat treatment: hydrogen treatment) for further improvement in electrical properties. The crystalline structures of pure and Ga doped ZnO thin films were investigated by the analysis of X-ray diffraction (XRD) pattern which was performed on a Philips PW3710 X-ray diffractometer at 40 kV and 30 mA with Cu Kα radiation (λ= 0.1542 nm). The surface morphology and cross-section of the films were observed with a Hitachi S-4200 field emission scanning electron microscope (FESEM). The electrical resistance was measured by a four-point probe method. The optical property was analyzed using a Hitachi U-3000 UV–VIS spectrophotometer. Results and discussions Figure 1 shows the x-ray diffraction (XRD) patterns of the ZnO thin films doped with different Ga concentrations after the calcinations in air at 550°C for 1 h and the followed annealing in Ar/H2 (97/3) atmosphere at 500°C and the gauge pressures of 0.1 kg/cm2 for 2 h. All the film show the existence of a very strong peak corresponding to (002) diffraction peak was observed for each case. This revealed that the resultant GZO thin films had preferential orientation along the c-axis, which could be referred to the self-ordering effect caused by the minimization of crystal surface free energy and the interaction between the deposited materials and the substrate surface. It was also observed that the peak corresponding to the (002) reflection increased with Ga incorporation in the film. The d-spacing calculated using Bragg’s Law for ZnO film with 0 at%, 2 at%, 4 at% and 6 at% of Ga were show in Figure 2. The d-spacing was decreased with a further increased in the Ga content in the film. This behavior indicated that the Ga was substitution of Zn in the GZO thin film. 1.370 6%Ga-ZnO

Intensity

2%Ga-ZnO

d-spacing (Angstrom)

1.365 4%Ga-ZnO

1.360

1.355

ZnO

30

40

50

60

2θ

70

80

1.350

0

2

4

6

Ga (at%)

Fig. 1 XRD patterns of the as-prepared ZnO thin Fig. 2 Effect of the d-spacing of ZnO thin films films doped with different gallium doped with different gallium concentrations. concentrations. The surface morphologies of ZnO thin film doped with different concentration of Ga were observed by a field emission scanning electron microscope (FESEM, Hitachi S-4200) was shown in Figure 3. The average grain size decreased with incorporation of Ga in doped films. The doping of Ga led to the sintering of GZO grains and this effect became more significant at higher Ga contents. It is known that the melting points of metals may decrease by reducing their size at nanometer scale, so the role of Ga as a sintering aid might be attributed to their low melting point. In addition, from the SEM micrograph for the cross-section of thin films, the film thickness could be estimated to be about 300 nm.

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(a)

(b)

(c)

(d) (e) (f) Fig. 3 FE-SEM images of GZO thin films with (a) 0 at%, (b) 1 at%, (c) 2 at%, (d)3 at%, (e)5 at%, and (f)9 at% of gallium. The average grain size decreases with incorporation of gallium in the film. The UV–VIS transmittance spectrum and the Ga versus hν plot of the as-prepared GZO thin films are shown in figure 4. The Ga doped ZnO film shows a transparency of more than 85% in the spectral range of 400–700 nm. There was a slight variation in the transparency for different amounts of Ga doping. The optical absorption coefficient α can be obtained through I = I0e-αt, where I and I0 are the intensities of the transmitted light and the incident light, respectively, and t is the thickness of the GZO film. In the direct transition semiconductor, the absorption coefficient (α) follows the following relationship with optical band gap (Eg); αhν= B(hν- Eg)1/2

(1)

where h is Planck’s constant, ν is the frequency of the incident photon and B is a constant which depends on the electron–hole mobility. The optical band gap can be determined by extrapolation of the linear region from the α2 versus hν plot near the onset of the absorption edge to the energy axis. The band gap of the undoped ZnO film was found to be 3.275 eV, which agrees well with the bulk band gap of ZnO and Ga doped ZnO film was show in Figure 4(b). Further, it is clearly seen that the absorption onset of Ga-doped films is slightly blue shifted from undoped ZnO. The blue shift of absorption onset is associated with the increase in the carrier concentration blocking the lowest states in the conduction band, well known as the Burstein–Moss effect [21, 22]. Figure 5 shows the sheet resistance of the as-prepared GZO films and H2 annealed with different Ga concentrations. The sheet resistance for the as-prepared undoped ZnO film was found to be 6MΩ/sq. (resistivity; 114Ω-cm). However, the sheet resistance was significantly decreased with the incorporation of Ga in the films. The decrease in the sheet resistance in the case of doped films is due to the increase in carrier concentrations supplied from the substitution of Ga by replacement of the host Zn atoms. The substituted Ga atoms ionize into Ga3+ so that a free electron can be contributed from each Ga atom [23]. These results corroborate well with the blue shifting of the optical band gap as observed from the Ga at% versus hν plot. However, a slight increase in the sheet resistance was observed with the increase in the Ga concentration above 2 at%. At higher Ga concentrations, the carrier concentration decreases because increasing the dopant atoms may cause segregation of neutral Ga atoms at the grain boundaries which do not contribute free electrons.

Applied Mechanics and Materials Vols. 479-480

3.40

100

(b)

(a) 80

3.35

60

ZnO 1% Ga 2% Ga 3% Ga 4% Ga 5% Ga 7% Ga 9% Ga

40

20

0 300

400

500

600

hν (eV)

Transmittance(%)

43

3.30

3.25

700

3.20 0

2

4

Wavelength(nm)

6

8

10

Ga (at%)

Fig. 4 (a) Transmittance spectra and (b) the Ga (at%) versus hν plot of the ZnO thin films doped with different gallium concentrations. The as-prepared films were post-annealed at 500℃ in a H2 atmosphere for 2 h to further reduce the sheet resistance and hence the resistivity. The electrical conductivity of ZnO is believed to be controlled by zinc interstitials [24] and/or oxygen vacancies [25] which act as n-type donors. Hydrogen acts as a reducing agent and hence an oxygen deficient non-stoichiometric ZnO film is produced after H2 annealing. Therefore, the decrease in resistivity by H2 annealing may be due to zinc interstitials and/or oxygen vacancies [26] in the films. As shown in figure 5, the sheet resistance of the GZO films was reduced by four orders of magnitude after annealing in a H2 atmosphere. The lowest sheet resistance of 261Ω/sq. (resistivity; 7.5×10-3Ω-cm) was obtained for the films with 2 at% of Ga. The obtained minimum resistivity for the ZnO films with 2 at% Ga is very similar to the resistivity value (6.3 ×10-3Ω-cm) reported by Fathollahi and Amini [20]. (b)

Resistivity (Ω -cm)

Sheet resistance (ohm/sq)

1

as-prepared H2 annealed

7

10

6

10

4

10

0.1

0.01

3

10

2

10

0

2

4

Ga (at%)

6

8

10

1E-3 0

2

4

6

8

10

Ga %

Fig. 5 Variation of the sheet resistance of as-prepared and 500℃ H2-annealed GZO thin films with different Ga concentrations(a). The inset shows the resistivity of the GZO thin films after 500℃ H2-annealing(b). Summary In conclusion, Ga-doped ZnO thin films were successfully prepared by a simple sol–gel spin coating technique. XRD results showed preferential c-axis orientation of the crystallites and the size of the grains was found to decrease with Ga incorporation in the films. A lowest resistivity of 7.5 × 10-3 Ω-cm was obtained for the ZnO film doped with 2 at% Ga. The films showed more than 85% transparency in the entire visible region. The band gap of the Ga-doped ZnO films is blue shifted from that of the undoped ZnO film, which can be explained by the Burstein–Moss effect.

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Acknowledgments This work was performed under the auspices of the Ministry of Economic Affairs in Taiwan, which the authors wish to express their thanks. References [1] G. K. R. Senadeera, K. Nakamura, T. Kitamura, Y. Wada and S. Yanagida: Appl. Phys. Lett. 83 (2003), 5470 [2] K. Tonooka, H. Bando and Y. Aiura: Thin Solid Films 445 (2003), 327 [3] Z. Q. Xu, H. Deng, Y. Li, Q. H. Guo and Y. R. Li: Mater. Res. Bull. 41 (2006), 354 [4] J. H. Lee and B. O. Park: Thin Solid Films 426 (2003), 94 [5] J. Herrero and C. Guillen: Thin Solid Films 451–452(2004), 630 [6] D. Basak, G. Amin, B. Mallik, G. K. Paul and S. K. Sen:J. Cryst. Growth 256 (2003), 73 [7] M. Ohyama, H. Kozuka and T. Yoko: J. Am. Ceram. Soc. 81 (1998), 1622 [8] Y. Yamamoto, K. Saito, K. Takakashi and M. Konagai: Sol. Energy Mater. Sol. Cells 65 (2001), 125 [9] A. Sanchez-Juarez, A. Tiburcio-Silver, A. Oritz, E. P. Zironi and J. Rickards: Thin Solid Films 333 (1998 ), 196 [10] Y. Natsume and H. Sakata: Mater. Chem. Phys. 78 (2002), 170 [11] B. E.Sernelius, F.-K. Berggren, Z.-C. Jin, I. Hamberg and C. G. Granqvist: Phys. Rev. 37 (1998), 10244. [12] D. F. Paraguay, J. Morales, L.W. Estrada, E. Andrade and M. Miki-Yoshida: Thin Solid Films 366 (2000), 16. [13] J.-H. Lee, K.-H. Ko and B.-O. Park: J. Cryst. Growth 247 (2003), 119 [14] K. Yim, H. W. Kim and C. Lee: Mater. Sci. Technol. 23 (2007), 108 [15] O. Nakagawara, Y. Kishimoto, H. Seto, Y. Koshido, Y. Yoshino and T. Makino: Appl. Phys. Lett. 89 (2006), 091904 [16] Q. B. Ma, Z. Z. Ye, H. P. He, S. H. Hu, J. R. Wang, L. P. Zhu, Y. Z. Zhang and B. H. Zhao:J. Cryst. Growth 304 (2007), 64 [17] K. T. R. Reddy, T. B. S. Reddy, I. Forbes and R. W. Miles: Surf. Coat. Technol. 151 (2002), 110 [18] A. R. Kaul , O. Y. Gorbenko, A. N. Botev and L. I. Burova: Superlatt. Microstruct. 38 (2005), 272 [19] M. Snure and A. Tiwari: J. Appl. Phys. 101 (2007), 124912 [20] V. Fathollahi and M. M. Amini: Mater. Lett. 50 (2001), 235 [21] E. Burstein: Phys. Rev. 93 (1954), 632 [22] T. S. Moss: Proc. Phys. Soc. Lond. B 67(1954), 775 [23] J. Hu and R. G. Gordon: J. Appl. Phys. 72 (1992), 5381 [24] K. I. Hagemark and L. C. Chacka: J. Solid State Chem. 15(1975), 261 [25] J. Schoenes, K. Kanazawa and E. Kay: J. Appl. Phys. 48 (1977), 2537 [26] F. Oba, A. Togo, I. Tanaka, J. Paier and G. Kresse: Phys. Rev. B 77 (2008), 245202

Applied Mechanics and Materials Vols. 479-480 (2014) pp 45-49 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.45

Nonlinear Evolution of the Travelling Waves in Roll Coating Flows of Thin Viscoelastic Polymer Falling Films Po-Jen Chenga, Kuo-Chi Liub, Cheng-Chi Wangc Far East University, No.49, Zhonghua Rd., Xinshi Dist., Tainan City 74448, Taiwan a [email protected], [email protected], [email protected] Keywords: Polymer liquid films, Hydrodynamic stability, Rossby number

Abstract. Roll coating is widely used to apply a thin liquid film to a continuous, flexible substrate. It is known that macroscopic instabilities of the film system can result in a non-homogenous film growth to fluid flow. The influence of the Rossby number, the viscoelastic parameter, and the roller radius on the nonlinear hydrodynamic stability of a thin viscoelastic polymer fluid film coating flow down a rotating vertical roller is investigated. In contrast to most previous studies, the solution scheme employed in this study is based on a numerical approximation approach rather than an analytical method. The size of the explosive supercritical instability region increases significantly as the roller rotates. It is shown that the stability of the liquid film is enhanced by reducing the viscoelastic effect or decreasing the speed of the rotating roller. At higher values of the Reynolds number, the tendency of the rotation effect to prompt thin-film instability increases with an increasing roller radius. Introduction It is essential that the underlying flow characteristics and time-dependent properties of the fluid film are thoroughly understood in order to ensure the quality of the coating results. Roll coating is widely used to apply a thin liquid film to a continuous, flexible substrate. In practice, coating liquids often contain viscoelastic polymer fluids. The non-Newtonian behavior can drastically change the nature of the flow near the free surface and consequently alter the performance of a coater [1]. The hydrodynamic stability of fluid films flowing along a vertical cylindrical surface has attracted particular attention due to its relevance to numerous industrial applications. It indicated that the lateral curvature of the roller exerted a destabilizing effect on the film flow system [2]. Extensive studies on the hydrodynamic stability problems regarding the non-Newtonian fluid films flowing along a free surface have been already made by several researchers. Chang [3] employed the method of nonlinear analysis to study the nonlinear stability of thin micropolar fluid film flowing down on a vertical moving plate. The results of their study indicated that the micropolar parameter plays an important role in stabilizing a film flow. Gorla [4] displayed the rupture times for the dilatant fluids are higher than that of Newtonian fluid. Cheng et al. [5] and Sirwah and Zakaria [6] studied the nonlinear stability analysis of thin viscoelastic liquid film flowing down on a (moving) vertical cylinder. They also demonstrated that the viscoelastic property has destabilizing effect on the nonlinear film flow system. Surface coating of a moving substrate by a liquid layer is of importance in a variety of industrial processes. In coating applications, the quality of the final product is largely dependent on the hydrodynamic stability of the liquid film as it flows over the substrate. Therefore, the problem of ensuring the stability of the thin film system has attracted significant attention in the literature. The hydrodynamic stability of films flowing down a rotating vertical roller has received comparatively less attention. In the case of a rotating roller, the governing equation of the thin film must take account of the centrifugal force. Chen et al. [7] analyzed the stability of thin Newtonian films flowing down a rotating vertical cylinder by an analytical solution, and showed that the film flow became increasingly unstable as the rotational speed of the cylinder increased. Davalos-Orozco and Ruiz-Chavarria [8] investigated the linear stability of fluid films flowing along the internal and external surfaces of a rotating vertical cylinder. Their results showed that the centrifugal force induced by the cylinder rotation compensated for the destabilizing effects of surface tension and therefore enhanced the stability of the film system. The problem of weakly

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nonlinear stability analysis of a thin liquid film with condensation effects during spin coating was investigated by Chen and Lin [9]. The authors revealed that decreasing the rotational speed and the radius of the rotating circular disk will stabilize the flow. Accordingly, the present study conducts a systematic investigation into the stability of a thin fluid film flowing down the external surface of a rotating vertical roller. In contrast to previous studies [5, 7], the problem is addressed using a numerical approximation method rather than an analytical approach. The analysis focuses particularly on the respective effects of the Rossby number, viscoelastic effect, and the roller radius on the stability of the thin film. Numerical examples are presented to verify the solutions and to demonstrate the effectiveness of the proposed modeling procedure. Mathematical Modeling The problem considered in this study of a viscoelastic polymer fluid film flowing along the outer surface of an infinitely-long vertical roller. The unsteady hydrodynamic flow is governed by the continuity equation, the momentum equations, and the corresponding boundary conditions can be expressed in cylindrical coordinates (r * , z * ) as ref [5]. Furthermore, it is reasonable to assume that the tangential velocity is constant in the radial direction of the thin film, i.e., v * = R * Ω * , where Ω * is the angular velocity of the rotating roller. For convenience, the dimensionless quantities are defined in ref [5] which Re is the Reynolds number, λ* is the perturbed wave length, ν 0* is the kinematic viscosity of the fluid, α is the dimensionless wave number, S is dimensionless surface tension, h0* is the film thickness of the local base flow, and u 0* is the reference velocity. To find the effects of angular velocity Ω * , the viscoelastic coefficient k 0* , and the roller radius R* on the stability of the flow system, the dimensionless Rossby number β , the viscoelastic parameter k , and the dimensionless radius of the roller R are introduced

β=

Ω * h0* k 0* R* , k = , R = . u 0* ρ * h0*2 h0*

(1)

Thus, the non-dimensional governing equations for the fluid film system are obtained as p r = α [Re −1 (r −1ϕ rrz − r − 2ϕ rz )] +

( Rβ ) 2 + O(α 2 ) , r

(2)

r −1 (r (r −1ϕ r ) r ) r = 4Γ + α Re[− p z + r −1ϕ tr + r −2ϕ z ϕ rr − r −3ϕ z ϕ r − r −2ϕ r ϕ rz + k (3r −5ϕ r ϕ z − 3r − 4ϕ z ϕ rr − 3r − 4ϕ r ϕ rz + 2r −3ϕ rz ϕ rr − r − 2ϕ rz ϕ rrr

.

(3)

+ r − 2ϕ z ϕ rrrr + r − 2ϕ rr ϕ rrz − r − 2ϕ r ϕ rrrz + r −3ϕ tr − r −2ϕ trr + r −1ϕ trrr )] + O(α 2 )

The corresponding boundary conditions are given as follows: At the roller surface (r = R )

ϕ = ϕr = ϕ z = 0 .

(4)

At the free surface (r = R + h) (r −1ϕ r ) r = α ⋅ Re⋅ k[(−2r −4ϕ r2 + 4r −3ϕ r ϕ rr − 2r −2ϕ rr2 )h z − r −4ϕ z ϕ r + r −3ϕ z ϕ rr + r − 2ϕ z ϕ rrr + 3r −3ϕ r ϕ rz − r − 2ϕ r ϕ rrz − 2r − 2ϕ rr ϕ rz − r − 2ϕ tr + r −1ϕ trr ] + O(α 2 )

p = −2S ⋅ Re −5 / 3 (2Γ)1/ 3 (α 2 hzz − r −1 ) + α {[ −2 Re −1[(r −2ϕ r − r −1ϕ rr )hz + r −2ϕ z − r −1ϕ rz ]} + O(α 2 ) ht − r −1 (ϕ r hz + ϕ z ) = 0 .

,

,

(5) (6)

(7)

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Since the small wave numbers α considered in the present analysis may introduce flow instabilities, the dimensionless stream function, ϕ , and pressure, p, are expanded in terms of some small wave number α as follows:

ϕ = ϕ 0 + αϕ 1 + O(α 2 ) ,

(8)

p = p 0 + αp1 + O (α 2 ) .

(9)

Substituting Eqs. (8) and (9) into Eqs. (2)~(7), the governing equations of the thin-film system can be collected and solved on an order-by-order basis. For r − R ≤ h , the film thickness is very small, and hence power-series approximation solutions can be obtained up to the order of (r − R ) 5 at the zeroth- and first-orders of the stream function. Substituting the solutions of the zeroth- and first-order equations into the dimensionless free surface kinematic equation given in Eq. (7), the following generalized nonlinear kinematic equation can be obtained: ht + A(h)h z + B (h)hzz + C (h)hzzzz + D(h)hz2 + E (h)h z hzzz = 0 ,

(10)

where A(h) , B (h) , C (h) , D (h) and E (h) are are functions of h which are available from the authors. In the case where the Rossby number is equal to zero, the kinematic equation given in Eq. (10) describes the flow of a fluid film down a stationary vertical roller. The long-wave perturbation method is employed to investigate linear and nonlinear stability theories then to conduct a numerical characterization of thin film flows traveling down a rotating roller. The normal mode approach is first used to compute the linear stability solution for the film flow. The method of multiple scales is then used to obtain the weak nonlinear dynamics of the film flow for stability analysis. The deriving process as well as the derived results have been presented in previous work [5] in which d i is the linear growth rate of the amplitudes, E1 is the coefficient of Ginzburg-Landau equation, εa 0 is the threshold amplitude, and Ncr is the nonlinear wave speed.

Numerical Examples In the linearly stable subcritical region, the small perturbed waves decay as the perturbation time period increases. Conversely, in the linearly unstable supercritical region, the perturbed waves grow as the perturbation time period increases. Figure 1 shows that the size of the linearly unstable region (d i > 0) increases as the the Rossby number increases. In other words, the roller rotation effect has a destabilizing effect. It can be seen that the amplitude growth rate increases with an increasing k, and an increasing Re . In addition, it shows that the wave speed in the supercritical region remains constant for all values of the wave number, Reynolds number, roller radius, Rossby number, and viscoelastic parameter, respectively. Overall, the results show that the liquid film becomes more stable as the Rossby number decreases and the viscoelastic parameter decreases or as the roller radius increases at smaller values of the rotational speed. In the nonlinear stability solutions, the hatched regions adjacent to the neutral stability curves in figure 2 show that the thin-film flow system contains both subcritical instability regions (d i < 0, E1 < 0) and explosive supercritical instability regions (d i > 0, E1 < 0) for the values of β , k, and R considered in the present study. It can be seen that the neutral stability curves corresponding to d i = 0 and E1 = 0 , respectively, are shifted in the upward direction as the increased β , the increased k , and the decreased R. In other words, the subcritical stability region decreases in size with an increasing Rossby number, an increasing viscoelastic parameter, and a decreasing roller radius whereas the supercritical instability region increases. Figure 3(a) shows the threshold amplitude in the subcritical unstable region for various wave numbers as a function of the Rossby number for constant Re=3, k=0.1, and R=20. The results show that the threshold amplitude reduces as the Rossby number increases. In additional, it shows that the threshold amplitude reduces as the viscoelastic parameter increases. Figure 3(b) indicates that the threshold amplitude reduces as

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the larger roller radius (R=50) at the high rotational speed ( β = 0.5). In general, a reducing value of the threshold amplitude implies that the thin-film flow system becomes inherently more unstable. If the initial finite-amplitude disturbance is less than the threshold amplitude, the system will be conditionally stable. However, if the finite-amplitude disturbance exceeds the threshold amplitude, the system becomes explosively unstable. In the linearly unstable region, the linear amplification rate is positive while the nonlinear amplification rate is negative. Therefore, the effect of a linear infinitesimal disturbance in the unstable region causes the amplitude of the disturbed wave to approach a finite equilibrium value rather than an infinite value. Figure 4 shows the threshold amplitude in the supercritical stable region for various wave numbers as a function of the viscoelastic parameter and constant Re=5, R=20, and β = 0.2 . The results show that the threshold amplitude increases with an increasing viscoelastic parameter. According to linear theory, the wave speed is a constant value for all wave numbers, Rossby numbers, viscoelastic parameter, and roller radii. However, the nonlinear wave speed, given varies with the wave number, Rossby number, viscoelastic parameter, and roller radius. Figure 5 plots the nonlinear wave speed against the wave number as a function of the Rossby number. It shows that the maximum nonlinear wave speed decreases with decreasing β . The results presented in this study have shown that the stability of a viscoelastic polymer film travelling down a rotating vertical roller is significantly dependent on the Rossby number ( β ), the viscoelastic parameter (k), and the roller radius (R). Specifically, the stability of the liquid film flow is enhanced at smaller values of β , and smaller values of k. For the limiting case of β = 0 , the problem becomes one of a film flowing down a stationary vertical roller. Computing the corresponding flow solutions, it is found that the flow field becomes relatively more unstable as the viscoelastic parameter increases. This finding is consistent with the results presented in the literature [5]. Moreover, setting k=0, i.e. removing the viscoelastic effect, the solutions obtained for the thin-film system are found to be in good agreement with those given by Chen et al. [7].

Acknowledgements The financial support provided to this study by the National Science Council of Taiwan under Grant No. NSC 99-2221-E-269-009-MY2 & NSC 101-2221-E-269-007 is gratefully acknowledged.

α

α

di < 0

di < 0 E1 < 0

di > 0 E1 > 0

di > 0

di < 0 E1 > 0

β

di > 0 E1 < 0

Re

Re

Fig. 1 Linear neutral stability curves for three Fig. 2 Neutral stability curves for k=0.1, β =0.2, and different values of β . Note that R=20 and k=0.1

R=20

Applied Mechanics and Materials Vols. 479-480

2εa0

49

β

2εa0

R

α Fig. 3(a) Threshold amplitude in subcritical unstable region for three different values of β . Note that Re =3, R=20, and k=0.1 2εa0

α Fig. 3(b) Threshold amplitude in subcritical unstable region for three different values of R. Note that Re =3, β = 0.5 , and k=0.1 β

k

(β = 0, 0.2, 0.4)

α Fig. 4 Threshold amplitude in supercritical stable region for three different values of k. Note that Re =5, β =0.2, and R=20

α Fig. 5 Nonlinear wave speed in supercritical stable region for three different values of β . Note that Re =5, k=0.1, and R=2.

References [1] G. A. Zevallos, M. S. Carvalho, and M. Pasquali: J. Non-Newton. Fluid Mech. Vol. 130 (2005), p. 96. [2] C. I. Hung, , C. K. Chen, and J. S. Tsai: Int. J. Heat Mass Transfer Vol. 39 (1996), p. 2821. [3] C. L. Chang: J. Phys. D: Appl. Phys. Vol. 39 (2006), p 984. [4] R. S. R. Gorla: Transactions of the ASME: J. of Appl. Mech. Vol. 68 (2001), p. 294. [5] P. J. Cheng, C. K. Chen, and H. Y. Lai: Nonlinear Dynamics Vol. 24 (2001), p. 305. [6] M. A. Sirwah and K. Zakaria: Applied Mathematical Modelling Vol. 37 (2013), p. 1723. [7] C. I. Chen, C. K. Chen, and Y. T. Yang: Proc Instn Mech Engrs Part C: J Mechanical Engineering Science Vol. 219 (2005), p. 911. [8] L. A. Davalos-Orozco and G. Ruiz-Chavarria: Phys. Fluids A Vol. 5 (1993), p. 2390. [9] C. K. Chen, and M. C. Lin: Transactions of the ASME: J. of Fluids Engineering Vol. 131 (2009), p.101303-1.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 50-54 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.50

Photo-electronic Properties of Titanium Dioxide Nano Thin Films Sheng-Lung Tu1,a, Yen-Hsun Su2,b, Yun-Hwei Shen1,c, Dah-Tong Ray1,d, Yu-Chun Wu1,e, Tao-Hsing Chen3,f 1

Department of Resources Engineering, National Cheng Kung University, Tainan City 701, Taiwan 2

Department of Materials Science and Engineering, National Cheng Kung University,Tainan City 701, Taiwan (R.O.C.) 3

Department of Mechanical Engineering, National Kaohisung University of Applied Sciences, Kaohsiung 807, Taiwan a b c [email protected], [email protected], [email protected], d e [email protected], [email protected], f [email protected]

Keywords: ultra-high vacuum ion beam sputter, nano-titanium, nano titanium dioxide, photoelectric properties.

Abstract. In this study, nano-titanium films of different thickness were deposited. By adjusting it is found that when the thickness of the titanium films was in the nano-scale, the electric resistivity of the titanium films decreased. Furthermore, the deposited titanium was transformed into titanium oxide by maintain an oxygen atmosphere and using a rapid annealing furnace during sputtering. When oxidized nano titanium film is sputtered on a low-electric-resistive metal thin film, the photo-electronic properties of Nano-thin film will be enhanced. Introduction Among metal elements, i.e. titanium is a light and high-strength metal having a high strength-weight ratio [1]. Pure, titanium is quite ductile, especially in an oxygen-free environment with a shiny and metallic white color. Its relative high melting point (over 1649 °C or 3000 °F) makes it useful as a refractory metal. Titanium dioxide is semiconductor of n-type with large band gap. The band gap energy of one sharp mineral-based titanium dioxide is 3.2 eV [2], and the band gap of rutile-type titanium dioxide is 3.0 eV thus titanium dioxide has a very high optical activity. Titanium dioxide has been used in photoelectric conversion [3], solar cells, thin-film optical waveguides[4], interference filter films and photocatalytic materials and has gained of widespread interest [5]. The high optical activity, let Titanium dioxide induce photochemical reactions. Thus, titanium dioxide can be applied in photovoltaic cells and used as photocatalytic materials. Comparing with other materials with similar properties, it has the following advantages [6]: very stable photoelectric level, relatively cheap and non-toxic. In this study, the incident angle of an ultra-high vacuum ion beam sputter (UVIBS) toward a target is adjusted to deposit. nano-titanium films with different thicknesses. When the thicknesses of the titanium films are in nano-scale, it is found that the electric resistivity decreased from the bulk-value of 10-5 (Ω-m) dropping to 10-6 (Ω-m). When the titanium film thickness is less than 500 ~ 600 Angstrom, the electric resistivity becomes very small. This phenomenon can be applied in the fields of optical communication electrodes, sensor electrodes and solar cell electrodes. Furthermore, if the sputtering atmosphere is a controlled oxygen atmosphere and the deposited titanium can be transformed into titanium dioxide. The use of a rapid annealing furnace (Rapid Thermal Annealing; RTA) can accelerate transformation into titanium dioxide by the heated oxygen. When oxidized nano titanium film is sputtered on the low-electric-resistive metal thin film, the photo-electronic properties of nano-thin film will be enhanced. EXPERIMENTAL DETAILS Nano-scaled Ti thin film on a silicon wafer were prepared by ultra-high vacuum ion beam sputtering (vacuum-type IBS ; model-type: IBS - 2000 Nian, ULVAC) at room temperature. The Argon gas flow

Applied Mechanics and Materials Vols. 479-480

51

was 8 sccm. The corresponding pressure was 2.5 * 10-9 torr. The working pressure was 1.5 * 10-4 torr. The external chemical vapor deposition was 1.0 kV. The chemical vapor deposition of A / D was -0.5 kV. The orientation of palladium material was varied at different angles: -30 degrees, -20 degrees, -10 degrees, 0 degrees, +10 degrees, +20 degrees, +30 degrees. For the preparation the TiO2 thin films, the same conditions were used except the deposition angle. Furthermore, titanium was oxidized into titanium dioxide. In the sputtering atmosphere, it turned titanium dioxide into oxygen. A rapid annealing furnace (Rapid Thermal Annealing; RTA) was used to heat into the oxygen, gas and the titanium was transformed into titanium dioxide. Since the thickness of the film is too thin to analyze the morphology and structure SEM and XRD, alpha-step (New Alpha-Step Profilometer), and Raman scattering spectrum were used to measure the thickness and crystal structure of the thin film. The electrical propert of nano-titanium films were measured by the Si wafer probe test 4 (280SI, Four Dimensions / 280SI). A micro-Raman (Micro-Raman & Micro-PL / France Yvon / Labram HR) was used to measure the relationship between Raman scattering intensity and wave number. Raman scattering intensity peaks of anatase are at 395 cm-1, 513 cm-1, and 639 cm-1. While scattering peaks of rutile are at 447 cm-1 and 610 cm-1 from to the Raman scattering intensity peak position, the crystalline phase of titanium dioxide film can be determined. RESULTS AND DISCUSSION Characteristics of nano-scaled titanium films Fig. 1(a) shows that the relationship between the incident angle and the thickness of the titanium film. It can be seen that the thickness of the film prepared at minus- 20-degree about 800 Angstrom. The reason is that the distribution of the ion-beam plasma is close to the cosθ distribution, deposition rate will be higher for small angle depositions.

Thickness (Angstrom)

1200 1000 800 600 400 200 -40

-30

-20

-10

0

10

20

30

40

Rotation (degree)

Fig. 1(a) Relationship between angle and thickness Fig. 1 (b) is the relationship between thickness and resistance. It shows that withe the decreasing thickness of nano-scale titanium film is small, the resistance rate declines. Because of the quantum confinement effect of electrons, when the thickness of the semiconductor material is less than 500 Angstrom, the phenomenon of discontinuity in resistance occurs. When the size of nanostructure is less than the length of mean free path of electron, the wave function of electron will be confined by the boundary. Then the energy level of nanostructure will become discrete. In the same time, subband is formed [7]. Electrons transport between energy levels of materials, since the form electronic current is formed from the. When the energy levels of nanostructure becomes discrete and subband forms due to the quantum confinement effect, the resistivity of the film increases and fluctuate under 500 Angstrom. Characteristics of nano-titanium dioxide The titanium dioxide was sputtered at different angles by UVIBS in an oxygen atmosphere. The relationship between the sputtering angle and film thickness is shown in Fig. 2 (a). A film of thickness

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about 900 Angstrom can be prepared at the sputtering angle of -10 degrees, because the distribution of plasma generated ion-beam is a cosθ distribution, the deposition rate is slower for the small angle. Fig. 2 (b) shows the Raman scattering intensity of different incident angles. The Raman scattering peak for -30 degrees is 520 cm-1; -20 degrees is 520 cm-1; -10 degrees is 500 cm – 1; 0 degrees is 500 cm-1; 10 degrees is 520 cm-1; 20 degrees is 500 cm-1; 30 degrees is 500 cm-1. The peak at 513 cm-1 is the characterization peak of anatase. In Figure 2(b), there is a scattering peak at 513 cm-1. Therefore that, Ti has been transformed into anatase phase. The comparison reference of Ref [8], The nano-titanium dioxide film deposited by oxidation in an oxygen atmosphere via UVIBS preparation is an anatase type. The blue-shift at 520 cm-1 was due to the compressive stress caused by lattice compression. The lattice compression induces a higher energy state and consequently a blue shift. The red-shift at 500 cm-1 is due to the quantum size effect. A relaxed state in geometry will induce a redshift at the relatively low frequencies. In addition, the lattice compression results in the blue shift of Raman scattering frequency. The lattice compression results in the decrease of the bond length. Which causes a decrease of resonant wave length. and Raman scattering is also a kind of resonant mode, which results in the blue shift of frequency.

Resistivity (Ω-m)

e-12

e-13

e-14

200

300

400

500

600

700

800

900

Thickness (Angstrom)

Fig. 1(b) Relationship between thickness and resistance diagram for nano-scaled titanium films Thickness (Angstrom)

1400 1200 1000 800 600 400 200 -40

-30

-20

-10

0

10

20

30

40

Rotation (degree)

Fig. 2(a) Relation between different angles and thicknesses

Fig. 2(b) Raman scattering spectrum of nano-scaled titanium dioxide sputtered at different angles by UVIBS in an oxygen atmosphere.

Applied Mechanics and Materials Vols. 479-480

53

Characteristics of nano-scaled titanium dioxide prepared by a rapid annealing furnace. The thickness of nano-scaled titanium dioxide prepared at different sputting angles and oxidized in a rapid annealing furnace is shown in Fig. 3 (a). The thickness of nano-scaled titanium dioxide reaches the maximum value (about 1700 Angstrom) at the angle of 20 degrees. This sputtering angle also has the highest deposition rate. Because the plasma generated by ion-beam has a cosθ distribution, deposition rate is reduced for small angles. In addition, the restructuring energy provided by the rapid annealing furnace causes the rearrangement of surface atoms, as well as the thickness of sputtered film. The Raman scattering spectrum of the titanium dioxide oxidized in the rapid annealing furnace is shown in Fig. 3 (b). Fig3(b) presents the peaks for -30 degrees, -20 degrees, -10 degrees, 0 degree, 10 degrees, 20 degrees, 30 degrees are 520 cm-1, 520 cm-1, 520 cm-1, 540 cm-1, 520 cm-1, 570 cm-1, and 540 cm-1, respectively. Comparing the above results with the reference values of Ref [6], the characteristics peak of titanium dioxide is 513 cm-1. The nano-titanium dioxide formed by rapid annealing is anatase, however, the Raman peaks are at 520 cm-1, 540 cm-1, 570 cm-1 obviously. The stress initiated from lattice compression results in a high energy state, which results in a blue shift.

Thickness (Angstrom)

1800 1600 1400 1200 1000 800 -30

-20

-10

0

10

20

30

Rotation (degree)

Fig. 3(a) Thickness at different angles by UVIBS and oxidized in a rapid annealing furnace.

Fig. 3(b) Raman scattering spectrum of nano-scaled titanium dioxide sputtered at different angles by UVIBS and oxidized in a rapid annealing furnace. CONCLUSIONS In this study, nano-titanium films of different thicknesses were prepared by an ultra-high vacuum ion beam sputtering machine (UVIBS) and varying bombarding angles. When the thickness of the titanium film is in the nano-range, the resistance decreases from the bulk value of 10-5 (Ω-m) to 10-6 (Ω-m). When the titanium film thickness is less than 500 ~ 600 Angstrom, the decrease of resistance valve was the most significant. Because of the quantum confinement effect of electrons in the semiconductor material, 500-Angstrom nano-titanium films have a discontinuity between resistivity and thickness. This phenomenon can be used in future applications, such as electrodes of optical communication, sensors, and solar cells.

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Acknowledgments This work was financially supported by the National Science Council of Taiwan, No. 100-2218-E-259-003-MY3, which is gratefully acknowledged. References [1] J. Emsley: Nature's Building Blocks: An A-Z Guide to the Elements. 6th edition. Oxford University Press. 451 (2006). [2] M. K. Nazeeruddin, A. Kay, I. Rodicio, R. Humphry-Baker, E. Mueller, P. Liska, N. Vlachopoulos, and M. Gratzel: J. Am. Chem. Soc. Vol. 115 (1993), p. 6382. [3] B. O’Regan and M. Gratzel: Nature Vol. 353 (1991), p. 737. [4] A. D’Orazio, M. De Sario, L. Mescia, V. Petruzzelli, F. Prudenzano, A. Chiasera, M. Montagna, C. Tosello and M. Ferrari: J. Non-Cryst. Solids Vol. 322 (2003), p. 278. [5] V.G. Bessergenev, I.V. Khmelinskiia, R.J.F. Pereiraa, V.V. Krisukb, A.E. Turgambaevab and I.K. Igumenovb: Vacuum Vol. 64 (2002), p. 275. [6] A. Olea, C. Ponce and P.J. Sebastina: Sol. Energ. Mat. Sol. C Vol. 59 (1999), p. 137. [7] W.E. Buhro, V.L. Colvin. Semiconductor nanocrystals: Nat. Mater. Vol. 2 (2003), p.138. [8] P. Periyat, K.V. Baiju, P. Mukundan, P.K. Pillai, and K.G.K. Warrier: Appl. Cata. A-Gen. Vol. 349 ( 2008), p. 13

Applied Mechanics and Materials Vols. 479-480 (2014) pp 55-59 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.55

Step-stress Accelerated Degradation Testing of NBR Sealing Ring Xiaohong Wang1, a, Lizhi Wang1,b, Xin Zhang1,c, Qiuxi Li1,d 1

School of Reliability and System Engineering, Beihang University, Beijing 100191, China a

b

c

[email protected], [email protected], [email protected]

（

）

Keywords: Nitrile-butadiene rubber NBR ; compression set; Step-stress accelerated degradation testing

Abstract. As an important performance parameter of nitrile-butadiene rubber（NBR）sealing ring, the compression set is a main factor influencing rubber's life. Using the compression set amount as its degradation measurement and the temperature as accelerating stress, we perform the design and actual implementation of a set of accelerated degradation test of NBR considering step-stress. Then we evaluate the results using accelerated degradation model based on the drift theory of Brownian motion. Finally we get the estimation of reliable life of sealing ring under normal temperature. The research in this paper can also offer a new method for the application reliability and life evaluation of rubber products. Introduction By analyzing the failure of a certain electro-hydraulic system, we find that the system's main fault is jamming, performance degradation and leak, so the fault mechanism can be summed up in three kinds, namely the oil contamination, seal damage, and wear[1]. The failure of the sealing ring or the decline in sealing effect is responsible for the oil leakage which enables the external impurities into hydraulic system to pollute the internal oil and causes a series of subsequent damage which has a significant influence on the lifetime and reliability of hydraulic system. So sealing effect becomes a weak link in electro-hydraulic system. An experimental study was conducted on rubber sealing ring using the method of step-stress accelerated degradation test, for the following reasons[2]. Rubber products are widely applied in the industry and our life. In the process of manufacture, storage and application, the rubber’s physicochemical property and mechanical performance would degenerate for internal and external causes. This degradation may influence the products’ reliability and safety, which is a main failure mechanism of rubber, and is also called aging of the rubber. So it is meaningful to study the degradation of the rubber. There had been a lot of research in rubber’s degradation. Y.T.Hsu adopted several electrical approaches to monitor the electrical degradation of ethylene propylene rubber (EPR) cable[3]. Fengzhen Chen studied the thermal degradation of waste rubber[4]. M.Abdul Kader studied the rubber’s thermal ageing and degradation behavior[5]. Abhijit Jha[6], Shuguo Chen[7] and Jyh-Ping Lin[8] studied the thermal degradation behavior of different rubbers. Since nitrile rubber is a main seal material of electromechanical products in aviation, and has an important position in the industry, this paper will study the nitrile rubber O-rings’ degradation behavior. The traditional research method of rubber’s degradation is aging test or accelerated aging test. For example, P.Y.le Gac studied marine aging of a silica-filled chloroprene rubber with accelerated aging test[9]. Deng Huang developed an accelerated aging test with aging temperature of 70℃[10]. David R.Bauer use the temperatures in accelerated aging test as high as 70℃[11]. P.R. Morrell use Accelerated thermal aging to study the nitrile rubber O-rings with the temperature as high as 110℃[12]. However, as rubber develops, the tradition method may not satisfy when rubbers need to be developed with less time and resources, and convincing and statistic results could be achieved the same time. Under the circumstances, accelerated degradation testing (ADT) serves as an effective approach to study degradation, which is a whole set of modeling and statistics method developed after decades of

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research by Nelson[13], Meeker [14], Kvam[15], etc. Also, the testing has already been applied to many products like film resistance, MOS, logic chip, LED, carbolic fiber and so on. Therefore, ADT is chosen to study the nitrile rubber O-rings. Besides, the use of step- stress in degradation test can save test costs and test time more effectively. So it is quite necessary to study the method of accelerated degradation based on step- stress to get more information. Methodology The accelerated degradation test design on the rubber sealing ring includes pre-testing and formal test. Pre-testing was applied to determine the highest temperature the rubber sealing ring can withstand, the way of temperature stress loading and decide the initial performance degradation fitting model. Its specific contents include: according to the characteristics of NBR, we select 90℃as accelerating stress and input six rubber seal for constant stress accelerated testing. The performance testing cycle is 1 day, and the test time is 25 days. Based on the results of the pre-testing, input 12 rubber seals for formal step-stress accelerated degradation testing (SSADT). Specific test design is shown in Table 1. Table 1 NBR sealing ring SSADT scheme design table the way of temperature stress loading

step-stress

stress level

70[℃], 80[℃], 90[℃], 100[℃]

measuring period measure points

，90[℃], 100[℃] once a day ，16 below 80[℃]，18 below 90[℃]，14 below100[℃]

Below 70[℃], 80[℃] every 2 days 13 below70[℃]

measurement parameters

rubber ring axial thickness

measuring accuracy

0.01[mm]

test sample size

12

test fixure number test time

3, four rubber rings are placed above each fixure S3 > S2 > S1, which agrees with the photovoltaic efficiency. These results indicate that a higher electron recombination rate leads to a lower photovoltaic efficiency.

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Conclusions Vertically aligned ZnO nanostructure array on ITO or FTO substrates can be obtained by a CBD method from a zinc acetate solution with preformed ZnO seeding layer under controlled pH value. XRD patterns indicates a hexagonal wurtzite structure for ZNR and a (100) preferential crystal plane after etching. Increasing TiO2 coating times increases both the band and excitonic PLs of TiO2/ZnR before and after etching. XRD patterns of TiO2 cannot be observable for the TiO2/ZNR samples. The ZnO seed layer number (SLN) affects significantly the photovoltaic efficiency. Initially increasing the SLN increases the photovoltaic efficiency, however, exceeding the optimum SLN causes a decreased efficiency of the DSSC device. Acknowledgements This work was financially supported by the National Science Council of Taiwan, the Republic of China, under Grant numbers of NSC 100-2221-E-168-037 and NSC 100-2632-E-168-001-MY3.

a

d

b

c

e

f

Fig. 1 SEM images of (a)Top (b)Cross sectional views of ZnO seed layer (c)Top (d) Cross sectional views of the B5S4Z3T1E3 sampes (e)High resolution of (d) and (f)high resolution of B5S4Z3T0. a

b

Fig. 2 EDS diagram of the (a) B5S4Z3T1E3 and (b)B5S4Z3T5E3 samples

Applied Mechanics and Materials Vols. 479-480

2.0

31.86

Intensity (a.u.)

34.56 33.68 32

34

37.76

36

26.58

c b

Absorbance (a.u.)

a 36.36

30

73

1.5

(a) B5S4Z1T1 (b) B5S4Z2T1 (c) B5S4Z3T1

b

1.0

0.5

c

a 20

25

30

35

40

0.0 200

300

400

500

600

Wavelength (nm)

2 Theta , (degree)

Fig. 3 XRD patterns of (a) FTO substrates (b)B5S4Z3T1E3 (c)B5S4Z3T6E3

Fig. 4 Effect of CBD times on the optical absorption of unetched TiO2/ZNR samples

(a) B5S4Z3T1E3 (b) B5S4Z3T3E3 (c) B5S4Z3T5E3

10

c

b

5

a

0 400

450

500

550

600

Wavelength (nm)

(a) B5S1Z3T1 (b) B5S2Z3T1 (c) B5S3Z3T1 (d) B5S4Z3T1 (e) B5S5Z3T1

4

3

d a

2

e b

c

1

0 0.0

0.2

0.4

0.6

Voltage (V)

Fig. 5 Effect of spin coating time of TiO2 on the PL intensity of etched TiO2/ZNR samples

2 Current Density (mA/cm )

Current Density (mA/cm2)

PL intensity (a.u.)

15

Table. 1 Photovoltaic parameters of the DSSCs with ZnO seed layer number of the unetched TiO2/ZNR samples

0.00

d c

-0.02

Fig. 6 Effect of ZnO seed layer number on the I-V curves of the unetched TiO2/ZNR samples

e a

-0.04

-0.06

-0.08

-0.10 0.0

b (a) B5S1Z3T1 (b) B5S2Z3T1 (c) B5S3Z3T1 (d) B5S4Z3T1 (e) B5S5Z3T1 0.2

0.4

0.6

Voltage (V)

Fig. 7 Effect of ZnO seed layer number on the dark current of the unetched TiO2/ZNR samples

*: With etching by HCl and on FTO substrates

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References [1]P. Charoensirithvorn, Y. Ogomi, T. Sagwa, S. Hayase, S. Yoshikawa, J. Electrochem. Soc. 157 (2010) B354-B356. [2]J. Chae, M. Kang, J. Power Source 196 (2011) 4143-4151. [3]L.-Y. Lin, M.-H. Yeh, C.-P. Lee, C.-Y. Chou, R. Vittal, K.-C. Ho, Electrochimica Acta 62 (2012) 341-347. [4]D. Zhao, T. Peng, L. Lu, P. Cai, P. Jiang, Z. Biau, J. Phys. Chem. 112 (2008) 8486-8494. [5] J.T. Park, R. Patel, H. Jeon, D. J. Kim, J.-S. Shin, J. H. Kim, J. Mater. Chem. 22 (2012) 6131-6138. [6]J. Dewalque, R. Cloots, F. Mathis, O. Dubreuil, N. Krins, C. Henrist, J. Mater. Chem. 21 (2011) 7536. [7] K. Lee, D. Kim, P. Schmuki, Chem. Commun. 47 (2011) 5789-5791. [8]X. Feng, K. Shankar, O.K. Varghese, M. Paulose, T. J. Latempa, C.A. Grimes, Nano Lett. 8 (2008) 3781. [9] J. Chung, J. Lee, S. Lim, Phys. B, 405 (2010) 2593. [10] L. Dloczik, O. Ileperuma, I. Lauermann, L.M. Peter, E. A. Ponomarev, G. Redmond, N. J. Shaw, I. Uhlendorf, J. Phys. Chem. B, 101 (1997) 10281. [11] N. Kopidakis, K. D. Benkstein, J. V. d. Lagemaat, A. J. Frank, Phys. Rev. B, 73 (2006) 045326. [12] M. Quintana, T. Edvinsson, A. Hagfeldt, G. Boschloo, J. Phys. Chem. C, 111 (2007) 1035. [13] E.M. Kaidashev, M. Lorenz, H. Von Wenckstern, A. Rahm, H.C. Semmelhack, K.H. Han, G. Benndorf, C. Bundesmann, H. Hochmuth, M. Grundmann, Applied Physics Letters 82 (2003) 3901. [14] M. Law, L.E. Greene, J.C. Johnson, R. Saykally, P. Yang, Nature Materials 4 (2005) 455. [15] P.S. Archana, R. Jose, C. Vijila, S. Ramakrishna, Journal of Physical Chemistry C 113 (2009) 21538. [16] Y.F. Hsu, Y.Y. Xi, A.B. Djuriˇsi ´ c, W.K. Chan, Applied Physics Letters 92 (2008). [17] J.B. Baxter, A.M. Walker, K.V. Ommering, E.S. Aydil, Nanotechnology 17 (2006) S304. [18] C. H. Ku, J. J. Wu, Nanotechnology, 18 (2007) 505706. [19] C. K. Ku, H. H. Yang, G. R. Chen, J. J. Wu, Crystal Growth Design 8 (2008) 283. [20] M. Zhou, J. Yu, S. Liu, P. Zhai, L. Jiang, J. Hazard. Mater. 154 (2008) 1141. [21] L. Jing, Y. Qu, B. Wang, S. Li, B. Jiang, L. Yang, W. Fu, H. Fu, J. Sun, Solar Energy Mater. Solar Cells 90 (2006) 1773. [22] J. G. Yu, H. G. Yu, B. Cheng, X. J. Zhao, J. C. Yu, W. K. Ho, J. phys. Chem. B 107 (2003) 13871.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 75-79 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.75

Tuning the Torsion Mechanical Properties of Carbon nanotube by Feeding H2 Molecules Bin-Hao Chen1*, Yi-Wu Chao2, Cheng-Chi Wang2 1*

No.49, Zhonghua Rd., Xinshi Dist., Tainan City 74448, Taiwan, R.O.C. 74448 Department of Energy Application Engineering, Far East University

2

No.49, Zhonghua Rd., Xinshi Dist., Tainan City 74448, Taiwan, R.O.C. 74448 Department of Mechanical Engineering, Far East University 1

[email protected] Corresponding author

Keywords: Hydrogen Storage, SWCNT, Torsion

Abstract: The torsional response of single-wall carbon nanotubes filled with Hydrogen molecular (H2) under a combination of tension and torsion are conducted using molecular dynamics. The model accounts for the deformation of CNTs, and interactions among gas molecules; between gas and carbon atoms. The effect of particle loading is predicted to significantly change CNT’s critical torsional moment and stiffness. The critical torsion moment and shear modulus are predicted. This is therefore an approach by which the torsional mechanical properties and oscillation frequencies of carbon nanotubes may be tuned. Importantly, the predicted changes in torsional siffness are unique relative to conventional linear elastic materials and are indicative of nonlinear oscillations due to nonlinear mechanical effects. At higher torsional angle, van der Waal molecules reveal a stability effect on carbon nanotubes. Introduction Carbon nanotubes (CNTs) have been proposed as one of the most promising materials for nano-electro-mechanical system due to high elastic modulus, high failure strength and excellent resilience [1,2]. Recent development of many-body interaction [3,4] made possible realistic molecular dynamics (MD) simulations of carbon-made systems. We carried out such studies for carbon nanotubes under generic mode of mechanical load: torsion. A singular behavior of the nanotube energy at certain levels of strain corresponds to abrupt change in morphology. In this letter, we report the torsional instability analysis of single wall carbon nanotube filled with van der Waals molecules via molecular dynamics simulations. The simulations are carried out at a low temperature 77K which previous study obtained the physical adsorption inside CNT at this condition [A. C. Dillon]. Here we use atomistic simulations to study a flexible surface narrow carbon nanotube with tube diameters 10.8 Å. According to conventional physisorption principles, the gas-adsorption performance of a porous solid is maximized when the pores are no larger than a few molecular diameters [8]. Under these conditions, the potential fields produced at the wall overlap to produce a stronger interaction force than that observed in adsorption on a simple plane. However, the mechanisms responsible for the adsorption and transportation of hydrogen in nanoporous solids or nanopores are not easily observed using experimental methods. As a result, the use of computational methods such as molecular dynamics (MD) or Monte Carlo (MC) simulations have emerged as the method of choice for examining the nanofluidic properties of liquids and gases within nanoporous materials [9,10]. Several groups have performed numerical simulations to study the adsorption of water in CNTs [11-16], while others have investigated the diffusion of pure hydrocarbon gases and their mixtures through various SWNTs with diameters ranging from 2 ~ 8 nm [17-19] or the self- and transport diffusion coefficients of inert gases, hydrogen, and methane in infinitely-long SWNTs [20-21]. In general, the results showed that the transport rates in nanotubes

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are orders of magnitude higher than those measured experimentally in zeolites or other microporous crystalline solids. In addition, it has been shown that the dynamic flow of helium and argon atoms through SWNTs is highly dependent on the temperature of the nanotube wall surface [22]. Specifically, it was shown that the flow rate of the helium and argon atoms, as quantified in terms of their self-diffusion coefficients, increased with an increasing temperature due to the greater thermal activation effect. Previous MD simulations of the nanofluidic properties of liquids and gases generally assumed the nanoporous material to have a rigid structure. However, if the nanoporous material is not in fact rigid, the simulation results may deviate from the true values by several orders of magnitude. Several researchers have investigated the conditions under which the assumption of a rigid lattice is, or is not, reasonable [23, 24]. In general, the results showed that while the use of a rigid lattice was permissible in modeling the nanofluidic properties of a gas or liquid in an unconfined condition, a flexible lattice assumption was required when simulating the properties of a fluid within a constrained channel. Moreover, in real-world conditions, the thermal fluctuations of the CNT wall atoms impact the diffusive behavior of the adsorbed molecules, and must therefore be taken into account. This study performs a series of MD simulations to investigate the transport properties of hydrogen molecules confined within a narrow CNT with a diameter of 10.8 Å (~ 1 nm) at temperatures ranging from 100 ~ 800 K and particle loadings of 0.01~1 No/Å. To ensure the validity of the simulation results, the MD model assumes the tube to have a flexible wall. Hydrogen molecules are treated as spherical particles. In performing the simulations, the hydrogen molecules are assumed to have a perfectly spherical shape. In addition, the interactions between the molecule and the CNT wall atoms and the interactions between the carbon atoms within the CNT wall are modeled using the Lennard-Jones potential [25,26]. The simulations focus on the hydrogen adsorption within the SWNT not adsorption in the interstices or the external surface of nanotube bundles. Simulation Model Figure 1 shows a simulated nanotube exposed to torsion. The atomic interaction was modeled by the Tersoff-Brenner potential, which reproduced the lattice constants, binding energies, and the elastic constants of graphie and diamond [4]. The long range van der Waals interactions is calculated by Lennard-Jones 12-6 potential with well-depth energy of e = 4.7483×10-22 J and equilibrium distance of σ = 0.3407 nm. For effective comparison with theory, all simulations are performed at specified low temperature in a range 1~100K using Nosé-Hoover thermostat. A 1 fs time step was used in all MD simulations. A constant increment of shears strain, ∆γ = 10-4, is applied to two rings of atoms located at the tube ends. The increase of azimuthal angle φ between the tube ends results in the change of energy and morphology. At small strains the total energy grows as E (ε ) = E ′′ε , Shown in Fig. 1 are morphology changes of SWCNT under torsion with loading 1~100 hydrogen molecules. We can see clearly that the torsional deformation of a loaded SWCNT is significantly dependent on the number of loading particles. In the twisting direction, the tube buckles at a critical buckling strain γcr=7.6%. This means that the stability of a tube by feeding different number of particles may be quite different, suggesting particular caution in the use of CNTs as torsional components or hydrogen storage of nanomechanical device.where E ′′ = 59 eV atom . The patterns 1(a)-1(d) illustrate the corresponding morphological changes. The presence of three singularities was also observed in strain-energy curve. The shading indicates strain energy per atom, equally spaced from below 0.5 eV to above 1.5eV. The sequence of singularities in E (ε ) corresponds to a loss of molecular symmetry. The intrinsic symmetry of a graphite sheet is hexagonal. Since the elastic properties of a two-dimensional hexagonal structure are isotropic [11], it can be approx imated by a uniform shell with only two elastic parameters: flexural rigidity D, and its resistance to an in-plane stretching, the in-plane stiffness C. The energy of a shell is given by a surface integral of the quadratic form of local deformation [12], 1 2

2

C  2 (εx +ε y )2 − 2(1−v) εxε y −εxy2 ds E(ε ) = 12 ∫∫D (κx +κy ) − 2(1− v) κxκy −κxy2 + 2 1− v  

[

(

)]

[

(

)]

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Where κ is the curvature variation, ε is in-plane strain, and x and y are local coordinates. The values of D and C can be identified by using the data of Ref [13], we obtain C=59 eV/atom=360 J/m2 and D=0.85 eV. The Poisson ratio v=0.19 was extracted from a reduction of the diameter of a tube stretched in simulations. Shear stresses versus shear strain are shown in Fig. 3 for tube with different loadings. The shear stress is calculated by the differential of corresponding strain energy with respect to shear strain. It is seen that the mechanical behavior of all different loading conditions in the twisting direction is bilinear even tri-linear in the whole strain range before buckling. The strain energy displays three singularities corresponding to shape changes. The energy of sawtooth (8,0) tube 11 nm long and diameter 1 nm, as a function of torsion angle φ. At azimuthal angle φ1 = 2.7 the cylinder flattened into a straight axis spiral. At φ2 = 7.2 the whole helix buckles.

0p

10p

30p

50p

70p

100p

Fig 1 Morphological changes for a (8, 0) nanotube

Fig 2. Shear stress versus shear strain under different

under torsion

particle loading

Mechanical Response Shear stresses versus shear strain are shown in Fig.2 for different prticle loadings. The shear stresses here is calculated by the differential of the strian energy with respect to shear strian. The effective wall thickness is simplely choosen as 0.34nm for the convenience of comparison with previous results. From Fig 2, it is seen that the mechanical behavior of all tubes in the twisting direction is linear in the strain range from -5%- +5%. The strain-intensive shear modulus of about 0.38TPa are obtained form these different particle loading situations. Shear modulus of this study is comparable to other results. Lu reported a shear modulus about 0.45TPa; Hall obtained a shear modulus of 0.41TPa. Strain-hardening effect occurs almost in all different loading particles. The torsion behavior of all tubes is dependent on the number of loading particles inside the CNTs. Torsional Stiffening Effect Since filling CNTs with other materials has been shown to affect their torsional properties under torsional load, the effect of filling CNTs on torsion response under hydrogen molecules storage is consider here for CNTs that have aspect ratio of 10. Figure 3 illustrates how shear modulus variation (G/Gpris.) under torque for filled CNTs significantly increase in proportional to number of particles inside CNTs. However, the overall behavior is considerably different from the behavior of hollow CNTs and depends on the nature of filling materials. For this case, interaction between tube wall and loading particles (hydrogen molecules) is van der Waals force. While the net increment in critical torsional moment shows significant differences between hollow and filled CNTs. The maximum shear of filled CNTs can be increase to about 1.4 times larger than pristine one.

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Fig. 3 Variation curves of the critical as function of the H2 loading

It is therefore not surprising that Fig. 3 indicates that the torsional shear moduli of filled CNTs are higher than those without filled hydrogen. Interestingly, Fig. 3 also shows that the values of (G/Gpris.) for filled CNTs are significantly different from the values for hollow CNTs. According to previous studies, the shear moduli of filled CNTs do not depend on the type of filling materials due to the relatively weak van der Waals shear interactions between tube wall and filling materials [27]. Continuum mechanics and linear elasticity has applied to study the mechanical behavior of CNTs, either on their own or in combination with molecular dynamics or atomistic simulations. In linear elasticity, the total strain under combined tensile and torsional loading is expressed as sum of the strain energy for each direction. This means that there is no interaction between tension and torsion. However, as mentioned above, the torsional shear modulus of CNTs filled by van der Waals particles is significantly changed by filled particles. This indicates that filling particles enhance the mechanical coupling influences. Filled particles in CNTs combine the effects of both tension and torsion. The mechanical coupling effect influences the torsional response, which is probably caused by tensile strain energy that is much larger than torsional shear strain energy. Accordingly, the torsional shear modulus of CNTs under combine loading can be expressed as; G = Gpure + ∆Gcouple Where ∆Gcouple is the torsional shear modulus increased by the filling particle coupling effect. Linear elasticity indicates that the mechanics of materials in terms of unchangeable elastic moduli, and the torsional response of filled CNTs are beyond linear elasticity theory.

CONCLUSIONS The mechanical response of single-walled carbon nanotubes under torsion is studied using molecular mechanics simulations. In conclusion, we have shown that the critical torsional moment and shear modulus of hollow and filled CNTs under combined tensile and torsion loads increase as a results of the coupling. In particular, the important increase in torsion shear modulus indicates that the torsional responses under combined loading are beyond linear elasticity theory. The simulations furthur indicate that the coupling effects between tension and torsion also significantly increase torsional stiffness and oscillation frequency.This finding should lead to the preferential design of torsional NEMS devices. Acknowledgments: This work is supported by the National Science Congress R.O.C. under Grant No. NSC 101-2221-E-269-010

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References and Notes [1] H. Dai, E. W. Wong and C. M. Lieber, 1996 ,Science 272, 523 [2] T. W Ebbesen, Annu. Rev Mater. , 1994 , Sci. 24 235. [3] T. W. Ebbesen, H. J. Lezec, H. Hiura, J. W Bennett, H. F Ghaemi and T. Thio, 1996 , Nature 382 54P. M. Ajayan, L. S. Schadler, C. Giannaris and A. Rubio, 2000 , Adv. Mater. (Weinheim, Ger.) 12, 750 [4] A. Allaoui, S. Bai, H. M. Cheng and J. B. Bai, Compos. , 2002 , Sci. Technol. 62, 1993 [5] S. U. S. Choi, Z. G. Zhang, W. Yu, F. E. Lockwood, and E. A. Grulke, 2001 ,Appl. Phys. Lett. 79, 2252 [6] M. J. Biercuk, M. C. Llaguno, M. Radosavljevic, J. K. Hyun, 2002 , A. T. Johonson and J. E. Fischer, Appl. Phys. Lett. 80, 2767 [7] L. Dai, 2004 , Intelligent Macromolecules for smart device, Springer, Berlin [8] J. P. Salvetat, J. M. Bonard, N. H. Thomson, A. J. Kulik, L. Forro, W. Benoit and L. Zuppiroli, 1999 , Appl. Phys. A: Mater. Sci. Process, 69, pp255. [9] P. Calvert, 1999 , Nature 399, pp210. [10] R. J. Chen, Y. Zhang, D. Wang and H. Dai, J. Am. Chem. , 2001 , Soc. 123, pp3838 [11] P. G. Collins and P. Avouris, 2000 ,Nanotubes for electronics, Sci. Am. 283, pp38-45,. [12] N. G. Chopra, L. X. Benedict, V. H. Crespi, M. L. Cohen, S. G. Louie and A. Zettl, 1995 , Nature, 377, 135-138. [13] M. F. Tu, T. Kowalewski and R. S. Rouff, 2001 , Phys. Rev. Lett. 86, 87-90. [14] P. H. Zhang and V. H. Crespi, 1999 , Phys. Rev. Lett. 83, 1791-1794. [15] S. V. Rotkin and Y. Gogotsi, 2002 ,Mater. Res. Innovations 5, 191-200. [16] Rappè A. K., Casewit C. J., Colwell K. S., Goddard W. A. III, Skiff W. M., UFF, J. Am. Chem. , 1992 ,Soc., 114, 10024-10035. [17] J. M. Haile, Molecular Dynamic Simulation, John Wiley and Sons, 1992 , Inc. NewYork. [18] Müller-Plathe, F., J Chem. , 1997 , Phys., 106, 6082-6085. [19] Clifford W. Padgett and Donald W. Brenner, 2004 ,Nano lett. 4, 1051-1053. [20] María J. López, Angel Rubio and Julio A. Alonso,arXiv:cond-mat/0303648v1. [21] Gang Wu and Baowen Li,arXiv:0707.4241v1. [22] C. H. Chen and Y. C. Lee, J. , 2007 ,Micromech. Microeng. 17, 1252-1256. [23] R. E. Tuzun, D. W. Noid, B. G. Sumptr and R. C. Merkle, 1997 ,Nanotechnology 8, 112 [24] Y. Guo, N Karasawa and W. A. Goddard, 1991 , Nature 351, 464 [25] R. Richert and A. Blumen (ed) , 1994 ,Disorder Effects on Relaxational Processes: Glasses, Polymers, Proteins (New York: Springer) [26] Byeong-Woo Jeong, Jang-Keun Lim and Susan B. Sinnot, 2007 , Appl. Phys. Lett.91, 093102

Applied Mechanics and Materials Vols. 479-480 (2014) pp 80-85 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.80

Atomic Layer Deposited Al2O3 Barrier Layers on Flexible PET Substrates Rwei-Ching Chang1, a, Hsi-Ting Hou2, b, Fa-Ta Tsai3 c and Pei-Sin Jhu1, d 1

Department of Mechanical and Computer-Aided Engineering, St. John’s University, New Taipei City, 25135, Taiwan 2 Department of Electrical Engineering, Tamkang University, New Taipei City, 251, Taiwan 3 Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, 106, Taiwan a

[email protected], [email protected], [email protected], d [email protected]

Keywords: Barrier layers, Atomic layer deposition, Flexible substrates, PET, Aluminum oxide.

Abstract. Atomic layer deposition (ALD) is utilized to grow high performance aluminum oxide (Al2O3) barrier films on flexible PET substrates, where the effects of precursor pulse time and deposition temperature on the film properties are also studied in this work. Significant differences are observed that the water vapor transmission rate of the PET substrate is largely improved by coating the Al2O3 barrier films. Further observations on the surface roughness, optical transmittance, adhesion, mechanical properties of the deposited films are also conducted. The results show that the Al2O3 film deposited with 10 msec precursor pulse time and 60°C deposition temperature behaves the best performance. Introduction Atomic layer deposition (ALD) has potential benefits for various thin films deposition due to precise thickness controllability, large area uniformity, and low process temperature, which has become an important thin film growth technique [1]. ALD relies on a binary reaction sequence of self-limiting chemical reactions between gas phase precursor molecules and a solid surface. Typically, ALD films are extremely smooth and conformal to the underlying substrate surface. This conformal property of ALD films has allowed the successful coating of powders [2], nanoporous membranes and high aspect ratio trench structures [3]. ALD techniques exist for depositing a variety of substances including oxides, nitrides and metals [4], that usually performs at a lower temperature than chemical vapor deposition (CVD) [5]. Synthetic polymers are widely used in packaging because of their relatively low cost, high performance, and flexibilty especially. However, the moisture sensitivity restricts their extended use. One way to improve the water sensitivity is to coat a barrier layer on the polymer surface. Therefore, ALD provides a surface-controlled layer-by-layer deposition process that is suitable to produce inorganic barrier coatings on various materials [4]. Aluminum oxide (Al2O3) grown by ALD can work as a high-quality pore-free barrier film, which can be deposited on polymer substrates to coat effective permeation barrier against oxygen and moisture. The adhesion of ALD-grown Al2O3 film with the polymer substrate is commonly excellent because of the covalent bonding. Therefore, the ALD-grown Al2O3 films are successfully used in thin film encapsulation [6]. However, ALD is based on the thermal process in which the surface chemistry is only driven by thermal energy delivered to the substrate. Therefore, the properties of the ALD films are highly dependent on the deposition conditions [7, 8]. In this work, to improve the moisture pretection performance of PET substrates, ALD-grown Al2O3 barrier layers are investigated. A 100 nm thick Al2O3 film is grown by ALD with various 10, 15 msec precursor pulse time and 60, 80, 100 °C deposition temperature, respectively. Some major properties of the Al2O3 films, including roughness, adhesion, modulus, hardness, and optical transmittance are characterized. Specifically, the water vapor transmission rate of the PET substrates improved by coating Al2O3 films are also discussed.

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Specimen Preparation A 100 nm Al2O3 thin film is fabricated on the glass substrate by ALD with various temperaturesand pulse times. The ALD reactor is shown as Fig. 1, where the precursor and purging gas are controlled by switching valves and flow past the substrate surface and into a mechanical pump. The fabrication parameters of the ALD are listed in Table 1. Three substrate temperatures, 60, 80, and 100 °C, are considered, and the chamber pressure is controlled at 9×10-3 Torr. The precursor H2O, purging N2 gas, precursor TMA, and purging N2 gas are controlled to flow into the chamber in sequence. As shown in Fig. 2, the Al2O3 film sequentially grows with H2O precursor, 6000 msec of N2 purging, DEZ precursor, and 6000 msec of N2 purging, where two precursor pulse time (PT) are considered, 10 and 15 msec . The film thickness is controlled as 100 nm, consequently near 1000 cycles are needed.

Fig. 1 Schematic view of ALD reactor. Table 1 ALD parameters of coating Al2O3 films on PET substrates with various temperatures and precursor pulse times. Film type Al2O3 60, 80, 100 Temperature (°C) Chamber pressure (Torr) 9×10-3 H2O pulse time (msec) 10, 15 N2 pulse time (msec) 6000 TMA pulse time (msec) 10, 15 N2 pulse time (msec) 6000 Cycle number 1000 Film thickness (nm) 100

Fig. 2 Time sequence of Al2O3 films growth by ALD (unit: msec; PT=10 or 15 msec).

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Results and Discussion The surface condition of the atomic layer deposted Al2O3 films on PET substrates are first measured by the atomic force microscope (AFM). The AFM surface images are shown in Fig. 3 and the measured average roughnesses are listed in Table 2. Fig. 3(1) shows the AFM image of the PET substrate without coating the Al2O3 film, where the surface is smooth and the average roughness is 1.46 nm. After depositing Al2O3 films on the PET surface, the average roughness increases to 3.78 nm with the deposition conditions of 10 msec precursor pulse time and 60°C substrate temperature, as shown in Fig. 3(2). Comparing the roughness of all specimens listed in Table 2, it indicates the roughness of the Al2O3 film deposited with 10 msec precursor pulse time is better than that with 15 msec pulse time. Furthermore, the roughness of the Al2O3 film increases as the deposition temperature increases from 60 °C to 100 °C. It illustrates the Al2O3 film presents the best surface roughness with the deposition condition of 10 msec precursor pulse time and 60°C substrate temperature (Sample A).

(1) PET (Ra=1.46 nm)

(2) Sample A/PET (10 msec, 60°C, Ra=3.78 nm)

Fig. 3 AFM surface images of Al2O3 films on PET substrates deposited by ALD Table 2 Characteriztion of Al2O3 films on PET substrates deposited by ALD. Samples Sample A / PET Sample B / PET Sample C / PET Sample D / PET Sample E / PET Sample F / PET

Deposition TMA pulse time temperature (msec) (°C) 10 60 10 80 10 100 15 60 15 80 15 100

Ra (nm)

Hardness (GPa)

Er (GPa)

Critical load (mN)

3.78±0.72 4.09±0.98 4.25±1.95 4.00±1.16 4.22±2.52 4.44±2.76

3.29±0.33 2.93±0.17 2.74±0.49 2.82±0.17 2.64±0.13 2.37±0.20

21.1±0.6 19.4±0.5 21.5±0.7 21.8±2.8 20.5±1.7 19.7±0.27

11.6 10.5 8.1 9.4 7.8 6.7

Further observations on optical properties are also conducted. Optical transmittance of the specimens is measured by using an UV/VIS/NIR spectrophotometer (BWTEK BTC112) with normal incidence in the visible wavelength ranged from 400 to 800 nm, taking the air as reference. The results are shown in Fig. 4, where the average transmittance of the Al2O3 film on the PET substrate with 60 °C 10 msec pulse time is 86.02%, and the transmittance increases to 87.16%, 91.9%, 87.92% as the temperature increases to 80, 100 °C. Increasing the pulse time to 15 msec, the transmittance decreases to 84.82%, 85.91%, and 86.14% at 60 °C, 80 °C, and 100 °C deposition temperature, respectively. It indicates that the Al2O3 film deposited with 10 msec pulse time has better transmittance than that with 15 msec. Furthermore, the transmittance increases as the deposition temperature increases from 60 °C to 100 °C. However, there is only 3% transmittance difference for various deposition parameters.

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Fig. 4 Optical transmittance of Al2O3 films on PET substrates deposited by ALD. The critical load of micro scratch testing can be used to represent the adhesion of thin films. In this work, the micro scratch is conducted by a Rhesca CSR-02F thin film scratch tester. A 5 µm diameter stylus is utilized, and the stage angle is tilt 1° with speed 10 µm/s. In the micro scratch, the specimen is mounted on the tilt stage which moves horizontally to push up the stylus on the top end of the sensor. A load, as a consequence, is applied to the surface of the specimen by the stiffness and strain of the cantilever stylus. The cartridge of the micro scratch tester oscillates parallel to specimen surface at fixed amplitude acted by the build–in actuator. The friction between the specimen and the stylus causes relative movement and then generates electric output signals. As long as the specimen surface is not damaged, the sensor can generate output signals proportional to the stylus velocity. As the load reaches the critical value, some scratch noises are generated due to the destruction or rough surface of the sample film, which are reflected and observed as output signals. Fig. 5 shows the scratch results of the Al2O3 films on PET substrates. It illustrates the critical load of Al2O3 films deposited by ALD at 60 °C is 11.6 mN, at 80 °C is 10.5 mN, at 100 °C is 8.1 mN for 10 msec precursor pulse time. For 15 msec precursor pulse time, the critical load of Al2O3 films deposited at 60 °C is 9.4 mN, at 80 °C is 7.8 mN, and at 100 °C is 6.7 mN, respectively. The results indicate that the Al2O3 film deposited with 10 msec pulse time has better adhesion than that with 15 msec. Moreover, the adhesion decreases as the deposition temperature increases from 60 °C to 100 °C.

Fig. 5 Critical load of Al2O3 films on PET substrates deposited by ALD.

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Nanoindentation testing is performed by using a Hysitron Triboindenter fitted with a standard Berkovich indenter. The loading time, holding time, and unloading time of the indentation tests were all 5 sec. In this work, the peak load was carefully controlled so that the indentation depth was always less than 20% of the film thickness for each specimen. The hardness and elastic modulus of the thin film can be directly determined by the load-depth curve of the indentation. In nanoindentation testing, as the indenter presses into the sample, both elastic and plastic deformations occur, resulting in an imprint that conforms to the indenter shape. During the indenter withdraw, only the elastic portion of the deformation is recovered, which facilitates the use of an elastic solution in modeling the contact process [9]. Therefore, nanoindentation hardness H can be defined as H = Pmax / A (1) where Pmax represents the peak load and A is the projected contact area. The hardness is the mean pressure that a material can support under load. Furthermore, the elastic modulus of the indented sample can be inferred from the initial unloading contact stiffness, the slope of the initial portion of the unloading curve. Based on the traditional indentation analysis, the relation between the contact stiffness, contact area, and elastic modulus can be derived analytically and achieve a reduced elastic modulus Er as 1 / Er = (1 −ν 2 ) / E + (1 −ν i2 ) / Ei

(2)

where Ei and ν i are the elastic modulus and Poisson’s ratio of the indenter. However, the indenters used in the practical nanoindentation testing are not ideally sharp. An area function calibration is needed due to the blunting of the tip. Some other calibrations are also needed and some criterions should be obeyed to ensure the accuracy of the testing, including the calibration of thermal drift, machine compliance, electrostatic force, and the criterion of indent depth, surface roughness, etc. The standard analysis of nanoindentation is called Oliver and Pharr method [9]. Then, following the Oliver and Pharr method, the hardness and elastic modulus can be determined. Fig. 6 shows the load-depth curves of nanoindentation of the Al2O3 films on the glass substrates. The indentation probe is loading near to 20 µN and then unloading, while a 3 ~ 5 nm indentation impress is left on the film surface. It illustrates the maximum depth is 16.5 nm for Al2O3 deposited by ALD at 60 °C with 10 msec precursor pulse time, where the reduced modulus and hardness are 21.1 GPa and 3.29 GPa following the Oliver and Pharr method shown in Eqs. (1) and (2). For 80 °C and 10 msec, the maximum depth increases to 17.1 nm, and results 19.4 GPa reduced modulus and 2.93 GPa hardness. For 100 °C and 10 msec, the maximum depth is 16.8 nm, resulting 21.5 GPa reduced modulus and 2.74 GPa hardness. In the case of 15 msec pulse time, the maximum depth become 17.1, 17.6, and 18.2 nm for 60, 80, and 100 °C, resulting 21.8, 20.5, 19.7 GPa reduced modulus and 2.82, 2.64, 2.37 GPa hardness, respectively. The detailed experimental data are summaried in Table 2. It illusterates that the hardness of the Al2O3 deposited with 10 msec pulse time is better than that with 15 msec. The film hardness decreases as the deposition temperature increases from 60 °C to 100 °C.

Fig. 6 Force-displacement curves of nanoindentation of Al2O3 films on PET substrates deposited by ALD.

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The water vapor transmission rates (WVTR) are measured according to the modified gravimetric method (ISO 2528:1995) and expressed as g/m2/day in conditions of 25 °C and 100% relative humidity. The experimental results of WVTR of all specimens are listed in Table 3. It indicates the WVTR of the Al2O3 films on PET substrate ranges from 4.51 to 5.98 g/m2/day, where the value of the PET substrate without Al2O3 films is 11.08 g/m2/day. The result illustrates coating Al2O3 films can effectively reduce the WVTR of the PET substrate, meaning the Al2O3 films provide the function of water vapor protection. It slaso indicates sample A (10 msec and 60 °C) behaves the best water vapor protection. Table 3 WVTR of Al2O3 films on PET substrates deposited by ALD. (Unit: g/m2/day) Sample A Sample B Sample C Sample D Sample E Sample F / PET PET / PET / PET / PET / PET / PET 1 4.4318 4.9858 5.2628 4.7088 4.9858 5.5398 10.2485 2 4.7088 4.7088 5.8167 4.1548 5.2628 6.0937 11.0795 3 4.7088 4.4318 5.2628 4.4318 5.2628 5.8167 11.0795 4 4.1548 4.7088 4.9858 4.9858 4.9858 6.3707 10.8025 5 4.4318 4.7088 5.2628 4.7088 4.4318 6.0937 11.3565 6 4.4318 4.9858 4.9858 4.4318 5.2628 5.8167 11.6335 7 4.7088 5.2628 5.2628 4.7088 4.7088 6.0937 11.3565 Average 4.51 4.83 5.26 4.99 4.59 5.98 11.08 Errors ±0.36 ±0.40 ±0.27 ±0.83 ±0.16 ±0.44 ±0.83 Day

Conclusions Using ALD, a 100 nm Al2O3 barrier film is coated on the flexible PET substrate with 10, 15 msec precursor pulse time, and 60, 80, and 100 °C deposition temperature. The effects of the pulse time and deposition temperature on the microstructure, adhesion, mechanical, optical properties, and water vapor transmission rates of the Al2O3 films are discussed. The results show that the Al2O3 films deposited with 10 msec precursor pulse time presents better surface roughness, optical transmittance, adhesion, hardness, and water vapor transmission rate than that deposited with 15 msec precursor pulse time. Moreover, the roughness, adhesion, hardness, and water vapor transmission rate of the deposited Al2O3 films are improved as the deposition temperature increases from 60 to 100 °C. In summary, the Al2O3 film behaves the best performance with the deposition condition of 10 msec precursor pulse time and 60°C deposition temperature. References [1] H. Kim, J. Vac. Sci. Technol., B: Microelectron. Nanometer Struct. 2 (2003), p.31. [2] J.D. Ferguson, A.W. Weimer, S.M. George, Thin Solid Films 371 (2000), p. 95. [3] M. Ritala, M. Leskela, J. Dekker, C. Mutsaers, P.J. Soininen, J. Skarp, Chem. Vap. Deposition 5 (1999), p.7. [4] J.W. Elama, Z.A. Sechrista, S.M. George, Thin Solid Films 414 (2002), p. 43. [5] D. Kim, H. Kang, J.M. Kim, H. Kim, Applied Surface Science 257 (2011), p. 3776. [6] Y.G. Lee, Y.H. Choi, I.S.Kee, H.S. Shim, Y.W. Jin, S. Lee, K.H. Koh, S. Lee, Organic Electronics 10 (2009), p. 1352. [7] T. Hirvikorpi, M. Vaha-Nissi, J. Nikkola, A. Harlin, M. Karppinen, Surface and Coatings Technology 205 (2011), p. 5088. [8] J.N. Ding, X.F. Wang, N.Y. Yuan, C.L. Li, Y.Y. Zhu, B. Kan, Surface and Coatings Technology 205 (2011), p. 2846. [9] W.C. Oliver and G.M. Pharr, J. Mater. Res. 7 (1992), p. 1564.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 86-90 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.86

Study the rheological property of gel abrasives in magnetic abrasive finishing A-Cheng Wang1, a, Lung Tsai1,b and Yan-Cherng Lin2,c 1

Chien Hsin University of Science and Technology, 229, Chien-Hsin Rd., Chung-Li, Taoyuan county, 320, Taiwan

2

Nankai University of Technology, 568, Chung Cheng Rd., Tsao-Tun, Nan Tou county, 542, Taiwan a

b

c

[email protected], [email protected], [email protected]

Keywords: magnetic abrasive finishing, gel abrasive, rheological property, plasticity

Abstract. Magnetic finishing with gel abrasive (MFGA) performs better than magnetic abrasive finishing (MAF) in terms of polishing efficiency. However, silicone gels are semi-solid polymer gels with deforming properties that are temperature dependent materials, ultimately degrading the polishing efficiency in MFGA significantly. Therefore, this study evaluated the MFGA mechanism to elucidate the properties of silicone gels in order to attain both the finished effect in MFGA and effective gel abrasives to produce a highly efficient polished surface. Cylindrical rods were polished using silicone gels with different plasticity to determine the temperature of abrasive media in the working area. Next, circulating effects of abrasive media were identified to ensure the efficiency in MFGA. Additionally, finding the relation between the concentrations of abrasive media and circulating effect in the working area. Experimental results showed that silicone gels with low plasticity produced high temperature of abrasive media in MFGA, and high temperature of abrasive medium made excellent circulating effect in the working area, inducing high material removal and fine surface roughness. Introduction Magnetic abrasive finishing (MAF) has excellent ability to polish, deburr or remove deteriorated layers from a workpiece and easily obtain a mirror-like surface [1-3]. However, the abrasives are easily flown away from the working area regardless of either un-bonded magnetic abrasives or sintering magnetic abrasives used in MAF; this situation will reduce the polished efficiency and induce the pollution problem in the environment. Application of magnetic finishing with gel abrasive (MFGA) can alleviate the abrasive media problems mentioned above. Wang et al. [4] applied silicone gel to mix steel with grits and silicon carbons as a gel abrasive. This gel abrasive could be closely wrapped around the cylindrical rod without magnetic forces and steel grits and silicon carbons would not fly away by the centrifugal force in MFGA. The results showed that roughness improvement rate still remains at a high level of 90% when the same abrasive medium (35 grams) is used 15 times to finish 15 workpieces; thus this gel abrasive has an excellent ability for recycling. Extensively adopted in abrasive flow machining (AFM), rheological properties of the abrasive medium indicated that medium viscosity reduced drastically after temperature was increased slightly [5-6]. Moreover, silicone rubber, an effective abrasive medium that has a high viscosity and a low flow rate, easily polished WEDM surfaces [7]. However, the difference between MAF and MFGA and the rheological properties of the silicone gel in MFGA were not identified in this research. This study attempts to find how the gel properties affect the polishing efficiency. Methods Materials. Polymer gel was the most important material used in this study to mix the ferromagnetic particles and the abrasives. Silicone gels, semi-solid polymers, have a deformable characteristic, and do not attach itself on the workpiece after contact, making it an excellent material to form the base of

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the gel abrasive [10]. These gels with various plasticity 80, 120, 160, as shown in Fig. 1, were used as bonding gels in MFGA; gels have small plasticity indicating these gels can easily change their shapes under stress (left gel of Fig.2). Given the flexible property of the gel abrasives, this medium can wrap around the workpiece closely. Ferromagnetic particles and abrasives mixed in the silicone gel were steel grit (SG) and silicon carbon (SiC). Mixed ratio of the gel abrasive depended on the weights of the silicone gel, SG and SiC. An attempt was made to determine the polishing effect in the die/mold by choosing the mold steel of SKD-11 as the working material in MFGA. Given that the short working gap can identify the large magnetic force in MAF, the working gap between the cylindrical rod and magnetic poles was set at a small distance of 1 mm apart.

Fig. 1 Silicone gels with different plasticity Procedures. Proper weight ratios of the silicone gels, SG and SiC were chosen as the abrasive medium and then stirred by the mixing machine to become a uniform medium. The cylindrical rod of SKD-11 was then clamped by the chuck. Next, the magnetic gel abrasive was inserted into the working gap and covered over the rod. Finally, the setting parameters from the control panel were selected to proceed with the finishing. Temperature of the working area would affect the plastic deformation of silicone gel; therefore, a thermal couple was embedded into the gel abrasive to detect the temperature of silicone gel near the machining surface. Figure 2 shows the workpiece wrapped by the gel abrasive, as well as the magnetic field in MFGA. According to this figure, the abrasive was not only pressed by the magnetic forces, but also constrained by the viscous forces of the silicone gel; in addition, all of the constrained forces were flexible in MFGA. For this reason, the self-sharpening, the self-adaptability and the controllability in MFGA were more excellent than the same ability in MAF.

Fig. 2 Schematic diagram of the magnetic field in the gel abrasive Results and discussion Given the reason to understand the polishing effect of silicone gel in MFGA, with and without silicone gel was studied in these experiments first. Then silicone gels with different plasticity were used to finish the workpiece 30 minutes, to see the change of these gels in the machining process. Finally, different silicone gels with various abrasive ratios were investigated to obtain the polishing efficiencies in MFGA.

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Effects of MAF or MFGA. Given the ability of the silicone gel to produce a flexible constraint in the abrasive medium, this study investigated the finishing efficiency of MAF or MFGA first. MAF and MFGA didn’t add any lubricant and abrasive in the machining process. Figure 3 shows the effects of MAF or MFGA on temperature of abrasive media near machining surface. According to these results, temperature of abrasive medium on MAF only increased 15oC during finishing 30 minutes continuously; however, temperature of abrasive medium on MFGA dramatically expanded from 26oC to 110oC during the same time. Owing to silicone gels have poor heat conduction, and these gels wrapped the workpiece very closely; therefore, temperature of abrasive medium near machining surface would hugely increase in MFGA. However, silicone gels are temperature dependent material, high temperature of working area would result a soft gel to circulate on the workpiece surface, inducing fine self-sharpening effect in MFGA. Fig. 4 presents a change of abrasive medium after finishing 30 minutes continuously. Fig 4(b) is a change of UMA medium in MAF; from this Fig., we could easily find the flyaway abrasives SiC were stuck on the magnetic poles; explaining why the efficiency of MAF was poor with no extra abrasives were added in the working area. However, the abrasives SiC were constrained by silicone gel in MFGA, so we hardly found SiC adhering on the magnetic poles in Fig. 4(d). Furthermore, being used abrasive medium (black color) was circulated out of working area in the same Fig., identifying excellent self-sharpening effect in MFGA. Mesh of SiC: #6000 Mesh of SG: #70 Rotation rate: 1300rpm

120 100 Temperature ( )

℃ 80

Current: 2A Vibrational frequency: 6Hz Sil_G:SG:SiC (g): 10:15:10

60 40 20

MAF

MFGA

0 0

5

10

15

20

25

30

Finishing time (min)

Fig. 3 Effects of MAF or MFGA on temperature

(a) Before finishing (MAF) (b) 30 minutes finishing (MAF)

(c) Before finishing (MFGA)

(d) 30 minutes finishing (MFGA)

Fig. 4 Change of abrasive medium after finishing 30 minutes Silicone gels with various plasticity. Fig. 5 displays the effects of silicone gels with different plasticity on temperature of abrasive media near machining surface. According to those results, temperature of abrasive media raised with increasing the finishing time in MFGA, temperature of silicone gel with plasticity 80, 120, 160 could reach to 111oC, 101oC, and 74oC. The reason was that

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silicone gels with low plasticity had good ability to circulate in the working area, so new abrasives would easily appear to abrade the surface; these new cutting edges produce high machining temperature in MFGA. Since temperature of silicone gels with plasticity 80 and 120 could exceed 100oC after finishing 30 minutes, those two gels could handily circulate in the working area; therefore, excellent efficiency could be obtained by these gels. For example, using silicone gels with plasticity 80 or 120 as abrasive medium, surface roughness of workpiece could be decreased from 0.655µm Ra to 0.025 or 0.021µm Ra. Fig. 6 demonstrates change of the silicone gels with different plasticity after finishing 30 minutes. Given to high temperature of silicone gels with plasticity 80 or 120 after finishing 30 minutes, Fig. 6(b) and 6(d) exhibited noteworthy circulations of abrasive media. Nevertheless, silicone gel with plasticity 160 had high hardness, causing low circulating effect in MFGA. Consequently, only little circulation was found in the machining area, explaining why silicone gel with high plasticity could not produce excellent polishing efficiency. 120

#120 #160 #80

100

Temperature ( )

℃ 80 60

Current: 2A Mesh of SiC: #6000 Mesh of SG: #70 Rotation rate: 1300rpm Vibrational frequency: 6Hz Sil_G: SG: SiC (g): 10:15:10

40 20 0

0

5

10

15

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Finishing time (min)

Fig. 5 Effects of silicone gels with different plasticity on temperature of abrasive media

(a) Before finishing (Silicone (b) 30 minutes finishing gel with plasticity 80) (Silicone gel with plasticity 80)

(c) Before finishing (Silicone (d) 30 minutes finishing gel with plasticity 120) (Silicone gel with plasticity 120)

(e) Before finishing (Silicone gel with plasticity 160)

(f) 30 minutes finishing (Silicone gel with plasticity 120)

Fig. 6 Change of silicone gels with different plasticity after finishing 30 minutes

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Conclusions New magnetic abrasive medium, using silicone gels with different plasticity to mix steel grits and silicon carbon, were developed to enhance the efficiency of MAF in this study. Since silicone gels are semi-solid polymers that have good deformable ability and these gels don’t stick on the workpiece after contact, so gel abrasives were easily produced and it was easily cleared away from the workpiece after MFGA. Silicone gels are temperature dependent materials, temperature of abrasive medium reached to 110oC in the working area with using silicone gels as bonding gels; these gels produced a fluid property in a high temperature environment. Abrasive media created a fine circulation in MFGA if silicone gels slowly flow in the working area; then abrasives were easily replaced by the circulating effect in the finishing process. This phenomenon could not happen in MAF; therefore, MFGA functioned better than MAF in the polishing efficiency. Silicone gels with high plasticity are harder than the silicone gels with low plasticity, temperature of high plasticity gels are smaller than the temperature of low plasticity gels. In our experiments, temperatures of silicone gels with plasticity 80 and 120 both exceed 100oC in the working area within 30 minutes, but temperature of silicone gels with plasticity 160 only raised to 74oC within the same time, explaining why silicone gels with plasticity 80 and 120 induced excellent circulating effect in MFGA. Hence, silicone gels with plasticity 80 and 120 performed better than silicone gel with plasticity 160 during polishing 30 minutes in terms of efficiency. Acknowledgement The authors would like to thank National Science Council of the Republic of China for financially supporting this research under Contract No. NSC 97-2221-E-231-002. References [1] J.D. Kim, M.S. Choi, Study on magnetic polishing of free-form surface, Int. J. Mach. Tools Manuf. 37 (8) (1997) 1179-1187. [2] B.H. Yan, G.W. Chang, J.H. Chang, R.T. Hsu, Improving Electrical Discharge Machined Surfaces Using Magnetic Abrasive Finishing, Mach. Sci. Technol. 8 (1) (2004) 103-118. [3] S. Yin, T. Shinmura, Vertical vibration-assisted magnetic abrasive finishing and deburring for magnesium alloy, Int. J. Mach. Tools Manuf. 44 (2004) 1297-1303. [4] A.C. Wang, S.J. Lee, Study the characteristics of magnetic finishing with gel abrasive, Int. J. M. Tools Manuf. 49 (2009) 1063-1069. [5] A.J. Fletcher, A. Fioravanti, Polishing and honing process: an investigation of the thermal properties of mixtures of polyborosiloxane and silicon carbide abrasive, Proceed. Inst. Mech. Eng. 210 (1996) 256-265. [6] V.K. Jain, C. Ranganatha, K. Muralidhar, Evaluation of rheological properties of medium for AFM process, Mach. Sci. Technol. 5 (2) (2001) 151-170. [7] A.C. Wang, S.H. Weng, Developing the polymer abrasive gels in AFM process, J. Mater. Process. Technol. 192-193 (2007) 486-490.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 91-95 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.91

Experiment on Intermittent Gas Jet Assisted Modulated Fiber Laser Drilling J.-C. Hsu1,a, C.-Y. Liao1,b, C.-C. Ho1,c, Y.-J. Chang1,d and C.-L. Kuo1,e 1

Department of Mechanical Engineering, National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan a

[email protected], [email protected], [email protected], d [email protected], [email protected]

Keywords: Intermittent gas jet, modulated fiber laser, laser drilling.

Abstract. In this paper, intermittent gas jet assisted laser drilling on stainless steel (SUS304) with a fiber laser of wavelength 1090 nm is studied. Compared with the conventionally used continuous gas jets in assisting laser drilling, the intermittent gas jet assisting can effectively increase the material removal rate. The intermittent gas jet can be modulated with the frequency to effectively reduce the over-cooling effect by the assist gas. Experimental result shows that the drilling depth and machining time can be improved. The effects of the intermittent gas jet pressures and the synchronicity of gas and laser pulses on the laser drilling are investigated and discussed. It is observed that the intermittent gas jet method obviously reduces heat loss and increases the machining efficiency during the laser drilling. Compared with result of using the continuous gas jet, laser drilling with the intermittent gas jet at 40 Hz increases the drilling depth with an improvement of 10%. It is worth noting that the intermittent gas jet method can also reduce the quantity and cost of gas while the gases such as helium and argon gases are applied. Introduction Over the past few decades, many technological advances have been made in the field of laser drilling [1–4]. Laser drilling is a non-contact machining process in which a laser beam is focused onto a spot to produce sufficient power densities to melt or even vaporize the surface material and thus forming a hole. It is capable of drilling high quality holes with large aspect ratio at high machining rate for a variety of materials [5–8]. To achieve a high machining rate, high-pressure gas jets are commonly used to assist the laser drilling. The gas jets can eject molten material from the hole during laser drilling with its high gas pressure [9]. Typically, the gas jet is continuously supplied, and the gas pressure is restrained properly to compromise the possible side effect of cooling, while the cooling effect may diminish the laser drilling efficiency. As a result, the continuous gas jet method in assisting the laser drilling is subjected to the over-cooling difficulty to fully bring its function for ejecting the molten material from the hole in drilling. Moreover, the reflected gas flows with the molten slag and laser-induced plume from the processing hole may shelter the processing laser beam and reduce the processing efficiency [5, 9, 10]. To date, much work has been carried out to study gas jet assisted material-ejection mechanisms during laser drilling. Tsai and Lin [11] characterized the plume particles removal in laser ablation by using a swirling flow nozzle. Their results show that the laser induced plume can be removed efficiently and the surface roughness was significantly reduced by implementing a swirling flow in laser ablation. Chen et al. [12] reported a modeling study of gas flow in laser machining and studied the interaction of a supersonic, turbulent axis-symmetric jet with the work piece. Khan et al. [10] reported on the machining rates and hole quality for modulated laser percussion drilling of 200-mm thick 316L stainless steel performed with micro supersonic gas jets produced using nozzles of 200, 300 and 500 mm nominal throat diameters. Khan et al. [13] studied the use of high-pressure gas jets in laser-drilling process to have significant influence on the melt ejection mechanism. The simulations predict the formation of surface pressure fluctuations that have a broad spectrum due to the turbulent nature of the jet and the blunt shock oscillation on the surface.

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In this paper, we propose the utilization of intermittent gas jets to assist laser drilling for stainless steel sheets. To the best of our knowledge, the effectiveness of using intermittent gas jets in assisting laser drilling has not been investigated up to now. The intermittent gas jet we used in this study is to supply intermittent pressure gas during laser drilling to eject the molten material from the processing hole discontinuously in time. The intermittent frequency of the gas jet can be tuned to control timing for the molten material ejected. In the time intervals the gas is not applied, laser energy accumulation for ablating the material can be much more efficiently. The over-cooling issue in the high-pressure continuous gas jet method can then be managed, and the laser beam sheltering can also be reduced. More effective material-ejection during laser drilling may be achieved by using higher-pressure gas pulses with over-cooling excluded. The machining efficiency is compared with the results obtained using continuous gas jet, and the influences of the intermittent gas intensity are discussed. Experimental Details Stainless steel SUS304 sheets with thicknesses of 0.5 and 1.0mm were used as the workpiece material. The sheets were drilled by fiber-optical delivered 30W continue-wave (CW) Nd:YAG laser emitting at 1090 nm wavelength. Air was used as the assist gas in the experiments. Laser drilling of blind-hole (drilled in the 1.0 mm thick sheets) and through-hole (drilled in the 0.5 mm thick sheets) were considered in this study, respectively. Each case in the experiments was repeated three times, and the mean values of the three measurements were used as output at each set of parameters. Schematics of the experimental setup are shown in Fig. 1. Left panel of Fig. 1 shows the scheme of the confirming measurements of pressures, delay time, and frequency of the intermittent gas and the frequency and delay time of the laser beam. Right panel of Fig. 1 shows the scheme of laser drilling experiment and breakthrough detection. The detection of the laser beam was using a photo detector (Thorlabs, Model: DET100) The apparatus was setup on a platform of a Sodick AQ35L EDM machining center. The optical fiber was used to transfer the light from the Nd:YAG laser system to the focal lens. Workpiece was fixed on a XY micro stage. Laser beam was focused on the surface of the workpiece. The focal length is 150 mm. A gas nozzle unit was placed in between the focus lens and the workpiece to supply the assist gas (air in this study). The gas nozzle and the laser beam were adjusted to be coaxial. The pressure of the assist gas was controlled by a pressure gas supply unit, and the assist gas was delivered into the nozzle unit passing through and controlled by an electromagnetic (EM) valve (MAC, model: 36A-ACA-JDAA-1BA). The opening duration and frequency of the EM valve and modulated frequency and duty cycle of the laser beam were controlled with a Darlington circuit and single-chip microcontroller (PIC 18F4520) via a computer.

1090 nm Laser Source

1090 nm Laser Source PC

Focal lens Single Chip

PC

Focal lens Single Chip

EM Valve

EM Valve Gas Nozzle

Pressure Gas Supplier

Pressure Sensor

Gas Nozzle Pressure Gas Supplier

Workpiece

Photo Sensor Oscilloscope

Photo Sensor Oscilloscope

FIG. 1. Left panel: Scheme of the confirming measurements of the intermittent gas pressures, delay time, and frequency and the laser frequency and delay time. Right panel: Scheme of the laser drilling experiments and breakthrough detection. Continuous or intermittent gas jet was used on the workpiece during the laser drilling.

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Table I. Processing parameters in the experiments of the laser drilling with gas jet assisting. Laser type Laser wavelength Laser power Modulated laser frequency Focal length

fiber laser 1090 nm 30 W 40 Hz 150 mm

Nozzle exit to workpiece dist. Nozzle exit diameter Processing time (blind holes) Gas frequency Workpiece thickness

1.0 mm 0.4 mm 40 sec 40 Hz 0.5 mm / 1.0 mm

Experimental Results Figure 2 shows the measured voltage signals with the gas pressure sensor for the continuous gas and intermittent gas at different supplied gas pressures. Note that the measure method obtained close end (internal) pressures where the maximum pressure value defines real exported gas jet pressure to the workpiece. In the continuous gas jet, the measured gas pressures well match the supplied gas pressure values shown by the gas supplier, while only the measured value for the 500 kPa gas is a little lower. For the intermittent gas jets, the intermittent frequency was f = 40 Hz. All the measured intermittent gas pressures were much lower than the supplied gas pressures, which mean significant internal pressure loss in the intermittent gas jet supply system. To better control the synchronicity between the intermittent gas jet and modulated fiber laser, the delay times of the gas and laser were measured and are shown in Fig. 3. The delay time of the intermittent gas jets relative to the laser beam is about 14.5 ms (where there are small variations with different gas pressures). The delay times were used to compensate the arriving time of intermittent gas jet applied on the workpiece during the laser drilling.

4

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0 0.2

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FIG. 2. Measured voltage signals and internal gas pressure with the gas pressure sensor for the continuous gas jets (left panel) and intermittent gas jets (right panel) at different supplied gas pressures.

Figure 4(a) shows the experimental drilled depths of blind holes on the 1.0 mm thick steel sheets using continuous and intermittent gas jets at different supplied gas pressures during the laser drilling. The intermittent gas jets were considered to be synchronous (i.e., no relative delay time) and to be T/4 delay relative to the fiber laser application, where T=1/f is the period of the intermittent gas and the laser. The processing parameters are listed in Table I. In Fig. 4(a), the drilling depths are obviously improved using the intermittent gas jets, compared with the case using the continuous gas jet. The improvement is attributed to the reduction of cooling effect by gas jet during the fiber laser drilling. Continuous gas jet is applied on the workpiece whenever the on time and off time of the fiber laser drilling, which means reheating of the workpiece in the beginning of every laser pulse so that the laser energy is not very efficiently used. The intermittent gas jets, however, do not cool down the workpiece when gas is not applied, and there can be more molten material ejected while the efficiency of laser heating is increased. The case of using synchronous gas jet shows about 10% improvement in depth.

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8 7

Voltage (V)

6 5 Delay time

4 3 2 1 0 0

0.01

0.02 Time (sec)

0.03

0.04

FIG. 3. Measured delay times of the intermittent gas jets and modulated laser beam.

Figure 4(b) illustrates the microscopic pictures of the cross section of the laser drilled blind holes with the continuous and intermittent gas jet assisting. It is worth noting that tuning the on time duration, timing, and frequency of the intermittent gas jets may further improve the drilling efficiency of the modulated laser based on above observation and discussion. Figure 5 shows the experimental breakthrough time of fiber laser drilling through holes in the 0.5 mm thick steel sheets with the continuous and intermittent gas jets at different supplied gas pressures. The breakthroughs were detected by the photo sensor (see Fig. 1) beneath the workpiece. It is shown that the machining time to reach breakthroughs can be significantly reduced by using the intermittent gas jets to assist. The synchronous intermittent gas jets reduce the breakthrough time more than that with a T/4 time delay intermittent gas jets. The saving time is about 4 to 5 seconds for the synchronous case compared with the continuous case, and 1 to 3 seconds saving for the case of T/4 delay. This is also corresponding to a higher efficiency in the laser drilling. In Fig. 5, higher gas pressure results in less breakthrough time. As expected that a high pressure gas jet can eject molten material efficiently; however, it accompanies significant cooling effect. The experiment shows that the intermittent gas jet assist reduces the cooling effect, and the gas exerting timing to eject the molten material is influential. 520 500

Intermittent gas (synchronous) Intermittent gas (T/4 delay) Continuous gas

Continuous Gas Jet

Depth (um)

480 460

Intermittent Gas Jet (T/4 delay)

440 420 Intermittent Gas Jet (synchronous)

(a)

400 100

100 kPa

200 300 400 Supplied Gas Pressure (kPa)

500

200 kPa

300 kPa

400 kPa

500 kPa

(b)

FIG. 4. (a) Experimental drilled depths of blind holes on the 1.0 mm thick steel sheets using continuous and intermittent gas jets at different supplied gas pressures during the laser drilling. (b) Microscopic pictures of the cross section of the laser drilled blind holes using the continuous and intermittent gas jet assisting with the supplied gas pressures equal to 100, 200, 300, 400, and 500 kPa.

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Breakthrough Time (sec)

39

35

FIG. 5. Experimental breakthrough times of pulsed laser drilling through holes in the 0.5 mm thick SUS304 stainless steel sheets with the continuous and intermittent gas jets at different supplied gas pressures, detected by the photo sensor beneath the workpiece.

31

27

23 100

Intermittent gas (synchronous) Intermittent gas (T/4 delay) Continuous gas

200 300 400 Supplied Gas Pressure (kPa)

500

Summary and Conclusions Intermittent gas jet assisted modulated laser drilling in SUS304 steel was experimentally studied. The 1090 nm modulated fiber laser was used. We set up the intermittent gas jets with a frequency of 40 Hz the same as the chosen modulated frequency of the laser in the machining. Experiments of laser drilling blind holes and through holes were conducted. The experimental results showed that the intermittent gas jet assist can obtain better drilling efficiency compared with the typical continuous gas jet assist. We also examined the influence of synchronous and T/4 time delay gas jets for assisting laser drilling, where the on time and off time of the intermittent gas were equal within a time period. In both drilling the blind holes and through holes, the synchronous intermittent gas jet assist shows higher drilling efficiency. The boost of the laser drilling efficiency is attributed to the reduction of the cooling effect and effective molten material ejection when the gas jet is applied during laser drilling. Acknowledgement J.-C. Hsu and C.-Y. Liao acknowledge the National Science Council of Taiwan for financial support (Grant No. NSC 101-2221-E-224-015) References [1] R. Biswas, A. S. Kuar, S. Sarkar and S. Mitra: Opt. Laser Tech. Vol. 42 (2010), p. 23. [2] S. Bandyopadhyay et. al.: Opt. Laser Eng. Vol. 43 (2005), p. 163. [3] E. Kacar et. al.: J. Mater. Processing Tech. Vol. 209 (2009), p. 2008. [4] M. Ghoreishi, D. K. Y. Low and L. Li: Int. J. Mach. Tools Manuf. Vol. 42 (2002), p. 985. [5] D. K. Y. Low, L. Li and A.G. Corfe: Appl. Surf. Sci. Vol. 154–155 (2000), p. 689. [6] J. Gurauskis et. al.: J. Euro. Ceram. Soc. Vol. 28 (2008), p. 2673. [7] A. S. Kuar, B. Doloi and B. Bhattacharyya: Int. J. Mach. Tools Manuf. Vol. 46 (2006), p. 1301. [8] D. K. Y. Low, L. Li, A.G. Corfe and P.J. Byrd: Int. J. Mach. Tools Manuf. Vol. 41 (2001), p. 361. [9] H. K. Sezer, L. Li and S. Leigh: Int. J. Mach. Tools Manuf. Vol. 49 (2009), p. 1126. [10] A. H. Khan et. al.: Opt. Laser Eng. Vol. 45 (2007), p. 709. [11] D. Y. Tsai and J. Lin: Opt. Laser Tech. Vol. 39 (2007), p. 219. [12] K. Chen, Y. L. Yao and V. Modi: J. Manuf. Sci. Eng. Vol. 122 (2000), p. 429. [13] A. H. Khan et. al.: Opt. Laser Eng. 44 (2006), p. 826.

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Temperature Effect on Mechanical Properties of Aluminum Film Shiuh-Chuan Her1,a and Yi-Hsiang Wang1 1

Dept. Of Mechanical Engineering, Yuan Ze University, 135, Yuan-Tung Road, Chung-Li, 320, Taiwan a

email : [email protected]

Keywords: electron-beam vapor deposition, aluminum film, nanoindentation test.

Abstract. Aluminum films were prepared on the glass substrate by electron-beam vapor deposition. Nanoindentation tests were employed to determine the hardness and Young’s modulus of the Al film. The effect of substrate temperature on the mechanical properties of the Al film was investigated. Experimental results show that the hardness of Al film is increasing with the increase of the substrate temperature. It can also be observed that the Young’s modulus of Al film doesn’t significantly depend on the substrate temperature. Introduction Metallic thin films with excellent heat resistance, thermal reflection, and corrosion resistance are widely used in various applications. Among them, aluminum (Al) has three major advantages with respect to other metals [1]. (1) It is a lightweight metal, therefore it does not increase the overall density significantly, (2) its crystalline structure is very similar to the substrate avoiding lattice's mismatch that in some cases could drive the detachment of the coatings, (3) aluminium is a primary alloy element, therefore the material can be easily recycled without any purification process. However, the disadvantage of using Al layer is that they tarnish under ordinary atmospheric conditions yielding to a significant change of the film properties. Al film is widely used especially in transparent and heat reflecting layer stacks. Examples are transparent heat mirrors for the reduction of heat load in cars and buildings and light tunnel mirrors in projection display system. Many techniques have been used to deposit Al films, such as sputtering, e-beam evaporation, chemical vapor deposition, thermal spray, pulse laser deposition. Depending on the deposition conditions and techniques, Al films may present considerably different structural, optical and mechanical properties. Chang et al. [2] developed a composite coating consisting of thermal sprayed aluminum layer and anodic film on AISI 1020 steel. They found the corrosion and wear resistance of thermal sprayed aluminum coating were significantly enhanced after anodizing. Liu et al. [3] deposited Al films on different types of substrate surfaces to investigate the effect of process variables on the deposition and film characteristics. Lee et al. [4] examined the weldability of Al coated steel sheets by Nd:YAG laser. Han et al. [5] reported Al thermal spraying coating material presented the best corrosion protection characteristics. Eve et al. [6] investigated the thermal and mechanical fatigue behavior of thin Al film on polycarbonate for micro-optical components. Electron-beam vapor deposition was adopted in this study because of its good stability in generating a Al film on a substrate. The morphology of the Al film, which is important for its optical and mechanical properties, could be controlled by the thickness of the metal and substrate temperature. Some investigations show that the optical properties can be influenced by film thickness for metallic thin films [7-9]. This may be attributed to the structure variation as films grow from the islands on the substrate to a continuous film. Young’s modulus and hardness are the key parameters in the study of the wear and adhesion of thin films to the substrates and their responses to the mechanical loads. Since the mechanical properties of the nano materials may be significantly different from those of bulk materials. Therefore, there is a need to study the mechanical properties of the thin film at the nano scale. Various techniques have been developed for evaluating the mechanical properties of thin films. Among them, nano-indentation [10,11] has become the most widely adopted technique in the study of the

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mechanical properties, such as hardness and Young’s modulus, on small scale or near surfaces. This paper deals with the experimental results and qualitative discussion of the relationship between the mechanical property and the substrate temperature. Al films were deposited onto glass substrate by electron beam (e-beam) vapor system. The effects of substrate temperature on the hardness and Young’s modulus of Al films were investigated by nanoindentation test. Film Preparation A series of aluminum films were prepared by using electron beam vapor system (JOEL EGO-206M) on B270 glass substrate. The target is an aluminum metal disk (40 mm diameter) with a purity of 99.995 %. The distance between the target and substrate is approximately 50mm. Prior to deposition, the substrates were cleaned in soap solution, submerged in acetone solution and in an ultrasound bath for 10 minutes after rising with distilled water. Then the substrates were dried by blowing nitrogen over them before the application of deposition. The chamber is equipped with a rotary vane pump, a root pump and a cryogenic pump. After a pumping time of two hours, the chamber was evacuated down to a base pressure 1 × 10 −6 torr . Film growth was carried out with the deposition rate adjusted
/s . Sulfur and oxygen from the atmosphere can react with by the current to approximately 40 ~ 50 A the surface of the Al film, leading to a change in the optical and mechanical properties of the film. For the ex-situ analysis of the Al film, a significant alternation of the film properties through a reaction of the film surface with the atmosphere ought to be avoided. A thin silicon oxide layer ( SiO2 ) was grown on the aluminum film surface by the vapor deposition in the same vacuum chamber to prevent the Al film from the interaction with the atmosphere. In this way, four sets of Al films were prepared at substrate temperatures of 220 C , 1000 C , 2000 C and 3000 C , respectively. Mechanical Properties The mechanical properties (hardness and Young’s modulus) of the Al films are characterized using nanoindentation techniques. Oliver and Pharr [10, 11] developed a most comprehensive method for determining the hardness and modulus from load-indention curve. The results were analyzed according to the equation 2β S = 2aE r = Er A

π

where a is the contact radius and A is the projected contact area. β is used to account for the geometric shape of different indenters. For a Berkovich indenter β = 1.034 . S is the contact stiffness corresponding to the slope of the load-indention curve at the beginning of the unloading. E r is the reduced modulus expressed in terms of the elastic modulus E and Poisson’s ratio ν of the indenter and the indented material as follow

1 1 − ν s2 1 − ν i2 = + Er Es Ei

(1)

where subscript i and s represent the indenter and substrate, respectively. For a diamond Berkovich indenter Ei = 1140 GPa and ν i = 0.07 . The hardness was determined using the equation

H=

Pmax Ac

(2)

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Where Ac is the area of the indentation at a maximum applied load Pmax . By knowing precisely the geometry of the indenter, Ac can be expressed in terms of the indentation depth h directly determined from measurements. In this study, the nanoindentation experiments were performed using Mico Material Co. Nano Test. Indentation was made using a Berkovich indenter calibrated with a standard silica specimen. A typical load-displacement curve consists of three segments: loading to a peak load; holding at the peak; unloading back to the zero loads. A holding period of at least 5 seconds was applied to allow the time-dependent effects to diminish. Typical load - indentation curve of Al films deposited on the glass with substrate temperatures of 22 0 C , 1000 C are presented in Fig.1. In Fig.1 the indentation depth is normalize by the film thickness, and three curves in each figure corresponding to three different maximum indentation depths. By using the continuous stiffness measurement mode, nano indenter allows the hardness and modulus to be determined as a function of indentation depth. The Young’s modulus and hardness can be determined by employing eq(1) and eq(2), respectively. The Young’s modulus and hardness of Al films (versus normalized indentation depth) are presented in Fig.2 and Fig.3, respectively. It shows that the hardness is decreasing as the indentation depth increases. Al films prepared at substrate temperatures of 22 0 C and 2000 C exhibit higher hardness than the films prepared at substrate temperatures of 1000 C and 3000 C . It can also be observed that the Young’s modulus of Al film doesn’t significantly depend on the indentation depth and substrate temperature. Conclusions Aluminum films were prepared on the glass substrate by electron-beam vapor deposition. The effect of substrate temperature on the mechanical properties of Al films was investigated. The conclusions arising form this experimental study are summarized as follows: (1) The hardness of Al film is decreasing as the indentation depth increases. (2) The hardness of Al films is increasing as the substrate temperature increases. (3) The effects of substrate temperature and indentation depth on the Young’s modulus of Al film are less significant while comparing with the hardness.

hmax 42.96nm hmax 84.66nm 1.4

hmax 128.41nm

hmax 128.55nm

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hmax 44.9nm hmax 86.93nm

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120

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120

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(a) substrate temperature 22 0 C (b) substrate temperature 1000 C Fig.1: Load versus displacement curves of Al films deposited at dfferent substrate temperatures

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99

22 C 100 C 200 C

60

a) P G ( s lu u d o m s' g n u o y

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50

40

30 0.0

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0.2

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Fig.2: Young’s modulus versus normalized indentation depth of Al films prepared at different substrate temperature

10 22 C

8

100 C 200 C

) a P (G ss e n d r a h

6

300 C

4 2 0 0.0

0.1

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0.3

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indentation depth (h/t)

Fig.3: Hardness versus normalized indentation depth of Al films prepared at different substrate temperature References [1] U. Bardi, S. Caporali, M. Craig, A. Giorgetti, I. Perissi, J.R. Nicholls, Surface & Coatings Technology, Vol. 203 (2009), p. 1373 [2] C.H. Chang, M.C. Jeng, C.Y. Su, C.L. Chang, Thin Solid Films , Vol. 517 (2009), p. 5265 [3] Y. Liu, L.J. Overzet, M.J. Goeckner, Thin Solid Films, Vol. 510 (2006), p. 48 [4] J.H. Lee, J.D. Kim, J.S. Oh, S.J. Park, Trans. Nonferrous Met. Soc. China, Vol. 19 (2009), p. 946 [5] M.S. Han, Y.B. Woo, S.C. Ko, Y.J. Jeong, S.K. Jang, S.J. Kim, Trans. Nonferrous Met. Soc. China, Vol. 19 (2009), p. 925 [6] S. Eve, N.Huber, A. Last, O. Kraft, Thin Solid Films, Vol. 517 (2009), p. 2702 [7] V.L. Schlegel, T.M., Cotton, Anal. Chem. Vol. 63 (1999), p. 241 [8] C. Charton, M. Fahland, Surf. Coat. Technol. Vol. 174-175 (2003), p. 181 [9] X. Sun, R. Hong, H. Hou, Z. Fan, J. Shao, Thin Solid Films, Vol. 515 (2007), p. 6962 [10] W.C. Oliver, G.M. Pharr, J. Mater. Res., Vol. 7 (1992), p. 1564P [11] G.M. Pharr, G.M. Oliver, F.B. Brotzen, J. Mater. Res., Vol. 7 (1992), p. 613

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Artificial photosynthesis of formic acid using Iron doped TiO2 Amir Abidov, Sungjin Kim* Department of Advanced Materials and Engineering, Kumoh National Institute of Technology, 61Daehak ro, Gumi, Gyeongbuk, South Korea Gumi, Gyeongbuk, South Korea Presenting author: Amir Abidov / email: [email protected] *Corresponding author: Sungjin Kim / email: [email protected] Keywords: Artificial photosynthesis, hydrogen storage, hydrocarbons, Fe doped TiO2, CO2 reduction.

Abstract. Formic acid has attracted much of interest due to potential using in Direct-formic acid fuel cells. Photosynthesized formic can be used as the hydrogen carrier because it is liquid at standard temperature and pressure. It is much safer and easier for handling and storing than hydrogen. It can be directly fed to the fuel cell and not need to be reformed. In this paper formic acid was artificially photosynthesized in photocatalytical reactor using Iron ion doped TiO2. Water was used as a hydrogen source. CO2 was introduced using continuous bubbling. Highest formic acid yield was obtained at 600W visible light irradiation using 3g/L photocatalyst load and 5L/min CO2 gas flow rate at continuous stirring. Resulted acid was characterized using UV-visible absorbance spectrophotometer, Proton Nuclear Magnetic Resonance Spectrometer (HNMR), and gas chromatography (GC). Introduction High price on energy sources challenges to develop new renewable energy technologies such water splitting and artificial photosynthesis of hydrocarbons. Hydrogen from water is a renewable source. However hydrogen gas storing is difficult and dangerous. Formic acid attracted much interest as hydrogen storage. This is due to formic acid is safer than hydrogen. It is liquid at room temperature and doesn’t require special storage conditions such as pressure and temperature. Another benefit, formic acid is more effective than methanol in fuel cells. It doesn’t need to be reformed and can be fed directly into DFAFC (Direct Formic Acid Fuel Cell). DFAFC’s are good candidates for portable electronic devices energy storage. Another uses for formic acid are important chemical precursor and chemical intermediate. It is also used in livestock feed storage and sanitary sphere as antibacterial agent. Formic acid can be produced by chemical, electrochemical, thermochemical and photochemical method. All of mentioned methods have advantages and disadvantages. Thermochemical, electrochemical, photoelectrochemical methods require much energy making ineffective using it. Photocatalytical conversion consumes free and renewable source - solar energy. In this process photogenerated electron/hole pairs take part in 2 reactions: (eq. 1) Water splitting, (eq. 2) CO2 reduction. During this process fabrication of hydrocarbons e.g. formic acid occurs. 2

→

+4 +

→

+4





=−1.23 V,

(eq. 1)

= −1.65 .

(eq. 2)

Excellent studies have been made on artificial photosynthesis of formic acid. In 1994 Frigyes Solimosi et al., converted H20+CO2 over Rh doped TiO2 into mixtures of hydrocarbons:

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formaldehyde, methanol and formic acid. Shunsuke Sato et.al in 2011 reported about selective CO2 conversion to formate conjugated with H2O oxidation utilizing semiconductor/complex hybrid photocatalyst. Achieved conversion efficiency was 0.03-0.04%. Formic acid was successfully obtained by Rajesh K. Yadav using graphene-based visible light active photocatalyst which covalently bonded the chromophore. Another researchers reported about CO2 reduction using ALa4Ti4O15 (A = Ca, Sr, and Ba) in liquid phase reactor. Hirano et al. (1992) and Wu et al. (2005) used copper-metal supported TiO2 for photocatalytic CO2 reduction to methanol and formic acid in aqueous media and vapor respectively. Finding best candidate for photoconversion of H2O+CO2 to formic acid is much of interest. Reported catalysts are not enough reusable (Cu, Cd), expensive (Rh, Pt, Ag, Ru, Pd) or difficult to fabricate. This makes inefficient their application for artificial photosynthesis. Also only introduced dopant is not enough to effectively produce desired hydrocarbons. Particle size, morphology, surface area, dopant amount and position (surface, bulk) plays crucial role in selectivity and photoactivity. There is no enough research papers about CO2 photoconversion to formic acid using Fe doped TiO2 photocatalyst. In our previous [11-12] papers we reported about excellent photocatalytic activity of Fe doped TiO2 prepared by mechanochemical milling for photodegradation of organic dyes. Due to these properties we decided to utilize it for photoconversion of CO2 and H2O to hydrocarbons. In the present study artificial photosynthesis of formic acid using Fe doped TiO2 is reported. Effect of particle size on formic acid selectivity is analyzed. Experimental procedure and characterization Photocatalytic process was carried out in simple batch glass reactor (Fig. 2.). Fe doped TiO2 powder was dispersed in DI water. Reactor was prepurged with CO2 for 1 hour before exposing to light. CO2 diffusion in water was obtained by continuous bubbling and vigorous mechanical stirring. 2x300W halogen lamp was used as a light source. Cooling water shield served to cut heat irradiation. Liquid samples were extracted at a regular period of time. TiO2 powder was separated using centrifuge and filtered using syringe filter. Absorbance of resultant liquid was using Shimadzu 3600 UV-visible NIR spectrophotometer (UV/Vis). As formic acid is responsible for absorption between 226-500nm, this range was measured [13]. Absorbance peaks of reference formic acid and photosynthesized were compared. Additional tests were performed using gas chromatography (GC). In order to choose the best candidate for CO2 photoconversion with high selectivity to formic acid different particle size (25nm, 200nm, 400nm) TiO2 photocatalyst powders were used. For comparison bare TiO2 powder was tested in this experiment. No formic acid was detected. For ensuring that fabricated formic acid is photosynthesized several blank tests were performed. Reactor without light illumination, containing TiO2 dispersion in water continuously stirred and CO2 purged. Another two are with light illumination but without TiO2 and without CO2 gas. In these blank experiments no hydrocarbons were detected. This confirms that fabricated formic acid is artificially synthesized.

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Fig. 4 UV-visible absorption spectra of liquid samples during 6 hours reaction using 200nm doped TiO2

Fig. 3 UV-visible absorption spectra of initial DI water (blue), reference formic acid 10% vol. (black) and photosynthesized formic acid (red).

Results and discussion Fig. 3 shows UV absorbance spectrum liquid sample after 6 hours of photocatalytic process. Initial water is marked with blue color. For comparison reference formic acid (10% vol) was measured. It can be seen that formic acid has strong absorbance between 185nm and 250 nm as was mentioned in [13]. Artificially photosynthesized sample’s peak is identical to reference and situated between 240m and 185nm. Lower absorbance is due to lower concentration than those of reference. Also fabricated sample contains methanol and other subproducts this can explain absorbance’s shift to lower wavelength. In order to obtain formic acid photosynthesis dynamics, extracted samples were measured every 30 min. It was found that formic acid production doesn’t remain steady it decreases gradually. After 3 hours formic acid concentration reached its maximum point. This is due to formic acid was not separated from water in reactor during experiment. It is not easy to explain this phenomenon. Several reasons can cause it. Formic acid can be further reformed to methanol or formaldehyde. Another explanation is while reaching maximum concentration radicals began to attack formic acid molecule subsequently decomposing it to subproducts. Which one is the main contributor to decreasing of formic acid’s concentration is subject for additional research. Fig. 5 shows dynamics of formic acid fabrication using different particle size of TiO2 powder. It can be seen that selectivity of formic acid is strongly dependent to particle size. 25 nm Fe doped TiO2 (P25 Degussa) shows the quickest formic acid formation.

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Fig. 5 Effect of particle size of Fe doped TiO2 on formic acid yield

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Fig. 6 Effect of TiO2 load on formic acid yield

However further concentration of formic acid decreased and became stable. Highest concentration was obtained for 200nm sized doped TiO2 after 3 hours. Further increasing particle size decreased formic acid yield. This is due to lower surface are. In our previous paper we reported that amount of TiO2 plays crucial role in photocatalytic reaction [11]. Fig. 6 shows effect of photocatalyst load on formic acid yield. This result demonstrates increase in formic acid yield. It can be seen that maximum formic acid yield was Fig. 6 Effect of gas flow rate achieved with 6 g/l of TiO2 catalyst load. Additional increasing of photocatalyst amount leads to decreasing of formic acid synthesis rate. This has been explained on the basis of fact that excess of photocatalyst powder decreases light penetration with subsequently decreasing photoactivated volume [14]. Effect of CO2 gas flow rate is presented in fig. 6. It was found that at 3 l/min maximum formic acid yield was achieved. This can be ascribed with sufficient CO2 was supplied for reaction. Summary Formic acid was successfully fabricated by artificial photosynthesis method using Fe doped TiO2. It was found that 200nm particle size photocatalyst performed high CO2 conversion selectivity to formic acid. Maximum formic acid yield is possible under particular conditions: 200 nm size Fe doped TiO2, CO2 gas flow rate 3 l/min and 5 g/l photocatalyst concentration. Acknowledgements This paper was supported by Research Fund, Kumoh National Institute of Technology.

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References [1] Shunsuke Sato et.al, Selective CO2 conversion to formate conjugated with H2O oxidation utilizing semiconductor/complex hybrid photocatalyst, J. Am. Chem. Soc., 2011, 133 (39), pp 15240–15243 [2] Satoshi Yotsuhashi et. Al., Enhanced CO2 reduction capability in an AlGaN/GaN photoelectrode, Appl. Phys. Lett. 100, 243904 (2012); http://dx.doi.org/10.1063/1.4729298 (3 pages) [3] Kosuke Iizuka et.al Photocatalytic Reduction of Carbon Dioxide over Ag Cocatalyst-Loaded ALa4Ti4O15 (A = Ca, Sr, and Ba) Using Water as a Reducing Reagent, J. Am. Chem. Soc., 2011, 133 (51), pp 20863–20868 DOI: 10.1021/ja207586e [4] Rajesh K. Yadav et.al. A Photocatalyst–Enzyme Coupled Artificial Photosynthesis System for Solar Energy in Production of Formic Acid from CO2, J. Am. Chem. Soc., 2012, 134 (28), pp 11455–11461, DOI: 10.1021/ja3009902 [5] M. Halmann, Photoelectrochemical reduction of aqueous carbon dioxide on p-type gallium phosphide in liquid junction solar cells, Nature 275, 115 - 116 (14 September 1978); doi:10.1038/275115a0 [6] D. Canfield et. al. Reduction of Carbon Dioxide to Methanol on n ‐ and p ‐ GaAs and p ‐ InP . Effect of Crystal Face, Electrolyte and Current Density, doi: 10.1149/1.2120090 J. Electrochem. Soc. 1983 volume 130, issue 8, 1772-1773 [7] H. Yamashita et al., Photocatalytic reduction of CO2 with H2O on TiO2 and Cu/TiO2 catalysts, Research on Chemical Intermediates January 1994, Volume 20, Issue 8, pp 815-823 [8] S. Ha; R. Larsen, Direct formic acid fuel cells with 600 mA cm Cells 2004;4(4):337-343.

-2

at 0.4 Vand 22°C, Fuel

[9] Kimfung LI, Conversion of Solar Energy to Fuels by Inorganic Heterogeneous Systems, Chinese Journal of Catalysis, 2011, Vol. 32 No. 6, Article ID: 0253-9837(2011)06-0879-12, DOI: 10.1016/S1872-2067(10)60209-4 Review: 879–890. [10] Frigyes Solimosi et al., Photocatalytic reaction of H2O+CO2 over pure and doped Rh/TiO2, Catalysis Letters, 27, 1994, 61-65 [11] Amir Abidov et al., The Evaluation of Photocatalytic Properties of Iron Doped Titania Photocatalyst by Degradation of Methylene Blue Using Fluorescent Light Source, 2013, Advanced Materials Research, 652-654, 1700 [12] Amir Abidov et al. Photoelctron Spectroscopy Characterization of Fe doped TiO2 Photocatalyst, Int. Journal of Materials, Mechanics and Manufacturing, Vol. 1, No. 3, 2013, pp. 294-296. [13] Ramsberger et al. The ultraviolet absorption of formic acid, J. Am. Chem. Soc., 1926, 48 (5), pp 1267–1273. [14] Rajesh J. Thillai Sivakumar Natarajan, and Hari C. Bajaj, Ind. Eng. Res. 2009, 48, 1026210267

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Graded silicon nanostructure arrays for tailoring antireflection performances Cheng-Chuan Wang1,a, Chia-Yun Chen1,b, Ya-Ching Chou1,c 1

Industrial Technology Research Institute (ITRI), Material and Chemical Research Laboratories (MCL), Hsinchu, Taiwan, 31040, R.O.C. a

b

c

[email protected], [email protected], [email protected]

Keywords: Silicon nanostructures, antireflection, wetting property, etching

Abstract. Advances in nanofabrication have resulted in great potentials for improving in both device performance and the manufacturing process of various applications. One revolutionary example is silicon (Si) nanostructures, typically using Si nanopore arrays or Si nanowire arrays, to construct high efficient and low-cost solar cells. In this work, we develop the innovative combined nanostructure arrays with tailored structural profiles using inexpensive, simple and rapid etching processes, whose total reflection is suppressed to 1.6%, approximately 39% less than Si nanopore arrays, and 20% less than Si nanowire arrays. In addition, systematic investigations on wettability of textured Si surfaces reveal the inherent surface oxidation during etching process. These combined nanostructure arrays with tailored antireflection performances, along with the in-depth studies of underlying etching mechanisms, may benefit both the yield and cost efficiently in industrial standard of silicon solar cells. Introduction In the past several decades, silicon nanowires (SiNWs) have been considered as potentials candidates for improving in both device performance and the manufacturing process of various applications, including electronic, biological and photovoltaic devices. The striking property of silicon nanowires correlates with their unique features for harvesting light, including enhanced light absorption and antireflective characteristics; the former originates from multiple scattering of incident light and excitation of guided resonances, and the latter causes the broadband suppression of the Fresnel reflection due to their structures in sub-wavelength scale [1-6]. Nevertheless, the concern lies in the increased surface recombination by incorporating SiNWs to the architecture of solar cells. These features are found to be more pronounced with the increase of nanowire length. Specifically, Si nanowire based solar cells even enable the superior absorption of light, but the performances of solar cells are still challenged by the significant surface recombination of minority carriers. Hence, the light trapping of SiNWs should be further improved within finite length of Si nanowires, and an effective approach for suppressing the reflection loss of Si nanowires with lengths less than a micrometer is quietly desirable. Experimental Two-step Ag-assisted chemical etching is performed on single-crystal (100) P-doped silicon wafers with resistivity of 0.01–0.05Ω-cm, as shown in Figure 1(a). Prior to the first-step etching, Si substrates are rinsed by Acetone/IPA/DI water several times and then soaked in an etching solution containing 0.02M AgNO3 and 4.5M HF. Local oxidation and dissolution of Si atoms via galvanic displacement cause the formation of silver nanoparticles, with surface density of the order of 1010cm-2(i). After rinsing by DI water, the Si substrates are immediately soaked in a diluted HNO3 solution for few minutes. The surface density of Ag nanoparticles significantly decreases the order of 108cm-2 (ii). These Ag nanoparticles with wide separated distributions act as microscopic cathodes, initiating the formation of nanopore arrays when soaking the substrates in a mixture of 0.3M H2O2

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and 4.5M HF(iii). The dissolution of Si atoms takes place beneath the Ag+/Si interface, following this reaction as bellow [7]: n 4−n H 2O2 + 6 HF → nH 2O + H 2 SiF6 + H2 (1) 2 2 After then, the residual Ag nanoparticles are removed completely by dipping the substrates in a concentrated HNO3 solution (iv). A top-view image of the fabricated NP arrays is shown in Figure 1(b), where one can observe clearly the distinct nanopores with average sizes in the radial direction of 79 nm following the normal Gaussian distribution, as shown in the inset of Figure 1(c). In addition, the surface fraction of Si is around 62%, as carefully estimated based on a scanning electron microscope (SEM) image. In the second-etching process, a mixture of 0.02M AgNO3 and 4.5M HF is utilized to construct dense aligned NW arrays (v), as illustrated in Figure 1(a). The involved reaction can be represented as follows [8-10]: Si +

Si + 4 Ag + + 6 HF → H 2 SiF6 + 4 Ag + 4 H + (2) In short, overall etching is initiated by the reduction of Ag ions on the Si surface because of the electrochemical potential of Ag+/Ag, which is more positive than the Fermi level of Si. Accordingly, Ag seeds are formed on the top surface of nanoparticle arrays by injecting holes to the valence band of silicon. A preferential dissolution of Si at Ag seed/Si interface is maintained by the reduction of more Ag ions, and thereby leaves the aligned nanowire arrays (vi). Subsequently, the concentrated HNO3 solution is used again to dissolve the Ag nanoparticles covering the Si surfaces (vii). A top-view image of the dense nanowire arrays fabricated on the etched nanoparticle arrays is shown in Figure 1(c). There are no distinct differences in surface morphologies compared with the nanowire arrays formed on the polished Si substrates. The estimated distribution of nanowire diameters and fill factor are shown in the inset of Figure 1(c), indicating normal Gaussian distributed diameters averaging 71 nm and 25% in the surface fraction of Si, respectively.

Fig. 1 (a) Schematic illustrations of processes for preparing graded Si nanostructure arrays. (b) Top-view SEM image of wide separated nanoparticle arrays. Inset: Size distribution of as-prepared Si nanoparticles. (c) Top-view SEM image of dense nanowire arrays. Inset: Size distribution of as-prepared SiNWs.

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Results and discussion The surface wetting properties of Si substrates and as-prepared graded nanostructure (GN) arrays are investigated by employing contact angle measurements, respectively. As shown in Figure 2(a), the contact angle of Si substrates is 95.6o. Nevertheless, the resulting contact angle of GN arrays is smaller than 5o, implying the occurrence of surface oxidation during etching process, as shown in Figure 2(b).

Fig. 2 Result of contact angle measurement for (a) Si substrate, (b) as-prepared Si GN arrays and (c) Si GN arrays after dipping in HF solution. To clarify this issue, the sample was dipped into diluted HF solution for one minute, prior to measuring its contact angle. Evidently, the surface wettability of oxide-dissolved GN arrays turns to be super hydrophobic with the contact angle of 152.5o, originating from the inherent hydrophobicity of Si, as well as increased surface roughness from Ag induced etching process. The optical properties of nanostructures possess significant dependence on their structural geometry. In GN arrays, there are two representative layers, the dense NW, with Sifraction=25%, and the separated NPs, with Sifraction=62% on the surfaces, respectively. Unlike the individual NW or NP used as antireflection layers, the GN arrays further allow flexibility to enhance their antireflection performances, which are extremely in demand in the high conversion efficiency of solar cells [11]. Figure 3(a) shows morphology evolutions of four various GN arrays, in which the overall thickness of GN arrays are maintained at 1800±75 nm. Nevertheless, the thickness of NW arrays is well modulated at 450±35 nm, 670±60 nm, 875±45 nm, and 1260±70 nm, followed by a linear characteristic of NW length on etching time. Notice that all four various GN arrays present smooth composite interfaces between NP and NW arrays, and these features, along with the adjustable profiles of the combined nanostructures, benefit a simple and reproducible method for tailoring antireflection properties. The total reflectance spectra of the four distinct GN arrays are shown in Figure 3b. For comparison, similar measurements are also performed on individual NW and NP arrays with the same thickness as that of GN arrays (1800±80 nm). As shown in Figure 3b, all structures manifest suppressed reflectivity compared with polished Si (>35%). The sub-wavelength feature of the nanostructures leads to multiple scattering of sunlight across them to enhance greatly their capability of light trapping. More importantly, compared with individual nanowire or nanoparticle arrays, all of the GN arrays more effectively reduce reflectance between the air and the Si substrates over the major spectral irradiance of sunlight. These combined nanostructures essentially introduce the gradient refraction index at each interface, in which the high density of vertical pores at the upper layer of GN arrays can dramatically reduce the mismatch in refraction index at air/GNupper layer. On the other hand, the steady transition of morphology at GNdown layer/Si is fulfilled by the low density of vertical pores in the down layer of GN arrays. Leading among those four distinct GN layers is GN-III, whose average reflectivity is suppressed to 1.6%, approximately 39% less than single nanparticle arrays, and 20% less than individual nanowire arrays. In fact, in the GN-III arrays with dense nanowires along with separated nanoparticle arrays, the effective n at both interfaces changes smoothly, leading to lower light reflection beyond single nanowire or nanoparticle arrays.

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Fig. 3 (a) Morphology evolutions of four various GN arrays. The total thickness of every GN arrays is maintained at 1800nm±80 nm. The scale bar is 250 nm, respectively. (b) Optical reflectance spectra of nanoparticle, nanowire and various GN arrays, respectively.

Summary In conclusion, we have developed combined nanostructure arrays with tailored structural profiles. By simply controlling etching durations, various GN arrays can be fabricated well, with smooth composite interfaces between the nanoparticle and nanowire arrays and the adjustable profiles. These tailored nanostructures possess a sharper decrease in reflectivity over the major irradiance of sunlight, because of their smooth change in effective refraction index between the air and beneath the Si, further promising a low-cost, large-area, and versatile technique in diverse applications, including optical and electro-optical devices and other antireflection designs.

Acknowledgement The authors thank the Ministry of Economic Affairs, Taiwan, for financially supporting this study.

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References [1] L. Hu and G. Chen: Nano Lett., 7 (2007), 3249. [2] E. Garnett and P. Yang: Nano Lett., 10 (2010), 1082. [3] J. Li, H.Y. Yu, S. M. Wong, X. Li, G. Zhang, P. G. Q.Lo and D. L. Kwong: Appl. Phys. Lett., 95 (2009), 243113. [4] C. Lin and M. L. Povinelli: Opt. Express 17 (2009), 19371. [5] K. Peng, Y. Xu, Y. Wu, Y. Yan, S. T. Lee and J. Zhu: Small 1 (2005), 1062. [6] V. Sivakov, G. Andra, A. Gawlik, A. Berger, J. Plentz, F. Falk and S. H. Christiansen: Nano Lett., 9 (2009), 1549. [7] C. Chartier, S. Bastide and C. L. Clement: Electrochem. Commun., 53 (2008), 5509. [8] K. Q. Peng, H. Fang, J. J. Hu, Y. Wu, J. Zhu, Y. J. Yan and S. T. Lee: Chem. Eur. J., 12, (2006),7942. [9] C. Y. Chen, C. S. Wu, C. J. Chou and T. J. Yen: Adv. Mater., 20 (2008), 3811. [10] P. K. Singh, R. Kumar, M. Lal, S. N. Singh and B. K. Das: Sol. Energy Mater. Sol. Cells, 70 (2001), 103. [11] K. Q. Peng, Y. J. Yan, S. P. Gao and J. Zhu: Adv. Mater., 14 (2002), 1164.

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Thermoelectric Properties of Transition Metal Deposited MWCNT Buckypaper Jih-Hsin Liu1,2,a, Lakshmanan Saravanan2,b, Hsin-Yuan Miao1,2,c,* and Li-Chih Wang2,3,d 1

Department of Electrical Engineering, Tunghai University, Taichung, 40704 Taiwan

2

Tunghai Green Energy Development and Management Institute, Tunghai University, Taichung, 40704 Taiwan

3

Department of Industrial Engineering and Enterprise Information, Tunghai University, Taichung, 40704 Taiwan

a

[email protected], [email protected], *[email protected], [email protected]

Keywords: MWCNT, Buckypaper, SEM, Thermoelectric, Seebeck coefficient

Abstract. In this work, we report the preparation of transition metal deposited flexible multiwalled carbon nanotube buckypaper for thermoelectric applications. MWCNT buckypaper prepared by dispersion and filtration method was then deposited with the transition metals such as silver (Ag) and copper (Cu) by the electrodeposition method. We measured the voltage yield of Ag and Cudoped buckypaper by making the temperature gradient along the sample. We established the temperature dependent Seebeck coefficient for Ag and Cu-doped buckypaper and found significant increase in the S(T). It is also revealed that remarkable rise in the value of S(T) and output voltage by connecting 3-sheets of BP in series. Here we determined the enhancement of Seebeck coefficient by increasing the number of BP sheets, thereby improving the thermoelectric efficiency. Furthermore, these paper-like CNT films show good flexibility, which makes them possible to be widely applied in various flexible energy conversion devices. Introduction Thermoelectric (TE) materials, which can convert thermal energy to electric energy, have attracted much attention due to their applications in solid state cooling and power generation from waste heat [1]. The efficiency of TE materials is determined by the figure of merit, ZT = S2σT/κ, where S, σ, T and κ are the Seebeck coefficient, electrical conductivity, absolute temperature and thermal conductivity respectively. The search for better thermoelectric materials has recently accelerated due to advances in materials synthesis and processing, e.g. the use of nano materials to decrease the thermal conductivity, doped materials to increase the power factors [2], and quantum size effect to increase the Seebeck coefficients [3]. The emergence of nanotechnology creates new opportunities to design nanostructured materials to achieve high thermoelectric efficiency. Traditional TE materials are basically low band gap semiconductors, e.g. Bi2Te3, PbTe, Sb2Te3 and Co4Sb3 etc., which are stiff and expensive. Carbon nanotubes (CNTs) due to their chemical stability, flexibility, strong mechanical properties and superior electric properties [4], are known to be attractive candidates for building new types of electronic devices. In particular, the development of CNT-based flexible electronics has attracted great attention. Recently, devices based on networks of carbon nanotubes (CNTs) have attracted considerable research attention [5,6] owing to their potential in overcoming some of the technological challenges involved in the integration of single nanotube devices into scalable integrated circuits. Thin sheets comprised of randomly oriented MWCNTs, commonly referred as buckypaper (MWCNT-BP), are expected to exhibit excellent electrical and thermal properties. Many techniques, such as plasma spraying and sol gel coating are used to coat materials with different coating layers, but the electrophoretic deposition is an effective way of coating materials for various applications in a short time and low cost [7]. In this work, attempts have been made for the preparation of flexible silver (Ag) and copper (Cu) deposited MWCNT buckypaper composite

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films with enhanced thermoelectric properties. It delivers the higher value of thermal output voltage and found increase in the temperature dependent Seebeck coefficient S(T). This study provides a meaningful revelation for the future research to improve the thermoelectric properties of the CNT bulk network nanostructures. Experimental Techniques Preparation of Silver and Copper Deposited Buckypaper. The modified procedure for the fabrication of MWCNT buckypaper was followed from the earlier reports [8,9]. For the electrophoretic deposition of silver and copper on BP, the plating solution was prepared with silver nitrate and copper nitrate as precursors. Two different compositions of 0.01M and 1M were prepared both for coating silver and copper NPs on the surface of buckypaper. In the experiment, electrophoresis was carried out by applying a voltage of 4.5 V by Keithley 2410 at room temperature. After an electric field applied in the plating solution the dissociation metal ions then absorbed on both the surface of the buckypaper to form an invisible film. The positive part of the plating is connected with graphite and negative part to buckypaper. The samples were rinsed with DI water and the product then placed in a hot plate at 60°C for 30 min under O2 atmosphere, to remove the residual solution and the metal ions can more evenly distributed in the buckypaper. The BP sample deposited with 0.01M of Ag and Cu referred as 0.01M Ag-BP and 0.01M Cu-BP and with 1M of Ag and Cu deposited BP sample referred as 1M Ag-BP and 1M Cu-BP respectively. Measurement Techniques. The surface morphology was analyzed by field emission scanning electron microscope (FE-SEM) with JEOL JSM-7000F. The voltage output and the Seebeck coefficient (S) were extracted by applying a temperature gradient (RT – 600 K) along the sample and measuring the thermoelectric voltage. A Keithley 2410 was employed as a source meter. Two thermoelectric devices, one as a heat source and another as a heat sink, were used to create a temperature gradient across the BP samples. Two thermocouples were used to measure the temperatures simultaneously. We also measured the Seebeck coefficient (S) for 3 sheets of buckypaper with same size connected in series for all the samples. Results and Discussion Morphological Analysis. FESEM images of pure RBP and transition metal deposited, 1M Ag-RBP and 1M Cu-RBP buckypapers, respectively was shown in Fig. 1 (a-c). Fig. 1 (a) shows the random entanglement of MWCNTs network structures of pure RBP. We can also clearly see the porous structure of RBP, indicates the complete removal of surfactants between the tubes. The presence of metal nanoparticles was clearly seen in the Fig. 1 (b) for Ag-BP and in Fig. 1 (c) for Cu-BP samples. The porosity of the buckypaper was slightly filled with the metal nanoparticles and some NPs stick on surface of the CNTs, also clearly revealed from the FESEM images. The photo image of flexible MWCNT buckypaper was displayed in Fig. 1 (d). Thermoelectric Voltage Analysis. Fig. 2 shows the thermoelectric voltage output for 3-sheets of buckypaper connected in series for all the samples. Intuitively, good thermoelectric materials should possess high S to have high voltage output, high σ to reduce Joule heat loss, and low κ to maintain large temperature difference. Stable current were applied to the heaters, and two Keithley 2410 voltmeters measured the thermal voltage output on the sample. The measured output voltage for pure RBP is 3.3 mV and it increases for Ag and Cu doped BP samples. The output voltage value for 0.01M Ag-BP, 1M Ag-BP, 0.01M Cu-BP and 1M Cu-BP is 4.3, 5.5, 4.4 and 6.8 mV respectively. By connecting the 3-sheets of buckypaper in series, the value of the thermoelectric voltage abruptly increases. The value of output voltage for 3-sheets which is connected in series as shown in the schematic diagram in inset of Fig. 2, is 8.7, 13.9, 16.0, 13.1, 19.85 mV for BP, 0.01M Ag-BP, 1M Ag-BP, 0.01M Cu-BP and 1M Cu-BP respectively.

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Fig. 1 FE-SEM images of (a) Pure BP (b) 1M Ag-BP (c) 1M Cu-BP and (d) photo image of flexible buckypaper

Fig. 2 Thermoelectric voltage output for 3-sheets of pure and metal deposited buckypapers connected in series. Inset shows the schematic for 3-sheets of BP connected in series. Seebeck Coefficient. It has been reported that the electrical conductivity of a CNT films is dependent on CNT fabricating process, film thickness, doped chemicals and the functional groups on CNTs [10,11]. It was also stated that the electric conductivity of the macroscopic assemblies of CNTs such as buckypaper, pellet, thin films and fibers, are dependent on inter-CNT transport of charge carriers [12]. The thermally activated tunneling of charge carriers at inter-CNT contacts is considered as one of possible explanation for the electrical conduction [11]. The Seebeck coefficient (S) is related to the transport of energetic charges, whereas the electrical conductivity is related to the transport of all mobile charges [13]. The measurement for Seebeck coefficient results

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are plotted in Fig. 3. The measured S(T) for a single layer of pure and metal deposited RBP samples are shown in Fig. 3 (a).

Fig. 3 Seebeck coefficient for all the BP samples (a) single layer and (b) 3-layers in series The quantum confinement effect of charge carriers within low-dimensional structures that possess physical dimensions comparable to the electronic wavelength can potentially increase the Seebeck coefficient. The temperature dependent Seebeck coefficient S(T) value for pure BP was 13.5 µV/K and found increases for the BP samples doping with silver was -17.5 and -20.5 µV/K respectively for 0.01M Ag-BP and 1M Ag-BP and for copper the S(T) value is -16.5 and -24.5 µV/K for 0.01M Cu-BP and 1M Cu-BP respectively. The observed increase in the values of S(T) are, -32, -46, -52, -45 and -64 (µV/K) for 3-sheets of RBP, 0.01M Ag-BP, 1M Ag-BP, 0.01M CuBP and 1M Cu-BP respectively, which is connected in series. Here we found that, increase the number of sheets/surface area of the buckypaper, thereby increasing the thermoelectric power factor for enhancing the efficiency of the MWCNT buckypaper. Conclusion In this investigation, flexible films of transition metals deposited BP composite such as Ag/MWCNT and Cu/MWCNT with enhanced thermoelectric performance were prepared via electrophoretic deposition. We observe the increase in the thermoelectric voltage by the deposition of silver and copper on the surface of the MWCNT network. It was found that the improved thermoelectric properties of synthesised BP samples, are greatly increased the Seebeck coefficient value. We also determined increase in the Seebeck coefficient to ~52 and ~64 (µV/K) respectively by connecting the transition metal deposited BP of 1M Ag-BP and 1M Cu-BP sheets in series. This approach can also make possible to deposit/doping various metals or metal alloys on carbon nanotube networks (BP) to prepare a variety of CNT–metal composites for a broad range of potential thermoelectric applications. Acknowledgments This work is supported by the program of Global Research and Education on Environment and Society (GREEnS), Tunghai University, Taiwan and by the National Science Council, Republic of China (NSC101-2221-E-029-006 and NSC101-2221-E-029-010).

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References [1] Minnich, A.J., Dresselhaus, M.S., Ren, Z.F., Chen, G. Bulk nanostructured thermoelectric materials: current research and future prospects (2009) Energy Environ. Sci., 2 (5), pp. 466-479. [2] Heremans, J.P., Jovovic, V., Toberer, E.S., Saramat, A., Kurosaki, K., Charoenphakdee, A., Yamanaka, S., Snyder, G.J. Enhancement of Thermoelectric Efficiency in PbTe by Distortion of the Electronic Density of States (2008) Science, 321 (5888), pp. 554-557. [3] Szczech, J.R., Higgins, J.M., Jin, S. Enhancement of the thermoelectric properties in nanoscale and nanostructured materials (2011) J. Mater. Chem., 21 (12), pp. 4037-4055. [4] Lota, G., Fic, K., Frackowiak, E. Carbon nanotubes and their composites in electrochemical applications (2011) Energy Environ. Sci., 4 (5), pp. 1592-1605. [5] Gohier, A., Dhar, A., Gorintin, L., Bondavalli, P., Bonnassieux, Y., Cojocaru, C.S. All-printed infrared sensor based on multiwalled carbon nanotubes (2011) Appl. Phys. Lett., 98 (6), pp. 063103-063105. [6] Yeh, Y.C., Chang, L.W., Miao, H.Y., Chen, S.P., Lue, J.T. Model analysis of temperature dependence of abnormal resistivity of a multiwalled carbon nanotube interconnection (2010) Nanotechnol. Sci. Appl., 3, pp. 37-43. [7] Boccaccini, A.R., Keim, S., Ma, R., Li, Y., Zhitomirsky, I. Electrophoretic deposition of biomaterials (2010) J. R. Soc. Interface, 7, pp. S581-S613. [8] Wang, Z., Liang, Z., Wang, B., Zhang, C., Kramer, L. Processing and property investigation of single-walled carbon nanotube (SWNT) buckypaper/epoxy resin matrix nanocomposites (2004) Composites Part A, 35 (10), pp. 1225-1232. [9] Chen, Y.W., Miao, H.Y., Zhang, M., Liang, R., Zhang, C., Wang, B. Analysis of a laser postprocess on a buckypaper field emitter for high and uniform electron emission (2009) Nanotechnology, 20 (32), pp. 325302-325309. [10] Artukovic, E., Kaempgen, M., Hecht, D.S., Roth, S., Gruner, G. Transparent and Flexible Carbon Nanotube Transistors (2005) Nano Lett., 5 (4), pp. 757-760. [11] Bekyarova, E., Itkis, M.E., Cabrera, N., Zhao, B., Yu, A., Gao, J., Haddon, R.C. Electronic Properties of Single-Walled Carbon Nanotube Networks (2005) J. Am. Chem. Soc., 127 (16), pp. 5990-5995. [12] Itkis, M.E., Borondics, F., Yu, A., Haddon, R.C. Bolometric Infrared Photoresponse of Suspended Single-Walled Carbon Nanotube Films (2006) Science, 312 (5772), pp. 413-416. [13] Yu, C., Kim, Y.S., Kim, D., Grunlan, J.C. Thermoelectric Behavior of Segregated-Network Polymer Nanocomposites (2008) Nano Lett., 8 (12), pp. 4428-4432.

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Morphology and Microstructure of Aggregates and Gelation Behaviour of Poly (3-hexylthiophene) in Xylene Solution Jean-Hong Chen1, a, *, Jian-Yi Li1, 2, b, Lung-Chuan Chen1, c and Ching-Iuan Su2, d 1

Department of Materials Engineering, Kun Shan University, Tainan 71003, Taiwan, R.O.C. Department of Materials Science & Engineering, National Taiwan University of Science and Technology, Taipei 10672, Taiwan, R.O.C. a [email protected], [email protected], [email protected], d [email protected]

2

Keywords Poly (3-hexylthiophene); Microstructure; Photophysical Properties

Abstract. In this work, we investigate the morphology and microstructure of the aggregates, and the gelation behaviour of Poly(3-hexylthiophene) (P3HT) conjugated polymer in xylene solution as functions of P3HT concentration and aging time by the means of ageing time test, wide angle X-ray diffraction (WAXD), scanning electron microscopy (SEM), UV-visible absorption (UV-vis) and photoluminescence (PL) spectra. The result reveals that the gelation time of P3HT/xylene solution decreases markedly with increasing P3HT concentration. The photophysical properties of the P3HT aggregates in P3HT/xylene solution increase as P3HT concentration and ageing time are raised. It indicates that the well soluble P3HT polymer chains in xylene solution present microphase separation and self-assemble into stiff sheetlike structure, which associates by rodlike nanowhiskers of P3HT polymers during aging. Upon prolonged aging, the sheetlike structure of P3HT aggregates to from the three-dimension network that improves the electronic particle mobility in the organic solar cell. Introduction Polymer-based bulk heterojunction (BHJ) solar cells are a hopeful technology that might provide low cost solar power conversion because of the high throughput roll-to-roll techniques to form the active layer [1-3]. In the Polymer-based BHJ solar cell, the morphology of the poly(3hexylthiopehene) (P3HT) and phenyl-C61-butyric acid methyl ester (PCBM) composite has dominated research in improving efficiency of the solar cell has been the optimization of the twophase nanostructure of the donor and acceptor materials [4-7]. Various researchers have been used to control the nanoscale film morphology of the P3HT/PCBM BHJ solar cells; include solution precipitation of P3HT nanofibers [8], thermal annealing, pre- and post cathode deposition, solvent annealing [7,9], and use of mixed solvents as a means to control aggregation of the polymer [12-14]. P3HT are the thermochromism or solvatochromism polymers, which independent concentration, corresponded to presence of two coexisting phases in the solution state: P3HT in solution and it in microcrystalline aggregates [13]. Within the crystal, the extended trans conformation for the alkyl side chains which are oriented along the lateral a-axis direction and the π-π stacking of the thiophene rings is along b axis. Among crystallinity defines the degree of longrange order in a material, and strongly affects its properties. The more crystalline a polymer, the more regularly aligned its chains. The nominal melting point of P3HT crystalline in was typically above 200 oC [14]. Recently, Malik et al. provided the first insight into the gelation mechanism of P3HT/xylene solution [15]. This process was proposed to consist of two steps, namely, a coil-tohelix transition of P3HT chain conformation followed by crystallization as the rate determining step. Crystalline fibrils constituting a network structure were observed from the AFM micrograph of the dried gels; therefore, it was suggested that the crystallites acted as the cross-linking junctions to yield the gel property. It was noted in the paper that this conclusion was made based on the assumption that the morphology in the wet gel was not perturbed upon drying for carrying out the ex-situ microscopy experiment. In previous work, we have identified the formation of nanowhiskers of P3HT in the wet gel with xylene in the initial stage at room temperature [16]. However, the rodlike segments of P3HT were found to form local network aggregates in the freshly solution.

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Upon prolonged aging, the prepared solution was transformed into a gel with the presence of long nanowhiskers. The nanowhiskers formation was accompanied by the crystallization of P3HT with ca. 32% ultimate crystallinity, and the limited crystallizability was attributed to the network aggregate structure formed by P3HT prior to the gelation. In recent, P3HT exhibited nanowhiskers or nanowire morphology has been reported in many researchers with cast directly from the solution with a poor solvent [8] or subjected to a post-treatment by solvent vapour [17]. The whiskers were usually long plate in shape, with micrometers in length, tens of nano-meters in width, and only several manometers in thickness [8,17,18]. Further studies have revealed the crystalline nanowhiskers associated to form the three-dimensional network-like nanosheets at wet gels, where the crystalline P3HT backbones were found to lie normal to the whisker length and sub. Therefore, the nanosheets formation is closely associated with the nanowhiskers that self-assemble and crystallization of the P3HT backbones [17-19]. The P3HTs in microcrystalline nanosheets and nanowhiskers aggregates can be probed by UV-visible absorption (UV-vis) and photoluminescence (PL) emission spectra. The absorption peak at about 430nm attributed to P3AT in solution, while, that at about 560 and 607 nm attributed to P3AT in aggregation and/or microcrystallization is certainly involved in the thermochromism of the P3ATs [19]. The present work focuses on characterizing the network structures of the sheetlike in P3HT gels that arise from the colloidal self-assembly of P3HT conjugated polymer with different P3HT concentrations in xylene solution. Herein, probing the structure of the P3HT gel in situ, here we undertake UV-vis and PL spectra to study the gel formed by prolonged room-temperature aging of a semidilute P3HT/xylene solution. It will be shown that the gelation behaviours in a strong enhance of aggregates intensity and changes of spectra profile. It indicates a transformation from the sheetlike structure formed by P3HT rodlike segments to long semicrystalline macroscopic network to yield the gel property was discussed in the articles. Experimental Preparations of solutions. P3HT conjugated polymer was obtained from UniRegion Bio-Tech. Inc. The molecular weight of P3HT measured by GPC with THF solvent and PS standard is ca. 65,000 g/mole, respectively. The concentrations of blended P3HT in xylene solution are ca. 0.1, 0.5, 1.0, 1.5, 2.0, 2.5 and 3.0 wt%. The solutions of P3HT/xylene were prepared by stirring their mixtures at ca. 60 oC for 8 hr, where macroscopically homogeneous solutions were observed by naked eyes. The P3HT/xylene gels were obtained by aging the solutions at ambience temperature ca. 20 oC for sufficiently long time of 2 week. Morphology of the aggregates of P3HT. The morphologies of the aggregates of P3HT/xylene aged wet gels were investigated with an optical microscope (OM) (Zeiss Axioskop-40). The aggregate structures of P3HT in aged wet gels were separated in MCH solvent, subsequently, drops the dispersed aggregates solution in a glass slides and freeze drying at -80 oC. The morphology of the nanosheets was investigated with a field-emission scanning electron microscope (FESEM) (Hitachi S-4700). Spectral characterizations. The UV-vis absorption measurements for the -* transition of P3HT solution was performed using a Hitachi U-3010 Spectrophotometer. For the aged semidilute solutions and gels the samples were sandwiched between two microscope cover glasses to obtain the solution or gel layers of about 100 m in thickness. The reported absorbances of the samples have been corrected for the solvent background. The photoluminescence (PL) spectra were recorded by using a Perkin-Elmer LS55 spectrophotometer. The samples were placed in sealed glass tubes with the thickness of 1 cm for the measurements. The excitation wavelength was 320 nm. The temperature-dependent experiments were realized by using a thermostat tube heating system. Results and Discussion It is well known that conjugated polymer solutions undergo physical gelation upon prolonged isothermal aging due to very slow dynamics associated with the structural reorganization [10,16]. In a previous study, we found that the gelation of semidilute PF8/MCH solutions was driven mainly by a macrophase separation proceeding via the spinodal decomposition mechanism, yielding the

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coexistence of an isotropic liquid phase and a nematic phase [20]. The aggregation behaviour of P3HT in xylene solution can be reflects directly from its aging time test. Fig. 1 shows the gelation time of P3HT/xylene solutions as a function of P3HT concentration at room temperature. For this experiment, the solutions also accompany the aging time induces chromism phenomena; from the orange to the deep-purple color, upon prolonged aging. The result indicates that decreases markedly in the gelation time as the P3HT content is increased attributes to aggregation or association between P3HT chains promotes by the higher P3HT concentration. 400

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The formation of aggregates of P3HT in the freshly-prepared solutions well with the emergence of P3HT aggregates probed easily by the UV-vis absorption (UV-vis) and photoluminescence (PL) spectroscopy. Fig. 2 displays the change of UV-vis absorption spectrum of various concentrations P3HT/xylene solutions as a function of aging time. However, the spectrum of the fresh solution (aging time = 0 min) shows a peak at 453 nm associated with the π-π* transition of the dissolved P3HT chains in the solution [20,21]. As the aging progresses, two additional peaks at 565 and 610 nm gradually develop, which can be assigned to 0-0 singlet transition and a vibronic side band [21], respectively, associated with P3HT in the ordered state [11,21]. This vibronic coupling in the ordered state of P3HT is due to the interchain interaction involved in aggregation, gelation, and crystallization. Herein, the UV-vis absorption spectrum indicates that the aggregates of P3HT in P3HT/xylene solution increase as P3HT concentration and ageing time are raised. It indicates that the well soluble P3HT chains in solution state assemble into stiff sheetlike aggregates, which associates by rodlike nanowhiskers of P3HT polymers, promote by the P3HT content and ageing time. (a)

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The change of PL spectrum of P3HT/xylene solutions upon prolonged aging was shown in Fig. 3. It can be seen that the fresh solution (aging time=0min) shows a peak at 570 nm associated with the ππ* transition of the dissolved P3HT chains in the solution. Upon prolonged aging, the crystallization of P3HT during aging induces the development of two additional emission peaks at 640 and 690 nm, which can be associated with P3HT in the ordered state as same as the UV-vis spectrum. The formation of red-shifted emission peaks in PL spectrum is a well-known consequence of the improved electron delocalization in the solid state or good intermolecular ordering in semicrystalline conjugated polymers [20,21]. P3HT/Xylene 0.1 wt%

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P3HT/Xylene 0.5wt%

(a)

420 min

800

90 min 60 min 30 min 0 min

400

500

600

Wavelength (nm)

(c)

P3HT/Xylene 1.5wt%

90 min

800

(d)

P3HT/Xylene 3.0wt%

50 min 40 min

50 min

30 min

40 min

20 min

30 min

10 min

PL intensity , a.u.

PL intensity , a.u.

60 min

20 min 10 min 0 min

400

700

Wavelength (nm)

500

600

700

0 min

400

800

500

600

700

800

Wavelength (nm)

Wavelength (nm)

Figure 3. The in-situ normalized PL spectrum for various concentrations of P3HT in xylene solutions as a function of age time: (a) 0.1, (b) 0.5, (c) 1.5, and (d) 3.0 wt%. The emitting peak at 575 nm attributes to the isolate polymer chain in P3HT solution and the emitting peaks at 640 and 690 nm attribute to the P3HT aggregate domains in aged solution.

We assume that the absorbance of the UV-vis peak at 610 nm is directly proportional to the crystallinity of P3HT formed during aging; the relative crystallinity at a given aging time ta can then be calculated by Eq. 1: χ C (t a ) 

I 610 nm ( t a )  I 610 nm (0) I 610 nm ()  I 610 nm (0)

(1)

In contrast to the conventional sigmoidal curve found for polymer crystallization, the crystallinity development of P3HT during aging is found to closely follow the classical Avrami equation [22], c(ta) = 1 - exp(-ktn), the c(ta) thus calculated are plotted against aging time, as presented in Fig. 4. 1.0

1.5

log -ln [ 1- X(t) ]

0.0

-1.0 3.0 wt% 2.0 wt% 1.0 wt%

2.0

-2.0

0.7 wt% 0.5 wt% 0.3 wt% 0.2 wt%

-3.0 0.80

1.20

1.60

2.00

2.40

2.80

Log (t), min

Figure 4. Avrami plots of the P3HT aggregates during aging deduced from the PL spectra in Figure 4. The Figure shows the growth of the P3HT aggregates is found to be from 2.0 to 1.5 with P3HT correspond to the structure of aggregates is from sheet-like into coexist sheet- and rod-like as P3HT content is increased.

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This exponential function indeed corresponds to the Avrami equation with the characteristic exponent n from 2.0 to 1.5 as P3HT concentration is increased. In the case of instantaneous nucleation, the close proximity of n to the value of 2.0 signals a two-dimensional sheetlike growth at lower P3HT content, while that of 1.5 implies coexisting the one- and two-dimensional growth of the P3HT crystallites, consistent with the co-formation of nanosheets and nanowhiskers morphologies of the P3HT aggregates in higher P3HT content. Therefore, the domain size of the sheetlike morphology of the P3HT aggregates decreases significantly with increasing P3HT concentration means that the aggregation between P3HT chains was retarded by the entanglement of P3HT chains, as shown in Fig. 5. (a)

(b)

5.0m

(c)

5.0m

(d)

Figure 5. Optic-microscopy and SEM images of various concentrations P3HT gels at room temperature: (a) 0.5 and (b) 1.5wt% of OM, and (c) 0.5, and (d) 1.5wt% of SEM images.

Conclusion In the homogeneous P3HT/xylene solution, it developed the stiff sheetlike aggregates during ageing at ambient condition, which associated by rodlike nanowhiskers of P3HT polymers through - stacking force in the polymer rich domain. The growth mechanism of the P3HT aggregates changed markedly; from two-dimensional into coexisting one- and two-dimensional mechanism, as the P3HT concentration was increased. In the P3HT/xylene gels, the aggregation of P3HT was retarded significantly by the P3HT contents. Therefore, the morphology of the aggregate structure in the wet P3HT gels presented the sheet-like structure with ca. 80 nm thickness of P3HT nanosheets associates to form the three-dimension network structure. Acknowledgments We acknowledge the financial supports of the National Science Council of the Republic of China under grant Nos. NSC 100-2221-E-168-015 and NSC 100-2632-E-168-001-MY3. References [1] H. Sirringhaus, P. J. Brown, R. H. Friend, M. M. Nielsen, K. Bechgaard, B. M. W. LangeveldVoss, A. J. H. Spiering, R. A. J. Janssen, E. W. Meijer, P. Herwig and D. M. de Leeuw: Nature Vol. 401 (1999), p. 685. [2] P. W. M. Blom, V. D. Mihailetchi, L. J. A. Koster, and D. E. Markov: Adv. Mater. Vol. 19 (2007), p. 1551. [3] B. C. Thompson and J. M. J. Frechet: Angew. Chem., Int. Ed. Vol. 47 (2008), p. 58. [4] V. Shrotriya, J. S. Huang, Y. Yao, T. Moriarty, K. Emery and Y. Yang: Nat. Mater. Vol. 4 (2005), p. 864.

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[5] J. Y. Kim, K. Lee, N. E. Coates, D. Moses, T. Q. Nguyen, M. Dante and A. J. Heeger: Science Vol. 317 (2007), p. 222. [6] S. E. Gledhill, B. Scott and B. A. Gregg: J. Mater. Res. Vol. 20 (2005), p. 3167. [7] Y. Zhao, Z. Y. Xie, Y. Qu, Y. H. Geng and L. X. Wang: Appl. Phys. Lett. Vol. 90 (2007), p. 043504. [8] S. Berson, R. De Bettignies, S. Bailly and S. Guillerez: Adv. Funct. Mater. Vol. 17 (2007), p. 1377. [9] S. Miller, G. Fanchini, Y. Y. Lin, C. Li, C. W. Chen, W. F. Su and M. Chhowalla: J. Mater. Chem. Vol. 18 (2008), p. 306. [10] J. K. Lee, W. L. Ma, C. J. Brabec, J. Yuen, J. S. Moon, J. Y. Kim, K. Lee, G. C. Bazan and A. J. Heeger: J. Am. Chem. Soc. Vol. 130 (2008), p. 3619. [11] M. Dante, A. Garcia and T. Q. Nguyen: J. Phys. Chem. C. Vol. 113 (2009), p. 1596. [12] Y. Yao, J. H. Hou, Z. Xu, G. Li and Y. Yang: Adv. Funct. Mater. Vol. 18 (2008), p. 1783. [13] S. Joshi, S. Grigorian and U. Pietsch: Phys. Status Solidi A Vol. 205 (2008), p. 488. [14] L. H. Jimison, M. F. Toney, I. McCulloch, M. Heeney and A. Salleo: Adv. Mater. Vol. 21 (2009), p. 1568. [15] S. Malik, T. Jana and A. K. Nandi: Macromolecules Vol. 34 (2001), p. 275. [16] C. Y. Chen, S. H. Chan, J. Y. Li, K. H. Wu, H. L. Chen, J. H. Chen, W. Y. Huang and S. A. Chen: Macromolecules Vol. 43 (2010), p. 7305. [17] D. H. Kim, Y. D. Park, Y. Jang, S. Kim and K. Cho: Macromol. Rapid Commun. Vol. 26 (2005), p. 834. [18] J. H. Liu, M. Arif, J. H. Zou, S. I. Khondaker and L. Zhai: Macromolecules Vol. 42 (2009), p. 9390. [19] W. Y. Huang, P. T. Huang, Y. K. Han, C. C. Lee, T. L. Hsieh and M. Y. Chang: Macromolecules Vol. 41 (2008), p. 7485. [20] C.Y. Chen, C. S. Chang, S. W. Huang, H. L. Chen, J. H. Chen, C. I. Su and S. A. Chen: Macromolecules Vol. 43 (2010), p. 4346. [21] R. Österbacka, C. P. An, X. M. Jiang and Z. V. Vardeny: Science Vol. 287 (2000), p. 839. [22] M. J. Avrami: Chem. Phys. Vol. 7 (1939), p. 1103; M. J. Avrami: Chem. Phys. Vol. 9 (1941), p. 177.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 121-125 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.121

Small Scale Effect on Nonlinear Vibration of Fluid-Loaded Double-Walled Carbon Nanotubes with Uncertainty Tai-Ping Chang1, a 1

Department of Construction Engineering, National Kaohsiung First University of Science and Technology, Kaohsiung, 824, Taiwan a

[email protected]

Keywords: Small scale effect, Nonlinear vibration, Double-walled carbon nanotubes, Random material properties, Nonlocal elasticity theory.

Abstract. This paper investigates the statistical dynamic behaviors of nonlinear vibration of the fluid-loaded double-walled carbon nanotubes (DWCNTs) by considering the effects of the geometric nonlinearity and the nonlinearity of van der Waals (vdW) force. Besides, the small scale effects of the nonlinear vibration of the DWCNTs are studied by using the theory of nonlocal elasticity. The nonlinear governing equations of the fluid-conveying DWCNTs are formulated based on the Hamilton’s principle. The Young’s modulus of elasticity of the DWCNTs is assumed as stochastic to actually describe the random material properties of the DWCNTs. By utilizing the perturbation technique, the nonlinear governing equations of the fluid-conveying can be decomposed into two sets of nonlinear differential equations involving the mean value of the displacement and the first variation of the displacement separately. Then we adopt the harmonic balance method in conjunction with Galerkin’s method to solve the nonlinear differential equations successively. Some statistical dynamic response of the DWCNTs such as the mean values and standard deviations of the amplitude of the displacement are computed; meanwhile the effects of small scale coefficients on the statistical dynamic response of the DWCNTs are investigated. Introduction A landmark paper on Carbon nanotubes (CNTs) by Iijima [1] has attracted worldwide attention due to their potential use in the fields of chemistry, physics, nano-engineering, electrical engineering, materials science, reinforced composite structures and construction engineering. Carbon nanotubes (CNTs) are used for a variety of technological and biomedical applications including nanocontainers for gas storage and nanopipes conveying fluids [2-4]. The single-elastic beam model [5-6] were widely adopted to study the dynamic behaviors of fluid-conveying single-walled carbon nanotubes (SWCNTs) and multi-walled carbon nanotubes (MWCNTs). Normally speaking, the beam models mentioned above are linear; however, the vdW forces in the interlay space of MWCNTs are essentially nonlinear. Furthermore, the slender ratios are normally large if the beam models are adopted, that is, the large deformation will occur. Therefore, it is quite essential to consider two types of nonlinear factors, namely, the geometric nonlinearity and the nonlinearity of vdW force in investigating the dynamic behaviors of fluid-conveying MWCNTs. To be realistic, the Young’s modulus of elasticity of carbon nanotube (CNTs) should be considered as stochastic to actually describe the random property of the CNTs under certain conditions. In the present study, we investigate the stochastic dynamic behaviors of nonlinear vibration of the double-walled carbon nanotubes (DWCNTs) conveying fluid by considering the effects of the geometric nonlinearity and the nonlinearity of van der Waals (vdW) force. Besides, the small scale effects of the nonlinear vibration of the DWCNTs are studied by using the theory of nonlocal elasticity. Based on the Hamilton’s principle, the nonlinear governing equations of the fluid-conveying double-walled carbon nanotubes are formulated. The Young’s modulus of elasticity of the DWCNTs is considered as stochastic with respect to the position to actually characterize the random material properties of the DWCNTs. The effects of small scale coefficients on the statistical dynamic response of the DWCNTs are investigated.

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Nonlinear beam model for fluid-conveying DWCNTs

Fig. 1. Fluid-conveying double-walled carbon nanotubes. In Fig. 1, the double-walled carbon nanotubes (DWCNTs) is modeled as a double-tube pipe which is composed of the inner tube of radius R1 and the outer tube of radius R2 . The thickness of each tube is h , the length is L , and Young’s modulus of elasticity is E . It is noted that the Young’s modulus of elasticity E is assumed as stochastic to actually describe the random material property of the DWCNTs. The internal fluid is assumed to flow steadily through the inner tube with a constant velocity U . Besides, the boundary conditions of the DWCNTs are assumed as clamped at both ends. Based on the theory of Euler–Bernoulli beam and a nonlinear strain–displacement relationship of Von Karman type, the displacement field and strain–displacement relation can be written as follows: ∂w ∂u 1  ∂w  ui ( x, z, t ) = ui ( x, t ) − z i , wi ( x, z, t ) = wi ( x, t ) , ε i = i +  i  ∂x ∂x 2  ∂x 

2

(1)

where x is the axial coordinate, t is time, ui and wi denote the total displacements of the ith tube along the x coordinate directions, ui and wi define the axial and transverse displacements of the ith tube on the neutral axis, ε i the corresponding total strain, and the subscript i = 1 and i = 2. Notice that tube 1 is the inner tube while tube 2 is the outer tube. The potential energy V stored in a DWCNTs and the virtual kinetic energy T in the DWCNTs as well as the fluid inside the DWCNTs can individually be computed. Based on Hamilton’s principle, the variational form of the equations of motion for the DWCNTs can be given by t1

∫ (δ V − δ T − δΨ ) dt = 0

(2)

t0

where δΨ is the virtual work due to the vdW interaction and the interaction between tube 1 and the flowing fluid. By utilizing the Eqs. (2) and considering the boundary conditions of the clamped ends, and the assumption that all variables and derivatives are zero at t = t0 and t = t1 , all the terms L

t

involving [⋅]0 and [⋅]t1 vanish. In addition, considering the moderate large-amplitude deflection, 0

cosθ1≈1 and sin θ ≈ −∂w / ∂x are adopted in the following derivation. By neglecting the rotation inertia and utilizing Eqs. (2), and adopting the the theory of nonlocal elasticity and the formulations derived by Chang [7,8], after some tedious derivations we can obtain the coupled nonlinear governing equations for the free vibration of DWCNTs conveying fluid based on nonlocal elasticity therory as follows: 1

1

 ∂ 2 w  ∂2w ∂ 4 w1 ∂ 4 w1 2 2 2  2 2 1 1   E ( x) I1 − ( e0 a ) MU  2  − 2 ( eo a ) MU 3 − ( eo a ) ( M + m1 ) 2 2 + MU ∂x ∂t ∂x ∂t ∂x  ∂x 2    2 2 2 2 ∂2w ∂2w ∂w ∂w ∂ 2 w  ∂w   E ( x) A MU 2  ∂ w 3MU 2  ∂w  ∂ w 1+ 1+ 1 +( M + m ) 1 +2MU 1 − MU 1 1 1  dx − ∫0L  1    1 1  ∂x   2 L   2 2 2 2  ∂ 2 L 2 ∂ x ∂ x ∂ t ∂ t x ∂x ∂x ∂t      ∂x  ∂2 ∂x 2

3

   ∂2  ∂ 2    ∂ 2    = 1-(e0 a ) 2 2  c (w − w ) + c   1-(e0 a ) 2 2  w2  − 1-(e 0 a) 2 2  w1   3  ∂x  1 2 1 ∂x    ∂x     

(

)

(3)

Applied Mechanics and Materials Vols. 479-480

∂2 ∂x 2

 2 ∂ 2 w  ∂ 4w  2 + m ∂ w2 − ( e a )2 m 2 −   E ( x) I 2   2 0 2 ∂t 2 ∂x2  ∂x 2∂t 2   

∫

L

0

2

2  ∂w2   E ( x) A2  ∂ w2  ∂x   2 L  dx ∂x 2    

123

(4)

3

= -(1-(e0a) 2

∂2 ∂ 2    ∂ 2      )(c1 (w2 − w1 )) − c3  1-(e0a) 2 2  w2  − 1-(e0 a)2 2  w1   2 ∂x ∂x    ∂x     

In Eqs. (3-4), it is assumed that the small scale effects on the nonlinear terms due to geometrical nonlinearity are neglected since they are normally small compared with those on the linear terms. Statistical dynamic analysis of nonlinear vibration of DWCNTs In the present study, the Young’s modulus of elasticity E(x) is considered as stochastic to actually characterize the random properties of the DWCNTs and it is assumed as Gaussian distributed. Applying the perturbation technique on the Young’s modulus of elasticity E(x), the following equations can be written: (5) where E ( x) is the mean value of the Young’s modulus of elasticity E(x), ε is a zero-mean small parameter, and ε E I ( x) is the first variation of the Young’s modulus of elasticity E(x). Similarly, the displacement w1 ( x), w2 ( x) of the DWCNTs can be written as follows: E ( x) = E 0 ( x) + ε E I ( x) +
0

w1 ( x ) = w10 ( x ) + ε w1I ( x ) +


(6) (7) w2 ( x) = w ( x ) + ε w ( x) +
where w10 ( x), w20 ( x) are the mean values of displacement of the inner and outer tubes separately. Substituting Eqs. (5-7) into Eqs. (3-4), we can obtain the following two coupled equations based on the zero order of ε : 0 2

I 2

4 0 4 0 4 0  E 0 I − ( e0 a )2 MU 2  ∂ ( w1 ) − 2 ( eo a )2 MU ∂ w1 − ( eo a )2 (M + m1 ) ∂ w1 4 3  1  ∂x ∂x ∂t ∂x 2∂t 2 2

2

∂ 2 ( w10 )  MU 2 E 0 A1  L  ∂ ( w10 )  ∂ 2 ( w10 ) 3MU 2  ∂w10   ∂ 2 w10  + MU − + dx +  ∫0      2  ∂x 2 L   ∂x  ∂x 2 2  ∂x   ∂x 2   2L ∂ 2 ( w10 ) ∂ 2 w10 ∂w0 ∂w0 ∂ 2 w0 +(M + m1 ) + 2MU − MU ( 1 )( 1 )( 21 ) 2 ∂t ∂x∂t ∂t ∂x ∂x 2

(8)

3

   ∂2  ∂2  = 1-(e0 a)2 2  c1 ( w20 − w10 ) + c3 1-(e0 a)2 2  ( w20 − w10 )  ∂x  ∂x     4 0 2 0 4 0 0 0 2 L   ∂ ( w ) ∂ ( w ) ∂ w E A ∂ w ∂ 2 ( w20 ) 2 2 2 2 2 2 E 0Ι 2 + m − e a m − dx ( )   2 0 2 ∂x 4 ∂t 2 2 L ∫0  ∂x  ∂x 2 ∂x 2∂t 2    ∂2  ∂2  = − 1-(e0 a) 2 2  c1 ( w20 − w10 ) − c3  1-(e0a) 2 2  ( w20 − w10 )  ∂x  ∂x    

(9)

3

Based on the first order of ε , we can achieve two coupled equations which are not expressed explicitly for the sake of simplicity. First of all, we have to solve w10 , w20 in Eqs. (8-9). By applying the harmonic balance method and Galerkin’s method and substituting wi0 = Aiφ1 ( x) sin(ωt ) (i = 1, 2) into Eqs. (8-9), after some tedious derivations the relationship between the amplitude Ai and the resonant frequency ω of the lowest-order mode φ1 ( x) can be achieved as follows (10) G1 A1 + G2 A13 + G3 ( A2 − A1 ) + G4 ( A2 − A1 )3 = 0 G5 A2 + G6 A23 + G3 ( A2 − A1 ) + G4 ( A2 − A1 )3 = 0 (11) 0 0 After solving coupled Eqs. (10-11) for the amplitudes A1 , A2 , we can obtain w1 , w2 readily. Substituting w10 , w20 into the two coupled equations for the first order of ε , and adopting the same technique for solving w10 , w20 , finally we can obtain w1I , w2I without any difficulties except the derivations is somewhat lengthy.

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Numerical examples and discussion In the numerical computations, the clamped-clamped boundary conditions are considered for the DWCNTs conveying fluid. The inner and the outer tubes are assumed to have the same Young’s modulus, the same thickness and the same mass density. The numerical values of the parameters are adopted as follows: Mean value of Young’s modulus E=1 Tpa, tube thickness h=0.34 nm, mass density ρ = 2300 Kg / m 3 , the mass density of water flow is ρ f = 1000 Kg / m3 , the inner radius R = 0.7nm and 1

the outer radius R2 = 1.04nm and mean square values of ε is assumed as E ε 2  =0.01. The relations of the 



mean value of amplitude versus frequency are depicted in Fig. 2. It can be seen that the mean value of the amplitude increases with the increase of the frequencies. It is completely reasonable that the relation between the mean value of the amplitude and the frequency is nonlinear; in addition, the mean value of the amplitude of the outer tube is larger than that of the inner tube. Furthermore, it is noted that the mean value of the amplitude gets larger as the small scale coefficient e0 a increases for the fixed frequency. In Fig. 3, the standard deviation of the amplitude is plotted with respect to the frequency. As it can be found from the figure that the standard deviation of the amplitude increases nonlinearly with the increase of the frequencies, and it is noted that the standard deviation of the amplitude of the outer tube is larger than that of the inner tube. 7 A1, e0a/L=0.0 A2, e0a/L=0.0

6 Mean value of amplitude (nm)

A1, e0a/L=0.1 A2, e0a/L=0.1

5

A1, e0a/L=0.2 A2, e0a/L=0.2

4

3

2

1

0 3.55

3.56

3.57

3.58

3.59 3.6 3.61 Frequency (Hz)

3.62

3.63

3.64

3.65 10

x 10

Fig. 2. Mean value of amplitude versus frequency for different values of e0 a / L .

Standard deviation of amplitude (nm)

0.6

0.5

0.4

0.3

SD of A1, e0a/L=0.0 SD of A2, e0a/L=0.0

0.2

SD of A1, e0a/L=0.1 SD of A2, e0a/L=0.1

0.1

SD of A1, e0a/L=0.2 SD of A2, e0a/L=0.2

0 3.55

3.56

3.57

3.58

3.59 3.6 3.61 Frequency (Hz)

3.62

3.63

3.64

3.65 10

x 10

Fig. 3. Standard deviation of amplitude versus frequency for different values of e0 a / L .

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Conclusions In the present study, we investigate the stochastic dynamic behaviors of nonlinear vibration of the double-walled carbon nanotubes (DWCNTs) conveying fluid by considering the effects of the geometric nonlinearity and the nonlinearity of van der Waals (vdW) force. In addition, the small scale effects of the nonlinear vibration of the DWCNTs are studied by using the theory of nonlocal elasticity. Based on the Hamilton’s principle, the nonlinear governing equations of the fluid-conveying double-walled carbon nanotubes are formulated. The Young’s modulus of elasticity of the DWCNTs is considered as stochastic to actually characterize the random material properties of the DWCNTs. By using the perturbation technique, the nonlinear governing equations of the fluid-conveying double-walled carbon nanotubes can be decomposed into two sets of nonlinear differential equations involving the mean value of the displacement and the first variation of the displacement separately. Then the harmonic balance method and Galerkin’s method are adopted to solve the nonlinear differential equations successively. Some statistical dynamic response of the DWCNTs such as the mean values and standard deviations of the amplitude of the displacement are calculated, meanwhile the effects of the nonlocal scale coefficients on the statistical dynamic response of the DWCNTs are investigated. It can be concluded that the mean value and standard deviation of the amplitude of the displacement increase nonlinearly with the increase of the frequencies. Besides, these stochastic dynamic responses get larger as the small scale coefficients get larger. It is noted that the computed stochastic dynamic response plays an important role in estimating the structural reliability of the DWCNTs.

Acknowledgments: This research was partially supported by the National Science Council in Taiwan through Grant No. NSC-99-2221-E-327-020. The author is grateful for the financial support. References [1] S. Ijjima: Nature Vol. 354 (1991), p. 56. [2] G. E. Gadd et. al.: Science Vol. 277 (1997), p. 933. [3] G. Che et. al.: Nature Vol. 393 (1998), p. 346. [4] J. Liu et. al.: Science Vol. 280 (1998), p. 1253. [5] J. Yoon, C.Q. Ru and A. Mioduchowski: Int. J. Solids Struct. 43 (2006), p. 3337. [6] L. Wang and Q. Ni: Comput. Mater. Sci. Vol. 43 (2008), p. 399. [7] T. P. Chang: J. Mech. Vol. 27 (2011), p. 567. [8] T. P. Chang: Appl. Math. Model. Vol. 36 (2012), p. 1964.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 126-130 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.126

Determination of the Optimal Locations for Injection Molding Gates with Higher Order Response Surface Approximations Kun-Nan Chena and Wen-Der Ueng Department of Mechanical Engineering, Tungnan University, New Taipei City, Taiwan a

[email protected]

Keywords: Injection molding, Gate location, Response surface approximations, Global optimization.

Abstract. This paper proposed a gate location optimization scheme to minimize the maximum injection pressure in plastic injection molding. The method utilized a series of higher order response surface approximations (RSA) to model the maximum injection pressure distribution with respect to gate locations, and the global minimum of these response surface models were subsequently sought by a global optimization method based on a multi-start sequential quadratic programming technique. The design points for RSA were evaluated by the finite element method. After a sequence of repetitions of RSA and optimization, the converged minimizer would represent the optimal gate location. A rectangular plate with two segments of different thicknesses was selected to demonstrate the effectiveness of the procedure. The variation of the thicknesses causes the optimal gate location to deviate from the center and induce multiple valleys in the maximum injection pressure distribution, which is ideal for the application of the higher order RSA and a global searching technique. Introduction Injection molding is commonly utilized for mass production of thin shell plastic parts. The quality of a molded part is significantly affected by various factors including the geometric parameters of the mold and the process parameters of the molding conditions. Among these parameters the location of the gate is one of the most important factors since it dictates the way of the plastic melt flowing into the mold cavity. Inappropriately located gates can result in molded parts suffered with excessive injection pressure, warpage, and overpacking, etc. The injection pressure is limited by the capacity of the injection machine used, and when the limit is exceeded, the pressure must be adjusted. By relocating the gate position, the maximum flow length can be altered and the injection pressure can be reduced. Zhai and Shen [1] proposed a flow resistance search scheme to find the optimum gate location by moving the gate along the direction with maximum flow resistance. The original concept of response surface methodology (RSM) [2] was to combine statistical design of experiments and data fitting techniques to describe the mathematical relationships between the design factors and the objective function based on experimental data, and to attain the optimal response model as well as to provide insight through graphical description of the model [3]. Performing design of experiments (DOE) using RSM can reduce the number of experiments required and the results leading to the optimal conditions linking the input factors and the output responses can be obtained through many different means. Many engineering analysis, design, and optimization problems can be solved by response surface approximations (RSA), which replace complex or totally unknown input-output relations with simplified mathematical functions. Liu, Haftka and Akgun [4] proposed a two-level structural optimization design scheme on airplane wing structure made from composite materials using RSM. The final results satisfied the strength and the sizing constraints as well as the composition constraints of the composite materials. Myers [5] reviewed the theories and applications of RSM and provided an extensive list of RSM related articles. Recently, applying DOE or RSA to improve the quality of injection molding has been reported by several authors. Ozcelik and Erzurumlu [6] utilized DOE and the finite element software MoldFlow to study the best gate location and warpage on the molded parts. Kurtaran and Erzurumlu [7] integrated finite element analysis, DOE, RSA, and genetic algorithm (GA) to perform warpage minimization on thin shell plastic parts.

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This paper proposed a gate location optimization scheme to minimize the maximum injection pressure in plastic injection molding. The method utilized a series of higher order RSA to model the maximum injection pressure distribution with respect to gate locations, and the global minimum of these response surface models were subsequently sought by a global optimization method based on a multi-start sequential quadratic programming technique. The design points for RSA were evaluated by the finite element method. After a sequence of repetitions of RSA, optimization and reduction of the design domain, the converged minimizer would represent the optimal gate location. The proposed procedure was realized with a Matlab code to perform DOE, RSA and global optimization, and with the MoldFlow software to simulate an injection molding process. Response Surface Approximations A system with complex or unknown input-output relationships can be represented by the following mathematical function: y = ƒ(x1, x2, …, xk) + ε

(1)

where f is a simple function (usually a polynomial), x1, x2, …, xk represent the independent variables which are also called the factors, k denotes the number of factors, y is the dependent variable or the response affected by the factors, and ε is the error term. As an example, a response surface approximation of the response y using a second order, k factors polynomial can be written as k

k

i =1

i =1

k −1

k

yˆ = β 0 + ∑ βi xi + ∑ βii xi2 + ∑ ∑ βij xi x j

(2)

i =1 j = i + 1

where βi are the coefficients that can be determined using regression analysis and least square solutions. Before forming Eq. 2 and solving for βi, experiments must be conducted using factor values defined by design of experiments. A face-centered central composite design (FCCD) includes 2k factorial designs, 2k axial design points, and kc center points, adding up to 2k+2k+kc total design points. In order to apply least square solutions, the number of observed data points has to be greater than the number of the undetermined coefficients. For a second order and k factors polynomial, there are (k+1)(k+2)/2 coefficients. Since the mathematical function of RSA is a smooth surface, any usual optimization method may be employed to find the optimal solution once the RSA is constructed. In this research, higher order response surface approximations of the maximum injection pressure at the end of filling stage as a function of gate location are employed, in an attempt to capture the multi-modal characteristics often presented in injection molding for a complex molded part. Using x1 and x2 to represent the coordinates of the gate location, a full factorial design for constructing a fourth order, two factors polynomial will consist of 25 design points, and there will be a total of 25 finite element analyses required in a design run. The fourth order, two factors polynomial has the form yˆ = β 0 + β1 x1 + β 2 x 2 + β 3 x1 x2 + β 4 x12 + β5 x22 + β 6 x1 x 22 + β 7 x12 x2 + β8 x13 + β 9 x23 + β10 x1 x 23 + β11 x12 x 22 + β12 x13 x 2 + β13 x14 + β14 x 24

(3)

where ŷ is the RSA of the injection pressure at the end of fill, and the number of undetermined coefficients βi is 14. Eq. 3 can be solved by the least square method to find the unknown coefficients. Multi-start Sequential Quadratic Programming Technique Once the RSA for the injection pressure at the end of filling stage as a function of gate location is constructed, the next step is to search for the global minimum of this approximation function. Since higher order response surface approximations are used, multiple local minima are expected. A global optimization technique employing a modified sequential quadratic programming (SQP) method equipped with a multi-start capability is adopted to solve the problem. The basic scheme of an SQP technique can be expressed in the following steps: Step 1: Set up and solve a quadratic programming (QP) subproblem, giving a search direction. Step 2: Test for convergence, stop if it is satisfied.

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Step 3: Step forward to a new point along the search direction. Step 4: Update the Hessian matrix in QP and go to step 1. In order to search for the global optimum, the concept of multi-start global optimization procedure is combined with the SQP method. Let F* denote the global maximum and r be the number of sample points falling within the region of convergence of the current overall maximum F after n points have been sampled. Then, under statistically noninformative prior distribution, the probability that F be equal to F* satisfies the following relationship [8]: Pr[F=F*]≧q(n, r)=1-[(n+1)!(2n-r)!]/[(2n+1)!(n-r)!]

(4)

A very high probability (>0.999) was set in this study to ensure the global optimum would be attained. Gate Location Optimization for Injection Molding Problem Definition. The objective is to find the gate location (x1 and x2) such that the maximum injection pressure at the end of fill is minimized. This gate location optimization problem can be stated as follows Minimize f(x1, x2) = pmax Subjected to x1, x2 ∈ Ω

(5)

where f is the objective function; x1 and x2 are the gate coordinates; pmax is the maximum injection pressure at the end of filling stage; and Ω is the feasible domain. To solve the gate location optimization problem, move limits are first defined and DOE is performed according to the limits. The move limits should cover the entire feasible domain of the molded part in the first iteration run, and be gradually shrunken during the subsequent runs. Finite element analysis is performed at each design point to create a response surface approximation of the pmax distribution in the feasible domain, and then the multi-start global optimization procedure is executed to establish the global minimum of the RSA. A new design is formed around the global minimum using a new set of reduced limits. Again, an RSA is produced and SQP carried out. If two global minima in two consecutive runs are within an acceptable tolerance, the process is considered converged and the optimal gate location is found; otherwise, the iteration process continues. In this research, the software package MoldFlow was used for finite element analyses to simulate the melt filling process, and Matlab was employed for DOE, RSA, and global optimization. The Numerical Example. The example selected was a rectangular plate structure of size 150 mm by 80 mm with two different thicknesses, 3 mm and 2 mm. The geometry of the plate and the meshing for finite element analysis can be seen in Fig. 1. The material used was High Impact Polystyrene (Styron 478, Dow Chemical, USA) and the process conditions were: mold temperature 50 °C, injection temperature 200 °C, and injection flow rate 100 cm3/s.

Fig. 1. Geometry and finite element grid for the molded part There were 25 sets of design points created by DOE in each run. The reducing factor for move limits between two iterations was set to 0.5. In the first run, the entire length and width of the plate were set as the feasible domain, and the coordinates of the gate locations corresponding to the 25

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points and the maximum pressures based on finite element analyses at these gate locations are given in Table 1. The RSA of the maximum pressure distribution as a function of the gate coordinates is illustrated in the form of a contour plot in Fig. 2(a). Two distinct local minima along the centerline x2 = 40 mm are clearly visible. The multi-start SQP was applied on the RSA and a 99.9% certainty for a global optimum was achieved in 20 starts of initial guesses. The minimizer for the global minimum in the first run is (x1*, x2*) = (120.26 mm, 38.59 mm), and at this location the predicted maximum pressure is 21.34 MPa. Using this optimal coordinates as the gate location to perform a finite element analysis, the pressure distribution of the molded part at the end of fill is displayed in Fig. 2(b) and it attains the maximum pressure of 21.9 MPa on the edge of the gate. Table 1. Data set used to create the RSA in the first run x1 (mm) 0.00 37.50 75.00 112.50 150.00 0.00 37.50 75.00 112.50 150.00 0.00 37.50 75.00

x2 (mm) 0.00 0.00 0.00 0.00 0.00 20.00 20.00 20.00 20.00 20.00 40.00 40.00 40.00

Max. pressure (MPa) 32.973 29.944 29.405 24.282 30.978 30.624 27.149 27.208 22.963 30.224 28.994 24.463 22.815

x1 (mm) 112.50 150.00 0.00 37.50 75.00 112.50 150.00 0.00 37.50 75.00 112.50 150.00

x2 (mm) 40.00 40.00 60.00 60.00 60.00 60.00 60.00 80.00 80.00 80.00 80.00 80.00

Max. pressure (MPa) 20.034 27.630 30.072 27.453 27.262 22.902 30.115 32.385 29.859 29.821 24.500 30.931

After eight iterations, the optimization process seemed to have converged. The last (the 8th) set of RSA of the maximum pressure distribution as a function of the gate coordinates and the finite element analysis result using the optimal gate location are shown in Fig. 3. The minimizer for the global minimum in the last run is (x1*, x2*) = (94.20 mm, 39.77 mm), and at this location the predicted maximum pressure is 15.76 MPa (Fig. 3(a)). A finite element analysis gave the maximum pressure of 15.87 MPa occurred at the gate location (Fig. 3(b)). Compared to 22.82 MPa for the molded part with the gate located at the center (x1, x2) = (75 mm, 40 mm), the maximum injection pressure was significantly reduced with the gate located at the optimal position. This research proposed the use of higher order RSA to solve optimal gate location problems for injection molding. The multi-modal phenomenon, which can be more properly approximated by higher order RSA, can be demonstrated by performing finite element analyses with gate locations along the centerline (x2 = 40 mm). The maximum pressure at the end of fill for gates located along this centerline can be seen in Fig. 4. The multiple valleys and the sharp drop around x1 = 90 mm can cause a serious problem for the second order RSA, which are more widely used. Conclusions This research proposed an optimal gate location scheme for injection molding by using higher order response surface approximations and a modified sequential quadratic programming method for global optimization. With higher order RSA, the multi-modal phenomenon occurred in injection molding of a rectangular plate structure with two different thicknesses can be properly approximated. Global optimization was achieved by employing a multi-start SQP procedure. Since RSA, which are smooth functions, were constructed to represent the functional relation of the gate locations and maximum injection pressures, the proposed procedure guarantees a successful search of a global optimum. However, to ensure a better curve fitting result for RSA, as the iteration process proceeds, a reducing search domain with move limits are necessary. The numerical example has shown that an optimal gate location for the injection molding of the rectangular plate was found in just eight iterations, and the maximum injection pressure was reduced form 22.82 MPa for the model with the gate located at the center to 15.87 MPa at the optimal location.

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Fig. 2. (a) Contour plot of the RSA in the first run; (b) Finite element analysis result for the pressure distribution of the molded part using the optimal gate location in the first run

Fig. 3. (a) Contour plot of the RSA in the 8th run; (b) Finite element analysis result for the pressure distribution of the molded part using the optimal gate location in the 8th run

Fig. 4. Maximum pressure at the end of fill for gates located along the centerline (x2 = 40 mm) References [1] M. Zhai, C. Shen, An optimization scheme based on flow resistance to locate optimum gate of complex part, Journal of Reinforced Plastics and Composites. 24 (2005) 1559-1566. [2] G.E.P. Box, K.B. Wilson, On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society. B 13 (1951) 1-45. [3] R.H. Myers, D.C. Montgomery, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, John Wiley & Sons, Inc., New York, 1995. [4] B. Liu, R.T. Haftka, M.A. Akgun, Two-level composite wing structural optimization using response surfaces, Struct Multidisc Optim. 20 (2000) 89-96. [5] R.H. Myers, Response surface methodology – current status and future directions, Journal of Quality Technology. 31 (1999) 30-74. [6] B. Ozcelik, T. Erzurumlu, Comparison of the warpage optimization in the plastic injection molding using ANOVA, neural network model and genetic algorithm, Journal of Materials Processing Technology. 171 (2006) 437-445. [7] H. Kurtaran, T. Erzurumlu, Efficient warpage optimization of thin shell plastic parts using response surface methodology and genetic algorithm, Int. J. Adv. Manuf. Technol. 27 (2006) 468-472. [8] J.A. Snyman, L.P. Fatti, A multi-start global minimization algorithm with dynamic search trajectories, Journal of Optimization Theory and Applications. 54 (1987) 121-141.

CHAPTER 2: Optoelectronics and Optical Systems

Applied Mechanics and Materials Vols. 479-480 (2014) pp 133-136 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.133

Simulation of Broadband Transmission Photonic Crystal Waveguide Crossing with Linear Taper Yih-Bin Lin1,a, Rei-Shin Chen1,b , Ting-Chung Yu1,c, and Ju-Feng Liu2,d 1

Lunghwa University of Science and Technology, No.300, Sec.1, Wanshou Rd., Guishan, Taoyuan County, Taiwan (R.O.C.) 2

China University of Science and Technology, No. 245, Sec.3, Yen-Chiu-Yuan (Academia) Rd., Nankang, Taipei, Taiwan (R.O.C.)

a

[email protected], [email protected], [email protected], [email protected]

Keywords: waveguide crossing, photonic crystal, linear taper.

Abstract. A novel design of photonic crystal waveguide crossing with taper structure is proposed. Simulations are performed by finite-difference time-domain method. The results show the proposed design has both high transmission and low cross talk characteristics. The transmission band and low cross talk band can be tuned to match each other by adjusting the taper structure.. Introduction It is crucial to intersect waveguides in constructing integrated optical circuits, because complex system involving multiple waveguides and devices need to use chip area efficiently. Many designs of waveguide crossing are proposed in dielectric waveguide systems [1-3] and in photonic crystal systems [4][5]. For photonic crystal systems, the previous designs [4][5] although have low cross talk, but the transmission bandwidth is narrow because of their design with cavity structures. In this paper, we proposed a new design of waveguide cross for photonic crystal systems. By using linear taper structure, our design has broadband of high transmission and low cross talk as well. Simulation and Results The structure of the conventional waveguide crossing for two-dimensional photonic crystals is shown in Fig.1(a). The waveguide crossing consists of two line-defect waveguides crossing each other. The device is designed to let optical wave coming from the input end and propagating to the throughput end. If optical wave leaks to the side branches, it becomes cross talk which is the noise of the other channel.

Fig. 1. The conventional waveguide crossing structure. The red circles in Fig.1 are dielectric material with refractive index n=3.4. The white region between the red circles is free space with unit refractive index. The dielectric circles are periodically

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arranged to form rectangular lattices with period a and the radius of the rods is r=0.18a. Simulation is performed by FDTD method and a Gaussian beam is launched. The transmission of throughput, cross talk, and reflection of the conventional waveguide crossing shown in Fig.1 is simulated. The simulation results show that the transmission is about 0.3~0.4, the cross talk is greater than 0.2, and the reflection coefficient is about 0.2 while the normalized frequency fn=a/λ ranged from 0.37 to 0.43. Therefore, the conventional waveguide crossing is not practical because of its large cross talks and reflections.

Fig. 2. The proposed waveguide crossing with linear taper structure. In this paper, we proposed a new design of waveguide crossing with linear taper structures as shown in Fig.2. The taper structures are formed by shifting the rods at two sides of the waveguides. The blue circles indicate the shifted rods from their lattice positions. The linear taper has the width W and length L as shown in Fig.2. The four ports of the proposed waveguide crossing are identical and have the same widths and lengths. The proposed waveguide crossing is simulated by FDTD method for L=7a and W=2.8a, 2.9a, 3.0a, 3.1a, 3.2a, and 3.3a. The simulation results of the proposed waveguide crossing are shown in Fig.3. For the case of L=7a and W=2.8a in Fig.3(a), the transmission spectrum has a wide transmission band for transmission efficiency greater than 0.8. The central frequency ft of the transmission band is 0.4025 for W=2.8a. While W is increased to 2.9a, we found that the transmission band is shift toward the lower frequencies as ft =0.4129. For W=3.0a, the transmission band moves further toward lower frequencies and the central frequency ft of the transmission band is 0.4060. For W=3.1a and W=3.2a, The central frequency ft of the transmission band are 0.4003 and 0.3952, respectively as shown in Fig.3(b). The cross talk of the proposed waveguide crossing is also analyzed from the simulation results. The cross-talk spectra show that there exists a wide frequency band for cross talk smaller than -20dB, and the cross-talk spectra each has a dip at frequencies fC's. Unlike the central frequencies in transmission spectra, the dip frequencies fC's shift toward higher frequencies as the taper width W is increased from 2.8a to 3.2a. The dip frequencies fC's are 0.4005, 0.4006, 0.4010, 0.4023, and 0.4049 as the taper width W is increased from 2.8a to 3.2a. The relationship of the central frequency ft ,the dip frequency fC , and the low-reflection frequency fr with respect to the linear taper width W are shown in Fig.4. As the linear taper width W increases, the high-transmission and low-reflection band moves toward the lower frequency, but the low cross talk

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frequency movers tower the higher frequency. The results show that the proposed waveguide crossing has both broadband transmission and low cross talk characteristics if the linear taper width W is carefully designed.

Fig. 3 (a) The transmission spectra of the proposed waveguide crossing with linear taper for taper width W= 2.8a, 2.9a, and 3.0a.

Fig. 3 (b) The transmission spectra of the proposed waveguide crossing with linear taper for taper width W= 3.1a, 3.2a, and 3.3a.

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Fig. 4 Central frequency ft of transmission band, dip frequency fC of cross-talk spectrum, and low-reflection frequency fr versus linear taper width W. Conclusions A new design of waveguide crossing with linear taper structure for tow-dimensional photonic crystals is proposed. The proposed design has high transmission efficiency with broad bandwidth. The proposed design also has very low cross talk. By adjusting the linear taper width of the taper structure, the central frequency of transmission band can match the dip frequency of the cross talk spectrum. The proposed waveguide crossing will be useful for compact photonic crystals circuits in the future. References [1] H. Liu, H. Tam, P.K.A. Wai and E. Pun: Optics Communications, Vol. 241, (2004), p.99. [2] T. Fukazawa, T. Hirano, F. Ohno and T. Baba: Japanese Journal of Applied Physics, Vol. 43, (2004), p.646. [3] F. Shinobu, Y. Arita and T. Baba: Electronics Letters, Vol. 46, (2010), p.1149. [4] S.G. Johnson, C. Manolatou, S. Fan, P.R. Villeneuve, J.D. Joannopoulos and H.A. Hous: Optics Letters, Vol. 23, (1998), p.1855. [5] S.F. Mingaleev, M. Schillinger, D. Hermann and K. Busch: Optics Letters, Vol. 29, (2004), p.2858.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 137-142 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.137

A Study on Measurement of Photoplethysmograph Using a Smartphone Camera Jae Hoon Jeong1,a, Sung Min Kim 1,b, Sung Yun Park1,c and Sangjoon Lee 1,d 1

Department of Medical Biotechnology, Dongguk University-Seoul, 100715 Seoul, South Korea a

[email protected], [email protected], [email protected], [email protected]

Keyword: Photoplethysmography, Bio-Signal Sensor, m-Health, CMOS-Camera

Abstract. In this study, we proposed a method for measuring photoplethysmographic using a smartphone camera. A development algorithm is consists 6 procedures. The first is to convert RGB to Gray level from a camera image, the second is to detect ROI from image, the third is to extract photoplethysmography signal from a camera image, the fourth is to filter baseline, and the last is to oversample procedure using cubic spline interpolation. The proposed algorithm has been tested using several smartphone with a person and which can effectively acquire person’s PPG signal at any situation. We supposed that the proposed algorithm can easily adapt for a smartphone m-health system. Introduction Plethysmography has been largely used to measure a volume change of blood vessel and a velocity of blood when blood is pumped from the heart and reaches a limb. Its wave form is similar to an arterial pressure. The measuring spots are the limb’s fingertip and toe end, radial artery and ear regions. For the Plethysmography, an ultrasound, photo and laser are used, but a photo-diode has been currently well used because of its easy implementation and cheap price. The Plethysmography measurement using Photo-Diode is called ‘PPG(Photoplethysmography)’ and it can produce the wave form by transmitting and reflecting a light source with 660nm∼1,000nm wavelength at the measurement position. For applications, it has been well used to diagnose arteriosclerosis by calculation of blood vessel tension because it can measure the change in blood flow velocity through volume change of blood vessel. When the blood vessel gets stiff by arteriosclerosis and blood is carried from the heart to the blood vessel, an expansion of blood vessel is small, a pressure in the blood vessel increases and the blood flow increases. It is called PWV(Pulse Wave Velocity)[1]. On the contrary, when the blood vessel softens, the expansion of blood vessel is big and the blood flow velocity slows. Also, the pulse oxygen saturation (SPo2) in blood vessel can be measured through observing a color change when the oxygen of Hemoglobin is included, by analyzing another wavelength’s light source (Red:660nm, Infrared:940nm). As it has the similar wave form to arterial blood pressure, the study of measuring a continuous blood pressure in non-invasive form has been briskly conducted. Plethysmograph using the existing light source has the simple measuring method, but has a problem of the wave form’s reproducibility by testee’s movement, measuring finger position, finger’s temperature and measuring posture even though its wave becomes highly significant. Accordingly, in order to solve such problem, the study of measuring PPG through CMOS Camera has been conducted. PPG can be measured through noncontact measurement by using an external light source. Also, the PPG measuring methods using flash source of Smartphone and CMOS Camera have been recently studied, and a small number of u-health-relevant applications using it have been produced and sold. However, they have the different measuring method and algorithm of extracting the PPG signal from image signal, so that the performance has not been accurately evaluated. This study is intended to suggest the algorithm of measuring the PPG signal from images taken from CMOS Camera, and to conduct the evaluation of PPG signal measured by conventional method, the evaluation of PPG signal by similarity and ROI range, the evaluation of PPG signal measured by CMOS Camera of smartphone, and the evaluation of PPG signal by type light source.

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Material and Method A. Multi Parameter bio-signal measurement sensor The PPG measuring method using CMOS Camera was first introduced by Kenneth Humphreys[2], and is divided into the method of measuring at 40cm and longer distance by noncontact measurement and the method of measuring by contact measurement as shown in Fig. 1 (a)(b), respectively. Both methods need the light source of 660nm~1,000nm, and the non-contact measurement can measure the PPG signal at a certain position through ROI extraction. However, if the testee’s finger moves, ROI must be calculated again and has lower integrity of signal than the contact measurement. In this study, the PPG signal is measured by method of contacting the fingertip to CMOS Camera Lens is used.

(a)

(b)

Figures. 1 Sensor measurement concept (a) CMOS Camera Lens (b) Contact measurement method

B. Algorithm Block Diagram

Figures. 2 Algorithm Block Diagram

Fig. 2 shows the whole algorithm block diagram and indicates six steps from images taken from CMOS Camera Sensor to the obtainment of PPG signal. Step 1 is a process of converting the Color RGB signal into Gray Level. Step 2 is a process of distinguishing the image region which applies the PPG signal most in the converted gray level image as the ROI section is detected. In Step 3, the PPG signal is actually extracted from the operated ROI coordinate, and the data is actually extracted with the PPG signal from the ROI image in Step 4. In Step 5, the high pass filter of 0Hz ~ 0.1Hz signal is made to reduce an impact of testee’s movement or external light interference on CMOS Camera, or an impact of low frequency signal section’s baseline drift by mixing the testee’s respiration signal. In Step 6, oversampling using the Cubic Spline Interpolation technique is done to synchronize the sampling rate of actual PPG signal because the image is 25-Frame per second.

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C. Conversion to Gray Scale and Region of Interesting Operation As shown in Fig. 3 Plethysmography measurement by CMOS Camera is possible when it measures the change of brightness by each frame of images from the camera. Each pixel of image is composed of total 24-Bit( R, G, B)’s color images, and the color images are re-configured to the gray scale images in order to improve the change of brightness and the image processing velocity. As the method of converting into the gray scale, there are Luma method which is the most-used ITU-R BT.601 Standard, the Arithmetic mean method, HSV(Hue Saturation, Value), and BCH(Brightness, Chroma, Hue). In this study, HSV method which expresses the brightness most was selected. The evaluation of PPG signal’s efficacy by representative gray scale conversion method will be explained and discussed in Fig. 3.

Figures. 3 ROI Operation

When the color image is converted into the gray scale, the region which applies the PPG signal most is produced according to the camera flash’s light diffusion degree of Smartphone which is touched by fingertip as shown in Fig. 1(b). This section is called ROI(Region of Interesting). After acquiring images for 2 seconds to extract this region, the ROI region is extracted by methods defined in the below Eq. 1, Eq. 2, Eq. 3, Eq. 4, Eq. 5. , ,,

(1)

, ,

, , ,

,,

,

, ,

,, ,

,

(2)

(3) ,

(4) (5)

In Eq. 1, X and Y means a resolution of all pixels on X-axis and Y-axis of video, and Div and Div means a number of sectors to be divided from all images. X and Y means the number of x-axis and y-axis’s pixels of sector to be divided from each x-axis and yaxis’s all pixels respectively. In Formula 2, M , , means each sector’s mean value of k(th) image frame, and P x, y, k means the pixel value of gray scale on each x-axis and y-axis of k(th) image frame. Formula 3 and 4, as the process of measuring the real ROI region, is the formula of calculating the maximum value for 2 seconds (48-Frame) after calculating the mean value of each sector in the present frame and the previous frame. In Formula 4, I , J means the sector’s coordinate and becomes the ROI region to be searched.

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D. ROI to PPG Data Conversion When the ROI region happens by Eq. 1, Eq. 2, Eq. 3, Eq. 4, Eq. 5 in 2-second image, the PPG signal is extracted in the same way as Eq. 6 in the selected ROI region. In Eq.6, means the PPG signal in k(th) frame from the Smartphone CMOS Camera, and is calculated with the mean values of pixels in ROI region of the sector of I(th) on the x-axis and J(th) on the y-axis in k(th) Frame.

;

∗

∗

, ,

(6)

+

(7)

Signal from Eq. 6 can be converted to the form that the camera focus function ; and by human respiration are convoluted in the ideal PPG signal and the noise is added in the impact by light , as shown in Eq. 7. A distortion of Baseline is made due to ; , as shown in Fig. 4 (a). In order to reduce such impact, the Baseline Filter is used in the same way as Eq. 8 and 9. Eq.8 means 2K point Moving Average Filter and indicates the whole points of signal. Accordingly, after Eq. 8, the Baseline of is expressed as shown in Fig. 4. In Eq. 9, Base i means the wave form that is swapped on the basis. As indicated and are added, the effect of Baseline Filter can be produced. In in Eq. 10, when Eq.10, PPG i means the baseline filtered-PPG signal. +

where,

≤
70%) and a wide acceptance angle (>1o). The acceptance angle θ90% is defined as the incidence angle corresponding to 90% of the maximum optical efficiency η at normal incidence. Similarly, the definition of acceptance angle θ50% is the incidence angle corresponding to 50% of the maximum optical efficiency η at normal incidence. In this study, the basic design parameters of a two-reflector solar concentrator are determined based on the formulae developed by Gordon et al. [6, 9, 10]. Ray-tracing simulation is then applied to predict the optical performance of the concentrator with various types of SOE. For each type of SOE, a parametric-design process is performed to achieve optimum design parameters of the SOE. Finally, the predicted performances of the two-reflector solar concentrator with optimum SOE designs are presented and discussed. Two-Reflector Solar Concentrator The two-reflector solar concentrator comprises a primary mirror (M1), a secondary mirror (M2), a solar cell and an SOE (Fig.1). The initial design parameters of the concentrator are as follows: the diameter of the M1 = 120mm, the diameter of the central hole of M1 = 20mm, and the size of the square solar cell is 5.5mm by 5.5mm. In addition, the geometric concentration ratio (GCR) is 373x. The other preliminary design parameters of the two mirrors are then determined based on the equations proposed by Gordon et al. [6, 9, 10]. After applying ray-tracing simulation to evaluate the optical performance, the selected two-reflector concentrator is non-coplanar (Fig.1), and the numerical aperture (NA2) of M2 is 0.25. Figure 1 illustrates the design and dimensions of the two-reflector concentrator with an SOE.

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Fig. 1. Illustration and dimensions of the two-reflector solar concentrator SOE of Pyramid shape Three types of SOE are considered to increase the acceptance angle of the two-reflector solar concentrator, including (1) Type I – Refractive pyramid-shaped SOE, (2) Type II - Reflective pyramid-shaped SOE, and (3) Type III - Refractive Cone-shaped SOE, as depicted in Fig. 2(a)~(c), respectively. In this study, the transmittance of refractive SOE is assumed as 96%, and the reflectance of reflective SOE is assumed as 98%. Fig. 2(d) depicts the two major design parameters of SOE, parameter B (related to the top entrance area) and the height H. Notably, parameter B represents the edge length of the top area for the pyramid-shaped SOEs (Fig. 2(a), (b)), and it denotes the diameter of the top area for the cone-shaped SOE (Fig. 2(c)). For the pyramid-shaped SOEs, the dimension of the bottom area is the same as the solar cell (5.5mm x 5.5mm); while for the cone-shaped SOEs, the diameter of the bottom area is 5.5mm. The effects of the design parameters, H and B, on the improvement of the optical efficiency of the two-reflector concentrator are studied by ray-tracing simulations. A parametric design process for each type of SOE is performed to attain preliminary optimum design parameters of the SOE. Finally, the simulation results of selected optimum designs of SOE are compared and discussed. (a)

(b)

(c)

(d)

Fig. 2. Illustration of SOEs: (a) Refractive-Pyramid (b) Reflective Pyramid, (c) Refractive-Cone, (d) Basic parameters, SOE I: Refractive Pyramid. Fig. 3 (a) and (b) depict the effects of design parameters B (edge length of top area) and H (height) of SOE I on the optical efficiency of the solar concentrator when the incidence angle is 0o (normal incidence) and 1o, respectively. As shown in Fig. 3(a), when H (height) is fixed, the optical efficiency under normal incidence decreases as B (top edge length) increases. According to the simulation results shown in Fig. 3(a) and 3(b), feasible parameter sets (H, B) are chosen as (10, 12), (13, 12), (15, 12) and (18, 12) for further investigation. (a)

(b) 80

84 83

H=10

82

H=13

81

H=15

80

H=18

79

Optical Efficiency (%)

Optical Efficiency (%)

85

70 H=10

60

H=13

50

H=15

40

H=18

30 20

78 8

10

12

14

Top Edge Length B (mm)

16

18

8

10

12

14

16

18

Top Edge Length B (mm)

Fig. 3. Effects of parameters of the refractive-pyramid SOE on the optical efficiency: (a) incidence angle = 0o (normal incidence), (b) incidence angle = 1o

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SOE II: Reflective Pyramid. Fig. 4 (a) and (b) show the effects of design parameters B and H of SOE II on the optical efficiency of the solar concentrator when the incidence angle is 0o (normal incidence) and 1o, respectively. Fig. 4(a) indicates that the optical efficiency under normal incidence decreases with an increase of H or B, except for the case of H=13 and B=16. However, Fig. 4(b) reveals that the optical efficiency of SOE II is lower than 70% when the incidence angle is 1o. This phenomenon will limit the application of SOE II. (a)

(b) 88

H=10

84

H=13 H=15

82

H=18

Optical Efficiency (%)

Optical Efficiency (%)

80 86

80

70 H=10

60

H=13 H=15

50

H=18

40 30 20

78 8

10

12

14

16

18

8

10

12

Top Edge Length (mm)

14

16

18

Top Edge Length (mm)

Fig. 4. Effects of parameters of the reflective-pyramid SOE on the optical efficiency: (a) incidence angle = 0o (normal incidence), (b) incidence angle = 1o Discussion of Pyramid-Shaped SOE. Comparing Fig. 3(b) and Fig. 4(b), it is found that a refractive pyramid SOE generally lead to a higher optical efficiency than a reflective pyramid SOE when the incidence angel is 1o. This implies that the improvement of acceptance angle of the concentrator is better by using SOE I than SOE II. Therefore, the feasible parameter sets of SOE I are adopted for the two-reflector concentrator and the optical efficiency under various incidence angles are simulated and depicted in Fig. 5. Among the 4 feasible designs of SOE I, the 2 designs with parameter sets of (H=13, B=12) and (H=15, B=12) have been chosen as preliminary optimum designs because their optical efficiencies are stable and remain higher than 60% even at incidence angles of 1.2 o.

Optical Efficiency (%)

90 80 H=10 B=12 70

H=13 B=12 H=15 B=12

60

H=18 B=12

50 40 0

0.2

0.4

0.6

0.8

1

1.2

1.4

Incidence Angle (degrees)

Fig. 5. Optical efficiency of two-reflector solar concentrator with a refractive-pyramid SOE under various incidence angles SOE of Cone Shape SOE III: Refractive Cone. Fig. 6 (a) and (b) illustrate the effects of design parameters B (diameter of top area) and H (height) of SOE III on the optical efficiency when the incidence angle is 0o (normal incidence) and 1o, respectively. Fig. 6 (a) reveals that the optical efficiency under normal incidence decreases when the height (H) of the SOE III increases. In the contrary, under an incidence angle of 1o, a higher SOE III will result in a better optical efficiency (Fig. 6 (b)). According to the parametric analyses of SOE III (Fig.6), the feasible parameter sets (H, B) are chosen as (10, 12), (13, 12), (15, 12) and (18, 12) for further investigation. Fig. 7 illustrates the optical efficiency of the concentrator with the 4 feasible designs of SOE III under various incidence angles. Among the 4 feasible designs of SOE III, the design with parameter sets of (H=18, B=14) is chosen as a preliminary optimum design of SOE III because of its higher

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optical efficiency at large incidence angles. Comparing Fig. 5 and Fig.7, it is observed that generally the optical efficiency of concentrator with SOE III drops more rapidly than the concentrator with SOE I when the deviation of incidence angle increases. (a)

(b) 80

86

70

84

Optical Efficiency (%)

Optical Efficiency (%)

85

83 82 81

H=10

80

H=13 H=15

79 8

10

12

14

16

50 40

H=10 H=13

30

H=18

78

60

H=15 H=18

20

18

8

10

12

Diameter of top area (mm)

14

16

18

Diameter of top area (mm)

Fig. 6. Effects of parameters of the refractive-cone SOE on the optical efficiency: (a) incidence angle = 0o (normal incidence), (b) incidence angle = 1o 90

Optical Efficiency (%)

80 70 60 H=10 B=12

50

H=13 B=12

40

H=15 B=12 H=18 B=14

30 0

0.2

0.4

0.6

0.8

1

1.2

1.4

Incidence Angle (degrees)

Fig. 7. Optical efficiency of two-reflector solar concentrator with a reflective-cone SOE under various incidence angles Discussion The optical performances of the solar concentrator with the 2 optimum designs of SOE I and 1 optimum design of SOE III are compared and summarized in Fig. 8 and Table 1. Fig. 8 shows the optical efficiency of the concentrator with the 3 SOEs under various incidence angles. Table 1 summarizes the design parameters of the three optimum SOE designs and the resulting optical performances of the two-reflector concentrator, including the optical efficiencies at incidence angles of 0o and 1o, and acceptance angles θ90% and θ50%. According to Table 1 and Fig. 8, the two-reflector concentrator along with the optimum refractive-pyramid SOE Q1 (with height H=13mm and edge of top area B=12mm) exhibits a highest optical efficiency of 84.24% than the other two optimum designs of Q2 (82.83%) and Q3 (82%) at normal incidence. In addition, the solar concentrator with SOE Q3 exhibits a highest corresponding acceptance angle θ90% of 1.06 o, while the acceptance angles θ90% for Q2 and Q1 are 1.03 o and 1.00o, respectively. 90

Optical Efficiency (%)

85 80 75 Q1

70

Q2

65

Q3

60 55 0

0.2

0.4

0.6

0.8

1

1.2

1.4

Incidence Angle (degrees)

Fig. 8. Optical efficiency of two-reflector solar concentrator with 3 optimum SOEs

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Table 1 Optical performance of the two-reflector solar concentrator with 3 optimum SOEs θ 90% θ 50% η opt (at 0 ° ) η opt (at 1° ) H(mm) B(mm) SOE Q1 Q2 Q3

Refractive Pyramid Refractive Pyramid Refractive Cone

13

12

84.24%

75.64%

1.00

1.39

15

12

82.83%

75.00%

1.03

1.54

18

14

82.00%

74.82%

1.06

1.51

Conclusions This study explores the optical performance of a non-coplanar, two-reflector solar concentrator along with various designs of SOE by ray tracing simulation. Parametric design process is applied to determine preliminary optimum parameter sets of SOE. Three preliminary optimum SOE designs, Q1, Q2 and Q3, have been determined and the resulting optical performances are compared in this study. A large acceptance angle (over 1o) and high optical efficiency η (over 80%) under normal incidence have been achieved with the designed concentrator using any of the three optimum designs of SOE. More specifically, the simulation results reveal that the optimum SOE design of Q1 leads to a highest optical efficiency of 84.24% at normal incidence, while the optimum SOE design of Q3 results in a best acceptance angle θ90% of 1.06o. A better optimization approach will be utilized in the future for further improvement of the SOE design. Acknowledgement The authors would like to thank the National Science Council of the Republic of China for financially supporting this research. References [1] A. Luque, S. Andreev, Concentration Photovoltaic, Springer Verlag, Berlin, 2007. [2] R. Winston, J.C. Miñano, P. Benítez, Nonimaging Optics, Elsevier-Academic Press, New York, 2005. [3] C. F. Chen, C. H. Lin, H. T. Jan, A solar concentrator with two reflection mirrors designed by using a ray tracing method, Optik, 21, (2008) 1042-1051. [4] V. M. Andreev, V. A. Grilikhes, A. A. Soluyanov, E. V. Vlasova, M. Z. Shvarts, Optimization of the secondary optics for photovoltaic units with fresnel lenses, Proc. of the 23th European Photovoltaic Solar Energy Conference, (2008) 126-131. [5] M. Hernández, A. Cvetkovic, P. Benítez, J. Miñano, High-performance Köhler concentrators with uniform irradiance on solar cell, Proc. of SPIE, 7059 (2008) [6] J. M. Gordon, D. Feuermann, Tailored imaging optics for concentration and illumination at the thermodynamic limit, Proc. of SPIE, 5529 (2004) [7] M. McDonald, S. Horne, G. Conley, Concentrator design to minimize LCOE, Proc. SPIE, 6649 (2007) [8] S. Horne, G. Conley, J. Gordon, D. Fork, P. Meada, E. Schrader, T. Zimmermann, A Solid 500 Sun Compound Concentrator PV Design, Photovoltaic Energy Conversion, IEEE 4th World Conference, 1 (2006 ) 694–697 [9] J. M. Gordon, D. Feuermann, Optical performance at the thermodynamic limit with tailored imaging designs, Appl. Opt. 44 (2005) 2327-2331 [10] N. Ostroumov, J. M. Gordon, D. Feuermann, Panorama of dual-mirror aplanats for maximum concentration,” Appl. Opt. 48 (2009) 4926-4931.

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Integrated Multi-Object Taguchi method with Optical Design for Contact Lenses Chih-Ta Yen1,a, Ing-Jr Ding1, Hsu-Chih Cheng2, Jhe-Wen Ye1,b, and Jyun-Min Shih1,c 1

Department of Electrical Engineering, National Formosa University, Yunlin, Taiwan

2

Department of Electro-Optics Engineering, National Formosa University, Yunlin, Taiwan a

b

c

[email protected], [email protected], [email protected]

Keywords: Optical design, Taguchi methods, Principal component analysis, Optimization, contact lenses

Abstract. The multi-object Taguchi method of contact lens design for myopia and astigmatism eyes was proposed. With two spherical surfaces assembled in the optical system, the design could take advantage of compacting overall volume size. But in this design, the value of spherical aberration (SA) at wide radius of contact lenses seems lower. If we corrected the design to improve the value of SA, coma aberration (TCO) value would become lower relatively. In this study, we integrated the Taguchi method and principal component analysis (PCA) to optimize the multiple quality characteristics (SA and TCO) of the contact lenses. With the combination of the methods, a set of optimum design parameters was well selected to balance the values of SA and TCO that improve the SA 25.63%, and TCO 91.88%. It was concluded that the integration of the Taguchi method and PCA succeeded in optimizing the SA and TCO values, and the contact lenses could be well designed without sacrificing system performance. Introduction The main issue of the eye naturally occurring aberration phenomenon, curvature of the eye is not the spherical diameter equidistant, careful observation of the cornea and the lens curvature of the eye of the more prominent eye central, surrounded by relatively flat, this way, the light entering the eye elapsed since the refraction angle of refraction, will be showing a certain degree of aberration [1]. This study should assist optical designers in further optimizing contact lenses (myopia is 550 degrees and astigmatism is 175 degrees) after normal optimization by current optical software, in order to achieve its theoretical maximum performance. The Taguchi method for the design parameters [2] of the contact lenses is introduced in this research to efficiently eliminate third-order aberrations, such as spherical aberration [3]. The Taguchi method has been successfully developed to optimize and analyze design processes with static and dynamic characteristics [4]. The Taguchi method can only be applied to a single performance quality characteristic [5]. The principal component analysis (PCA), a useful statistical technique, was applied to examine the relationships between a given data set of multiple performance characteristics (MPC) to improve the performance of the system. With the aid of PCA,

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the principal components and their explanatory power could be further integrated as a single quality characteristic for the MPC optimization of the lens [6, 7]. Methodology of Optical Design for Contact Lenses The following steps are taken to design contact lenses. First, the design specifications should be given in accordance with the design requirements. Second, in compliance with the design specifications, Liou & Brennan eye model was constructed by the optical emulation software Code V. Third, we optimized the lens design by applying the necessary restrictive conditions. Finally, the initial design of the contact lenses was completed. Table 1 shows the design specifications of the contact lenses. The aspheric surfaces are employed in front and rear lens [8]. The contact lenses layout is presented in Figs. 1. Table 1. Lens specifications design data of contact lenses. Initial Conditions of Design The radius of contact lenses 8.6 [mm] The thickness of contact lenses The index of refraction

0.04 [mm]

The semi-aperture of contact lenses

7.3 [mm]

The coefficient for the quadratic surface

0

1.489

Fig. 1. Lens layout Theory and formulas In this study, Taguchi method and the PCA was employed to optimize the performances of the contact lenses. The Taguchi method The Taguchi method is a powerful experimental design tool developed by Taguchi and Konishi [9] for solving the engineering problems of optimizing the performance, quality and cost of a product or process in a simpler, more efficient and systematic manner than traditional trial-and-error processes.

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Table 2. Third-order aberration of initial design Third-order aberration value Spherical aberration (SA)

-0.032433

Tangential coma (TCO)

0.037380

Tangential astigmatic (TAS)

-0.494827

Sagittal Astigmatic (SAS)

-0.439797

Petzval (PTB)

-0.412282

Distortion (DST)

-0.321980

Taguchi method uses an orthogonal array to execute experiments and to analyse results. Orthogonal arrays consist of inner and outer columns, with the former designated the control factors while the latter is named the noise factors. In general, the performance of the contact lenses is governed by five control factors, each with three level settings. Accordingly, the Taguchi trials were configured in an L18 orthogonal array. The control factors and three levels were listed in Table 3. Table 3. Control Factors and their levels Control factors

Levels 2 8.6 mm

3 8.7 mm

A

The Radius of Contact Lenses

1 8.5 mm

B

The Thickness of Contact Lenses

0.03 mm

0.04 mm

0.05 mm

C

The Index of refraction

1.434

1.489

1.49

D

The Semi-Aperture of Contact

7

7.1

7.2

E

The coefficient for the quadratic surface

0

-0.05

-0.1

The quality of the design solution obtained from each run in the orthogonal array is evaluated using a signal-to-noise (S/N) ratio. Depending on the experimental objective, different quality characteristics may be pertinent. In the Taguchi methodology, the quality of any particular design solution is quantified using a ratio. The form of this ratio depends on the particular aspect of the product or process being optimized, and can be generalized as either “nominal is best,” “smaller is better,” or “larger is better” [10]. In the current Taguchi experiments, the objective is to reduce the spherical aberration and coma aberration. Consequently, the success of any factorial combination in reducing the spherical aberration and coma aberration is evaluated using the smaller-the-better ratio. Ni y2 Smaller the better： SN i = −10 log(∑ i ) (1) i =1 N i The principal component analysis (PCA) approach More than one correlated quality characteristic is usually considered in a lens design product. PCA is an effective means of determining a small number of constructs, which account for the main sources of variation in such a set of correlated quality characteristics [11].

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The experimental data after normalization are substituted in Matlab software and then we could obtain the correlation coefficient vector (R), eigenvalues, eigenvectors, proportion explained and principal component scores. The PCA of the MPC observed in the L18 experiments leads to three PCs with eigenvalues of 1.5575, 0.9634 and 0.4792. The first PC has an explanatory power of 51.9% for the total variance of the data set about the multiple performance characteristics. The eigenvectors can be treated as the weighting number such that the matrix of the three PCs. Conclusions The research concludes that the application of the Taguchi method, coupled with principal component analysis, is effective and efficient, and helps to improve the values of SA, TCO and MTF of the contact lenses and the performance characteristics have been successfully optimized to meet our expectations. By comparing the optimum parameter combinations confirmation test with the initial parameters, a decrease of 25.63% in SA and 91.88% in TCO significantly improves multiple quality characteristics of optical design. References [1] M. Nowakowski: Study of Ocular Aberrations Within a 10 deg Central Visual Field (MS., National University of Ireland, Galway 2011) p. 9. [2] C. Lin, C. Wu, P. Yang, and T. Kuo: Display Technology, Vol. 5 (2009) No. 8, p.323. [3] A. Pablo, G. Antonio, V. Eloy, G. Concepcion, C. Nicolas and B. EstherImage: OSA Technical Digest Series (Santa Fe, New Mexico, February 19, 1999). paper SuC4. [4] L.J. Yang: Journal of Materials Processing Technology, Vol. 113 (2001) No.1, p.521. [5] L.I. Tong, C.T. Su and C.H. Wang: International Journal of Quality and Reliability Management, Vol.14 (1997) Issue 4, p.367. [6] R.K. Tomita and S.W. Park: Chemical Engineering Journal, Vol.90 (2002) No.3, p.28. [7] L.I. Tong and C.T. Su: Total Quality Management, Vol.8 (1997) Issue 6, p.409. [8] W.A. Douthwaite: Contact Lens Optics and Lens Design (Butterworth-Heinemann, 2006), p. 27. [9] G. Taguchi and T. Yokoyama: Taguchi Methods: Design of Experiments (Dearborn, MI: ASI Press, 1993) [10] H.H. Le: Taguchi Methods Principles and Practices of Quality Design (Gau Lih, Taiwan 2008). [11] J.H. Sun, Y.C. Fang, B.R. Hsueh and W.C. Lai: Optics and Lasers in Engineering, Vol. 48 (2010) Issue 4, p.411.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 170-173 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.170

Improvement on Zhang's Camera Calibration Jihun Park1,a , and Sunghun Park2,b 1 Hongik

University, Dept. Computer Engineering, 94 Wowsanro, Mapo, Seoul, Korea 2 Myongji

University, Dept. Management Information Systems, 34 Geobookgolro, Seodaemoon, Seoul, Korea a

[email protected], b [email protected]

Keywords: moving camera calibration, quaternion, maximum likelihood estimation, root finding.

Abstract. This paper presents an improved initial guessing method for the famous Zhang's camera calibration method for a moving camera. Given three or more known points in a scene, we can compute initial guessing values for maximum likelihood estimation for varying focal camera calibration. This method is useful in structure from motion, which needs consecutive video camera calibration using a known camera distortion. Introduction This paper presents an improved initial guessing method for the famous Zhang's camera calibration method.[1] Zhang's method is restricted to a fixed focal camera calibration. But the method presented by this letter can handle varying focal length as well as fixed focal length portable cameras. Zhang's method consists of three stages of 2D to 2D homography matrix computation. For Zhang's calibration method, man-made grid pattern images are commonly used for camera calibration. But we can sometimes find right angle shapes or grid patterns with known side ratios in a real life scene. These patterns give clues for world coordinate points of target objects in a scene. In structure from motion, we get previously computed world coordinate points as well as corresponding image points. The proposed camera calibration is useful for a moving camera external parameter computation for the following adjacent scene which includes previously computed known points. Given three or more points provided in a scene, we can compute initial guessing values for maximum likelihood estimation using Newton's root finding algorithm for a nonlinear set of equations. Figure 1 shows an overview of our single stream video tracking. In the procedure, feature point extraction is provided by user. We have developed various phases related with camera calibration and 3D scene analysis. There are two kinds of feature points: one kind of points have 3D coordinate information, and the others points do not have 3D coordinate information but they do have correspondence information on two or more view images. Given feature points with 3D coordinate, the left side of figure 1 the first phase of computation is computing initial guessing values given three planar points on a single input image using Newton's root finding method, Using the computed guessing values, camera projection is done and checked with actual image. If there are mismatch, then camera parameters as well as lens distortion parameters are purturbed to find the best camera parameters which makes smallest disparity errors. This part of computation can be done using single input image as well as multiple images. The right side of figure 1 is computation process for two or more images. For this process, we do not know 3D coordinate information. But we know correspondence relation appearing on two or more images. Given feature points and correspondence relation, we compute undistorted images using guessed lens distortion parameters, and compute 3D ray vectors casted from various views. The shortest distance between rays are computed, and the middle point on the shortest distance is projected back on the image. The disparity between actual points on the image and projected intersection point is computed. The projection disparity errors are minimized using maximum likelihood estimation (called parameter optimization or nonlinear programming). As a result, we find an optimal set of camera parameters as well as lens distortion parameters. As a result, 3D coordinate information

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Corresponding 3D coord info

+ Extracted

+ Correspondence

Feature Points

Initial camera Parameters

171

relation

Undistort Image Rays Intersection

Projection Projection Disparity Disparity

+ N

Optimum?

N

Perturb Variables

Perturb Variables

Distortion

Y DONE

Fig. 1: Overview of camera calibration and 3D scene analysis of feature points with correspondence relation is computed, and these can be used for consecutive 3D scene analysis, such as structure from motion, in a video stream. Assumptions used in this paper are as follows: (1) we use only one moving camera, that is to say image distortion rate is the same for all images, (2) feature points computation and correspondence relation are provided as input. A camera scan a stationary target object to get two or more images of different views of the target object for 3D stationary scene analysis. Point information on the background stationary acene is accumulated through out the a video sequence while the target object coordinate points are computed for the stationary scene only, and they are used to track a moving object throught the entire video sequence. We need pixel position information on the tracked object as well as on the fixed environmental object. Algorithm for Camera Calibration Zhang's Algorithm for Camera Calibration. We try to use Zhang's notation[1] for a comparison purpose. For n images and m points, Zhang optimized following maximum likelihood estimation function Σni=1 Σm ˆ i (A, Ri , ti , Mj )∥2 (1) j=1 ∥mij − m where A the is camera intrinsic matrix, R is the camera rotation matrix, t is the camera translation vector, and m ˆ i (A, Ri , ti , Mj ) is the projection of 3D point Mj in image i. Every maximum likelihood estimation needs a set of initial guessing values. Zhang used following camera projection equation sm = A [ R t ]M

(2)

where s is the scale factor related with a camera focal length, m is the image point vector, and M is the 3D world point. Zhang uses complicated three stages to solve a 2D to 2D homography problem, but we used three known 3D world point and corresponding 2D image point relation for camera external parameter computation.

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Improved Initialization Computation. Projective camera model of equation (2) was actually implemented by using quaternion extended with translation. Quaternion q has a constraint of ∥q∥ = 1. s is set as a constant. We used four variables for quaternion while three variables for translation. For three known points, focal length is treated as a constant while focal length becomes a variable for four known points. Given three known points and a quaternion constraint, we have a total of seven equations with seven variables. We can derive a symbolic equation for the seven variables and seven nonlinear equations root finding. If four points are known, we solve a total of eight nonlinear equations with eight variables. For nonlinear equation solving, quaternion constraint equation must be included. We still need starting value guessing for solving Newton's root finding. Because the set of nonlinear equations are derived from taking camera picture, we can set a limited orientation direction used as a starting value set for root finding. In equation (2), we get two equations, in x and y, for a single known point. For a triangle shape in a grid pattern scene, an image point at a right angle becomes (0, 0, 0), while other two end tip points become (a, 0, 0) and (0, b, 0) where a and b is determined according to a known side ratio. For a grid pattern in a image, 3D point information can be retrieved similarly. At least three points computed from an early stage of structure from motion are needed for computing initial values of a consecutive camera calibation. Improved 3D Calibration Computation. For the initial value computation of maximum likelihood estimation, we assumed a 2D plane in 3D world, this is same as Zhang's method. This 2D to 2D homography part included in the likelihood estimation function is the same as equation (1). However, in order to increase camera calibration accuracy, 2D to 2D homography computation is not enough because we can get the same image with different 3D distance and focal length pair. Our actual maximum likelihood estimation uses extra 3D points that do not exist on the 2D plane used for initial guessing computation. Usually 3D position is not known for these extra points. Let us assume mk is a k-th projected point on an image. This point can be observed as a pixel from image i and image j denoted as mik and mjk respectively, but 3D position is not known for mk . From image i and image j we can assume two casted rays for mk , rayi from mik and rayj from mjk respectively. Ideally these ¯ kij be a mid point on a two rays should meet but usually they do not due to calibration error. Let M line which connects rayi and rayj in a shortest distance. If we have m 3D position known points and extra p points with 3D position unknown, our modified maximum likelihood estimation function is w1 Σni=1 Σm ˆ i (A, Ri , ti , Ml )∥2 l=1 ∥mil − m p ¯ kij )∥2 +w2 Σk=1 Σni=1 Σnj=i+1 ∥mik − m ˆ i (A, Ri , ti , M

(3)

where w1 and w2 are weight factors. These values depend on m and p. We used seven variables for camera position and orientation, one variable for a varying focal length, four variables for lens distortion and five variables for camera intrinsic matrix. For n input images, we used (8n + 9) variables. We could reduce the number of variables by using quaternion. The number of variables heavily affect the performance of maximum likelihood estimation. We used GRG2[2] to implement maximum likelihood estimation, called parameter optimization. Experimental Results and Conclusion For the camera calibration, Zhang's method[1] requires at least two images, while the method presented by this paper only requires a single image. But for an accurate camera calibration, we need at least two images to handle extra 3D points with unknown 3D positions. In order to demonstrate that our camera calibration works correctly, we have generated various 3D volume reconstruction from silhouette. Because we can symbolically derive equations needed for Newton's root finding method, the initial guessing value computation can be done faster if we derive inverse matrix symbolically in advance. Because the suggested maximum likelihood estimation includes non-planar points, the calibration is more accurate. All codes were written in C programming language. Input images were taken using

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Fig. 2: The three dimensional volume reconstructions after camera calibration and 3D scene analysis.

IXY810 and IXUS210 portable digital cameras. We have provided background eliminated images as well as feature point correspondence. Figure 2 shows various 3D volume reconstructions including a human hand reconstruction which uses three known computed points without any implied 3D position information, for camera calibration. Other input images contain clues for 3D positions in the scenes. Acknowledgements This work was supported by 2013 Hongik University Research Fund. References [1] Z. Zhang, "A Flexible New Technique for Camera Calibration," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no 11, pp. 1330-1334 (2000) [2] L. S. Lasdon and A. D. Warren and A. Jain, and M. Ratner, "Design and testing of a generalized reduced gradient code for nonlinear programming," ACM Trans. Math. Software, vol. 4, no. 1, pp. 34-50 (1978)

Applied Mechanics and Materials Vols. 479-480 (2014) pp 174-178 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.174

Video Matching by One-Dimensional PSNR Profile Shi-Wei Lo National Center for High-performance Computing, No. 7, R&D 6th Rd., Hsinchu Science Park, Hsinchu City, Taiwan, R.O.C. [email protected] Keywords: Video matching, Similarity measuring.

Abstract. This paper addresses a compact framework to matching video sequences through a PSNR-based profile. This simplify video profile is suitable to matching process when apply in disordered undersea videos. As opposed to using color and motion feature across the video sequence, we use the image quality of successive frames to be a feature of videos. The PSNR quality is featured as a video profile rather than the complex visual information analysis. The experimental results show that the proposed approach permits accurate of matching video. The performance is satisfactory on determine correct video from undersea dataset. Introduction The amount of digital videos are generated rapidly and added into digital libraries every day. The need for management of this content by effective techniques such as duplicated detection, copy detection and retrieval are currently important. In the video retrieval, the primary technique is the similarity measuring of visual information between videos. Recently, many researchers focused on extracting the color and motion information that across frames to form a descriptor for video matching. In this paper, a compact framework for video matching is proposed that employ the PSNR (Peak Signal-to-Noise Ratio) quantization to represent a video as a serial profile. Video retrieval is mainly performed in the content-based video matching technique. The techniques for content-based video retrieval relied on the feature extraction of object from its color and motion information. Many researchers already looked into the problem of video retrieval. However, the complex content analysis demands more computational effort to determine the essentiality features of objects in video sequences. Moreover, the features extracted from the relevance of motion trajectory are usually applied on the specific video that contains evident moving objects [1, 2]. Ke et al. presented a semantic query by created the temporal frequent pattern tree [2]. They are using a mixture of Gaussians model to detect the moving objects and then apply tracking to obtain the motion trajectories. These trajectories are used to build the motion events that represent the videos by a temporal frequent pattern tree. Each event have been annotated and used for the future queries. Basharat et al. used interest point trajectories to generate the video spatiotemporal volumes. The point trajectories are generated by Scale-invariant feature transform then mixed with color, texture and motion features to represent a video as a volume. The Earth Mover’s Distance approach were employed for the matching of volume features. In this field of research, few approaches used motion information that relies on evident moving objects and predictable planar trajectories. These approaches are also limited due to the adverse image quality, large motion, random motion, deformed objects and disarray or unstructured scenes. For example, these video usually contains driving car, floating ship, walking human, takeoff plane, etc. In these cases the motion trajectory can be easy to extract and used to matching the trajectory of object in other videos. Otherwise, for enhancement, color information is also couple with motion trajectory to apply on the video matching process. However, in the field of undersea video, the random motion trajectory of many moving objects and the blurred correspondence of color that cause fail to the content-based feature extraction. There still remains a difficult problem that to design a simple descriptor for the disarray and unstructured scene of widespread field.

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Therefore, a new approach that employs the PSNR as a video profile is proposed in this paper, the video profile includes the dynamic diversity of video sequences from the PSNR quantization. The feature profile of video are used to measuring the similarity within video matching process. The proposed video matching process is mainly followed in two steps as follows sections: (1) PSNR Profile : extracting the PSNR profile from video sequences to form a profile to represent the videos (2) Video Matching : measure the similarity of features of profile then retrieve the most similar video. This paper presents a PSNR profile to characterize the video clips and search the query video by matching process. After these the matching process, the most similar video from database are retrieved. This approach does not extract any region correspondence of color and motion information from video frames but using the frames’ PSNR factor within video sequence to characteristic a video profile. The results of this experiment clearly showed that this method achieved the good accuracy for video matching process. Video matching framework The purpose of this paper was to establish the profile of video that used to deal the matching process between query video and the video database. There are two steps for video matching framework: (i) Producing the video profile by frame-based PSNR quantization. (ii) Evaluating the similarity of profile for video matching. Those two steps was illustrated to the following respectively. A. PSNR Profile PSNR is most commonly used to assess quality of image after the lossy compression coding. PSNR is an approximation matrix to human perception of reconstruction quality when comparing efficiency of compression codecs. Generally, the higher PSNR factor express that the higher quality of reconstruction, compressed image higher similar to original image. The temporal variation in adjacent frame of the sequence is characterized as a video profile that used for video matching process. The PSNR profile includes variable factors, which indicate the level of image quality variation between consecutive frames. PSNR used for the area between the images is given in Eq. (1) and Eq.(2). The PSNR is defined via the Mean Squared Error (MSE) [3]. Given a frame I with image size of m*n and next frame K, MSE is defined as: (1) Then PSNR is defined as: (2) Here, MAX is the maximum pixel value of the image and is 255 in gray level. The PSNR output a factor of quality assessment of two adjacent frames. For PSNR factors, a higher score represents a higher quality between frames. In other words, the slightly content variation occur in frames. The factors were represent as a profile of video. The PSNR profiles are used to determine similarity between query video and database as shown in Fig. 1. B. Video Matching Hausdorff distance measures the distances between two sets of points. Thus, it can be used to measure the similarity between two patterns of points when they are superimposed on one other [4]. Hausdorff distance can be used in a wide range of applications, such as scene recognition, tracking, engineering drawing understanding, and aerial image analysis [5]. Here the Hausdorff distance is used to measure PSNR profile for the similarity of videos. Given two point sets A and B, the Hausdorff distance between A and B is given in Eq. (3). The A and B can be profile of query video clip and video database respectively. H(A,B) = max(h(A,B),h(B,A)), (3) where h(A,B) = maxa A minb B║a - b║, from A to B, and h(B,A) is from B to A. Commonly, the h(A,B) is not equal to h(B,A) but in proposed one dimensional sequence, the point sets, can be arrange

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in time series model that restrict the distance from A to B as same as from B to A. Therefore, the calculation of h(B,A) can be avoided with this model. The Hausdorff distance will be computed by search in full length of signature and produced distance in each search step. Then produce the similarity of the two input profile. The minimum Hausdorff distance min[H(A,B)] represents the maximum similarity index of database that is most similar to query video clip. Experimental Video Set The experimental video clips were taken from ReefVid: Free Reef Video Clip Database (http://www.reefvid.org). Each video include at the least one shot or more than two shots. The video clips include many shot were able to reappear the complexity of actual situation of recording. The sample image from the video database listed in Fig. 2. In addition, most of clips are taken from undersea and include extensive camera motion such as pan/tile/zoom/tracking. These video also not have the editor’s graphical effects such as fade in, fade out and dissolves. The video clips have image size of 384x288 and coded at 25 fps of MPEG-4. The clips lengths varied from 48 frames (video-740) to 7061 frames (video-420). Query video clips were picking up from the video database. Then query video clip were perform search in entire video database by compute the similarity of profiles.

Fig. 1 The example of PSNR profile from video clip1.

Fig. 3 Thumbnail of a portion of the experimental video database. The database contain 800 different clips. (ReefVid: Free Reef Video Clip Database. http://www.reefvid.org/).

Fig. 4 The video matching result of the query video (clip100). The top 10 most similarity videos has been plot. The lower value of similarity factor (minimum Hausdorff distance) is mean that the profile is more matching to the profile of query clip.

Fig. 6 The top 9 most similar videos to the query clip (clip100) are returned from the database. The order of similarity related to clip100 is from (A) to (I): clip100, clip 639, clip215, clip207, clip697, clip124, clip216, clip522, clip723.

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Fig. 8 The top 9 most similar videos to the query clip (clip400) are returned from the database. The order of similarity related to clip100 is from (A) to (I): clip400, clip740, clip760, clip609, clip821, clip680, clip798, clip22, clip597.

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Fig. 10 The top 9 most similar videos to the query clip (clip800) are returned from the database. The order of similarity related to clip100 is from (A) to (I): clip400, clip297, clip700, clip207, clip27, clip723, clip216, clip204, clip777.

Results The proposed video matching process has been validated by experiments with a coral reef video database. The video matching process that use Hausdorff distance to measuring the similarity of videos. Fig. 3 shows the similarity factor (Hausdorff distance) of query clip-100 to the top 10 similar video. The query clip-100 have perfect match to itself and its similarity factor is located in zero. Each query video could plot similar figure as the same way. The top 9 clips in the dataset most similar to query clip100 are shown in Fig. 4. Similarly, Fig. 5 and Fig. 6 show the top 9 clips in the dataset most similar to query clip400 and clip800. It is evident that the query clips match themselves, with similarity factors tending to zero. We were thus able to evaluate the search strategy of using similarity factors derived from the Hausdorff distance. Each query clip was accurately retrieved as the most similar, using the proposed PSNR profile. Therefore, the reported experimental results demonstrated that the proposed technique was both robust and accurate. Conclusions This paper presents a compact video matching framework for the undersea video database. The PSNR variation extracting from video is used to create video profile. The videos are represented by this concise profile for matching process. Hausdorff distance performed the matching process with video profile to retrieve most similar videos. The experimental results show that each query video can be retrieve accurately. We described an original and efficient framework to the video matching process. It involves the PSNR profile and the Hausdorff distance. These results show that this approach can provide remarkable accuracy for retrieving original video clips from video database. Furthermore, the video profile technique can also be exploited for further application such as fast video copy detection and fast near duplicated video detection.

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References [1] A. Basharat, Y. Zhai, M. Shah, Content based video matching using spatiotemporal volumes. Computer Vision and Image Understanding. Vol.110, (2008), 360-377. [2] J. Ke, Y. Zhan, X. Chen, M. Wang, The retrieval of motion event by associations of temporal frequent pattern growth. Future Generation Computer Systems. Vol.29, (2013), 442-450 [3] Q. Huynh-Thu, M. Ghanbari, Scope of validity of PSNR in image/video quality assessment. Electronics Letters. Vol.44, (2008), 800-801. [4] W.H. Press, Numerical recipes in C : the art of scientific computing, 2nd ed., Cambridge University Press, Cambridge ; New York, 1992. [5] Y. Xilin, I.C. Octavia, Line-Based Recognition Using A Multidimensional Hausdorff Distance. IEEE transactions on pattern analysis and machine intelligence. Vol.21, (1999), 901-916.

CHAPTER 3: Machine Parts and Mechanisms, Design and Manufacturing

Applied Mechanics and Materials Vols. 479-480 (2014) pp 181-186 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.181

An Investigation into Optimized Ti-6Al-4V Titanium Alloy Equal Channel Angular Extrusion Process Dyi-Cheng Chen 1,a , Yi-Ju Li 1 and Gow-Yi Tzou 2 1

Department of Industrial Education and Technology, National Changhua University of Education, Changhua 500, Taiwan 2

Department of Mechanical and Automation Engineering, Kao Yuan University, Kaohsiung 821, Taiwan a

：

email [email protected]

Keywords: Finite element, Titanium alloy, Equal channel angular extrusion, Taguchi method

Abstract. The shear plastic deformation behavior of a material during equal channel angular (ECA) extrusion is governed primarily by the die geometry, the material properties, and the process conditions. This paper employs the rigid-plastic finite element (FE) to investigate the plastic deformation behavior of Ti-6Al-4V titanium alloy during ECA extrusion processing. Under various ECA extrusion conditions, the FE analysis investigates the damage factor distribution, the effective stress-strain distribution, and the die load at the exit. The relative influences of the internal angle between the two die channels, the friction factors, the titanium alloy temperature and the strain rate of billet are systematically examined. In addition, the Taguchi method is employed to optimize the ECA process parameters. The simulation results confirm the effectiveness of this robust design methodology in optimizing the ECA processing of the current Ti-6Al-4V titanium alloy. Introduction In rolling, extrusion and forging processes, the workpiece is subjected to very high strains, which cause severe plastic deformation and a corresponding change in the physical and mechanical properties of the material. It has long been known that there are significant benefits to be gained from deforming metallic alloys under very high plastic strains. The equal channel angular (ECA) extrusion process and equal channel angular (ECA) pressing method were first developed by Segal et al. [1-2] as a means of introducing large plastic strains in a metal without causing any substantial change in the outer dimensions of the workpiece. Suh et al. [3] developed a simple 2D plane strain model to investigate material flow in ECA pressing. Srinivasan et al. [4] demonstrated that the magnitude of the maximum strain induced in a workpiece following a single pass through a die was determined by the angle of the round corner. Altan et al. [5] analyzed the material deformation during a 90o ECAE process using the upper-bound theorem. Son et al. [6] performed a FE investigation into the effect of the back pressure on the material behavior and strain distribution of a commercially available pure titanium (CP-Ti) specimen during ECAE. Chen [7] analyzes the plastic deformation behavior of materials with internal defective voids during 1- and 2-turn ECA extrusion. This study employs the commercial DEFORMTM 2D rigid-plastic FE code to investigate the plastic deformation behavior of Ti-6Al-4V titanium alloy during ECA extrusion. The Taguchi method is then applied to establish the optimal processing conditions for the ECA extrusion of the current Ti-6Al-4V titanium alloy. Analytical method Although the deformation process in ECA extrusion has been treated analytically [8-9], a review of the literature suggests that the corresponding FE analyses have not been performed. Segal [2] showed that the strain induced in the billet is given by ε = 2 3 cot (φ 2 ) when ψ =0o.

(

)

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Iwahashi [8] proposed the following more general equation to describe the effects of φ and ψ on the induced strain, i.e.  φ ψ  φ ψ   2 cot  2 + 2  +ψ cos ec 2 + 2       (1) ε = 3       In ECA extrusion, the initial velocity field is generated under the assumption that the billet is a linear viscous material. The velocity boundary conditions and the frictional boundary conditions on the curved surface of the billet as it is driven though the die are imposed via the successive application of a skew boundary condition.

Application of Taguchi method to equal channel angular extrusion The Taguchi method uses a generic signal-to-noise (S/N) ratio to quantify the present variation for the internal angle between the two die channels, the friction factors, the titanium alloy temperature and the strain rate applied by the ram. Depending on the particular type of characteristics involved, different S/N ratios are applicable, including “lower is better” (LB), “nominal is best” (NB), or “higher is better” (HB). The S/N ratio for the LB characteristics of the current ECA extrusion process is given by William & Creveling [10] and Belavendram [11] as: 1 S / N = −10 log n

n

∑y i =1

2 i

   

(2)

where n is the number of simulation repetitions under the same design parameter conditions, yi indicates the obtained results, and subscript i indicates the number of design parameters arranged in the Taguchi orthogonal array (OA). In the Taguchi method, a design parameter is considered to be significant if its influence on the design solution is large compared to the experimental error, as estimated by the analysis of variance (ANOVA) statistical method. If a design parameter is found to be significant, it implies that this parameter plays a fundamental role in determining the optimal solution of the design problem.

Simulation process analysis The current analyses make the following assumptions: (1) the die is a rigid body; (2) the extrusion billet is a rigid-plastic material; and (3) the friction factors between the extrusion billet and the ram, die are constant. Figure 1 presents a schematic illustration of the ECA extrusion of the present Ti-6Al-4V titanium alloy. Note that φ indicates the internal angle between the two flow channels, Ro is the outer arc between the two flow channels, and Ri is the inner arc between the two flow channels.

Fig. 1 Schematic illustration of ECA extrusion process

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Figure 2 shows the effective strain distribution in the Ti-6Al-4V alloy under different ECA extrusion conditions. Specifically, this figure corresponds to ECA extrusion conditions of φ =120o, m (friction ratio)=0.1, temperature of titanium alloy=800oC, strain rate=0.01s-1, and Ro=Ri=6mm. It can be seen that the maximum effective strains in Figures 2 is 0.594 mm/mm. The effective strain 2 φ  per pass, ε , is given by ε = cot   , where φ is the internal angle between the two die 3 2 channels. Hence, the effective strain per pass in Figures 2 is calculated to be ε =0.67 mm/mm.

φ (o)= 120, m (friction ratio)=0.1, Ti(oC)=800, Strain rate (1/s)=0.01, Ro=Ri=6mm 0.594 mm/mm

1.19mm/mm

Fig. 2 Effective strain of Ti-6Al-4V alloy under different ECA extrusion processing conditions

Robust design of ECA extrusion The Taguchi loss function recognizes a customer’s desire for products which are consistent on a part-to-part basis, and the producer’s desire to reduce the product cost. The fundamental principle of the Taguchi robust design methodology is to optimize the product quality and the process design such that they become insensitive to unavoidable sources of variation. In the current study of the ECA extrusion of Ti-6Al-4V titanium alloy, the principal characteristics of robustness are the Y-load (punch load) of the extruded product and a reduced sensitivity to external noise. Factor selection As shown in Table 1, four design factors, each with three levels, were specified for the ECA extrusion process. Accordingly, the experimental trials were arranged in an L9(34) Taguchi OA. The design factors were assigned as follows: Factor A: the internal angle between the two die channels, Factor B: the friction factor, Factor C: the temperature of the titanium alloy, and Factor D: the strain rate of billet. The remaining ECA extrusion conditions were specified as Ro (outer arc of two die channels) and Ri (inner arc of two die channels). Table 1 Design parameters and levels in Ti-6Al-4V ECA extrusion process (Ro=Ri=6mm) Factors Description Level 1 Level 2 Level 3 φ (o) A 120 135 150 (Internal angle between the two die channels) B m (friction ratio) 0.1 0.25 0.4 o C Ti( C)(Temperature) 800 900 1000 D Strain rate (1/s) 0.01 0.1 1

Analysis of means Table 3 presents the S/N response tables for die geometries of Ro=Ri=6mm, while Table 4 presents the corresponding factor response data for the S/N ratio. In accordance with the principles of the Taguchi method, an assumption is made that a higher S/N ratio indicates an improved processing condition. Therefore, Figure 2 shows that for the die geometry of Ro=Ri=6mm, the

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optimal parameter settings are as follows: an internal angle between the two die channels of 150o (Factor A3), a friction factor of 0.1 (Factor B1), a titanium alloy temperature of 1000oC (Factor C3), and a strain rate of billet of 0.01s-1(Factor D1) for selected four factors and three level. Table 3 S/N ratio for Y-load (punch load) in Ti-6Al-4V ECA extrusion process (Ro=Ri=6mm) Average Experiment Y Load Y Load A B C D Y Load S/N ratio number (kN), y1 (kN), y2 (kN) 1 1 1 1 1 1.62 1.67 1.645 -4.32 2 1 2 2 2 1.14 1.17 1.155 -1.25 3 1 3 3 3 1.45 1.52 1.485 -3.43 4 2 1 2 3 1.38 1.39 1.39 -2.86 5 2 2 3 1 0.257 0.265 0.261 11.67 6 2 3 1 2 3.35 3.51 3.43 -10.71 7 3 1 3 2 0.233 0.231 0.232 12.69 8 3 2 1 3 2.74 2.82 2.78 -8.88 9 3 3 2 1 0.676 0.703 0.690 3.22 Mean of the total sum 1.452 -0.43 Table 4 Factor response table for S/N ratio (Ro=Ri=6mm) Control A B C D factor Level 1 -3.00 -7.97 1.84 3.52 Level 2 -0.63 0.51 -0.30 0.24 Level 3 -3.64 -5.06 2.34 6.98 Effects 5.34 5.48 14.95 8.58 Rank 4 3 1 2

Analysis of variance The results of the simulation trials were investigated using the ANOVA statistical analysis method. The corresponding results for the die geometry cases of Ro=Ri=6mm is presented in Table 5. The high confidence (at least 99%) and variance of Factors A, B, C and D indicate that the internal angle between the two die channels, the friction factor, the temperature of the titanium alloy, and the strain rate of billet all have a significant effect upon the Y-load (punch load) of the ECA extruded product. Confirmation experiment In the Taguchi methodology, a confirmation experiment is conducted using the optimal design parameters identified from the analysis of variance method to confirm that these parameters do indeed improve the quality of the design. Accordingly, a simulation was performed using the optimal design parameter combination for the die geometry of Ro=Ri=6 mm in selected four factors and three level, i.e. A3B1C3D1. The results indicated that the Y-load (punch load) of the new design was 0.132 kN with a S/N value of 17.59 (dB). These values represent an improvement over the original results, and hence confirm the effectiveness of the Taguchi design methodology in optimizing the current ECA extrusion process. Figures 5(a) and 5(b) show the damage value and effective stress distributions in the titanium alloy billets during ECA extrusion conducted under the optimal conditions of φ =150o, m=0.1, Ti=1000oC, and strain rate=0.01 s-1 in the die with a geometry of Ro=Ri=6mm. Figure 5(a) shows that the maximum damage value occurs in the surface region of the billet in the outer die channel. Meanwhile, Figure 5(b) reveals that the maximum effective stress occurs in the vicinity of the corner of the outer die channel.

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Table 5 Y-load (punch load) analysis of variance (ANOVA) (Ro=Ri=6mm) Factor Description SS DOF Variance F Confidence Significant?* φ (o) (angle) A 0.6400 2 0.3200 290.9 100% Yes B m (friction ratio) 0.9879 2 0.49395 449.1 100% Yes o C Ti( C)(Temperature) 12.7697 2 6.38485 5804.4 100% Yes D Strain rate (1/s) 3.3346 2 1.6673 1515.7 100% Yes Error 0.0098 9 0.0011 Total 17.742 17 *Note: At least 99% confidence

φ (o)= 150, m (friction ratio)=0.1, Ti(oC)=1000, Strain rate (1/s)=0.01, Ro=Ri=6mm Max. 20.8 MPa

Max. 0.206

(a) Damage value (b) Effective stress (MPa) Fig. 5 Numerical analysis of ECA extrusion process under optimal processing conditions

Conclusions This study has used the finite element code to investigate the plastic deformation behavior of Ti-6Al-4V titanium alloy during ECA extrusion processing. The results have shown that: (1) the internal angle between the two die channels, the friction factor, the temperature of the Ti-6Al-4V titanium alloy, and the strain rate of billet all have a significant effect upon the Y-load (punch load) of the ECA extruded product; (2) the maximum damage value occurs in the surface region of the billet in the outer die channel; and (3) the maximum effective stress occurs in the vicinity of the corner of the outer die channel. The simulation results confirm the effectiveness of the Taguchi robust design methodology in optimizing the ECA extrusion process for the titanium alloy. References [1] V.M. Segal, USSR Patent No. 575892 (1977) [2] V.M. Segal, V.I. Reznikov, A.E. Drobyshevskiy, V.I. Kopylov: Russ. Metall. 1, No. 99 (1981). [3] J.Y. Suh, H.S. Kim, J.W. Park, J.Y. Chang, Finite element analysis of material flow in equal channel angular pressing, Scripta Materialia 44 (2001) 677-681. [4] R. Srinivasan, Computer simulation of the equichannel angular extrusion (ECAE) process, Scripta Materialia 44 (2001) 91-96. [5] B.S. Altan, G. Purcek, I. Miskioglu, An upper-bound analysis for equal-channel angular extrusion, Journal of Materials Processing Technology 168 (2005) 137-146. [6] I.H. Son, J.H. Lee and Y.T. Im, Finite element investigation of equal channel angular extrusion with back pressure, Journal of Materials Processing Technology 171 (2006) 480-487. [7] D.C. Chen, C.P. Chen, Investigation into equal channel angular extrusion process of billet with internal defects, Journal of Materials Processing Technology 204 (2008) 419-424.

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[8] Y. Iwahashi, J. Wang, Z. Horita, M. Nemoto, T.G. Langdon, Principle of equal-channel angular pressing for the processing of ultra-fine grained materials, Scripta Materialia 35(2) (1996)143-146. [9] V.M. Segal, Equal channel angular extrusion: from macromechanics to structure formation, Materials Science and Engineering A 271 (1999) 322-333. [10] W.Y. William and C.M. Creveling: Engineering methods for robust product design, Addison-Wesley, Boston (1998) [11] N. Belavendram: Quality by design, Prentice-Hall, New York (1995)

Applied Mechanics and Materials Vols. 479-480 (2014) pp 187-191 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.187

Design of a Magnetic Gear Set with Low Torque Ripple Yi-Chang Wu1,a, Wan-Tsun Tseng2,b, Yueh-Dung Chen1 1

Department of Mechanical Engineering, Department of Electrical Engineering, National Yunlin University of Science & Technology, Taiwan, R.O.C. 2

a

b

[email protected], [email protected]

Keywords: magnetic gear set, torque ripple, finite-element analysis.

Abstract. Non-contact magnetic gears have recently attracted significant attention due to their lack of mechanical fatigue, the fact that they require no lubrication, their reduced maintenance, improved reliability, overload protection, physical isolation between input and output shafts, and potential for very high efficiency. This paper presents an external type magnetic gear set with arc-shaped magnets and parallel axes. The finite-element method is used as an assistant tool for the transmitted torque analysis. The effect of the number of magnet poles on the magnetic gear set torque ripple is also discussed. This examination offers insights beneficial to future magnetic gear mechanism design. Introduction Gear mechanisms are used to transmit motion and/or power from one rotating shaft to another. Mechanical gears with cut teeth are widely used in machinery such as automobile transmissions, robot manipulators, gearboxes, etc. Although they are able to achieve high transmitted torque densities, mechanical gears require lubrication, generate noise, and suffer from inherent friction that reduces their mechanical efficiency. By contrast, magnetic gears transmit torque between the input and output shafts by non-contact magnetic coupling rather than meshed mechanical gear teeth. Since there is no mechanical contact between the driving and driven gears, there is no wear, and no need for lubrication. Magnetic gears offer potential advantages such as reduced maintenance and improved reliability, low noise, inherent overload protection, high efficiency, precise peak torque transmission, tolerance for misalignment, and physical isolation between the input and output shafts. Magnetic gears therefore offer unique advantages as an alternative to mechanical gears. Various types of magnetic gears have been proposed, including parallel axes type external and internal magnetic gear sets [1-3], planetary type magnetic gears [4], magnetic worm gears [5], coaxial type magnetic gears [6], intersecting axes type magnetic Miter gears [7], etc. They are widely employed in industrial machinery, such as renewable energy machinery [8], integrated magnetic-geared permanent-magnet motors for electric vehicles [9], marine propulsion systems [10] and high-speed mining and quarrying machinery [11]. However, the main drawback of magnetic gear mechanisms is the generation of an inherent torque ripple that prevents a smooth output torque. The torque ripple always induces vibration, acoustic noise, possible resonance, speed ripples and position inaccuracy, which is detrimental to the output performance of a magnetic gear mechanism, particularly at light load and low speed. Traditional approaches for torque ripple reduction in electromagnetic devices include the stepped skewing of the permanent-magnet blocks, skewing the stator lamination, placing auxiliary salient poles on the stator, dummy slots on the pole face of the armature core, auxiliary slots on the magnetizing yoke of the permanent magnets, modifying the permanent magnet arc, etc. These techniques, however, are only viable for permanent-magnet type electric motors. The reduction of the torque ripple in magnetic gear mechanisms has received relatively little attention. The purpose of this paper is to investigate the effects of design parameters on the transmitted torque and torque ripple of an external magnetic gear set. An external type magnetic gear set with a gear ratio of 1:1 is first introduced. Then, Ansoft/Maxwell, a commercial finite-element analysis software, is employed to numerically simulate the transmitted torque waveform of this magnetic gear set so that the torque ripple can be calculated. The effect of the number of magnet pole pairs on the

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ripple of the transmitted torque are discussed in order to obtain a magnetic gear set with low torque ripple. An External Magnetic Gear Set A magnetic gear consists of a series of permanent magnets with alternate magnetization affixed to the inner surface of an iron yoke (for the internal type) or the outer surface of an iron yoke (for the external type). The number of poles of a magnetic gear is generally an even number. The simplest magnetic gear set is composed of two separated magnetic gears with two rotating shafts mounted on a common stationary frame. Fig. 1 illustrates an external magnetic gear set with arc-shaped permanent magnets. The area between the magnetic gears is the air gap, which is a space in which magnetic energy is stored. The magnetic iron yoke provides the base for mounting the magnets, and efficiently conducts the magnetic flux to form closed flux loops due to its high permeability. The rotations of the driving gear and the driven gear are in opposite directions for an external magnetic gear set, due to the same linear velocity at the midpoint of the center distance. When the driving gear is rotating, it imparts a transmitted torque to the driven gear and causes it to rotate due to the coupled magnetic flux lines. The transmitted torque is a periodic torque that varies with respect to the angular displacement of the driving gear. The period of the transmitted torque waveform is 360°/n, where n is the number of pole pairs. The maximum transmitted torque occurs when the angular displacement is half that of the magnet arc. Once the driving torque exceeds this critical torque, slipping occurs. Therefore, a magnetic gear set can be used as an overload protection device.

Fig. 1 An external magnetic gear set with the gear ratio of 1:1 Transmitted Torque Analysis Transmitted torque is the most important performance index of a magnetic gear set, and it is essential to predict the transmitted torque when designing a magnetic gear train. There are numerous ways to determine the magnetostatic field and transmitted torque of magnetic gears, including analytical methods and numerical methods. The finite-element analysis, a numerical method, is discretized geometrically and the magnetic field and the transmitted torque are numerically computed at discrete points in the magnetic gear set. It is a powerful and reliable tool for dealing with the design and analysis of magnetic gear devices before fabricating actual prototypes. Since the finite-element analysis produces the most accurate results if the geometric discretization is fine enough, it is applied to assist in numerically calculating the transmitted torque of the presented magnetic gear set. A commercial finite-element analysis package, Ansoft/Maxwell, is employed to calculate the transmitted torque. Table 1 presents the material parameters of the magnet and geometric dimensions for the magnetic gear topology, while Fig. 2 shows the magnetic gear topology with geometric definitions. When the driven gear is kept still and the driving gear is rotating, the transmitted torque against the rotational angle is illustrated in Fig. 3 using Ansoft/Maxwell. As depicted in Fig. 3, the maximum transmitted torque, which is also called the pull-out torque, is 4.06 Nm, and it occurs when the angular displacement is equal to half that of the magnet arc. When the driven gear is propelled by

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the driving gear, and rotates at identical angular speed with the driving gear due to the 1: 1 gear ratio, the transmitted torque transient waveform can be obtained as shown in Fig. 4. We find that an inherent transmitted torque ripple occurs in such a magnetic gear set. The period of the ripple torque is 360° /(2n)=360°/(2*6)=30° for the magnetic gear set shown in Table 1 with a gear ratio of 1: 1. The symbol n represents the number of pole pairs. Table 1 Material parameters of the magnet and geometric dimensions of the external magnetic gear set shown in Fig. 1 Material parameters of NdFeB (N-45) magnet Items Symbol Values Remanence (T) Br 1.1 Relative permeability 1.04 µr Magnet arc (degree) 30 τ Magnet height (mm) h 6.00 Axial length (mm) L 30.00 Number of pole pairs n 6 Geometric dimensions of the external magnetic gear set Items Symbol Values Inner radius of the iron yoke (mm) R1 10.00 Outer radius of the iron yoke (mm) R2 25.00 Air-gap length (mm) g 1.00

Fig. 2 An external magnetic gear topology showing geometrical definitions

Fig. 3 Transmitted torque waveform when the driven gear is kept still and the driving gear is rotating

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Fig. 4 Transmitted torque transient waveform Torque Ripple Reduction Transmitted torque exhibits an inherent torque ripple that causes vibration as well as preventing a smooth rotation. This pulsating torque is detrimental to output performance, especially in high-precision speed and position control applications. So, transmitted torque ripple reduction is a major concern for magnetic gear designers. The torque ripple is defined by the difference between the minimum and maximum transmitted torque divided by the average transmitted torque. For example, the maximum transmitted torque, minimum transmitted torque, and average transmitted torque shown in Fig. 4 are 4.06 Nm, 3.78 Nm, and 3.92 Nm, respectively. Therefore, the transmitted torque ripple of the presented magnetic gear set shown in Table 1 is 7.14%. We set the volume of the permanent magnet of each magnetic gear mechanism as identical for comparison purposes. Fig. 5 shows the transmitted torque ripple versus the number of pole pairs. We find that the torque ripple decreases as the number of pole pairs increases. This is because the period of the ripple torque decreases as the number of pole pairs increases. Therefore, the ripple torque increases the torque frequency, and decreases its amplitude.

Fig. 5 Transmitted torque ripple versus the number of pole pairs Conclusion In this study, the transmitted torque and torque ripple of an external magnetic gear set with arc-shaped magnets were investigated using finite-element analysis. The simulation results show that the torque ripple decreases as the number of pole pairs increases with an identical volume of total magnets. Therefore, it is suggested that high-precision speed and position control applications use

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magnetic gears equipped with a high number of pole pairs in order to reduce the torque ripple. These findings offer useful insights beneficial to future magnetic gear mechanism design. Acknowledgements The authors are grateful to the National Science Council (TAIWAN, R.O.C) for supporting this research under grant NSC 101-2221-E-224-019. References [1] Y.D. Yao, C.M. Lee, S.J. Wang and D.R. Huang, U.S. Patent 6,047,456 (2000) [2] K. Ikuta, S. Makita and S. Arimoto, in: Proceedings of the Micro Electro Mechanical Systems, MEMS '91, An Investigation of Micro Structures, Sensors, Actuators, Machines and Robots, Nara, Japan (1991), p. 125 [3] Y.C. Wu and C.W. Wang: Appl. Math. Inf. Sci. (2013), in press. [4] M. Fukuoka, K. Nakamura and O. Ichinokura: IEEE Trans. Magn. Vol. 47 (2011), p. 2414 [5] S. Kikuchi and K. Tsurumoto: IEEE Trans. Magn. Vol. 29 (1993), p. 2923 [6] K. Atallah and D. Howe: IEEE Trans. Magn. Vol. 37 (2001), p. 2844 [7] Y.D. Yao, D.R. Huang, C.C. Hsieh, D.Y. Chiang, S.J. Wang and T.F. Ying: IEEE Trans. Magn. Vol. 32 (1996), p. 5061 [8] L. Jian, K.T. Chau and J.Z. Jiang: IEEE Trans. Ind. Appl. Vol. 45 (2009), p. 954 [9] L. Jian and K.T. Chau: J. Asian Electr. Veh. Vol. 7 (2009), p. 1213 [10]Information on http://www.magnomatics.com/applications/Marine-Propulsion.aspx [11]Information on http://www.dextermag.com

Applied Mechanics and Materials Vols. 479-480 (2014) pp 192-196 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.192

Heat Transfer of Oscillating Fluid through Finned Heat Sink with Top Bypass Clearance Tzer-Ming Jeng1,a, Sheng-Chung Tzeng2,b, Wei-Ting Hsu3,c, Guan-Wei Xu4,d 1,2,3,4

Department of Mechanic Engineering, Chienkuo Technology University, No. 1, Chieh Shou N Rd., Chang Hua 500, Taiwan, R.O.C. a

[email protected], b [email protected], c [email protected], d

[email protected]

：

Keywords: Oscillating flow, finned heat sink, heat transfer, bypass clearance

Abstract. This work experimentally investigated the effect of the oscillating flow on the heat transfer enhancement of the finned heat sink with top bypass clearance. The cooling system of the finned heat sink usually employs the steady flow with fixed flow rate to complete the objective of forced convection. This work designed and manufactured a device to oscillate air flow. The experimental results indicate that it would obtain 10~34% heat-transfer increment for the oscillating-flow cases with sufficiently small bypass clearance. It demonstrates that the oscillating flow does promote the cooling performance of finned heat sink. 1.

Introduction The heat dissipated from the electric equipments and the power machines is growing

continuously. In order to protect these equipments and machines from being operated at the over high-temperature condition, the effective cooling system is necessary. Combining the finned heat sink with the steady flow of fixed flow rate is one of the simple and effective cooling technologies [1-4]. Besides, heat transfer in the oscillating flow has been a principal investigation area for past several decades. Oscillation-induced heat transport processes maintaining an effective heat transfer enhancement has been demonstrated [5-7]. Recently, the fluid flow and heat transfer characteristics of oscillating flow through porous media are explored [8-10]. All of these studies indicated that employing high amplitude and frequency of the oscillating flow would increase the heat transfer. It is because that the oscillating air flow would be unstable in the porous structure and increase the staying time of air through the porous media. Based on the above-mentioned literature survey, the study of applying the oscillating flow through the pin-fin heat sink to enhance heat transfer is few. Therefore, this work will build a device to oscillate air flow and experimentally investigate the effect of the oscillating flow on the heat transfer enhancement of the finned heat sink with top bypass clearance.

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2. Experimental Method 2.1. Experimental setup An experimental setup, as shown in Fig. 1, was built for the investigations of the heat transfer and fluid flow characteristics. The experimental setup included the air-supplying equipment, the oscillating-flow-generating equipment, the test section, the data-acquiring equipment, the smoke generator and the image-capturing equipment. The compressed air was generated by the 5HP air compressor firstly, then entered into an 800L steel tank to be reduced the flow impulse as well as flowed through the dryer and filter to be removed the water and impurities, and finally passed through the flow controller to be adjusted the flow rate. Before entering into the test section of the finned heat sink, the air went through the oscillating-flow-generating equipment to be become the oscillating flow. As shown in Fig. 1, the oscillating-flow-generating equipment was made of a motor, a switching valve and an inverter. By using the belt, the motor could drive the switching valve rotating in the pipe to reach the objective of opening and closing the air flow periodically. The test section, as shown in Fig. 2, was a square chamber made of the Bakelite. An aluminum-alloy circular pin-fin heat sink was installed in the test section. Dimensions of the heat sink are shown as Fig. 3. Three heights of the pin fins were employed, including 46, 30 and 20mm. The spreader of the heat sink was adhered with the film heater by the grease with the high thermal conductivity. The other side of the film heater was adhered onto the upper shroud of the test section. Four T-T-30SLE T-Type thermocouples through the upper shroud were connected onto the film heater to measure the heated wall. The film heater was heated by the DC power supply. The data-acquiring equipment, including the YOKOGAWA MX100 data recorder and the personal computer, was used to record the steady-state temperature data. The criterion of the steady-state data was the change of the temperature within 0.2°C during 15 minutes.

Fig. 1 Experimental setup and sketch map of oscillating-flow-generating device

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Fig. 2 Dimensions of test section and positions of thermocouples (Unit: mm)

Fig. 3 Dimensions of finned heat sink with Hf=46mm (Unit: mm) 2.2. Data reduction and uncertainty analysis According to the estimation method of heat loss, the inlet and outlet of the test channel were sealed tightly by polystyrene. Due to lack of air from/into the test channel for heat exchange, the heat supplied by the film heater (Qin) was almost equal to the heat loss (Qloss) dispersed from the outer surfaces of test channel. When estimating the heat loss, it was required to input different heat quantities and record the wall temperatures (Tw) and ambient temperatures (T∞) when the system reached a steady state. Therefore, the relationship between the heat loss and (Tw-T∞) was obtained. The measured data was used to determine the relevant dimensionless parameters, including average Reynolds number (Re) and average Nusselt number (Nu). Re =

ρ ⋅ Uave ⋅ Dh µ

(1)

Nu =

(Qin − Qloss ) ⋅ Dh A(Tw − T fb )kf

(2)

Where Uave is the average fluid velocity in the test section, Dh is the hydraulic diameter of the test section, Tw is the mean wall temperature, Tfb is the mean value of the air temperatures at the channel inlet/outlet ( (Ti + To ) / 2 ), Qin is the total input heat, Qloss is the heat loss, and A is the surface area of heated wall. The uncertainties of experimental results included the measurement and calculation deviations. The measurement deviation was caused by the errors of the instruments or manual reading, and the calculation deviation was formed by interactive operation of measured parameters. The uncertainties, analyzed by the method of Moffat [11], in average Reynolds number (Re) and average Nusselt number (Nu) were ±3.35% and ±6.96%.

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3. Results and Discussion Figure 4 displays the photos of flow visualizations. The operation condition was set as flow rate of 50 L/min and oscillating frequency of 2.5 Hz. The photos show clearly that the smoke flow was blown from the nozzle periodically. When the time was T s, a big amount of smoke was blown away at the exit of the nozzle. When the time marched to T+0.2 s, the amount of blown smoke became very small. It demonstrates that the present oscillating-flow-generating equipment did work. At the present study, the periods of the oscillating flow were 0.4, 0.2 and 0.133s separately for 2.5, 5 and 7.5Hz oscillating frequency (f). Figure 5 depicts the relationship between Nu and Re. The test results indicate that the Nu values of the oscillating flow were higher than those of the steady flow. The heat-transfer enhancement by the oscillating flow was about 10~34% for the cases with sufficiently small bypass clearance; it increased with the oscillating frequency. This phenomenon can be explained as follow. The oscillating-flow-generating equipment made the periodically changed flow rate. The air flow would be unstable in the passages among the fins due to the oscillation of flow rate, increasing the staying time of air through the fins. Therefore, the overall heat-transfer performance would be enhanced. Besides, the Nu values of the cases with the fin height of 46mm (i.e. no bypass flow) were 2~20% higher than those with the fin height of 30mm. The difference of Nusselt number between these two kinds of cases was bigger when the average Reynolds number was smaller and the oscillating frequency was higher. It means the bypass effect was remarkable at those conditions. Finally, one can also find that the oscillating flow could not promote the heat transfer for the cases with the fin height of 20mm; the Nu values of the oscillating flow were even lower than those of the steady flow obviously. It is because that the sufficiently big top clearance made more amount of the oscillating flow to bypass from the pin-fin array. It demonstrates that the heat transfer would be enhanced by the oscillating flow for the cases with sufficiently small bypass clearance, especially at high fin height and high oscillating frequency.

Fig. 4 Photos of flow visualizations (Qflow=50 L/min and f=2.5Hz)

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1600

1600

1600

H f =46mm

H f =30mm

H f =20mm

Oscillating flow, f=7.5HZ

Oscillating flow, f=7.5HZ

Oscillating flow, f=7.5HZ

Oscillating flow, f=5HZ

Oscillating flow, f=5HZ

Oscillating flow, f=2.5HZ

1200

Nu

Oscillating flow, f=5HZ

Oscillating flow, f=2.5HZ

1200

Nu

800

400

Steady flow

H f =46mm f=7.5HZ

800

H f =46mm Steady flow

400

0 1000

2000

3000

Re

4000

5000

Nu

H f =46mm f=7.5HZ

800

H f =46mm Steady flow

400

0 0

Oscillating flow, f=2.5HZ

1200

Steady flow

Steady flow

0 0

1000

2000

3000

4000

5000

0

1000

Re

2000

3000

4000

5000

Re

Fig. 5 Relationships between Nu and Re for the systems with Hf=46, 30 and 20mm

4. Conclusions This work designed and manufactured a device to oscillate air flow. The air flow would be unstable in the passages among the fins due to the oscillation of flow rate, increasing the staying time of air through the fins. Therefore, the overall heat-transfer performance would be enhanced. According to the present data, there was even 10~34% increment in the overall heat-transfer performance for the cases with sufficiently small bypass clearance. However, the oscillating flow could not promote the heat transfer for the cases with big bypass clearance; the Nu values of the oscillating flow were even lower than those of the steady flow obviously.

Acknowledgement The authors would like to thank the National Science Council of the Republic of China for financially supporting this research under Contract No. NSC 101-2622-E-270-005-CC3.

References [1] S.Y. Won, G.I. Mahmood and P.M. Ligrani: Int. J. Heat Mass Transfer Vol. 47 (2004), pp. 1731-1743. [2] T.M. Jeng: Int. Comm. Heat Mass Transfer Vol. 33 (2006), pp. 1139-1146. [3] T.M. Jeng and S.C. Tzeng: Int. J. Heat Mass Transfer Vol. 50 (2007), pp. 2364-2375. [4] T.M. Jeng: Int. J. Heat Mass Transfer Vol. 51 (2008), pp. 2214-2226. [5] Q. Dai and L. Yang: Applied Thermal Engineering Vol. 54 (2013), pp. 16-25. [6] F. Meng, M. Wang and Z. Li: Int. J. Heat Fluid Flow Vol. 29 (2008), pp. 1203-1210. [7] U. Akdag and A.F. Ozguc: Int. J. Heat Mass Transfer Vol. 52 (2009), pp. 2667-2672. [8] M. Kuosa, K. Saari, A. Kankkunen and T.M. Tveit: Applied Thermal Engineering Vol. 45–46 (2012), pp. 15-23. [9] M.T. Pamuk and M. Ozdemir: Experimental Thermal and Fluid Science Vol. 42 (2012), pp. 79-92. [10] Y. Su, J.H. Davidson and F.A. Kulacki: Int. J. Thermal Sciences Vol. 54 (2012), pp. 199-208. [11] R.J. Moffat: ASME J. Fluids Engineering Vol. 104 (1982), pp. 250-258.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 197-201 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.197

Reducing Cogging Force of a Permanent Magnet Transverse Flux Linear Synchronous Motor Wan-Tsun Tseng1, a Chen-Nan Kuo1 1

123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R.O.C. a

[email protected]

Keywords: Permanent magnet transverse flux linear synchronous (PMTFLSM), cross-shaped core, cogging force, thrust, finite element analysis (FEM), Taguchi’s parameter method

Abstract. This paper presents means to minimize the cogging force of a new type of permanent magnet excited transverse flux linear synchronous motor (PMTFLSM). The translator of this linear motor consists of cross-shaped core sets. Varying the parameters of air gap length, magnet dimensions, pole pitch and tooth width of the translator, the cogging force of the PMTFLSM will be analyzed. Taguchi’s parameter method including 2D finite element analysis (FEM) is employed to minimize the cogging force. Analytical and simulation results indicate the usefulness of our approach in practice Introduction Cogging force has been one of the most important issues to be dealt with in the field of permanent magnet linear motors, causing speed ripples, inducing vibrations and noises, and increasing the difficulty of position control [1]. All of these negative effects will become more aggravated, particularly under light loads and low speeds. So if the cogging force can be kept as minimal as possible, or even completely disappeared, the operation of motors will be improved significantly. In an iron core permanent magnet linear motor, the cogging force appears with the interaction between permanent magnets and armature core. For reducing cogging force, many techniques have been proposed in three general lines: 1) smaller flux in the air gap; 2) constant reluctance in the air gap wherever possible; and 3) best design of the geometrical arrangement between slots and magnets. All of these methods were introduced in the literature including the proper selection of pole and slot combination [2,3], smaller magnetic remanence or adjusting air-gap length [4], skewing slots or magnets [5], auxiliary slots [6], and semi-closed slot [7]. This paper is concerned with minimizing the cogging force of the permanent magnet excited transverse flux linear synchronous motor (PMTFLSM). Featuring a structure of cross-shaped cores of the translator, the afore-mentioned third method will be applied to this study. The theoretical cogging force can be obtained directly from partial differentiation of the magnetic co-energy in the air gap. Through the theoretical analysis, we come to find how each machine parameters affects the cogging force. Since the machine parameters have different influence on cogging force, the Taguchi’s parameter method coupled with 2D FEM is then used to minimize the cogging force for finding the best design parameters of the PMTFLSM. Theoretical Analysis Construction Model of the PMTFLSM. Under consideration in this work is a novel linear motor devised with cross-shaped cores. The cross-shaped cores are made as the translator and form the magnetic circuit perpendicular to the motion direction. Such a unique design presents its peculiarity. The motor consists of five main parts, namely the stator back iron, the cross-shaped translator core, permanent magnet, translator windings, as well as a magnetic insulated connecting rod. Fig. 1 is a 3D schematic diagram of the motor [8].

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τM

Back iron PM

S

N bM

Tooth head Index of cross-shaped core set

1

τR

lg

bZ 2

hM l i z

∆x

y

x

Fig. 2 Illustration of machine parameters 1: Back iron, 2: Cross-shaped core, 3: Permanent magnet, 4: Translator coil, 5: Connecting rod Fig. 1 Schematic of the novel PMTFLSM

The translator is composed of independent cross-shaped core sets, as shown in Fig. 1. A magnetic insulated rod links the cross-shaped core sets and connects with a driven load. Motor winding is wrapped around on the cross-shaped core set, each with two coils. The number of cross-shaped cores determines the thrust produced. A high thrust requires more cross-shaped cores. In this study, the translator contains six cross-shaped core sets. The geometrical arrangement of magnets and tooth heads of our PMTFLSM is illustrated in Fig. 2, where two magnets on an iron plate and appropriate tooth heads (No. 1 and 2) of the translator are shown. The remaining magnets and tooth heads are positioned likewise on the same scale. The direction of motion is referred to as x-axis. With reference to Fig. 2, following are construction parameters: τM : magnetic pole division; τR : translator pole pitch; bM : magnet width; bZ : width of the tooth head; hM : magnet height; lg : length of the air gap; li : effective air gap length; ∆x: axis displacement between magnet and translator. Calculation of the Cogging Force. To simplify our analysis, it is assumed that the flux leakage and the saturation in the magnetic circuit are negligible. The cogging force can be computed by the change of magnetic co-energy in the air gap, while the translator moves and has three components in x-, y- and z-directions in the Cartesian space. These three force components Fx, Fy and Fz can be determined in accordance with (1): Fx , y , z =

∂ W ' ( x, y , z ) ∂x

(1)

Here the component Fx is to examine, because it arises in the direction of motion. The other two components Fy and Fz are left out thanks to symmetrical construction or by the guidance of the translator. Recall that the translator is composed of several cross-shaped core sets (Fig. 2). If the magnetic pole division τM is not equal to the translator pole division τR, a displacement ∆x = τR - τM develops between the two pole axes. Therefore, the cogging force at the individual tooth head will differ and can be generalized with pole axis displacement ∆x. From (1) with Fourier expansion of the magnetic induction in air-gap, the analytically computed cogging force density Fcj(x) of individual tooth head is given by (2). ∞ F l 4B 1 Fcj ( x) = x = i ( g )2 ∑ cos2[ 2 lM 4µ0 π k =1 (2k − 1)

2( x + {cos[

(1 −

bM

τM

)(2k − 1)π ]⋅

2

bZ b − ( j − 1)∆x)(2k − 1)π 2( x − Z − ( j − 1)∆x)(2k − 1)π 2 2 ] − cos[ ]}, j = 1,2,3...

τM

τM

(2)

where Bg is the magnetic flux density produced in the air gap by a permanent magnet with linear demagnetization curve and lM is the magnet length. In this study j=6 is selected, which means that the

Specific Cogging Force Fcs [N/m]

Applied Mechanics and Materials Vols. 479-480

Table I Basic parameter settings Symbol

Description

hM bM Br τM bZ τR lg

Value

Magnet thickness [mm] Magnet width [mm] Magnet remanence [T] Magnet pole pitch [mm] Cross-core tooth width [mm] Translator pole pitch [mm] Air gap length [mm]

3.0 10.0 1.05 15.0 7.0 20.0 1.0

199

8000 7000 F.E.M. Analytical

6000 5000 4000 3000 2000 1000 0 -0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

Pole axis displacement ∆x/ τM Fig. 3 Influence of ∆x on cogging force

translator comprises of six cross-shaped core sets. The resulting cogging force is computed from the arithmetic sum of the cogging force arising at the individual tooth head. Following (2), the resulting cogging force Fcs(x) can be determined from (3). 6

Fcs ( x) = ∑ Fcj ( x) = j =1

{cos[

(2k − 1)π (2 x + bZ − 5∆x)

τM

∞

li 1 (2k − 1)π∆x ( )2 ∑ cos[ ] cos2[ 2 τ 2 µ0 π ( 2 1 ) k − k =1 M 4 Bg

] − cos[

(2k − 1)π (2 x − bZ − 5∆x)

τM

(1 −

bM

τM

)(2k − 1)π ][2 cos(

2

4(2k − 1)π∆x

τM

) + 1] ⋅

(3)

]}

It can be seen from (3) that the cogging force is affected by several factors, e.g. pole axis displacement ∆x, magnet width bM, tooth head width bZ, magnet height hM as well as the remanence of the permanent magnet Br. These factors possess different potencies on the cogging force. With the basic machine parameters of Table I, FEM simulations indicate how pole axis displacement ∆x results in cogging force, as shown in Fig. 3. The cogging force varies from 0 to about 7,000 N/m (analytical) while the ratio of ∆x/ τM changes between ±0.4. It can be confirmed as well that ∆x has the dominant influence on the cogging force. According to machine data in Table I and setting lM to 50 mm, the cogging force reaches to 21.37 N with ∆x = τM /3. Reducing Cogging Force with Taguchi’s Parameter Method Determining the Orthogonal Array. A structured approach to resolving the best combination of inputs to produce a product or a service, Taguchi’s method can be applied to this study for reducing cogging force. By using Taguchi’s method, the orthogonal array must be set up with selected factors and levels [9]. Because the first-step minimization of cogging force is done through theoretical analysis and the dominant factor ∆x is fixed at τM /3. The other four factors A, B, C, and D affecting the cogging force can be selected from (3) and Fig. 4. A is the tooth head width bZ. B represents the magnet width bM. C is defined as the air-gap length lg. And D refers to the magnet height hM. Each factor has three levels as shown in Table II. The L9 (34) orthogonal array and its experimental results are listed in Table III. Each experiment is conducted based on 2D FEM. B PM C

Back Iron PM Cross shaped core

D A

Fig. 4 Selected machine parameters (side view)

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Table III L9(34) orthogonal array

Ai

Bi

Ci

Di

Cogging Force [N]

1

7.0

10.0

0.8

2.0

16.47

Facto r E xp er iment Table II Selected parameters and its level Parameters

Level

Code

tooth head width bZ [mm] magnet width bM [mm] air-gap length lg [mm] magnet height hM [mm]

1

2

3

2

7.0

10.25

1.0

3.0

10.68

A

7.0

7.1

7.2

3

7.0

10.5

1.2

4.0

12.1

B

10.0

10.25

10.5

4

7.1

10.0

1.0

4.0

16.03

5

7.1

10.25

1.2

2.0

7.78

C

0.8

1.0

1.2 6

7.1

10.5

0.8

3.0

11.2

7

7.2

10.0

1.2

3.0

9.84

8

7.2

10.25

0.8

4.0

16.67

9

7.2

10.5

1.0

2.0

5.13

D

2.0

3.0

4.0

Table IV Mean values of each factor Level

Table V S/N values of each factor

Mean value A

B

C

D

Level

1

13.08

14.11

9.79

14.78

2

11.67

11.7

10.58

3

10.55

9.48

14.93

Mean value A

B

C

D

1

-22.33

-22.99

-23.39

-19.82

10.62

2

-21.34

-21.37

-20.52

-20.49

9.9

3

-20.46

-19.54

-19.92

-23.48

Fig. 5 Corresponding S/N ratio values for cogging force

Fig. 6 Comparison of cogging forces

Analysis of the S/N Ratio. As far as Taguchi’s method is concerned, using the S/N ratio (signal-to-noise) to represent the minimization quality is preferred. The cogging force is considered as the quality characteristic. The S/N ratio is given by (4). n

2

S / N = -10log(∑ y i / n) i =1

(4)

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201

where yi is the quality characteristic and n is the number for each group of experiments. From the experimental results in Table III, the mean value of each influence factor can be calculated and listed in Table IV. According to Table IV and (4), the corresponding S/N ratio values of cogging force can be obtained as shown in Table V. The influence of each factor on cogging force is shown in Fig. 5. Regardless of the category of performance characteristic, a greater S/N ratio implies better performance. Therefore, the best factor-level combinations from Fig. 5 can be selected to A3-B3-C3-D1. The cogging force of the selected combination was determined through 2D FEM simulations again. Table VI and Fig. 6 compare the magnitudes of cogging force resulting from the initial machine parameters and those from Taguchi’s method. An important finding is that the cogging force has been reduced from initial value of 15.02 N to 4.01 N, auguring well for our minimization technique. Conclusion The cogging force reduction of the PMTFLSM is studied in this paper. Through theoretical analysis and Taguchi’s method with joint use of 2D FEM, the cogging force is effectively reduced. Relevant factors such as the translator pole pitch, cross-shaped core tooth width, and parameters of the permanent magnet are analyzed. Simulation results show that each parameter gives rise to different potency for reducing motor cogging force. The optimized combination of machine parameters can provide to design a PMTFLSM with low cogging force Acknowledgment The authors wish to express their appreciation to National Yunlin University of Science and Technology, and National Science Council Taiwan for providing the research equipments of this study. References [1] S.W. Youn, J.J. Lee, H.S. Yoon and C.S. Koh: A New Cogging-Free Permanent-Magnet Linear Motor, IEEE Transactions on Magnetics,Vol. 44-7 (2008), p. 1785-1790 [2] J. Wang, D. Howe and G.W. Jewell: Fringing in Tubular Permanent-Magnet Machines: Part II. Cogging Force and Its Minimization, IEEE Transactions on Magnetics,Vol. 39-6 (2003), p. 3517-3522 [3] M. Aydin, R. Qu and T.A. Lipo: Cogging Torque Minimization Technique for Multiple-Rotor, Axial-Flux, Surface-Mounted-PM Motors: Alternating Magnet Pole- Arcs in Facing Rotors. IEEE Industry Application Conf., Vol. 1 (2003), p. 555-561 [4] A. Keyhani, C.B. Studer, T. Sebastian and S.K. Murthy: Study of Cogging Torque in Permanent Magnet Machines, IEEE IAS Annual Meeting, (1997), p. 42-49 [5] J.F. Gieras: Permanent Magnet Motor Technology: Design and Applications, CRC Press, (2010) [6] Y. C. Wu, Y. C. Hong: Cogging Torque and Ripple Torque Reduction of a Novel Exterior-rotor Geared Motor, Journal of Vibroengineering, Vol. 14, Issue 4 (2012), p.1477-1485. [7] RJ. Cruise, C.F. Landy: Reduction of Cogging Forces in Linear Synchronous Motors, IEEE AFRICON, Vol. 2, (1999), p.623-626 [8] W.T. Tseng and J.J. Wang: Cogging Force Analysis for Design of a Cross-shaped Core Permanent Magnet Linear Motor, 15th International Conference on Electrical Machines and Systems ICEMS (2012) [9] R.K. Roy: Design of Experiments Using the Taguchi Method, Wiley, (2001)

Applied Mechanics and Materials Vols. 479-480 (2014) pp 202-209 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.202

Design and Optimization on Active Engine Mounting Systems for Vibration Isolation Pak-kin Wong1,a, Zhengchao Xie1,b, Yucong Cao1,c, Ming Li2,d 1

Department of Electromechanical Engineering, Faculty of Science and Technology University of Macau 2

Department of Thermal Engineering, Jilin University, Changchun, China Macau, China

a

[email protected], [email protected], [email protected], [email protected]

Keywords: test bench model, finite element analysis, linear quadratic regulator, genetic algorithm, optimization

Abstract. In this paper, based on the previous research experiences in the lumped parameter modeling and study of active control mounts model, a test bench model of ACM in powertrain is described and the vibration model is implemented in MATLAB. In order to validate the implementation of the state equations in this work, a finite element analysis (FEA) method is used in ANSYS and compared with analytical model for validate. After the validation, the control strategy is integrated into the analytical model by using the linear quadratic regulator (LQR) method, which is a well know design technique that provides practical feedback gains. Furthermore, this work examines the application of genetic algorithms (GA) in optimizing the weight matrices of LQR. Finally, this work will be useful in improved prediction and performance of vehicle NVH. Introduction During the last decade, the noise, vibration and harshness (NVH) has received attention in several publications. As a result, engine mounts are becoming more important as being not only engine vibration isolation but also a part of engine support. One of the main functions of the automotive vehicle engine mounting system is to support the engine body and provide comfort ride for passengers by reducing vibration caused by engine excitation. Traditional elastomeric mount has a simple structure but just can only provide a small damping [1]. Hydraulic engine mounts (HEM) can offer a better performance than traditional elastomeric mount in the low frequency. During low-frequency high-amplitudes vibrations, the ideal mount should exhibit large stiffness and damping characteristics to reduce relative displacement transmissibility whereas for high-frequency low-amplitude vibrations the ideal mount should have low stiffness and damping [2]. For that the characteristics of passive elastomeric mount or semi-active mount can hardly meet the requirement of broad frequency band of engine vibration and noise reduction. One of the effective methods to reach ideal vibration isolation is using active control engine mounts (ACM) and the typical active control engine mount consists of a passive hydraulic mount, an active actuator, a vibration sensor, and electronic controller. Because passive hydraulic mount has superior isolation ability in the low

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frequency range, and active actuator can provide highly efficient vibration control performance in relative high frequency range, so the active engine mount can isolate the vibration of engine in much wider frequency range. At the same time, the numerical simulation shows that the active control engine mount is capable of significantly reducing the vibration transmission. Mathematical Modeling The modeling of the active engine system is restricted to three degrees of freedom. However, note that the assumptions are made for this system [3]. (1)The displacement is small compared to system dimensions. (2)The spring force is linear around the working point. (3)The upper plate (engine body) on the vibration isolation system is a rigid body. These assumptions are used to model the vibration system in this work and Figure 1 shows the coordinate system [3].

Fig.1 Coordinate system [3] The state space format for the equations of motion of vibration system is: •

x = Ax + Bu

(1)

y = Cx + Du

(2)

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Where matrix A, B, C and D are defined as:

 0  - 4 * (k + ka)/m  0 A =  0   0  0 

B

 0  1/m   0 =   - L2/2  0   - a + L1/2

1 0 0 - 4 * Da/m 0 0 0 0 1 0 - L2^2 * (k + ka)/Jxx - Da * L2^2/Jxx 0 0 0 0 0 0 0

0

1/m

1/m

0

0

- L2/2

L2/2

0

0

a - L1/2

a - L1/2

0  0 0 , 0 1  α β  0 0 0 0 0

  1/m   0 , L2/2   0  - a + L1/2  0

- 4 * (k + ka)/m - 4 * Da/m 0 0 0  0 0 - L2^2 * (k + ka)/Jxx - Da * L2^2/Jxx 0 C =   0 0 0 0 α    1/m 1/m 1/m 1/m   D =  - L2/2 - L2/2 L2/2 L2/2 , - a + L1/2 a - L1/2 a - L1/2 - a + L1/2   

α =-(L1^2*k+(-4*L1*a+4*a^2+L1^2)*ka/Jyy),

β =-Da*(L1^2-4*L1*a+4*a^2)/Jyy where ka is the actuator spring constant, Da is the damping parameter. Validation of the Mathematical Model In this section, the mathematical model is validated using a finite element model [4].

Fig.2 The finite element model

0  0 , β 

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Table.1 Validation of the mathematical model by comparing to the finite element model in MATLAB and ANSYS Frequency (Hz) Modes

Frequency (Hz) Finite Element Model

Mathematical model

Difference (%)

The first modal

6.84

6.84

0

The second modal

11.69

11.84

1.3

The third modal

11.73

12.76

8.0

Table 1 shows the modal frequency of the vibration system from both the finite element model in Figure 2 and the mathematical model by state space method. It can be seen that both modal frequency are very close to each other, so that it can said the model implemented in this work is reliable [5].

Parameter Da damping ka stiffness m upper mass L1 L2 a Jxx inertia of x-axis Jyy inertia of y-axis

Table.2 Model parameters Value 20Ns/m 8902N/m 19.274kg 0.348m 0.3m 0m 0.1446Kg/ m4s 0.1676Kg/ m4s

Control Strategy In this section, the control strategy will be analyzed by using the linear quadratic regulator (LQR) method, which is a well-known design technique that provides practical feedback gains [6]. The LQR controller in Simulink/MATLAB for this feedback active vibration control is shown in Figure 3, where step is disturbance input, u is the control vector.

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Fig.3 Implementation of LQR controller in Simulink/MATLAB Transmitted acceleration with and without control are presented in Figure 4 and Figure 5 in time domain.

Fig.4 Control response without LQR

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Fig.5 Control response with LQR It is observed that the vibration attenuation is obtained for a period less than 0.3 second. The result confirmed that the model with LQR control algorithm is able to reduce significantly the vibration transmission. Optimization Via GA The selection of weight matrices in LQR is very importance and it straight affects the control performance. But the weight matrices are usually set by experience of designer and so the optimal control performance could not be obtained. The genetic algorithm (GA) is an optimization and search technique based on evolution, and it has been applied to many optimization problems [7, 8]. This work examines the application of genetic algorithms in optimizing the weight matrices of linear quadratic regulator [9]. The objective function for GA is: min imizeL = EA(X ) / EApas + PA(X ) / PApas + RA(X ) / RApas

(3)

Where EA is the engine body vertical acceleration, PA is the pitching acceleration, Ra is the roll acceleration, pas is the passive acceleration. The result of the GA objective function in MATLAB/GADST GA toolbox is shown below:

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Fig.6 Fitness function value in GADST Conclusions In this paper, the vibration control performance of a choosed active control engine mount system with LQR controller is evaluated. A state space (SS) model, which includes the hydraulic engine mount and active control technique are implemented and mathematically analyzed [10]. The LQR controller was built and we got LQR control method can achieve better NVH performance than passive engine mount. Also, the application of GA for optimization design of LQR weight matrices is studied. References [1] Yunhe Yu; Nagi G.Naganathan, Rao V. A literature review of automotive vehicle engine mounting systems. Mechanical, Indust. Mfg., Eng. Dept., Univ. T., Toledo, OH 43606, United States. Mechanism and Machine Theory, v 36, n 1, p 123-142, January 1, 2001 [2] A. Geisberger; A. Khajepour; F. Golnaraghi. Non-linear modeling of hydraulic mount: theory and experiment. Journal of Sound and Vibration. 249 (2002) 371-397. [3] Thorsten Muller; Stefan Hurlebaus; Uwe Stobener. Modelling and Control Techniques of an Active Vibration Isolation System. 2005 IMAC-XXIII: Conference & Exposition on Structural Dynamics. [4] Xie, Zhengchao; Shepard, W. Steve, Jr. Development of a new finite element and parametric study for plates with compressible constrained layer damping. Source: JOURNAL OF COMPOSITE MATERIALS,Volume:46, Issue: 11, Pages: 1263-1273. [5] Xie, Zhengchao; Wong, Pak Kin; Huang, Xinzheng; Wong, Hang Cheong. Design of an Active Vehicle Suspension Based on an Enhanced PID Control with Wheelbase Preview and Tuning Using Genetic Algorithm. Journal of the Chinese Society of Mechanical Engineers, Transactions of the Chinese Institute of Engineers, Series C/Chung-Kuo Chi Hsueh Kung Ch'eng Hsuebo Pao, v 33, n 2, p 103-112, April 2012. [6] Yuan Yun; Yangmin Li. Active Vibration Control Based on a 3-DOF Dual Compliant Parallel Robot Using LQR Algorithm. 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems. p 775-780, December 11, 2009. [7] Xie, Zhengchao; Wong, Pak Kin; Ian Ian Chong. A genetic algorithm-based optimization design on self-sensing active constrained layer damped rotating plates. Department of Electromechanical Engineering, University of Macau, China. Journal of Intelligent Material Systems and Structures, v 22, n 17, p 2069-2078, November 2011.

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[8] Xie, Zhengchao; Wong, Pak Kin; Chong, Ian Ian. Modeling and analysis of rotating plates by using self-sensing active constrained layer damping. JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, Volume: 26, Issue: 10,Pages: 3009-3016. [9] Xie, Zhengchao; Wong, Pak Kin; Zhang, Long. Numerical Modeling and Control of Rotating Plate with Coupled Self-Sensing and Frequency-Dependent Active Constrained Layer Damping. Source: MATHEMATICAL PROBLEMS IN ENGINEERING, Article Number:194010, Published: 2012. [10] Xie, Zhengchao; Lou, Inchio; Ung, Wai Kin. Freshwater Algal Bloom Prediction by Support Vector Machine in Macau Storage Reservoirs. Source: MATHEMATICAL PROBLEMS IN ENGINEERING. Article Number: 397473, Published: 2012.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 210-214 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.210

Harmonic Analysis and Filter Design for the Light Rail Transit Systems Cheng-Ting Hsu1,a, Hung-Ming Huang1,b, Tsun-Jen Cheng1,c and Lian-Jou Tsai1,d 1

Department of Electrical Engineering, Southern Taiwan University of Science and Technology, Tainan, 710, Taiwan a

[email protected], [email protected], c [email protected](corresponding author), [email protected] Keywords: LRTS, Harmonic, Distribution System.

Abstract. This paper presents the light rail transit system (lrts) impact on the harmonic pollution of distribution feeder. To investigate the dynamic responses of the system voltage and current, the distribution system and lrts models are set up well by using the Alternative Transients Program (ATP). The harmonic analysis of the distribution system with the lrts is executed under various operation scenarios. The 6-pulses and 12-pulses rectifier are adopted for the lrts with a direct current (dc) power supply to the trams. Furthermore, the well-designed filters have also applied to improve the harmonic distortion resulted from the lrts. Introduction To meet the growing demand of public transportation, many counties and cities are keen on planning light rail transit system (lrts) which has been developed for many years in many countries. The lrts has the advantages of low cost, low noise, low-pollution, mature technology, short construction period, and easy maintenance. It is very suitable as the public transport of the metropolitan areas, and a variety of urban transport connections [1]. In addition, it may utilize electrical power from distribution systems of power grid because of its lower power requirements than the high-speed rail, traditional railway, and mass rapid transit systems. The tram, which bears dramatic transportation changes, is an irregular load and it carries a number of pieces of power electronic equipment, the power quality of the distribution system can inevitably be affected. [2]. It is necessary to set many limits on power quality issues. The lrts with different power supply configurations may cause voltage fluctuation, unbalance, harmonic and other power quality issues. In this paper, the harmonic problem resulting from the lrts is the main investigation issue. A Taiwan Power Company (Taipower) distribution feeder with four-wire and multi-grounded system is selected for study. And the ATP software [3] is applied to establish the different power supply structures of the lrts. The Fourier analysis is applied to calculate system harmonic voltage and current. After that, passive filters are designed to reduce harmonic pollution. Impact of the lrts on the power quality of the distribution systems The traction power substation (tss) supplies the lrts with either alternating current (ac) or direct current (dc) electrical power. The ac power tends to cause three-phase unbalance problem, while the dc power supply will generate a harmonic problem. In this paper, the dc supply systems are considered and harmonic improvement techniques are also introduced. Harmonic distortion is caused by nonlinear loads in the power system. Any periodic, distorted waveform can be expressed as a sum of sinusoids. The sum of sinusoids is referred to as a Fourier series of the function f(t), as shown in Eq. (1). ∞

f ( t ) = c 0 + ∑ c h cos (h ω t + θ h ) h =1

(1)

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Where ω is the fundamental frequency of f(t); c0 is the dc component, and ch and θh are the amplitude and phase angle for the hth harmonic order respectively. In this paper, the total harmonic distortion (thd) [4] is adopted to evaluate harmonic pollution. The thd is a measure of the effective value of the harmonic components of a distorted waveform. It can be written as follows: 2

thd(%) =

2

2

2

c 2 + c3 + c4 + c5 + ...... c1

× 100%

(2)

Power electronic devices such as rectifier, converter and inverter are the main sources of harmonic distortion in power system. Theoretically, a three-phase rectifier may cause the different orders of current harmonics as shown.

h = pn ± 1 n=1,2,3….. (3) Where p is the pulse numbers of the rectifier. The magnitude of each harmonic current is proportional to the reciprocal of the harmonic order h and is given by Ih =

1 × I1 h

(4)

For example, a 6-pulses rectifier may produce harmonic orders of 5th , 7th , 11th , 13th , etc., and a 12-pulses rectifier may produce harmonic orders of 11th , 13th , 23th , 25th , etc. It is very possible to cause an equipment malfunction or even severe damage due to serious harmonic pollution. To improve power quality, the IEEE standard [4]is adopted to restrict the harmonic voltage and current generated by the customers. The total harmonic voltage distortion is limited to 5% and the harmonic voltage distortion is limited to 3% individually. As mentioned above, the use of dc power supply in the lrts will cause harmonic problem. To solve this problem, a multi-pulses rectifier can be used. In addition, the passive filters can also be installed to filter off the harmonics. For a single-tuned filter, the resonant frequency is given by fs =

1 2π LC

(5)

Where L and C is the inductance and capacitance of the filter respectively.

Modeling of the distribution system and lrts Fig. 1 depicts the equivalent model of a multi-grounded four-wire distribution system by the ATP software. The 69kV high voltage side of the distribution substation is simplified as an ideal three-phase source with a short circuit capacity of 1000MVA. The test feeder is fed by a 69kV/11.4 kV, 25 MVA transformer sited in the distribution substation. The test system is an overhead feeder with 13 distribution transformers to serve the customers. The active power and reactive power consumption of the customers are 4560kW and 3420kvar, respectively. Besides, a capacitor bank with a rating capacity of 2100kvar is installed at the end of the feeder. It is assumed that the test distribution system is operated under balanced condition. The grounding resistance of the neutral point of the substation power transformer and the grounding points along the neutral wire are assumed to be 1 ohm and 25 ohm, respectively. The electrical power of the tram must be fed from the tss. The site of the tss is 300m from the distribution substation along the feeder. Figs. 2 and 3 show the two different operation modes of dc power supply to the trams. In the tss, the utility supply voltage of 11.4kV is step down by the three-phase transformer. The 6-pulses rectifier and 12-pulses rectifier are used respectively to convert the ac voltage into a 750V dc power supply for the trams of lrts. Subsequently, it is converted into ac power with controllable voltage and frequency to drive the induction motors with a total capacity of 720kW on the tram.

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Fig. 1 Modeling the test distribution system by ATP

Fig. 2 Tram fed by the tss with a 6-pulses rectifier.

Fig. 3 Tram fed by the tss with a 12-pulses rectifier.

Harmonic analysis This section executes the harmonic power flow analysis of an lrts tram with a dc power supply, connecting to the three-phase four-wire multi-grounding distribution feeder system. Case 1:The feeder without the lrts. The three-phase harmonic current and voltage at the feeder substation terminal without the tram loading are shown in Figs 4(a) and (b).The harmonic current orders of 2th and 3th are 0.214% and 0.112%,with harmonic voltages 0.167% and 0.081%, correspondingly. And the current and voltage thd are 0.28% and 0.21% respectively. The background harmonics are generated from the transformers, but the values are quite small and they have little impact on the system. 0 .2

Ia

Ib

Ic

0.2 0.15 0.1 0.05

Va

0 .1 8 Harmonic Voltage (%)

Harmonic Current (%)

0.25

Vb

Vc

0 .1 6 0 .1 4 0 .1 2 0 .1 0 .0 8 0 .0 6 0 .0 4 0 .0 2

0 2

3

4

5

6

7 8 9 10 11 12 13 14 15 H arm onic O rder

0 2

3

4

5

6

7

8

9

10 11 12 13 14 15

H a r m o n ic O r d e r

Fig. 4 (a) Harmonic currents (b) harmonic voltages at the feeder substation terminal for Case 1

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Case 2:The feeder with a 6-pulses rectifier tss power supply to lrts. The tss exploits a 6-pulses rectifier to supply dc power to the tram as shown in Fig. 2. Figs. 5 (a) and (b) show the three-phase instantaneous ac current waveform and harmonic currents of the 6-pulses rectifier. This typical 6-pulses rectifier input waveform generates 5th,7th,11th and 13th order harmonic currents, and the three-phases average harmonic currents for 5th,7th,11th and 13th order are 42.3%,11.1%, 4.5% and 2.6%, respectively. Figs. 6(a) and(b) show the three-phase harmonic currents and voltages at the feeder substation terminal. The three-phase average harmonic currents for the 5th,and 7th order harmonics and thd are 9.5%, 3.4 % and 13.7%, respectively. And the three-phase average harmonic voltages for the 5th, and 7th order harmonics and thd are 0.94%, 0.61% and 1.19%, respectively. To reduce the harmonic pollution produced by the 6-pulses rectifier, two single-tuned passive filters are designed to filter off the 5th and 7th order harmonics. The inductance and capacitance of the 5th filter are 1.93mH and 7.2uF, respectively. Also, the inductance and capacitance of the 7th filter are 0.79mH and 4.27uF. Figs. 7 (a) and (b) show the three-phase harmonic currents and voltages at the feeder substation terminal. The three-phase average harmonic currents for the 5th,and 7th order and thd are 0.29%, 0.24% and 1.54%, respectively. And the three-phase average harmonic voltages for the 5th , and 7th order and thd are 0.058%, 0.04% and 0.28%,respectively. It is found that the harmonic pollution can be improved significantly if the proposed filters are installed. Harmonic current (%)

50 Ia

Ib

Ic

40 30 20 10 0 2

3 4 5

6 7 8

9 10 11 12 13 14 15

Harmonic order

Fig. 5 The 6-pulses rectifier three-phase (a) instantaneous current waveform (b) harmonic currents. 1.5

15 Ib

Ic

Harmonic voltage (%)

Harmonic current (%)

Ia 12 9 6 3

Va

Vb

Vc

1.2 0.9 0.6 0.3 0

0 2

3

4

5

6

2

7 8 9 10 11 12 13 14 15 H a rm o n ic o rd e r

3

4

5

6

7 8 9 10 11 12 13 14 15 Harmonic order

Fig. 6 (a) Harmonic currents (b) harmonic voltages at the feeder substation terminal for Case 2.

Harmonic current (%)

Ia

1.5

Ib

Ic

1.2

Harmonic voltage (%)

0.3

1.8

0.25

Va

Vb

Vc

0.2

0.15

0.9 0.6

0.1

0.05

0.3

0

0 2

3

4

5

6 7 8 9 10 11 12 13 14 15 Harmonic order

2 3 4 5 6 7 8 9 10 11 12 13 14 15 Harmonic order

Fig. 7 (a) Harmonic currents (b) harmonic voltages at the feeder substation terminal for Case 2 with proposed filters.

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Case 3:The feeder with a 12-pulses rectifier tss power supply to lrts. The tss exploits a 12-pulses rectifier to supply dc power to the tram as shown in Fig. 3. Fig. 8(a) and (b) show the three-phase ac input current waveform and harmonic currents of the 12-pulses rectifier. This typical 12-pulses rectifier input current waveform generates harmonic orders of 11th and 13th, and the three-phase average harmonic currents for 11th and 13th order are 4.83% and 2.86%, respectively. Figs. 9(a) and(b) show the three-phase harmonic currents and voltages at the feeder substation terminal. The three-phase average harmonic currents for the 11th , and 13th order and thd are 2.2%,0.64% and 2.47%, respectively. And the three-phase average harmonic voltages for the 11th , and 13th order harmonics and thd are 0.38%, 0.25% and 0.51%, respectively.

Harmonic current (%)

6 Ia

Ib

Ic

4

2

0 2

3

4

5

6

7 8 9 10 11 12 13 14 15 Harmonic order

Fig. 8 The 12-pulses rectifier three-phase (a) instantaneous current waveform (b) harmonic currents. 0.6

3 Ib

Ic

Va

0.5

Vb

Vc

Harmonic voltage (%)

Harmonic current (%)

Ia

2.5

0.4

2

0.3

1.5

0.2

1

0.1

0.5

0 0 2

3

4

5

6

7 8 9 10 11 12 13 14 15 Harmonic order

2

3

4

5

6

7 8 9 10 11 12 13 14 15 Harmonic order

Fig. 9 (a) Harmonic currents (b) Harmonic voltages at the feeder substation terminal for Case 3

Conclusion If a 6-pulses rectifier is adopted in the tss, it is found that the thd of the three-phase average currents and voltages can reach the values of 13.7% and 1.19%, respectively. However, they can be reduced significantly to 1.54% and 0.28% accordingly if the proposed filters are installed. Furthermore, the average three-phase harmonic currents and voltages can also be reduced to the values of 2.47% and 0.51%, respectively when a 12-pulses rectifier is adopted in the tss. Acknowledgments. This work is supported by the NSC of Taiwan (NSC 101-3113-P-214-002) References [1] P. Neroth, Waiting for nowait - engineering transport, IET Magazine on Engineering & Technology. 4,10 (2009), 28-31. [2] P. E. Sutherland, M. Waclawiak and M. F. McGranaghan, System impacts evaluation of a single-phase traction load on a 115-kV transmission system, IEEE Trans. on Power Delivery. 21,2 (2006), 837-844. [3] ATP Draw version 1.0 Users Manual, SINTEF TR A4790. (1998) [4] IEEE PES Transmission and Distribution Committee, IEEE recommended practice for monitoring electric power quality, IEEE Std 1159. (2009)

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Modeling of a shape memory alloy beam and its stochastic chaos Gen Ge1a Jia Xu2b 1

School of Mechanical Engineering, Tianjin Polytechnic University, China 2

School of Mechanical Engineering, Tianjin University, China a

[email protected], [email protected]

Keywords: SMA beam, Stochastic Chao, Safe basin erosion

Abstract: The van-der-pol hysteretic cycle was applied to describe the hysteretic nonlinear characteristic of the strain-stress relation of a shape memory alloy (SMA). A new model with nonlinear damping of a simply supported SMA beam was proposed. The Criterions determining the stochastic chaos is obtained by the random Melnikov approach. The numerical results show the effectiveness of the theoretical analysis. Clear fractal boundaries of the system's safe basin is observed. Introduction Shape Memory Alloy (SMA) is a kind of smart materials and applied in engineering field widely. There are many mechanical models of SMA proposed in recent decades [1-3]. Most of them are based on thermodynamics theory and micromechanics theory. However, those mechanical models of SMA are mostly shown as equations with subsection function which are hard to be analyzed. In this article, we developed a new kind of Von-del-Pol hysteretic nonlinear model to characterize the oscillation mechanism of a simply supported SMA beam ignoring the temperature effects on hysteresis. Then the stochatic homoclinical bifurcation was detected by applying the Criterions proposed by Wiggins. The numerical tests confirmed the theoretical analysis. The modeling of the simply supported SMA beam The experimental hysteretic nonlinearity strain-stress curve of SMA [4] is shown in Fig.1. Now, VondelPol hysteretic cycle model was introduced to describe the hysteretic characteristic of SMA.

Fig1. The experimental stain-stress Curve

Fig2. The schematic diagram of stain-stress Curve

The initial Vondelpol hysteretic cycle model describes hysteretic cycle which is symmetrical about the initial point (0, 0). Since the curve is obtained by iso-stain loading test, the loading x is chosen as 1 while loading (-1 as unloading). The model can be shown as follows

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y = f ( x ) = f 0 ( x ) + a[1 − ( x / b) 2 ] x = b1 x + b2 x 3 + a[1 − ( x / b) 2 ] x

(1)

where f 0 ( x) is skeleton curve of hysteretic cycle, a and b are coefficients Supposing the strain-stress curve of SMA is symmetrical about the point G ( ε 0 , σ 0 ), the strain-stress curve of SMA can be shown in Fig.2. Substituting y = σ − σ 0 , x = ε − ε 0 into Eqs. (1). and considering the initial stress of SMA must be avoided, when ε = 0 , there is σ = 0 . Then the final expression of the stress-stain relation of SMA is:

σ = a1ε + a2ε 2 + a3ε 3 + ( a4ε − a5ε 2 )ε

(2)

where a1 = b1 + 3b2ε 02 , a2 = −3b2ε 0 , a3 = b2 , a4 = 2a / ε 0 , a5 = a / ε 02 , One hinged-hinged flexible beam is under bending moment M. The axial excitation may be expressed in the form N = p0 + p cos(Ωt ) .The transverse Gauss White noise excitation is in the form Fη (t ) where η (t ) is the standard white noise with zero mean and intensity D. The transverse

deflection w is expressed as: w(t , x ) = u (t ) sin(π x / l ) considering the boundary conditions: at x = 0 , w = 0, wxx = 0 ; at x = l , w = 0, wxx = 0 ,where u (t ) is the amplitude. Consider the . geometrical deformation condition ε = − y∂ 2 w / ∂x 2 . The bending moment M is presented as:

M = ∫ −σ ydA = b ∫

h

2

−h

− y[a1ε + a2ε 2 + a3ε 3 + (a4ε − a5ε 2 )ε ]dy

(3)

2

The dynamical motion equation is as expressed as Eq.(4) considering the Eq.s(2),(3).

∂ 2 M / ∂x 2 + N ∂ 2 w / ∂x 2 + c∂w / ∂t + ρ A∂ 2 w / ∂t 2 = Fη (t )

(4)

where c is the linear damping coefficient, ρ is the density of the SMA, and A is the area of the cross-section of the beam.Through the Galerkin approach, we obtain differential equation of motion governing the deflection of a beam:

u+

3a3 I 3π 8 3 a1 I1π 4 − p0π 2 c 3a5 I 3π 8 2 u + ( − u ) u + u = f1 cos(Ωt ) + f 2η (t ) ρ Al 2 ρ A 4 ρ Al 2 4 ρ Al 2

(5)

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Introducing the following no dimensional variables and parameter t * = a1 I1 / ( ρ Al 2 )t ,

Ω* = a1I1 / ( ρ Al 2 )Ω while dropping the asterisks in the following analysis, the no dimensional equation of motion is obtained as follows: u + ku + α u 3 + ( µ − γ u 2 )u = 0

(6)

12 8 12 8 2 2 where k =π4 − p0π2 / aI 1 1, α = 3a3 I3π 4a1I1 , µ = cl (ρ Aa1I1) , γ = 3a5I3π 4l (ρ Aa1I1) , f1 = pπ / a1I 1 f2 = 4l / (a1I 1π )

The stochastic Melnikov approach of the system As we know, Melnikov method is widely used to study the homoclinic bifurcations.. The equations for homoclinical orbits of (6) and the Melnikov function may be written as: u (t ) = ± −2k sech( − kt ) , v(t ) = ∓ 2 / α k Sech( − kt ) Tanch( − kt )

(7)

Applying the method proposed by Wiggins[7], the stochastic Melnikov integration is

M (t1, t2 ) =

∫

+∞

−∞

v[−(µ − γ u2 )v + f1 cos[Ω(t1 − t )] + f2η(t2 − t )]dt = −I + z(t1 ) + z(t2 )

where z (t2 ) =

∫

(8)

+∞

−∞

f 2 v(t )η (t2 − t )dt . The first two integrals in Eq. (8) represent the mean of the

Melnikov process due to damping force and periodic parametric excitation, and the last integral denotes the random portion of the Melnikov process due to bounded noise η (t ) .Thus, the variance of z (t2 ) as the output of the system can be expressed as

σ Z2 =

∫

+∞

−∞

H (ω ) 2 Sη (ω )d ω

where Sη (ω ) is the spectral density of η (t ) ( Sη =

(9) D ) and H (ω ) is the frequency response 2π

function of the system obtained through Fourier transform H (ω ) = f 2

∫

+∞

v(t )e −iωt dt

−∞

The criterion for possible chaotic motion based on Melnikov process is performed in mean square representation:

[−

4µ 23 16γ 52 2 Ω 2 π 2 D k + k ] ≤[ f1 csch( )] + f 2 2 2 3α 15α α 2π 2 k

+∞

+∞

−∞

−∞

∫ (∫

v(t )e − iωt dt )2 d ω

(10)

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The system parameters are chosen as: k = −1, α = 4, γ = 0.22, µ = 0.76, D = 1, Ω = 2 .Substituting the parameters into Eq.(11), it is clear that 0.057 ≤ 0.073 f12 + 0.053 f 22

(11)

The numerical results of basin erosion The decrease of safe basin's area is often called basin erosion. Since those intersections of stable and unstable manifolds map one to another, the manifolds present a convoluted structure that extends through a wide region of the phase space. The transient orbits near such a fractal basin boundary will be as convoluted as the boundary itself. So they are expected to cross the critical line very often, increasing dramatically the number of unsafe initial conditions. In view of this point, the erosion of the safe basin is usually related to fractal basin boundary of attractors. The safe basin without erosion is drawn within the region G surrounded by the coincident stable and unstable manifolds of the conservative case of the system, which is defined by

 1 1 1  G = ( x, y ) y 2 − kx 2 + α x 4 < H (−1.2 ≤ x ≤ 1.2, −1 ≤ y ≤ 1)  2 2 4  

（12）

The points in the region are set as an initial condition to perform the simulation of system (1). When the Hamiltonian value of any phase point of the system's trajectory is larger than H (which is set as 0.1 in this paper) within 100 thousand steps, this motion initiating from the corresponding initial point is considered to be unsafe and this initial point is discarded.

(a)

(c)

(b)

(d)

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(f)

Fig.3 The safe basin of the system under harmonic and white noise excitations.(a) f1=0,f2=0, (b) f1=2.7,f2=0, (c) f1=3.2,f2=0, (d) f1=2.7,f2=1.52 (e) f1=2.7,f2=1.52 (f) f1=3.2,f2=1.52 With the papameters satisfing conidtion (11), it is obvious that the erosion can be aggravated when the driving amplitude of the harmonic excitation, or the strength of the Gaussian white noise excitation is increased. The boundary of the safe basin can also become, by and by, fractal following the increase of the strength of the excitation when the system without damping force is excited only by the Gaussian white noise.

Conclusion The vanderpol cycle is introduced to describe the hysteretic nonlinearity in the strain-stress curve of the SMA. The vibrating model of a SMA beam is built. Based on Melnikov process, the criterion for possible chaotic motion is performed in mean square representation. The fractal boundaries are shown by numerical simulations.

Acknowledgements This work was supported by the National Natural Science Foundation of China (Grant No. 11272229) and Science Foundation of Tianjin education committee (Grant No.20120902)

References [1] J.G.Boyd, D.C.Lagoudas: International Journal of P1asticity Vol. 12 (1996), pp. 805-873. [2] E.J.Graesser, F.A.Cozzarelli: Journal of Intelligent Material Systems and Structures Vol. 5 (1994), pp. 78-89 [3] F.Auricchio, J.Lubliner: International Journal of Solids and Structures Vol. 34 (1997), pp. 3601-3618 [4] Z W Zhu, J Wang and J Xu: Applied Mechanics and Materials. Vol.44 – 47(2010),pp. 537-541. [5]

Nayfeh A H: method of normal forms (New York; John wiley &Sons) P14

[6] M. Belha: Mechanics Research Communications, 1998. 25,(1): 49-58, [7] Wiggins S: Global bifurcations and chaos: analytical methods. (New York: Springer; 1988).

Applied Mechanics and Materials Vols. 479-480 (2014) pp 220-224 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.220

Parametric Study of a Micromixer with Convergent-Divergent Sinusoidal walls Arshad Afzal1,a and Kwang-Yong Kim2,b 1,2

Department of Mechanical Engineering, Inha University, Incheon, 402-751, Rep. of Korea a

[email protected], [email protected]

Keywords: Sinusoidal walls, Convergent-Divergent microchannel, Mixing index, flow Separation, Dean vortices.

Abstract: A Parametric study of a passive micromixer with convergent-divergent channel walls of sinusoidal variation is conducted numerically using combined Navier-Stokes equations and convection-diffusion model for a Reynolds number range, 10 ≤ Re ≤ 70. Water and ethanol are used as working fluids for mixing analysis. Mixing performance was used to compare different configurations (layout) of the micromixer. In comparison with previously published design, which was based on Dean vortices in the sub-channels, the new configurations offered Dean vortices in the sub-channels and recirculation zones in the recesses of the channel for effective mixing. The proposed configurations are competitive in terms mixing performance and pressure loss. Finally, effect of two geometrical parameters viz. the ratio of throat-width to diameter of circular wall and the ratio of diameter of circular wall to amplitude, on mixing performance was studied over a chosen Reynolds number range. Introduction Micromixers are widely used for various applications in the fields of lab-on-a-chip and micrototal analysis systems (µ-TAS). From the point of view of fluid dynamics, the small characteristic dimensions of the channels and absence of turbulence make mixing a difficult task at the microscale. The Reynolds number (Re = Ul/υ, where l is the characteristic cross-sectional dimension of the channel, U is the average velocity, and υ is the kinematic viscosity of the fluid) was found to be less than 100 for flows of common liquids in most of micromixers at practical pressures. Micromixers can be divided into two broad categories: active and passive. Active systems require the application of an external force or field, viz. pressure or temperature disturbance, magnetic energy, or electrical energy to enhance mixing. However, the active types require complex fabrication procedures and are difficult to incorporate with micro systems. In contrast, passive micromixers use the geometries of the device to produce complex flow field for effective mixing. Depending on the mode of operation, different realizations of the passive micromixers have been developed Stroock et al. [1] used bas-relief structures on the floor of a channel to enhance the mixing process. The patterned topography was used to generate transverse flow that increases the interfacial area between the fluids to be mixed. Jiang et al. [2] conducted a numerical study for flows through meandering channels with square cross-section. The study reveals a strong dependence of mixing efficiency on the secondary flow in the channel. An experimental study carried out by Howell et al. [3] for flow through a curved channel showed the possibility to generate lateral mixing in microfluidic systems by simply directing the flow around a bend. Chung and Shih [4] carried out numerical and experimental investigations of rhombic microchannels with splitting and recombination of fluids and flow recirculation for enhancement of mixing. Ansari et al. [5] studied a planar micromixer based on unbalanced split and cross-collisions of fluid streams for 10 ≤ Re ≤ 80. The mixing was found to depend on the combined effects of unbalanced collisions and Dean vortices in the sub-channels. In a recent study, Afzal and Kim [6] used convergent -divergent sinusoidal walls to improve the mixing performance of a micromixer [5], with regular split and recombination and Dean vortices in the sub-channels. Also, the amplitude of the sinusoidal walls significantly affected the

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mixing efficiency of the micromixer. The present study aims to investigate the mixing performance and flow characteristics of the passive micromixer [6] with layout and geometrical parameters. A computational study was carried out using three-dimensional (3-D) Navier-Stokes equations for Reynolds numbers in the range, 10 ≤ Re ≤ 70. Micromixer Geometry The geometrical layout of the micromixer used in the present study is similar to Afzal and Kim [6] as shown in Fig. 1. The convergent-divergent walls are generated using a sine function of the form, y = A sin (2πx / λ) where A is the amplitude and λ is the wavelength of the sinusoidal function, respectively. The channel centerline is the axis of symmetry. The geometrical parameters related to sinusoidal walls viz. wavelength, λ and amplitude, A was fixed at 1120 µm and 200 µm, respectively. The channel is split into two sub-channels and recombined at regular intervals along the channel length. The throat-width of the convergent-divergent sections 'w' and diameter of the inner circular wall 'D' are variable geometrical parameters. The depth ‘d’ of the channel is 125 µm as measured in the z-direction. The cross-sections of the inlet channels are rectangle with dimensions of 0.1 mm × 0.125 mm. The axial lengths of the connecting channel (Lo), main channel (Lm), and exit channel (Le) are 0.2, 8.96, and 1.5 mm, respectively. For the chosen channel length (8.96 mm), the number of mixing cycles is equal to 8. Inlet 1

y Pitch x D

w

Outlet

w

Lo

h L

Le

1st Mixing cycle

Inlet 2

Fig. 1. Geometry of convergent-divergent micromixer [6].

Numerical Formulation and Mixing Quantification To study the flow characteristics and mixing fluids in the micromixer, numerical simulations were carried out using ANSYS CFX-11 [7], a commercial computational fluid dynamics (CFD) package based on the finite volume method. Multi-component model was used to study the concentration of the fluids in the micromixer domain Multi-component model offers the solution for fluid mixtures with different physical properties (density, viscosity etc.). It assumes that the various components of the mixture are mixed at molecular level; however, the bulk motion of the fluid is modeled by using a single velocity and pressure. The details of the governing equations, boundary conditions and numerical methods can be found in a previous paper [5, 6]. The properties of the working fluids (ethanol and water were used in this simulation) were measured at 20 ºC [5, 6] . A variance-based method was employed to evaluate the mixing performance of the micromixer. The variance of the mass fraction of the mixture on a cross-sectional plane normal to the flow direction can be expressed mathematically as,

σ=

1 N (ci − cm ) 2 ∑ N i =1

(1)

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where N is the number of sampling points on the plane, ci is the mass fraction at sampling points i, and cm is the optimal mixing mass fraction. Finally, the mixing index at any cross-sectional plane perpendicular to the axial direction is defined as, M = 1-

σ2 2 σ max

(2)

where σ max is the maximum variance over the range of data. The mixing index varies from 0 mixing) to 1 (100 % mixing).

(0 %

Results and Discussion As a preliminary step, the fluid mixing in the convergent-divergent microchannel with sinusoidal walls with different split and recombination arrangements was analyzed (M1, M2 and M3 in Fig. 2). Fig. 2 shows streamlines patterns on the central xy-plane at Re = 50. The mixing performance is found to depend on recirculation zones in the recesses and Dean vortices [8] in the sub-channels. It was observed that for Re >10, recirculation zones develop in the recesses of the channel. With increased Reynolds number, the size of recirculation zones was found to increase . However, the impact of these recirculations on fluid mixing was low as can be clearly seen in Fig. 3, which shows variations of mixing index at the exit with Reynolds number for M1, M2 and M3, respectively. The overall pressure drop is important in micromixer design, especially for the integration of the device with micro-analysis systems. It can be seen that the configurations M1 and M2 are competitive at Re = 70 (maximum mixing performance) in terms of mixing index and pressure loss. M1

M2

(a)

(b)

(c)

(d)

M3 y

x Fig. 2. Streamlines on the central xy-plane for Re = 50 (a) M1 (b) M2 (c) M3 and (d) Re = 10 (M2). 1

16000 M1 M2 M3

0.9

M1 M2 M3

14000

0.8 12000

Pressure Drop, Pa

Mixing Index

0.7 0.6 0.5 0.4

10000 8000 6000

0.3 4000 0.2 2000

0.1 0

10

20

30

40

Re

50

60

70

0

10

20

30

40

50

60

70

Re

Fig. 3. (a) Mixing index and (b) Pressure drop, at the exit versus Reynolds number for configurations M1, M2 and M3.

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Fig. 4 shows ethanol mass fraction distributions on cross-sectional planes along the axial length of the micromixer at the ends of 2nd ,4th ,6th and 8th mixing cycles (Fig. 1). At Re = 10, the centrifugal forces are weak and the fluids are mixing primarily by diffusion for all configurations. As shown in Fig. 4(a), the concentration layers are well-aligned throughout the length of the channel. However, at Re = 50, the concentration layers in the sub-channels are affected by secondary flows for configuration M1 and combined Secondary and recirculation flows for configurations M2 & M3, respectively. The recirculation zones act as micro-stirrers for the ethanol and water streams, and Dean vortices results in distortion of concentration contours [6].

(a)

(b)

(c)

y (d) z Fig. 4. Ethanol mass fraction distributions on cross-sectional planes for (a) Re = 10 (M2); and (b) M1 (c) M2 (d) M3 for Re = 50. 1

1 w/ D = 0.2 w/ D = 0.3 w/ D = 0.4

0.8

0.8

0.7

0.7

0.6 0.5 0.4

0.6 0.5 0.4

0.3

0.3

0.2

0.2

0.1

0.1

0

10

20

30

D /A = 2.0 D /A = 2.5 D /A = 3.0

0.9

Mixing Index

Mixing Index

0.9

40

Re

50

60

70

0

10

20

30

40

50

60

70

Re

(a) (b) Fig. 5. Dependence of Mixing index at the exit on (a) w/ D and (b) D/ A, with Reynolds number for configuration M1. The mixing behavior of the micromixer was investigated with the ratio of, throat-width to diameter of circular wall, w/ D and diameter of circular wall to amplitude, D/ A for wide Reynolds number range, 10 ≤ Re ≤ 70 as shown in Fig. 5 (a) and (b), respectively. As can be seen, the mixing index is

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very sensitive to w/ D. With increase in w/ D, the mixing quality deteriorates over the entire Re range considered. At low Re, the effect of w/ D is to increase the effective diffusion distance in the microchannel and reduce the intensity of secondary motion for higher Re. The mixing index remained invariant with D/ A. The maximum variation (max-min) in mixing index was found to be less than 5 % in the entire parametric space of D/ A and Re considered. Conclusions A passive micromixer with convergent-divergent walls of sinusoidal variation is investigated for a Reynolds number range, 10 ≤ Re ≤ 70. Different layout of the micromixer were considered and effect of geometrical parameters viz. the ratio of throat-width to diameter of circular wall, w/ D and the ratio of diameter of circular wall to amplitude, D/ A was analyzed for mixing performance. It was found that using alternate split and recombination of fluid streams, a competitive design of micromixer was obtained compared to reference design [6]. Finally, the results showed a significant dependence of mixing performance on the geometrical parameter w/ D. However, a little variation was observed with D/ A. References [1] A. D. Stroock, S. K. W. Dertinger, A. Ajdari, I. Mezic´, H. A. Stone and G. M. Whitesides: Science Vol. 295 (2002), p. 647 [2] F. Jiang, K. S. Drese, S. Hardt, M. Küpper and F. Schönfeld: AIChE J. Vol. 50 (2004), p. 2297 [3] P. B. Howell, Jr., D. R. Mott, J. P. Golden and F. S. Ligler: Lab Chip Vol. 4 (2004), p. 663 [4] C. K. Chung and T. R. Shih: Microfluid Nanofluid Vol. 4 (2008), p. 419 [5] M. A. Ansari, K. -Y. Kim, K. Anwar and S. M. Kim: J. Micromech. Microeng. Vol. 20 (2010), p. 1 [6] A. Afzal and K. -Y. Kim: Chem. Engg. J. Vol. 203 (2012), p.182 [7] CFX-11.0: Solver Theory, ANSYS (2007). [8] W. R. Dean: Philos. Mag. Vol. 4 (1927), p. 208

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Design and Manufacturing of Drug Eluting Depot Stents with Micro-sized Drug Reservoirs Hao-Ming Hsiaoa, Chun-Ting Yeh, Tsung-Yuan Wu, Li-Wei Wu, Bor-Hann Huang and Hsiao-Nan Yang Department of Mechanical Engineering, National Taiwan University, Taipei 106, Taiwan, ROC. a

[email protected]

Keywords: Drug-eluting stent, Drug reservoir, Depot stent, Key clinical attributes, Stent fatigue life.

Abstract. The effects of micro-sized through-hole drug reservoirs on several key clinical attributes of the drug eluting depot stent were investigated. Finite element models were developed to predict the mechanical integrity of a balloon-expandable stent at various stages such as manufacturing and deployment, as well as the stent radial strength and fatigue life. Results show that (1) creating drug reservoirs on a stent could impact the stent fatigue resistance to certain degrees, and (2) drug reservoirs on the stent crowns led to much greater loss in all key clinical attributes than reservoirs on other locations. Based on these findings, an optimized depot stent was proposed/manufactured and proven to be a feasible design. Introduction A stent is a tiny, coiled wire-mesh tube that can be deployed into an artery and expanded percutaneously using a balloon catheter during angioplasty to open a narrowed artery that has become clogged by the build-up over time of fat cholesterol or other substances. In the past few years, stent technology has advanced from the bare metal stent to the drug-eluting stent (DES). The adoption of the drug-eluting stent has resulted in a dramatic lowering in restenosis rates from the 20-30% range for the bare metal stent to less than 10% [1], leading to a worldwide uptake of this new technology in healthcare. In recent years, one of the innovative new concepts is the depot stent: a drug-eluting stent dotted with tiny holes, or “reservoirs”, that can be loaded with one or more drugs and polymers to release drug more specifically, potentially in various doses or formulations [2-3]. Unlike traditional DES, the depot stent does not need to be surface coated. Researchers believe they can control drug release by putting the drug and polymer mix into these tiny holes, instead of coating the entire device. However, putting drug reservoirs on the stent struts may weaken the stent structure and compromise the mechanical integrity. Therefore, the objective of this paper is to investigate the effects of these micro-sized drug reservoirs on the mechanical integrity of the depot stent. We developed several computational models to assess key clinical attributes of the depot stent using finite element analysis (FEA). An optimized depot stent was proposed and manufactured in attempts to increase the total drug capacity without significantly comprising the mechanical integrity. Method Depot Stent Configuration. The “standard” stent, which has the same geometry as the depot stent but no drug reservoirs, was first evaluated to establish the baseline. The simulation was then performed to investigate the effects of reservoir location on the mechanical integrity of the stent. Five equally-spaced circular reservoirs were cut on two major locations of the depot stent, namely, crowns and connectors (Fig. 1). These two locations represent two extreme cases on the stress/strain spectrum, with the crowns subjected to very high stresses/strains and the connectors subjected to almost none. The straight portion connecting two crowns is called the bar arm which has the stress/strain values in between. The diameter of each circular reservoir was 50% of the strut width, and the reservoir depth was 100% completely through the strut thickness. The spacing between two neighboring reservoirs was 0.15 mm.

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Fig. 1 Depot stent with reservoirs on the connectors (left) and curved crowns (right). Since adding the number of reservoirs increases the total drug capacity, investigation was also conducted on the depot stent with reservoirs evenly distributed on the entire stent to examine whether the mechanical integrity of such a stent is further compromised. The entire stent was covered by reservoirs with the same diameter and depth aforementioned. Finite Element Analysis. A stent placed in the vasculature is subjected to various modes of loading that may consequently compromise the mechanical integrity of the stent during its functional life. Several finite element models were developed to evaluate the mechanical integrity and fatigue resistance of the stent to various loading conditions. The entire stress/strain history of the stent in each loading step was considered to incorporate the effects of accumulated residual stresses/strains throughout the procedures. The performed FEA simulation determines the state of stress and strain, radial strength, and fatigue safety factor imposed by the following continuous steps: Step 1: Stent crimping from 2.54 mm to 2 mm OD (crimp) Step 2: Stent recoil after crimping (crimp-recoil) Step 3: Stent expansion to 6.0 mm ID (expansion) Step 4: Stent recoil after expansion (expansion-recoil) Step.5:.Stent fatigue under 180/80 mmHg systolic/diastolic pressure, or stent radial strength Since a stent has repeated patterns in the axial direction, three representative rings, as shown in Fig 1, were modeled to save computational time. The stent model was meshed with the 8-node linear brick element in incompatible mode (C3D8I). The element size was one-sixth of the strut width and one-third of strut thickness. The material properties of L-605 cobalt-chromium alloy were used along with the ABAQUS von Mises plasticity model with isotropic hardening. The Young’s modulus, Poisson ratio, and the yield stress are 203 GPa, 0.3, and 590 MPa, respectively. The ultimate stress, ultimate strain, and fatigue endurance limit are 1689 MPa, 60%, and 483 MPa, respectively [4-5]. In order to simulate the manufacturing (crimped onto a balloon catheter) and in vivo deployment (expanded into an artery) steps, two cylinders with diameters of 2.54 mm and 1.12 mm were added into the model with one inside the stent and the other outside the stent. The inside and outside cylinders were meshed with the 4-node quadrilateral surface element (SFM3D4). A frictionless contact was defined to prevent surface penetration with contact pairs defined. Stent Laser Cutting. When making a stent, several procedures of design, manufacturing, and testing are typically employed. A 2-D stent design is first sketched on the x–y plane and coded into the 3-D cylindrical coordinate system by wrapping the 2-D sketch around a target cylinder using the commercial CAD/CAM/CAE software. The coded stent geometry is then fed into the laser machine and the design pattern is cut onto the hypotubes. The fabricated stents are finally tested to evaluate whether the stent performance meets the initial design intent. A pulsed fiber laser machine with the maximum cutting power of 30 watts was developed (Fig. 2). Its software compiled the imported stent sketch and the designed cutting path into machine codes. The hypotube was held by the bushing holder on one end and the xyz positioner (Aerotech Inc.) on the other end. The xyz positioner was able to provide the axial feeding and the circumstantial rotation required for the stent laser cutting. The positioner accuracy was ±2 µm and ±25 arc seconds in the axial and circumstantial direction, respectively. The laser cutting head moved vertically to a height

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where the laser beam was able to focus on the tubing wall. The local controller adjusted the blowing of assistant gas (air and nitrogen) to reduce the heat affected zone.

Fig. 2 Schematic of pulsed fiber laser setup with xyz positioner. Results and Discussion Effects of Reservoir Location on Stent Mechanical Integrity. From Table 1, it is clear that the creation of through-hole reservoirs on connectors resulted in little or no change in equivalent plastic strain (PEEQ) and radial strength (RS). However, the degradation in the fatigue safety factor (FSF), a 10% reduction compared to the standard case, was the most significant of the key clinical attributes investigated. Table 1 Model Standard Hole-Connector Hole-Crown Hole-All Hole-Optimized

Effects of Through-Hole Reservoirs on Mechanical Integrity RS Variation PEEQ Variation FSF Variation (N/mm) (%) (%Str) (%) (%) 3.78 40.5 3.05 3.77 -0.26 40.8 0.74 2.75 -9.84 3.21 -15.08 47.4 17.04 1.68 -44.92 3.08 -18.52 46.8 15.56 2.02 -33.77 3.41 -9.79 36.7 -9.38 2.66 -12.79

However, the depot stent with through-hole reservoirs on the crowns led to significant changes in equivalent plastic strain (+17%) and radial strength (-15%) when compared to the standard case. Its fatigue safety factor declined even further from the standard case of 3.05 to 1.68 with a staggering 45% reduction, almost trimmed by half from its original value. From the comparison of these two reservoir locations (connector vs. crown), it is clear that creating reservoirs on the stent crowns has the most significant impact. Figure 3 shows the contour plots of the equivalent plastic strain developed during the crimping and expansion stages of the loading process. The maximum stress/strain occurred at the six o’clock location of each reservoir (on the inner surface of the crown). The reservoirs were distorted under expansion when the stent was subjected to higher stresses/strains. Table 1 also shows that, for the depot stent with through-hole reservoirs distributed all over the entire stent, all key stent attributes suffered quite significant losses in this specific case. Given that the curved crown is always a critical region in stent design, the optimized depot stent should have a through-hole design with reservoirs on the stent bar arms and/or connectors to have the maximum drug capacity without significantly comprising its mechanical integrity.

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Fig. 3 Contour plots of the equivalent plastic strain (PEEQ) of the stent with reservoirs on the crowns at crimping (left) and expansion (right). Proposed Depot Stent. We proposed an optimized depot stent which has reservoirs evenly distributed on the entire stent except crowns (Figure 4). The depot stent prototype was successfully fabricated. For the depot stent with reservoirs on the entire stent, the stress/strain distribution, as indicated by the colors, changed significantly due to the appearance of the through-hole reservoirs on the stent crowns (Figure 5(b)). However, for the proposed depot stent, the maximum equivalent plastic strain was actually reduced by 9% and the stress/strain distribution was spread out more uniformly when compared to other two cases (Figure 5(c)). Figure 5 also shows the Goodman diagram comparison of the pulsatile fatigue loading among the three cases. Calculated data of the standard case were well below the Goodman diagram failure line, indicating that the studied balloon-expandable stent (standard case) is able to pass the fatigue life of 4 x 108 cycles under pulsatile fatigue loading. Comparing Figure 5(a) to Figure 5(b), wherein the very same stent but with through-hole reservoirs on the entire stent was assessed, shows that the calculated data of this specific depot stent migrated towards the Goodman diagram failure line, indicating a significant drop of 34% in fatigue safety factor and thus much lower fatigue resistance to systolic/diastolic blood pressure. However, for the proposed depot stent, the fatigue safety factor was reduced marginally by only 13% when compared to the standard case (Figure 5(c)).

Fig. 4 Proposed depot stent (left) and its unpolished prototype (right). Conclusion The objective of this paper is to study the effects of through-hole drug reservoirs on key stent clinical attributes of the depot stent. In summary, the total drug capacity of the proposed depot stent could be tripled, with marginal trade-off in its key clinical attributes. The radial strength and the fatigue safety factor of the proposed depot stent were reduced by only 10% and 13%, respectively. Therefore, this depot stent is feasible and could carry more drugs and deliver them smartly than the current drug-eluting stents, thereby opening up a wide variety of new treatment potentials and opportunities. These results can serve as the guidelines to help future depot stent designs to achieve the best combination of stent mechanical integrity and smart drug delivery.

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Fig. 5 PEEQ contour plots of the standard stent (top), the stent with reservoirs on the entire stent (middle), and the optimized depot stent (bottom) and their corresponding Goodman diagrams. Acknowledgments This research was supported by the National Science Council and NTU-ITRI Nano Center in Taiwan through Grants NSC-101-2221-E-002-025 and NTU-ITRI-101E32074I. The authors gratefully appreciate the support and help from the NSC and NTU-ITRI Nano Center. References [1] M. Morice, P.W. Serruys, J.E. Sousa, J. Fajadet, E.B. Hayashi, M. Perin, A. Colombo, G. Schuler, P. Barragan, G. Guagliumi, F. Molnar, R. Falotico, A randomized comparison of a sirolimus-eluting stent with a standard stent for coronary revascularization, N. Engl. J. Med. 346 (2002) 1773-1780. [2] A. Finkelstein, D. McClean, S. Kar, K. Takizawa, K. Varghese, N. Baek, K. Park, M.C. Fishbein, R. Makkar, F. Litvack, N.L. Eigler, Local drug delivery via a coronary stent with programmable release pharmacokinetics, Circulation. 107 (2003) 777-784. [3] P.W. Serruys, G. Sianos, A. Abizaid, J. Aoki, P. den Heijer, H. Bonnier, P. Smits, D. McClean, S. Verheye, J. Belardi, J. Condado, M. Pieper, L. Gambone, M. Bressers, J. Symons, E. Sousa, F. Litvack, The effect of variable dose and release kinetics on neointimal hyperplasia using a novel paclitaxel-eluting stent platform - The paclitaxel in-stent controlled elution study (PISCES), J. Am. Coll. Cardiol. 46 (2005) 253-260. [4] H.M. Hsiao, A. Nikanorov, S. Prabhu, M.K. Razavi, Respiration-induced kidney motion on cobalt-chromium stent fatigue resistance, J. Biomed. Mater. Res. Part B, 91B (2009) 508-516. [5] H.M. Hsiao, Y.H. Chiu, K.H. Lee, C.H. Lin, Computational modeling of effects of intravascular stent design on key mechanical and hemodynamic behavior, Comput. Aided Design. 44 (2012) 757-765.

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Finite-Element Analysis of the Magnetic Field in a Magnetic Gear Mechanism Yi-Chang Wu1,a, Bo-Syuan Jian1 1

Department of Mechanical Engineering, National Yunlin University of Science & Technology, Yunlin County 640, Taiwan, R.O.C. a

[email protected]

Keywords: Magnetic gear, magnetic field, finite-element method.

Abstract. This paper presents a finite-element analysis (FEA) of the magnetic field of a magnetic gear mechanism. First, an external type magnetic gear mechanism, which consists of two identical magnetic gears with sector-shaped permanent magnets, is introduced. Then, the magnetostatic field distribution and transmitted torque of the magnetic gear mechanism are simulated by a commercial FEA package Ansoft/ Maxwell. Next, the effects of design parameters, including the air-gap length, the number of magnetic pole pairs and the height of permanent magnets, on the maximum transmitted torque are discussed. The results of this work are beneficial to the design of magnetic gear mechanisms. Introduction A gear is a rotating machine part which meshes with another gear to transmit motion and torque. A gear mechanism changes the speed, torque and direction of a power source and is widely used in industrial machinery. Traditionally, mechanical gears with cut teeth are employed for the purpose of transmission involving high torque densities. However, they usually require lubrication and cooling, and noise, vibration, reliability and efficiency can be significant concerns for any relevant engineering tasks. Recently, the concept of non-contact torque transmission through the interaction of permanent magnets has been attracting increasing industry attention. Magnetic gears offer the advantage insofar as the magnetic coupling between the input and output shafts is essentially frictionless saving lubrication costs and some maintenance. They cannot be damaged in over-torque situations as they merely slip once the maximum torque transmission has been overcome. Unlike mechanical gears, magnetic gears have unique features of overload protection, high efficiency, low noise, precise peak torque transmission and tolerance with regard to misalignment due to the magnetic coupling features. It has been shown that a transmitted torque density of 100kNm/m3 can be obtained, which is comparable to that of mechanical gears [1]. Therefore, such contactless torque transmission devices can be used in the following application fields: (1) overload protection applications requiring high levels of safety, such as cordless power tools, factory conveying equipments, and office automation apparatuses; (2) clean room applications requiring no metal powders, such as wafer-transfer robots, TFT-LCD/PDP manufacturing equipment, wafer steppers and semiconductor step-and-scan systems; and (3) powered mobility applications requiring high levels of efficiency, such as transmission systems for electric bikes, scooters, and other vehicles. The first patent related to a magnetic gear mechanism with only permanent magnets is found in a US patent by Faus [2] in 1941. Its configuration is quite similar to a set of meshed pin gears with different numbers of permanent magnets on two supporting disks. Hetzel [3] proposed a spur magnetic gear set with even numbers of rectangular permanent magnets on two rotors for a radial magnetic power transmission. The velocity ratio of this magnetic gear set is inversely proportional to the numbers of permanent magnets on two rotors. In 1991, Mabe [4] presented a magnetic planetary gear train, which is a speed changing mechanism with two degrees-of-freedom. It consists of a magnetic sun gear, a non-magnetic carrier, a magnetic ring gear and several magnetic planet gears. Even numbers of sector-shaped permanent magnets with alternating polarities are spaced around and inset into the circumference of the yoke of the magnetic gear. Yao et al. [5,6] proposed an external magnetic gear

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set with sector-shaped magnets mounted on the outer yoke surface. They presented a computer simulation and experimental analyses of the magnetic coupling between two magnetic gears with parallel axes. Prediction of the magnetic field is a prerequisite to investigating the performance of a magnetic gear mechanism. Notably, the finite-element method has been successfully used in the design and analysis of engineering devices. It is now an indispensable tool in the magnetic field analysis of magnetic transmission devices. Compared with analytical methods, the merits of the finite-element method include high accuracy and reliability. It is also applicable to any complicated geometrical structure. In this paper, the magnetostatic field distribution of an external magnetic gear mechanism is simulated by a commercial finite-element analysis (FEA) package Ansoft/ Maxwell. The effects of design parameters, including the number of magnetic poles, the height of magnets and the air-gap length between two meshed magnetic gears, on the maximum transmitted torque are discussed. Notably, the results of this discussion are shown to be useful in the context of designing magnetic gear mechanisms. An External Magnetic Gear Mechanism Fig. 1 shows the configuration of an external magnetic gear mechanism with parallel axes, which is analog to an external mechanical gear set. Each magnetic gear consists of three main parts: the non-magnetic shaft, the magnetic yoke to support magnets as well as to provide flux return paths and sector-shaped permanent magnets with alternate magnetic poles. Considering the magnetic circuit of such a magnetic set, permanent magnets on one shaft initially drive magnetic flux across the air gap and into permanent magnets on the other shaft. Then the flux travels circumferentially along the yoke and goes back across the air gap to form closed flux loops.

Fig.1 An external magnetic gear set Finite-Element Analysis The two-dimensional finite-element method is applied to assist in numerically calculating the magnetostatic field distribution and the transmitted torque of the magnetic gear mechanism shown in Fig. 1. It is a powerful and reliable tool to deal with the design and analysis of magnetic gear devices before fabricating actual prototypes. A commercial FEA package Ansoft/Maxwell is employed to the magnetic field and transmitted torque analyses. Fig. 2 shows the magnetic gear set to be analyzed, which is created by the Ansoft/Maxwell pre-processor. Fig. 3 presents the finite element meshing, where the total number of mesh elements is 17,410. The mesh quality is sufficiently high to guarantee the accuracy of numerical computation. The corresponding values of the magnetic properties and geometric dimensions of the external magnetic gear mechanism are listed in Table 1. Fig. 4 demonstrates the flux line distribution. Since the torque transmission is achieved by the direct interaction of closely arrayed permanent magnets, only these permanent magnets contribute to generate the transmitted torque. Fig. 5 shows the magnetic flux density distribution of the external magnetic gear mechanism when the driving gear rotates along half of the magnet arc. This is the position where the maximum magnetic flux density and maximum transmitted torque occur. Fig. 6 illustrates, when the driven gear is kept still and the driving gear is rotating, the calculated waveform of the transmitted torque developed on two gears. Here the maximum transmitted torque is 1.44Nm.

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The period of the transmitted torque waveform is 360°/n= 360°/6=60°. The symbol n represents the number of pole pairs. Fig. 7 shows the maximum transmitted torque plotted against the length of the air-gap. Table 1

Permanent magnetic properties and geometric dimensions of the external magnetic gear mechanism, as shown in Fig. 1 NdFeB (N-35) permanent magnet Items Values Remanence (T) 1.335 Relative permeability 1.09 Magnet arc (degree) 30 Magnet height (mm) 5.00 Axial length (mm) 20.00 Number of pole pairs 6 Geometric dimensions of the magnetic gear mechanism Items Values Inner radius of the iron yoke (mm) 10.00 Outer radius of the iron yoke (mm) 15.00 Air-gap length (mm) 1.50

Fig. 2 The external magnetic gear mechanism created by the Ansoft/Maxwell pre-processor

Fig. 4 Flux line distribution of the external magnetic gear mechanism

Fig. 3 Finite element meshing of the external magnetic gear mechanism

Fig. 5 Magnetic flux density distribution of the external magnetic gear mechanism

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Fig. 7 Maximum transmitted torque versus the length of the air-gap We set the volume of the permanent magnet of each magnetic gear mechanism to be identical for comparison purposes. It is clear that the maximum transmitted torque decreases as the length of the air-gap increases. As shown in Fig. 8, for this magnetic gear mechanism, the maximum transmitted torque increases as the magnet height increases and diminishes after it reaches 3mm. As presented in Fig. 9, the maximum transmitted torque of this external magnetic gear mechanism decreases in accordance with the increase of the number of pole pairs. Fig. 6 Transmitted torque waveform

Fig. 8 The maximum transmitted torque versus the magnet height

Fig. 9 The maximum transmitted torque versus the number of pole pairs

Conclusions In this paper, the FEA for the magentostatic field of an external magnetic gear mechanism with a gear ratio of 1:1 has been presented. The maximum transmitted torque of this external magnetic gear mechanism decreases in accordance with the increases of the air-gap lengths and the number of magnetic pole pairs. Upcoming work on this topic involves investigating the effects of gear ratios of meshed magnetic gears and the shapes of permanent magnets on the air-gap flux density and transmitted torque. Acknowledgment The authors are grateful to the National Science Council (Taiwan, R.O.C) for supporting this research under grant NSC 102-2221-E-224-016-MY2. References [1] K. Atallah and D. Howe: IEEE Trans. Magn. Vol. 37 (2001), p. 2844 [2] H.T. Faus, U.S. Patent 2,243,555 (1941) [3] M. Hetzel, U.S. Patent 3,792,578 (1974) [4] W.J. Mabe, U.S. Patent 5,013,949 (1991) [5] Y.D. Yao, D.R. Huang, S.M. Lin and S.J. Wang: IEEE Trans. Magn. Vol. 32 (1996), p. 710 [6] Y.D. Yao, D.R. Huang, C.C. Hsieh, D.Y. Chiang and S.J. Wang: IEEE Trans. Magn. Vol. 33 (1997), p. 2203

Applied Mechanics and Materials Vols. 479-480 (2014) pp 234-238 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.234

Kinematic Analysis of an 8-Speed Bicycle Transmission Hub Yi-Chang Wu1, a, Pei-Wun Ren2, Li-An Chen1 1

Department of Mechanical Engineering, National Yunlin University of Science & Technology, Taiwan, R.O.C. 2

Food Industry Research & Development Institute a

[email protected]

Keywords: kinematic analysis, transmission hub, gear mechanism.

Abstract. A transmission hub is a speed changing mechanism which is an important device in the transmission system of bicycles. This paper presents a kinematic analysis of an 8-speed bicycle transmission hub by using the fundamental circuit method. First, a distributed-flow type planetary gear mechanism, consisting of two parallel-connected transmission units and one differential unit, and the corresponding clutch sequence table of an 8-speed transmission hub are introduced. Based on the fundamental circuits, four kinematic equations of the transmission hub are derived. Then, the speed ratio of each speed is formulated, which is a function of the gear ratios of external and internal gear pairs. By submitting the numbers of gear teeth into these formulas, the value of speed ratio at each speed can be calculated. Finally, the power-flow diagrams at related speeds are presented to illustrate the power-flow paths of the transmission hub. Introduction A multi-speed transmission hub is a modern gearing device whereby the transmission mechanism is fully enclosed within the rear hub of the bicycle. In contrast to the derailleur system where the whole mechanism is exposed to the elements, the gears and lubricants of the transmission hub is sealed within the shell of the gear hub protecting it from water, grit and impact. The transmission hub usually requires less maintenance and can be more reliable over time than the comparable derailleur system, which may require more adjustments and replacement parts. An important feature is that the multi-speed transmission hub is able to change speed ratios when the rear wheel of the bicycle is not rotating. This can be useful for commuter cycling where frequent stops are necessary and for mountain biking where rough terrain is problematic for rolling gear changes. Therefore, multi-speed transmission hubs are becoming more and more popular on bicycles nowadays. Four companies currently build multi-speed transmission hubs. Sturmey-Archer and SRAM have a heritage dating back to the first decade of the 20th century. Shimano has manufactured transmission hubs since 1957, and Rohloff AG is a relatively new company producing a very technically advanced transmission hub. Notably, each manufacturer is discreet about the development of transmission hubs as they wish to protect commercial secrets. A multi-speed transmission hub generally employs a planetary gear train (PGT) to achieve a set of desired speed ratios [1]. However, the available number of speed ratios is governed by the kinematic structure of the PGT. Therefore, the kinematic analysis of the PGT, which deals with the relative motion among the various links by neglecting the inertial effects and the forces that cause the motion, is an important component of the study of multi-speed transmission hubs. There are different methods regarding the kinematic analysis of PGTs, e.g., the tabular method, the relative velocity method, the vector loop method, the train value method and the fundamental circuit method. Notably, the fundamental circuit method associated with the graph theory seems to be the most straightforward one. Graph theory used to represent the topological structure of a geared mechanism for the first time was introduced by Buchsbaum and Freudenstein [2]. Based on graph representation, Freudenstein and Yang [3] applied the concept of fundamental circuits for the kinematic and static-force analysis of planetary spur-gear trains. Later, Tsai [4] developed an algorithm for the kinematic analysis of the PGT with any number of links, which can be easily implemented on a computer for the automated analysis of PGTs. Yan and Hsieh [5,6] proposed a

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generalized approach for the kinematic analysis of all types of PGTs, including planetary bevel-gear trains and worm-gear differentials, using generalized fundamental circuit equations and compatibility equations. Hsu et al. [7] presented an interactive computer program for the kinematic analysis of PGTs with any number of degrees-of-freedom (DOF) according to the proposed graph representation of multiple joints. Liu et al. [8] determined kinematic relations between inputs and outputs in geared mechanisms based on the concept of kinematic fractionation. These systematic procedures utilizing graph theory provide efficient tools for the design and development of PGTs in numerous industrial applications. In this paper, the fundamental circuit method is employed to analyze the speed ratio of a bicycle transmission hub. First, the topological structure of an 8-speed transmission hub is introduced, and the features of this drive hub are also addressed. Then, kinematic equations derived from fundamental circuit equations of the planetary gear train are listed. The speed ratio at each speed of the transmission hub is calculated to clarify the numbers of under drives, direct drives and over drives. Finally, power-flow paths of this transmission hub at corresponding speeds are illustrated and checked to verify the feasibility of the 8-speed bicycle transmission hub. An 8-Speed Transmission Hub For any transmission hub, the number of speed ratios is determined by the kinematic structure of its PGT. Fig. 1(a) shows the schematic diagram of an 8-speed bicycle transmission hub, which is a kind of distributed-flow type drive hub, proposed by Wu et al. [9]; Fig. 1(b) presents the corresponding clutch sequence table. As seen in Fig. 1(a), the number of each link is labeled and the gear-teeth number of each gear element is also denoted. It consists of two parallel-connected transmission units and one differential unit to provide eight forward speeds. The input power from the sprocket splits into transmission Units I and II, then converges on the differential Unit III to transmit the output power to the hub shell. Transmission Unit I and differential Unit III are basic PGTs, namely PGT I and PGT III. Transmission Unit II comprises two basic PGTs II-1 and II-2 arranged axially in series. Each speed of this 8-speed transmission hub is controlled by the activation of rotating clutches A, B and C (one-way pawl-and-ratchet clutches) and locking clutches Cf1, Cf2 and Cf3 (slot-with-block clutches).

(a) (b) Fig. 1 Schematic diagram and clutching sequence table of an 8-speed bicycle transmission hub Kinematic Analysis For a PGT, a fundamental circuit is made up of one gear pair, which consists of two meshing gears i and j, and one carrier k to maintain a constant center distance between the two gears. This is symbolically denoted as (i, j)(k) [4]. In addition, the corresponding fundamental circuit equation is: ωi − γ j/i ωj + (γ j/i − 1)ωk = 0

(1)

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where ωi is the angular speed of link i, γ j/i = ± Z j / Zi represents the gear ratio, and Zi is the number of teeth on gear i. The positive sign of the gear ratio is for an internal gear pair and negative for an external gear pair. According to the structural characteristics, the number of fundamental circuits is equal to the number of gear pairs of a PGT. As depicted in Fig. 1(a), there are eight gear pairs in the transmission hub and eight fundamental circuits are identified as (1, 9)5, (4R, 9)5, (2, 10)5, (6R, 10)5, (3, 11)6C, (7R, 11)6C, (4S, 12)7C and (8, 12)7C, respectively. The related fundamental circuit equations are: ω1 − γ9/1ω9 + ( γ9/1 − 1)ω5 = 0

(2)

ω4 − γ9/ 4 ω9 + ( γ9/ 4 − 1) ω5 = 0

(3)

ω2 − γ10/ 2 ω10 + ( γ10/ 2 − 1)ω5 = 0

(4)

ω6 − γ10/ 6 ω10 + ( γ10/ 6 − 1) ω5 = 0

(5)

ω3 − γ11/3 ω11 + ( γ11/3 − 1)ω6 = 0

(6)

ω7 − γ11/7 ω11 + ( γ11/ 7 − 1)ω6 = 0

(7)

ω4 − γ12/ 4 ω12 + ( γ12/ 4 − 1)ω7 = 0

(8)

ω8 − γ12/8 ω12 + ( γ12/8 − 1)ω7 = 0

(9)

R

R

R

R

R

R

C

R

R

S

R

S

C

S

C

C

where ω4R = ω4S

=

ω4 , ω6 = ω6 R

= C

ω6 ,

and ω7 R = ω7 C

=

ω7

, respectively. By eliminating the angular

speeds of planet gears ω9 , ω10 , ω11 and ω12 from Eqs. (2)-(9), four kinematic equations, which are related to the relative motion among coaxial links of a PGT, of this transmission hub can be derived as: ω − K ω + ( K − 1) ω = 0

(10)

ω − K ω + ( K − 1) ω = 0

(11)

ω − K ω + ( K − 1) ω = 0

(12)

1

2

3

1 4

2

3

6

7

1

2

3

5

5

6

ω − K ω + ( K − 1) ω = 0

(13) where K1=-Ζ4R/Ζ1, K2=-Ζ6R/Ζ2, K3=-Ζ7R/Ζ3, and K4=-Ζ8/Ζ4S, respectively. Based on Eqs. (10)-(13), the formula of the speed ratio, which is defined as the ratio of the input link speed to the output link speed, of each speed for the 8-apeed transmission hub can be derived. By submitting the numbers of gear teeth into each formula, the value of the speed ratio at each speed is calculated, as shown in Table 1. As depicted in Table 1, speed S-1 is an under drive, speed S-2 is a direct drive and speeds S-3, S-4, S-5, S-6, S-7 and S-8 are over drives. 4

4 8

4

7

Analysis of Power-Flow Path The analysis of the power-flow path is a preliminary task in investigating the forces and torque values carried by individual components. It is also useful for engineering designers in checking the validity of the power-flow paths at each speed. We take speed S-1 as an expository example. At this speed, rotating clutches B and C are engaged, so carrier 5 is integrated with PGT II-1, PGT II-2 and carrier 7C to form a structural assembly. As can be seen in Fig. 2(a), the input power from the sprocket is transmitted to carrier 5 and splits into two power-flow paths. The first power-flow path is from carrier 5 via planet

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gear 9 to ring gear 4R and sun gear 4S. The second power-flow path is from carrier 5 via PGTs II-1 and II-2 to carrier 7C. The power from these two power-flow paths then converges on PGT III. Finally, the output power is transmitted from ring gear 8 to the hub shell. Fig. 2 shows the power-flow path of the 8-speed transmission hub at each speed. Table 1 The speed ratio of each speed of the 8-speed transmission hub Speed Formula Speed ratio K K 1 4 K K −1 1 4

S-1 S-2

1

S-3

1

S-5

1

 K −1 (K −1)(K −1)  4  1 + 2  K K  K 1 K 4  2 4

0.87 0.76

 K −1 (K −1)(K −1)  4  1 + 3  K K K K  1 4  3 4

0.68

K K 4 3 K K − K +1 4 3 4

S-6

S-8

1.00

K K 4 2 K K − K +1 4 2 4

S-4

S-7

1.18

1

1

0.62

 K −1 (K −1)(K −1)(K −1)  3 4  1 + 2  K K K  K 1 K 4  2 3 4

0.53

 1 (K −1)( K −1)(K −1)  3 4  + 2  K K K  K 4  2 3 4

0.49

(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)

Fig. 2 The power-flow path of each speed of the 8-speed transmission hub

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Conclusion In this paper, a kinematic analysis is performed to determine the speed ratio of an 8-speed bicycle transmission hub by using the fundamental circuit method. The results show that this transmission hub possesses an under drive, a direct drive and six over drives. The analysis of power-flow paths is useful for engineering designers in checking the validity of the power-flow paths at each speed. The proposed analysis approach can also be applied for the kinematic analysis of any multi-speed bicycle transmission hubs which use planetary gear trains. Acknowledgements The authors are grateful to the National Science Council (TAIWAN, R.O.C) for supporting this research under grant NSC 101-2221-E-224-019. References [1] Y. C. Wu and P. W. Ren: Information (Accepted on 2012.08.31). [2] F. Buchsbaum and F. Freudenstein: J. Mech. Vol. 5 (1970), p. 357 [3] F. Freudenstein and A. T. Yang: Mech. Mach. Theory Vol. 7 (1972), p. 263 [4] L. W. Tsai: Proceedings of the 9th Applied Mechanism Conference, Kansas, USA Vol. 1 (1985), p. 1 [5] H. S. Yan and L. C. Hsieh: Proceedings of the 8th World Congress on the Theory of Machines and Mechanisms, Prague, Czechoslovakia Vol. 6 (1991), p. 153 [6] L. C. Hsieh and H. S. Yan: Int. J. Veh. Des. Vol. 13 (1992), p. 494 [7] C. H. Hsu and K. T. Lam: ASME Transactions, J. Mech. Des. Vol. 114 (1992), p. 196 [8] C. P. Liu, D. Z. Chen and Y. T. Chang: Mech. Mach. Theory Vol. 39 (2004), p. 1207 [9] Y. C. Wu, P. W. Ren, C. H. Cheng and L. A. Chen: Proceedings of the 2013 Conference on Precision Machinery and Manufacturing Technology, Kenting, Taiwan (2013), Paper No. A003-1 (In Chinese)

Applied Mechanics and Materials Vols. 479-480 (2014) pp 239-243 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.239

Ground Vibration Characteristics for High-Speed Trains on Embankments Yit-Jin Chen1, Song-Wei Lin2 and Yi-Jiun Shen3 1

Department of Civil Engineering, Chung Yuan Christian University, Chung-Li 32023, Taiwan

2

GeoTech Science Co., 2F., No. 200, Sec. 3, Datong Rd., Xizhi Dist., New Taipei City 221, Taiwan

3

Structural Engineering Department II, CECI Engineering Consultants, Inc., No. 323 Yangguang St., Neihu District, Taipei 11491, Taiwan a

[email protected], [email protected], [email protected]

Keywords: Ground vibration, High-speed trains, Embankments, Influence distance, Propagation.

Abstract. This study explores the characteristics of ground vibration induced by Taiwan high-speed trains on embankments. A series of field measurement data is used for evaluating near-field vibration, far-field vibration, and vibration influence distance. Various influence factors, including train speed, ground shear wave velocity, frequency dependence, and volume of the structure, are applied for evaluation. Based on the analyses, the near-field ground vibration mainly depends on the train speed, ground shear wave velocity, and frequency dependence. The far-field vibration propagation is affected by ground shear wave velocity and frequency dependence. In general, the high frequency range has the highest attenuation coefficient and the low frequency range has the lowest. The influence distance in hard ground is the farthest, whereas the soft ground is the shortest. Finally, a specific ground vibration assessment is established using these characteristics. Introduction Ground vibration induced by high-speed trains can reach levels that disturb humans and interrupt sensitive instrumentation. Hence, numerous researchers have studied ground vibration characteristics. The main factors that affect the vibration levels can be grouped into vibration source, vibration path, and vibration receiver [1–2]. Recently, Chen et al. [3] measured the ground vibration induced by Taiwan high-speed trains on embankments with a wide variety of train speeds, geological conditions, and embankment heights. Their study mainly focused on the far-field vibration propagation. For engineering practice, understanding the characteristics of the vibration source, path, and influence distance on various influence factors is essential. Furthermore, a convenient assessment model is useful for engineers to first-order predict possible vibration effects in the preliminary design stage. Therefore, systematically understanding the ground vibration characteristics and establishing a simple vibration assessment for high-speed trains on embankments is important. In this study, extensive measurement data for Taiwan high-speed trains on embankments is used to analyze vibration characteristics. Then, based on these characteristics, a table is established that can be used as a preliminary ground vibration assessment.

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Database for Analysis A series of measurements was performed for this study. These measurements comprised different geological conditions and train speeds in eleven sites. Sites 1, 2, 8 and 10 were used for the study of near-field vibration and far-field vibration propagation, whereas other sites were used for near-field vibration only. The measurement of near-field vibration is 25 m from the track center. A wide variety of geological conditions and ground shear wave velocities were included. The geological conditions included alluvial soils (silty clay, silty sand, and sandy silt), gravels, and rocks (mudstone and sandstone), ranging from soft ground to hard ground. The ground shear wave velocity is used as an indicator to describe soil stiffness. The average ground shear wave velocity (Vs) was between 170 and 650 m/s. The database was considered a sufficient representative for the evaluation of ground vibration characteristics. Analysis Method The ground vibration level is expressed in terms of its root-mean-square (RMS) velocity using the decibel (dB) scale, and defined as: VL (in dB) = 20 log10 (vm/vref) (1) -6 where vm = the measured velocity, and vref = the referred velocity = 10 in/sec. The concept of total vibration energy was used in the study. The overall vibration level of 1/3 octave bands was used to evaluate the total vibration energy. The overall vibration level is transformed from the RMS vibration level of each 1/3 octave band using the following equation: n

VLoa = 10

∑ log1010VL(fk)/10 = 10 log10(100.1 VL(f1) +100.1 VL(f2)+．．．+100.1 VL(fn))

(2)

k =1

where VLoa is the overall vibration level in decibel, fk is the center frequency of each 1/3 octave band and VL(fk) is the vibration level for each center frequency. A simple equation by Gutowski and Dym [4], modified from Bornitz [5], was used to estimate vibration decay. Gutowski and Dym considered both geometric and material damping under a line-source into an expression of the Rayleigh wave (R-wave) attenuation as follows: V1=V2 × e − α ( r − r ) (3) where V1 and V2 are the vibration amplitudes at distances r1 and r2, respectively; and α is the vibration attenuation coefficient for the soil material. 2

1

Two types of ground vibration attenuations were evaluated from the measured results. Attenuation was initially analyzed regardless of the dependence of frequency. The overall vibration level (VLoa) of entire 1/3 octave bands (1 to 100 Hz), as shown in Eqn. (2), was used to evaluate the total vibration energy. With the overall vibration level of each measured point, the attenuation coefficient for high-speed trains can be back-calculated from four measurement points using Eqn. (3). The second approach involved the classification of the attenuation based on the low, middle, and high frequency ranges. The selection of the frequency range was based on the observation of many practical results and related literature [3,6,7]. Based on these principles, 21 frequencies for the 1/3 octave band with 1 to 100 Hz were divided into three groups, including low (1 to 8 Hz), middle (10 to 25 Hz), and high (31.5 to 100 Hz) frequency ranges.

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The vibration influence distance is defined as the location of the measured vibration which is close to the background vibration at a specific measurement site. Owing to the measurement site conditions, difficulties may arise in finding the required distance where the vibration is completely attenuated. Therefore, certain attenuation distances were inferred from the analysis of measured near-field and background vibrations, as well as vibration attenuation coefficient. Analysis Results of Near-Field Vibration The relationship between train speed and overall vibration level (VLoa) for entire, low, middle and high frequency ranges is indicated in Figs. 1(a) to 1(d), respectively. On average, the overall vibration level for entire frequency range increases slightly with increasing train speed, as shown in Fig. 1(a). This result is consistent with general supposition. For the frequency dependence factor, the trend is obvious in both low and middle frequency ranges [Figs. 1(b) and 1(c)], but not in high frequency range [Fig. 1(d)]. Furthermore, the vibration level seems to no longer increase and becomes flat for any frequency range in which the train speed is above 250 km/hr. Figs. 2(a) to 2(d) show the relationship of overall vibration level and ground shear wave velocity (Vs) for entire, low, middle, and high frequency ranges, respectively. For consistency, the data in Fig. 2 were from the train speed between 250 to 300 km/hr. As such, the near field vibration level decreases with increasing Vs in any frequency range. Therefore, the results show that the softer the ground, the higher the near field vibration level. The overall vibration level for entire frequency range is between 67 and 70 dB for the soft ground. Moreover, the trend is relatively obvious in high frequency range. However, the difference is minimal in the low and middle frequency ranges. The factor of the volume of structure, which is due to different embankment heights, has also been examined in this study, and no clear relationship was observed. Therefore, it is not presented. 100

100

100

(a) 80

40

20

60

40

20

150

200

250

300

0 100

350

80

Vibration Level, VLoa (dB)

60

60

40

20

150

200

250

300

350

60

40

20

0 100

Train Speed (km/hr)

Train Speed (km/hr)

(d)

80

Vibration Level, VLoa (dB)

Vibration Level, VL oa (dB)

Vibration Level, VL oa (dB)

80

0 100

100

(c)

(b)

150

200

250

300

350

0 100

Train Speed (km/hr)

150

200

250

300

350

Train Speed (km/hr)

Fig. 1. Relationship of VLoa and Train Speed for (a) Entire, (b) Low, (c) Middle, and (d) High Frequency Ranges 100 100

Alluvium Gravel Rock

(a)

90

(b)

90

80

Vibration Level, VL oa (dB)

Vibration Level, VL oa (dB)

80

100

Alluvium Gravel Rock

70

60

50

40

30

Alluvium Gravel Rock

(c)

90

70

60

50

40

30

70

60

50

40

30

Alluvium Gravel Rock

(d)

80

80

Vibration Level, VL oa (dB)

90

Vibration Level, VL oa (dB)

100

70

60

50

40

30

20

20

20

20

10

10

10

10

0 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800

0 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800

0 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800

0 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800

Ground Shear Wave Velocity, Vs (m/s)

Ground Shear Wave Velocity, Vs (m/s)

Ground Shear Wave Velocity, Vs (m/s)

Ground Shear Wave Velocity, Vs (m/s)

Fig. 2. Relationship of VLoa and Vs for (a) Entire, (b) Low, (c) Middle, and (d) High Frequency Ranges

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Analysis Results of Far-Field Vibration Propagation Chen et al. [4] studied the far-field vibration propagation for Taiwan high-speed trains on embankments. Fig. 3(a) shows the relationship between the attenuation coefficient (α) and ground shear wave velocity for entire frequency range. Regression analyses show that α is given: (n = 35, r2 = 0.87, SD = 0.38)

α = 0.58 + 549/Vs

(4)

in which n = data points, r2 = coefficient of determination, SD = standard deviation. The value of α decreases with increasing Vs. Therefore, the attenuation of ground vibration induced by high-speed trains is more obvious on the soft ground rather than on the hard ground. The variation of mean α values is 1.2-4.0 (10-3/m) following the order from hard to soft ground. The relationships of α and Vs for various frequency ranges are shown in Fig. 3(b). The low frequency range has the smallest α value when the high frequency range presents the highest value for all sites. Therefore, the attenuation in the low frequency range is less than that in the high frequency range. 6

10

Site 1 Site 2 Site 3 Site 4

Mean Attenuation Coefficient, a (10-3/m)

Attenuation Coefficient, a (10-3/m)

(a)

a = 0.58 + 549/VS n = 35, r2 = 0.87, SD = 0.38 4

2

(b)

High frequency range Middle frequency range Low frequency range

8

6

4

2

0

0 0

200

400

600

800

0

1000

200

400

600

800

1000

Ground Shear Wave Velocity, VS (m/s)

Ground Shear Wave Velocity, VS (m/s)

Fig. 3. Relationship of α and Vs for (a) Entire and (b) Various Frequency Ranges [4] Analysis Results of Vibration Influence Distance Train speed, ground shear wave velocity and frequency dependence are considered the main influence factors to the vibration influence distance (D). Figs. 4(a) to 4(d) show the relationship between vibration influence distance and ground shear wave velocity for entire, low, middle, and high frequency ranges, respectively. In these figures, the train speed is divided into three groups (160 to 180 km/hr, 180 to 250 km/hr, and >250 km/hr) to observe its effects. However, this impact seems minimal in the measured train speed range. 1000

1000

1000

200

600

400

200 0 100

200

300

400

500

600

700

Ground Shear Wave Velocity, Vs (m/s)

Influence Distance, D (m)

400

(d) 800

800

Influence Distance, D (m)

800

Influence Distance, D (m )

Influence D istance, D (m )

800

600

1000

(c)

(b)

(a)

600

400

600

400

200

200

800

0 100

200

300

400

500

600

700

Ground Shear Wave Velocity, Vs (m/s)

800

0 100

200

300

400

500

600

700

Ground Shear Wave Velocity, Vs (m/s)

800

0 100

200

300

400

500

600

700

800

Ground Shear Wave Velocity, Vs (m/s)

Fig. 4. Relationship of D, Vs, and Train Speed for (a) Entire, (b) Low, (c) Middle, and (d) High Frequency Ranges

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From Fig. 4(a), the influence distance clearly increases with increasing Vs. The influence distances in alluvium, gravel, and rock are 170 m to 200 m, 210 m to 230 m, and 260 to 310 m, respectively. The embankment in rock has the farthest distance of all the three soil types, whereas the alluvium has the shortest distance. Observing the frequency dependence, the low frequency range generally has the farthest influence distance. Meanwhile, the influence distance increases as the ground shear wave velocity increases for middle and high frequency ranges. Summary of Vibration Characteristics Based on above analysis results, the characteristics of ground vibration induced by Taiwan high-speed trains on embankments are summarized in Table 1. For convenience, the soil type is grouped into alluvium, gravel, and rock. Table 1. Summary of Vibration Characteristics for High-Speed Trains on Embankments Ground shear wave velocity Vs (m/s)

Alluvium

Ground type

Mean attenuation coefficienta

Overall vibration levela VLoa (dB) b

α (10 /m)

Entire

b

Low

Middle

High

170-240

65-69

45-52

50-64

Gravel

330-440

56-63

44-50

Rock

460-650

56-59

43-52

：

b

Influence distancea D (m)

-3

b

Entire

Low

Middle

High

Entire

Low

Middle

High

63-65

3.41

0.58

2.15

7.27

165-185 280-500 260-390 130-140

40-58

48-56

2.35

0.36

2.55

4.18

170-210 450-650 120-260 130-170

54-56

50-55

1.26

0.73

1.48

2.08

345-390 300-560 435-460 300-350

Note a - Train speed is between 160 km/hr and 300 km/hr. b - These express in entire, low, middle, and high frequency ranges, respectively.

Conclusions Based on the analysis results, the following conclusions were observed. a. The overall vibration level increases slightly with increasing train speed for entire frequency range. Meanwhile, the trend is obvious in both low and middle frequency ranges. b. The near field vibration level decreases with increasing ground shear wave velocity in any frequency range. c. The value of attenuation coefficient decreases with increasing ground shear wave velocity. d. The low frequency range has the smallest attenuation coefficient value when the high frequency range presents the highest value. e. The embankment in rock has the farthest distance, whereas the alluvium has the shortest distance. Furthermore, the low frequency generally presents the farthest influence distance. References [1] U.S. Department of Transportation, Federal Transit Administration, Transit Noise and Vibration Impact Assessment, Report Number FTA-VA-90-1003-06, (2006) [2] Y.J. Chen, S.H. Ju, S.H. Ni and Y.J. Shen: submitted to Journal of Sound and Vibration (2007) [3] Y.J. Chen, S.M. Chang and C.K. Han: submitted to Noise Control Engineering Journal (2010) [4] T. G. Gutowski and C. L. Dym: submitted to Journal of Sound and Vibration (1976) [5] G. Bornitz: submitted to Journal of Springer (1931) [6]

Y.J. Chen, T.J. Chiu and K.Y. Chen: submitted to Noise Control Engineering Journal (2011)

[7]

Y.J. Chen, T.C. Huang and Y.J. Shen: submitted to Noise Control Engineering Journal (2013)

Applied Mechanics and Materials Vols. 479-480 (2014) pp 244-248 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.244

Dynamic response of a Viscoelastic Damping Isolator under High Cyclic Loading B.W. Huang1a, J.-G. Tseng 2b and Y.L. Ke 1c 1 2

Department of Mechanical Engineering, Cheng Shiu University, Kaohsiung, TAIWAN.

Bachelor Program of Medical Engineering, Cheng Shiu University, Kaohsiung, TAIWAN. a

[email protected], [email protected] [email protected]

Keywords: damping isolator, viscoelastic, vibration.

Abstract. Viscoelastic damping isolator (VDI) is a new way to reduce the vibration of punch press in automobiles, motorcycles, IT, aerospace, mold and other industries. It not only reduces the vibration of large punching machine and equipment, but also decreases its maintenance costs and avoids endangering the surrounding environment. VDI is composed of partitions, damping fluid, steel springs and level adjusters. Different number of the partitions are welded on upper and lower rectangular steel plates, respectively. Steel springs are placed at the edges between the plates to support up to 150 tons of weight of the punch press. Screw level adjusters are place between lower and thick bottom plates to adjust the horizontal level of the isolator. The damping fluid is filled in the space between interlacing partitions approximate 60% of the height of the composed isolator. The impact energy produced by the presser is dissipated by shear deformation between the damping fluid and partitions. This article used 3D graphing software and finite element method (FEM) to investigate the dynamic characteristic of the damping isolator after impacted by the puncher. The normal mode analysis of the VDI is obtained. The isolator is settled within 0.3 seconds after 300,000 N shock impact and satisfies industrial specification of large punchers with loading frequency of 100 cycle/min. Introduction Commercially available isolators are mostly rubber-type and low viscosity liquid flow style dampers. After years of usage, rubber material occur aging and hardening problems. Similarly, the choice of damping coefficient of fluid flow type low viscous damping fluid should avoid small amount quantity and too high damping factor; otherwise axial force will increase close to the installation structure of the damper. The current isolators in the market cannot be adjusted the horizontal level directly but individually adjust the height of the isolator by hanging up the press equipment. Lu et al. [1] presented a experimentally verified generalized Maxwell model (GMM) for long-stroke fluid dampers installed under seismic isolation systems to provide supplementary damping. The GMM model is accurate in simulating the hysteretic property of the fluid damper under a wide range of excitation frequencies. Liu and Shao [2] used the finite element software to establish single and multi-layered rail model with constrained damped dynamic vibration absorber, with the consideration of irregularity effect. Vibration amplitude was reduced by 65% when installed a single-layered constrained damped dynamic vibration absorber. Pan et al. [3] presented the concept, design procedure, simulation and experimental evaluation results of a prototype optimal shock-damping caster in detail. The structure of the designed caster was simpler and the peak acceleration was 65% of the existing one. Cheung et al. [4] derived the HN optimization design of a hybrid vibration absorber (HVA), including both passive and active elements, for the minimization of the resonant vibration amplitude of a single degree-of- freedom (SDOF) vibrating structure by using the fixed-points theory. The proposed HVA not only overcome the limitation of low vibration absorption due to low mass ratio between the absorber and the primary structure but also provided good vibration reduction

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performance even at a low mass ratio. Saidi et al. [5] proposed a passive viscoelastic damper to reduce the vibrations of light material composite systems and long span floor. The rectification measures were normally required to reduce floor accelerations and the damper can be tuned to the fundamental frequency of the floor and can be designed to achieve various damping values. Oh and Choi [6] proposed a semi-active strategy to minimize performance deterioration of variable damping isolator due to chattering effects. Numerical simulation result obtained using a simplified on-board payload model demonstrate that the proposed LQ semi-active control logic with variable damping achieves much better isolation performance than the conventional semi-active control laws under single and fly-wheel force excitation environments. Abhinav Alva et al. [7] modeled a tuned mass absorber system when subjected to varying external frequencies to suppress the vibrations of a single degree of freedom system operating at its fundamental natural frequency by using ANSYS software. Valliappan and Qi [8] proposed a "smart" mild steel damper to provide active damping for seismic control of structures by FEM. Wong and Cheung [9] derived optimum parameters of a dynamic vibration absorber of non-traditional form and provided a large suppression of resonant vibration amplitude of the primary system excited by ground motion than the traditional absorber. Milecki and Hauke [10] investigated a semi-active industrial shock absorber with magnetorheological (MR) fluid, which is capable of controlling the stopping process of moving objects, e.g. on transportation lines. This research exams the normal mode vibration and impact analysis of VDI system by employing FEM. The simple structure of VDI can reduce the vibration amplitude excited by the large punchers with high loading 300,000 N and the 100 cycle/min frequency. Finite Element Analysis This study bases on the concept design of a VDI and employs Solidworks software to establish a 3D model including upper rubber board, upper steel plate, edge spring, central viscoelastic damping cavity, 90o arcuate partitions, lower steel plate, level adjusting device, bottom steel plate, and bottom rubber board. Outermost ring is the damper cavity housing composed of upper and lower parts of the partitions. The inner rings arranged intertwine among the upper and lower partitions. That is from outside to inside, the first, third, and fifth partitions are welded with the lower plate, while the second, fourth partitions are welded with the upper plate, as shown in Figure 1. The 3D graph is then imported into ANSYS software, low carbon steel, spring steel, nitrile rubber, and assumed damping lipid is set with corresponding material parameters including Young's modulus, Poisson's ratio and density, as shown in Table 1. Solid187 and Solid186 elements are chosen for steel and rubber material, respectively. These two kinds of elements are suitable for irregular grid, possess plasticity, hyperelasticity, stress strengthening, large deformation and large strain characteristics, and can reduce the free mesh inaccuracy problem. Figure 2 shows the mesh of the VDI system. The convergence of the VDI system is tested before normal analysis. Impact function is introduced at the upper plate of VDI to exam the settling time of the system. Select lower left corner of the top plate to measure the displacement and other conditions after the impact.

Figure 1 3D graphic model of the VDI.

Figure 2 Mesh diagram of the VDI system

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Table 1 Material parameter list of VDI system Young’s Poisson’s Density modulus Ratio (g/cm3) (MPa)

Material

Low carbon steel 200,000 (S25C) Spring steel (SUP-9) 200,000

0.3

1

0.29

7.85

Nitrile rubber (NBR)

3.5

0.49

7.87

Assume PDMS material to replace damping lipid

1.53

0.49

910.5

Table 2. Natural frequencies of first four modes of the VDI system Mode

Natural Frequencies (Hz)

1

39.26

2

42.34

3

46.91

4

79.30

Figure 3 Impact function position of the VDI system

Figure 4. The first mode shape at 39.26 Hz.

Figure 5. The second mode shape at 42.34 Hz.

Figure 6. Time response after the shock impact to the VDI system

Numerical Results and Discussions The convergence test of the VDI system without damping lipid is performed, before executing further analysis, to get stabilized element size and shape for more accurate results. The first natural frequency of the system is converged to 24.6 Hz with the element number approaches 120,000. Therefore, 120,000 elements are used for the following normal mode and impact analysis. Normal model analysis is performed of the VDI system with loaded viscoelastic damping fluid. To avoid fluid structure interaction and simplify the problem, low Young's modulus structural material (Polydimethyl- siloxane, PDMS) is assumed to replace the damping fluid. First four fundamental natural frequencies of the VDI system is shown in Table2. The mode shapes of first and second normal modes of frequency 39.26 Hz and 42.34 Hz are shown in Figure 4 and 5, respectively.

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Impact function with time duration of 0.01 second and impact force of 300,000N are simulated in the program. The results show that the steel spring can support the expected loading and the damping lipid can absorb the shock energy, y direction, within 0.3 seconds after the impact, as shown in Figure 6. These results satisfy the industrial specification of large punchers with 100 cycle/min operation frequency. Figure 7 show total deformation and distribution of the VDI under 300,000N shock impact loading. For the total deformation, the vibration amplitude will be also depressed within 0.4 seconds after the impact. It is found that the vibration can be depressed in this VDI system. The stress was also considered in this work. The maximum stress and distribution of the VDI under 300,000N shock impact loading is illustrated in Fig. 8. Figure shows that the impact stress is decreased after 0.3 second.

Figure 7. Total deformation and distribution underunder shock impact loading

Figure 8. Maximum stress and distribution shock impact loading

Conclusions This study uses ANSYS FEM to simulate dynamic characteristic. The obtained results are summarized as follows: 1. The viscoelastic damping lipid is assumed to be a low strength structure material (PDMS) to avoid fluid structure interaction and simply the problem. 2. The obtained natural frequencies can be used for designing fast punch press with the operation frequencies avoid those natural frequencies. 3. VDI system can dissipate the shock energy within 0.3 seconds from the punch press under 300,000N impact loading and can satisfy the industrial specification of large punchers with the frequency of 100 cycle/min. Acknowledgements This work presentation was financially supported by the National Science Council, Republic of China, through Grant NSC101-2221-E-230-001. References [1] L.Y. Lu, G.L. Lin and M.H. Shih: Eng. Struct., Vol. 34 (2012), p. 111. [2] L. Liu and W. Shao: Procedia Eng., Vol. 15 (2011), p. 4983. [3] R. Pan, J. Jiang and R.O. Buchal: J. Sound Vib., Vol. 289 (2006), p. 278. [4] Y.L. Cheung, W.O. Wongn and L. Cheng: J. Sound Vib., Vol. 331 (2012), p. 750. [5] I. Saidi, E.F. Gada,b, J.L. Wilson and N. Haritos: Eng. Struct., Vol. 33 (2011), p. 3317. [6] H.U. Oh and Y.J. Choi: Sens. Actuators, A, Vol. 165 (2011), p. 385.

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[7] R. Abhinav Alva and K.V. Gangadharan:, ARPN J. of Eng. Appl. Sci., Vol. 6 (2011), p. 77. [8] S. Valliappan and K. Qi: Comput. Struct., Vol. 81 (2003), p. 1009. [9] W.O. Wong and Y.L. Cheung: Eng. Struct., Vol. 30 (2008), p. 282. [10] A. Milecki and M. Hauke: Mech. Syst. Signal Process., Vol. 28 (2012), p. 528.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 249-253 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.249

Thermal Performances in Ribbed Rectangular Convergent and Divergent Channels M. S. Lee1,a, S. S. Jeong1, S. W. Ahn2,b 1

Dp. of Mechanical and System Engineering, Graduate School, Gyeongsang National University, Tongyeong 650-160, Republic of Korea 2 Dpt. of Mechanical and System Engineering, Gyeongsang National University, Tongyeong 650160, Republic of Korea a [email protected], b [email protected]

Keywords: ribbed rectangular convergent/divergent channel; heat transfer; friction factor; thermal performance comparison

Abstract. The rectangular convergent/divergent channels with one sided ribbed surface only have the inclination angles of 0.72oand1.43o at which the ribbed wall is manufactured with a fixed rib height ( e) =10 mm and the ratio of rib spacing (p) to height( e) =10. The comparison shows that among the four channels (Dho/Dhi =0.67, 0.86, 1.16, and1.49) the divergent channel of Dho/Dhi =1.49 has the highest thermal performance at the identical mass flow rate, and the divergent channel of Dho/Dhii =1.16 has the highest at the identical pumping power and static pressure drop. Introduction In the experimental investigations reported in the literature, the internal cooling passage of a gas turbine have been modeled by either square or rectangular channels equipped with turbulence promoters on the walls. The effects of geometric parameters such as the relative rib height, rib pitch, flow attack angle, duct aspect ratio, rib cross-section geometry, and rib configuration ( straight or vshape; continuous or discrete) have broadly investigated. The following is only a brief review of partial works. Han et al. [1] conducted a systematic investigation of the heat transfer and friction losses in rib-roughened surface. Wang et al. [2] found that for the developing region in the ribbed square convergent/divergent channels with the inclination of 1.0o a mild streamwise variation of cross-sectional area may induce significant difference in the developing local and average heat transfer behaviors. In this study, an experimental measurement was conducted to find the developed heat transfer and friction characteristics of turbulent flow in ribbed rectangular convergent/divergent stationary channels with uniform heat flux boundary condition on two walls only. The rectangular convergent/divergent channels have the inclination angles of 0.72oand 1.43o at the left and right sides only. Experimental Setup The forced air goes through a honeycomb, an entrance section of 2.5 m length, a test section of 1.0 m and a 3 inch diameter, 1.4 m length pipe, equipped with a multiport averaging Pitot tube to measure the flow rate. The straight square duct has a cross-section of 100 x 100 mm2. The rectangular convergent/divergent channels have the cross-sections of 100 x 100 mm2, 100 x 75 mm2 and 100 x 50 mm2 at the inlet and outlet as shown in Figure 1. The rib size and arrangement are presented in Figure 1 with a fixed rib height (e)= 10 mm and the ratio of rib spacing (p)/height(e) =10. The left and right side walls are heated and the top and bottom walls are insulated. The copper plate method ( in which each wall in the channel is divided into multiple regions comprising one high conductivity copper plate each) has been employed. Each of the 4 walls is subdivided into 10 sub-sequential streamwise regions, comprised of 1 copper plate (100 mm x 100 mm) each. The transversely located ribs are attached on the right side wall only. The other surfaces are left smooth. Ribs used are made of copper and attached to the copper plates using 0.05 mm thick double sided tape (to ensure thermal contact). The power input can be varied by controlling a single phase

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(a) Convergent channel

(b) Divergent channel

(c) Rib size and arrangement(right side surface) Fig. 1 Diagram of test section transformer and measured by measuring the voltage applied to the heater by a digital multi-meter. The thermocouple arrangement is presented in Figure 1. Each copper plate is instrumented with T type copper-constantan thermocouples; the right (ribbed) and left (smooth) copper plates have 2 thermocouples each. The thermocouples are buried inside a 0.4 mm diameter hole drilled on the plate and held in place by using an epoxy resin. These thermocouples are connected to a Yokogawa DA 100. The test section is installed in a 50 mm thick pine wood housing. Further insulation is provided by encapsulating the entire test section in a thick layer of glass wool. 12 pressure taps are set up at the same interval along the top smooth wall centerline. Static pressure is measured using a digital manometer with a resolution up to 0.01 mmH2O at the static pressure of 19.99mmH2O, depending on its value. The maximum uncertainty in the average Nusselt number was estimated to be less than 11 % and that for the friction factor less than 12%. The local heat transfer coefficient hx was calculated from the total net heat transfer rate (Q-Qloss) and the difference of the local wall temperature and the local bulk mean air temperature.

,

(1)

,

Where A is the heat transfer area of test section which means the projected area at the ribbed wall. The local wall temperature used in Eq. (1) was read from the output of the thermocouple. The local bulk air temperature of the air was calculated by the following equation: ,







(2)

Where A(x) is the heat transfer area from the channel inlet to the position where the local heat transfer coefficient was determined. The local Nusselt numbers were defined by:

/

(3)

Where h is the channel average convective heat transfer coefficient. The hydraulic diameter Dh represents Dhs at the straight square channel, Dhi at the convergent channel, and Dho at the divergent channel, respectively. The subscripts s, i, and o mean the straight cross sectional test section, the inlet of test section, and the exit of test section, respectively. The Reynolds number is defined by:

(4)

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Where the channel average velocity, stands for at the straight channel, at the convergent channel, and at the divergent channel, respectively. The friction factor of the convergent/divergent channel is defined as: (5) Where the total pressure difference ∆Pe = − − . In the tests, the Reynolds number varied from 15,000 to 89,000. Static pressure drops (Pi –Po) were measured along from the taps on the smooth top surface. Results and Discussion The Reynolds number dependences of the average friction factors for the various types of channels are presented in Figure 2. On the contrary to the public opinion, the friction factor of the ribbed divergent channel of Dho/Dhi =1.16 has somewhat the same level with the straight square channel of Dho/Dhi =1.0 having ribs, even though the channel of Dho/Dhi =1.16 is lower in the static pressure drops. It is attributed to the fact that the ratio of Dho/Dhi =1.16 produces the dynamic pressure difference due to the different cross-sectional area between the inlet and exit of the test section. The subscript ss is what was predicted by by Blasius’ equation for the smooth circular tube. The Reynolds number dependency of friction factors for all of ratios of Dho/Dhi exhibits the conventional character; friction factor has generally a decreasing level with increasing the Reynolds number. Figure 2 includes the experimental data of Chandra et al. [3] for the wall heat transfer and friction characteristics of a fully developed turbulent air in a constant cross sectional rectangular channel with transverse ribs on one wall, at which the pitch-to-rib height ratio, p/e, was kept at 8 and rib height-to-hydraulic diameter ratio, e/Dh, was kept at 0.0625. This reports a similar result with Dho/Dhi =1.0 in the present work. The friction factors in the channel of Dho/Dhi =0.67 are greater than those in the Dho/Dhi =1.49. It can be inferred that the convergent channel (Dho/Dhi =0.67) has the reducing cross-sectional area along the flow direction, leading to greater air blockage and vortex in the higher velocity. Regressing the rectangular convergent and divergent channel friction factor measurements, the following empirical power law correlations are obtained: 0.67≤Dho/ Dhi ≤ 0.86

f = 0.052 Re-0.0319(Dho/ Dhi) -5.14

0.86≤Dho/ Dhi ≤ 1.0

f= 0.05 Re-0.12(Dho/ Dhi) -11.9 f = 0.05 Re-0.115(Dho/ Dhi) 0.644 f = 0.0000125Re-0.57(Dho/ Dhi) 9.564

1. 0 ≤Dho/ Dhi ≤ 1.16

1. 16 ≤Dho/ Dhi ≤ 1.49

(6) (7) (8) (9)

Figure 3 compares the channel average Nusselt numbers against the ratio of Dho/Dhi on the ordinate with Reynolds number on the abscissa. In the rectangular convergent channels (Dho/Dhi i =0.67, 0.86) almost the same Nusselt numbers produce regardless of the ratio of Dho/Dhi . However, in rectangular divergent channels (Dho/Dhi =1.16, 1.49) the greater Nusselt number is observed in the larger ratio of Dho/Dhi. Measured Nusselt number for this current work can be correlated by: Nu = 0.48 Re0.58Pr0.4 (Dho/ Dhi) -0.21 0.58

Nu = 0.505 Re

0.4

Pr

(Dho/ Dhi)

0.39

0.67≤Dho/ Dhi ≤ 1.0

1.0≤Dho/ Dhi ≤ 1.49

(10) (11)

The three widely used constraints for thermal performance comparisons are adopted: identical flow rate, identical pumping power, and identical pressure drop. Based on the constant property assumption and the same characteristic length, the formulations of the three constraints are given in the following:

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Figure 2 Friction factors

Figure 3 Channel average Nusselt numbers

Identical Mass Flow Rate * = (12) Where the superscript “*” stands for the compared channel and the quantity without * for the reference channel(straight cross sectional channel). From Eq.(12), we can obtain the following relationship between the Reynolds number of the channel compared and the reference channel. *=

(

Where ∗

(

*/

(

∗

stands for the cross-section area.

(13) For the three cases compared, (

*/

=1 and

= 1.

Identical Pumping Power ∆

∆

*=

(14)

This leads to *=



(15)

∗

Identical Pressure Drop ∗= Then we have *=

(16) ⁄

∗

(17)

The ratio of the heat transfer between the compared channel and reference channel may be formulated as follows: ∗

=





∗

(18)

Where Nu represents the experimental correlation between the Nusselt number and the Reynolds number for the ribbed straight cross sectional channel. The comparisons of the channel average heat transfer performance for the four channels are shown in Figure 4, where the ratios of the heat transfer in the four ribbed channels are presented. For example, the symbol C1/S represents the ratio of the heat transfer of C1 (Dho/Dhi =0.67) over that of S(Dho/Dhi =1.0), and the symbol D1/S stands for the ratio of the heat transfer of D1(Dho/Dhi =1.16) over that of S. It can be seen from Figure 4(a) that in the identical mass flow rate, the heat transfer enhancement is about 16 to 25% and -9 to 0 % for the ribbed divergent channels (D1/S, D2/S) and convergent channels (C1/S, C2/S) , respectively, compared with the ribbed channel of straight cross section. From Figure 4(b), it can

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(a) Identical mass flow rate

253

(b) Identical pumping power

(c) Identical pressure drop Figure 4 Thermal performance comparisons be observed that in the identical pumping power, the heat transfer enhancement is about -43 to 9% and -62 to -37% for the ribbed divergent channels and convergent channels, respectively. Figure 4(c) represents that in the identical pressure drop, the heat transfer enhancement is about -29 to 13 % and -54 to -30% for the ribbed divergent channels and convergent channels. The above comparison definitely indicates that for the ribbed channels, the divergent channels have the higher thermal performance than those of the convergent channels. Conclusions Under the three constraints of comparison (identical mass flow rate, pumping power and pressure drop), the ribbed divergent channel of Dho/Dhi =1.16 has the greatest thermal performance at the identical pumping power and pressure drop, while the heat transfer in the ribbed convergent channels is generally deteriorated compared to the ribbed divergent channel. Acknowledgment This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (grant number: 2012001401). References [1] Han, J. C., Glicksman, L. R., Rohsenow, W. M., Int. J. Heat Mass Transfer, Vol. 21(1978), pp. 1143-1156. [2] Wang, L. B., Tao, W. Q., Wang, Q. W., Wong, T. T., Int. J. Heat and Fluid Flow, Vol. 22(2001), pp. 603-613. [3] Chandra, P. R., Niland, M. E., Han, J. C., ASME Journal of Turbomachinery, Vol. 119(1997), pp. 374-380.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 254-258 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.254

Finite Element Analysis of Bridge-Vehicle System With Randomness Tai-Ping Chang1, a 1

Department of Construction Engineering, National Kaohsiung First University of Science and Technology, Kaohsiung, 824, Taiwan a

[email protected]

Keywords: Bridge-vehicle system, Finite element method, Random material properties, Gaussian random process, Karhunen–Loéve expansion.

Abstract. This paper investigates the statistical dynamic behavior on the bridge–vehicle interaction problem with randomness in material properties and moving loads. The bridge is modeled as a beam with Gaussian random elastic modulus and mass density of material with random moving forces on top. The mathematical model of the bridge–vehicle system is established based on the finite element model in which the Gaussian random processes are represented by the Karhunen–Loéve expansion. Some statistical response such as the mean value and standard deviation of the deflections of the beam are obtained and checked by Monte Carlo simulation. Introduction Recently, the dynamic response of a bridge structure under moving loads has been investigated by many researchers. Fryba [1] obtained the analytical solutions for simply supported and continuous beams with uniform cross-section. Yang and Lin [2] obtained closed-form solution on the dynamic interaction between a moving vehicle and the supporting bridge using the modal superposition technique. For more complex bridge–vehicle models, the finite element method has been utilized to perform the dynamic interaction analysis. Henchi et al. [3] presented an efficient algorithm for the dynamic analysis of a bridge discretized into three-dimensional finite elements with a stream of vehicles running on top at a prescribed speed. The coupled equations of motion of the bridge–vehicle system are solved directly without an iterative method. Generally speaking, the conventional deterministic analysis obtains only an approximation of the actual response due to uncertainties in the structural properties and the external loadings. Therefore, it is quite necessary to perform the stochastic analysis for the bridge–vehicle interaction problem. Recently, some research work has been conducted on the dynamic response of a bridge deck with the road surface roughness modeled as Gaussian random processes. Some researchers [4-5] considered the randomness in the loadings due to the road surface roughness where the system parameters of both bridge and vehicle were treated as deterministic. Others had the randomness in the mass, stiffness, damping and moving velocity [6-8] of the moving vehicle and perturbation method was adopted to estimate the statistics of the structural dynamic response under random excitations. To model the uncertainties in structural analysis, stochastic finite element method is often used. Fryba et al. [9] computed the statistics of the dynamic response of a beam under a single moving force using the stochastic finite element analysis by using the first order perturbation in which the stiffness and damping were modeled as Gaussian random variables. Due to the fact that the perturbation method tends to lose accuracy when the level of uncertainty increases [10], the Karhunen–Loéve (K–L) expansion is used in the present study to represent the Gaussian random processes in the equation of motion of the bridge–vehicle system. The bridge response under Gaussian random vehicular forces which may have non-Gaussian properties will be approximated by Gaussian random processes. Recently, Wu and Law [11] proposed a new method to study the dynamic behaviors of bridge-vehicle system with uncertainties; their

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mathematical model is established based on finite element model in which the Gaussian random processes are presented by the Karhunen–Loéve expansion. A stochastic finite element model is proposed in the present study for the dynamic response calculation of a bridge structure considering stochastic loading with inherent randomness in a bridge–vehicle system. The algorithm based on the proposed model can handle complex random excitation forces with large uncertainties and relatively small uncertainties in system parameters. The bridge is modeled as a simply supported beam with Gaussian random elastic modulus and mass density of material and random moving forces on top. The forces have time-varying mean values and a coefficient of variation at each time instance, and they are considered as Gaussian random processes. The equation of motion of the bridge–vehicle system is presented using the Karhunen–Loéve expansion and the response statistics are obtained by solving the system equation of motion using the Newmark-β method. Some of the numerical results based on the proposed stochastic approach are checked by those obtained from the Monte Carlo simulation. Mathematical formulation

Fig. 1. Bridge-Vehicle system: Geometry and coordinate system of the beam A simply-supported beam of length L, width b and thickness h is considered, with the coordinate system placed at the mid-plane of the beam, with the moving loads on the top of the beam, as shown in Fig. 1, u ( x, t ) and w ( x, t ) are the displacements at any point in the x- and z-directions, respectively. The displacement field for the beam based on the first order shear deformation theory (FSDT) can be written as u ( x, z , t ) = u0 ( x, t ) + zφx ( x, t ) v ( x, z , t ) = zφ y ( x, t )

(1)

w ( x, z , t ) = w0 ( x, t ) where u0 and w0 are the axial and transverse displacements of a point on the mid-plane in the x- and z-directions, φx and φ y are the rotations of the normal to the mid-plane about the y- and x-axes, separately, and t is denoted as time. Based on the finite element formulation, we can obtain the following equation:

{ }

{ } { }



e +  K e  W e − F e = {0}  M e  W  

(2)

where {W e } denotes the element nodal displacement vector, [ M e ], [ K e ], [ F e ] denotes the element mass matrix, stiffness matrix and load vector respectively.

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The system equation of motion Based on the element stiffness, mass matrices and element load vector given in Eq. (2) and the assumption of Rayleigh damping, the system equation of motion of the bridge can be written in matrix form as

+ C W
+ K W = HF Md W d d

(3)

where M d , Cd and K d are the deterministic mass, damping and stiffness matrices of the bridge
and W

are the deterministic nodal displacement, velocity and structure, respectively; W , W acceleration vectors of the structure respectively and HF is the equivalent nodal load vector of the bridge–vehicle interaction forces. The nodal responses of the bridge model under moving forces can be obtained by directly solving Eq. (3). The displacement of the bridge at position x and time t can then be expressed as:

w ( x, t ) = H ( x ) W ( t )

(4)

{

T

where H ( x ) = 0  H ( x )i

}

T

0  0 and H ( x )i is the shape function of the beam structure.

H ( x ) is a 1× n vector with zero entries except at the order of the ith beam element on which the position x is located. System with random excitation and random system parameters The mass density ρ ( x, β ) , Young’s modulus E ( x, β ) and damping c ( x, β ) of the beam are assumed as Gaussian random processes, with mean value ρ , E , c and standard deviation σ ρ , σ E , σ c , respectively, and the random components of them can be denoted as ρ , E , c , respectively. The FEM

equation of motion of the structure with random material properties and random excitations can be written as follows



( t , β ) + CW
( t , β ) + KW ( t , β ) = HF ( t , β ) MW (5)
( t , β ) and W

( t , β ) are the random nodal displacement, velocity and acceleration where W ( t , β ) , W vectors of the structure, respectively. M, C, K are the stochastic mass, damping and stiffness matrices  , K = K +K  ,K  ,C = C + C ,M  ,C  are the random of the bridge structure, respectively; M = M d +M d d components of the system mass, damping and stiffness matrices, respectively, and they can be generated by assembling the corresponding elemental matrices accordingly. Based on Karhunen–Loéve expansion, the system stiffness matrix K can be expressed as NE

NE

i =1

i =0

K = K d + ∑ gi ( β ) K i = ∑ gi ( β ) K i

(6)

where N E is the number of components in the K–L expansion for the Young’s modulus after truncation, gi ( β ) is a set of uncorrelated Gaussian random variables, β denotes the random dimension, and K i can be assembled from the element stiffness matrix. Similarly the system mass matrix, damping matrix, force vector and displacement vector can be expressed in terms of K-L expansion. By substituting all the system matrices into Eq. (5) and taking the inner product on both sides of the equation with g m ( β ) and utilizing the orthogonal property, we can obtain

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ˆ
 ˆ 

ˆ ˆ M  {q(t )} + C  {q(t )} + K  {q(t )} =  H  {f (t )}

(7)

The nodal responses of the bridge are calculated by solving the system Eq. (7) using the Newmark-β n

( n ) ( t ) for the responses. The mean and the method to obtain the components q( ) ( t ) , q
( n ) ( t ) and q variance of the nodal displacements can then be evaluated readily.

Numerical results and discussion For simplicity, only one moving concentrated load is considered here, and the mean value of the moving load is assumed as P0 sin Ωt , where P0 is the amplitude of the moving load and Ω is the driving frequency of the moving load. In the following numerical computations, the beam under a harmonic moving load with constant velocity is dealt with using the FSDT and the proposed method. The following properties of the bridge model are adopted in the numerical computations: L = 40 m ; A = 4.8 m 2 ; I = 2.5498 m 4 . The simply supported beam is considered having the material properties with mean values as follows: E = 1.448 × 1011 Pa, G = 4.136 × 109 Pa, ν = 0.25, ρ0 = 1389.23 kg / m3 . Both the random elastic modulus and mass density are assumed with the same spatial correlation and the same level of Coefficient of Variation (COV). In the present study, COV is assumed as 10% for the elastic modulus, mass density and the harmonic moving load. In addition, the damping ratio is assumed to be the same for all the modes. In Fig. 2, the time history of mean value of the non-dimensional dynamic deflections at the midspan are presented for various values of the damping ratio in the case of V * = 0.10, Ω* = 0.20. It is noted that the non-dimensional dynamic deflections are normalized by the static deflection, D, of a beam under a point load P0 at the midspan. As it can be seen from Fig. 2, the non-dimensional dynamic deflections get smaller as the damping ratio increases, in addition, the numerical results based on the present study are checked by the Monte Carlo simulation and they are in excellent agreements. Fig. 3 shows the time history of standard deviation of the non-dimensional dynamic deflections at the midspan, the results from the Monte Carlo simulation are a little higher than those from the present study, especially for zero damping ratio. Nevertheless, they are still in fairly good agreements. V*=0.10, Ω *=0.20 0.6 0.4

Mean value of w(L/2,t)/D

0.2 0 -0.2 -0.4

ξi=0 %, PS

-0.6

ξi=0 %, MCS ξi=2 %, PS

-0.8

ξi=2 %, MCS ξi=5 %, PS

-1

ξi=5 %, MCS -1.2

0

0.1

0.2

0.3

0.4

0.5 T

0.6

0.7

0.8

0.9

1

Fig. 2. Time history of mean value of midspan displacements for V * = 0.10, Ω* = 0.20. PC=Present study, MCS=Monte Carlo simulation.

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V*=0.10, Ω *=0.20 0.06

Standard deviation of w(L/2,t)/D

0.04 0.02 0 -0.02 -0.04

ξi=0 %, PS ξi=0 %, MCS

-0.06

ξi=2 %, PS -0.08

ξi=2 %, MCS ξi=5 %, PS

-0.1

ξi=5 %, MCS -0.12

0

0.1

0.2

0.3

0.4

0.5 T

0.6

0.7

0.8

0.9

1

Fig. 3. Time history of standard deviation of midspan displacements for V * = 0.10, Ω* = 0.20. PC=Present study, MCS=Monte Carlo simulation.

Conclusions In the present study, we perform the statistical dynamic analysis on the bridge–vehicle interaction problem with randomness in material properties and moving loads. The bridge is modeled as a beam with Gaussian random elastic modulus and mass density of material with moving forces on top. These forces are time varying with a coefficient of variation at each time instance and they are considered as Gaussian random processes. The first order shear deformation theory is assumed for the beam model. The mathematical model of the bridge–vehicle system is established based on the finite element model in which the Gaussian random processes are represented by the Karhunen–Loéve expansion and the equations are solved by the Newmark-β method. Some statistical properties such as the mean value and standard deviation of the structural response are obtained, and the results based on the proposed method match with those from Monte Carlo simulation.

Acknowledgments: This research was partially supported by the National Science Council in Taiwan through Grant No. NSC-100-2221-E-327-026. The author is grateful for the financial support. References [1] L. Fryba: Vibration of solids and structures under moving loads, Thomas Telford, London (1999). [2] Y.B. Yang and C.W. Lin: J Sound Vib 284 (2005), p. 205. [3] K. Henchi et al.: J Sound Vib 212 (1998), p. 663. [4] T.P. Chang and Y.N. Liu: Int J Solids Struct 33 (1996), p. 1673. [5] J.G.S. Da Silva: Comput Struct 82 (2004), p. 871. [6] G. Muscolino, S. Benfratello and A. Sidoti: Probab Eng Mech 17 (2002), p. 63. [7] T.P. Chang, G.L. Lin and E. Chang: Int J Solids Struct 43 (2006), p. 6398. [8] T.P. Chang, M.F. Liu and H.W. O: Struct Eng Mech 31 (2009), p. 737. [9] L. Fryba, S. Nakagiri and N. Yoshikawa: J Sound Vib 163 (2003), p. 31. [10] G.I. Schuëller: Arch Appl Mech 75 (2006), p. 755. [11] S.Q. Wu and S.S. Law: Probabilist Eng Mech 25 (2010), p. 425.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 259-263 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.259

Design of Geneva Mechanism with Curved Slots Jung-Fa Hsieh1,a, Fu-Shou Wang2,b 1

Department of Mechanical Engineering, Far East University, Tainan County, 744, Taiwan Department of Mechanical Engineering, Far East University, Tainan County, 744, Taiwan a [email protected], [email protected]

2

Keywords: Geneva mechanism; Offset; Double-points, Singular points

Abstract A simple yet comprehensive method is proposed for the design of a Geneva indexing mechanism with curved slots. In the proposed approach, conjugate surface theory is employed to derive an analytical description of the profile of the curved slots with and without an offset feature. The use of an appropriate offset angle to eliminate the singular points and double-points on the profile of the curved slots is then demonstrated. Finally, a mock-up Geneva mechanism is constructed to demonstrate the feasibility of the proposed approach. The results confirm that the methodology presented in this study enables the integration of the design, analysis and machining tasks for a Geneva indexing mechanism, and therefore makes possible a flexible and automatic production process. Introduction The design of a conventional Geneva mechanism is generally straightforward since its structure consists primarily of no more than a driving crank and a wheel with straight slots. However, in such mechanisms, a major impact load is generated at the initial and final stages of the indexing operation as the roller enters and exits the slot, respectively. Fenton [1] used Geneva mechanisms in series such that the motion of the last wheel accelerates and decelerates smoothly regardless of the motion status at the intermediate mechanism. Alternatively, Cheng and Lin [2] was employed certain damping element in the mechanism to reduce the shock. Fenton et al. [3] and Lee [4] was to change the geometry for the wheel slot. Curved slots with designed motion law were applied as in the standard cam mechanisms. Figliolini and Angles [5] studied the kinematic synthesis of both conjugate Geneva mechanisms with curved slots and their pure-rolling cam-equivalent using the pressure angle as a merit of force transmission. Lee and Jan [6] utilized the theory of envelope to determine the geometry of Geneva mechanisms with curved slots. In addition, the undercutting as well as double-point condition was investigated. Hsieh [7] utilized a homogeneous coordinate transformation method to derive an analytical expression for the curved slots of the Geneva wheel and to generate the corresponding NC machining code. However, the singular and double-points on the curved slot profile were not addressed. Accordingly, the present study extends the work presented in Hsieh to present a more comprehensive methodology for the design, analysis and manufacture of Geneva indexing mechanisms with curved slots. Surface geometry Referring to Fig. 1(a), the angular displacement of the driving crank takes place in the clockwise direction about center 01. When the roller on the driving crank engages with the slot on the Geneva wheel and rotates through an angle 2β, the Geneva wheel rotates in the counterclockwise direction about center 00 through an angle 2α (referred to as the indexing angle). Figure 1(b) shows the roller, with center 0r, enters the curved slot at point A, axis 00x0, which rotates with the wheel, coincides with axis 0001, and θ1=0. Thus, from triangle 0r0001, it follows that R1 a1 R = = , (1) Sβ Sα S (π − α − β ) where a1 is the distance between the wheel axis, z0, and the crank axis, z1, R is the length of the driving crank, and R1 is the radius of the Geneva wheel. Finally, S denotes SINE.

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(a)

(b)

Fig.1. Geneva mechanism with curved slots Table 1 Kinematic parameters of Geneva mechanism Par. Link Link 1 Link 2

bi

θi

ai

αi

b1 0

− θ1 −θ2

a1 0

0 180 0

In order to determine the slot profile in terms of the designed parameters by using conjugate theory, one need to define the coordinate frames, starting with the Geneva wheel (marked as "0" in Fig. 1) and ending with the driving crank (marked as "2" in Fig.1). Once the frame (xyz)i (i=0,1,2) has been assigned to link i according to the Denavit-Hartenberg (D-H) notation [8], the kinematic parameters can be tabulated, as shown in Table 1. The configuration of frame (xyz)2 with respect to frame (xyz)0 is given by a1Cθ1   C (θ 2 + θ1 ) − S (θ 2 + θ1 ) 0  2 − S (θ 2 + θ1 ) − C (θ 2 + θ1 ) 0 − a1 Sθ1  i −1 0  A2 = ∏ Ai = , (2)  0 0 −1 b  i =1   0 0 0 1   The configuration of the roller frame (xyz)r with respect to frame (xyz)2 (see Fig.2) is given by the matrix 0 R 1 0 0 − 1 0 0  2 . (3) Ar =  0 0 − 1 0    0 1 0 0

Fig.2: Roller location with respect to driving crank The surface equation, rS, and unit outward normal, rn, of the cylindrical roller can be expressed with respect to frame (xyz)r as follows: T r S = [rCθ rSθ − u 1] (0 ≤ u ≤ λ ,0 ≤ θ ≤ 2π ) , (4)

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r

∂ r S ∂ rS n= × ∂u ∂θ

∂ r S ∂ rS × = [Cθ ∂u ∂θ

Sθ

0 0] , T

261

(5)

where θ represents the polar angle, u represents the height parameter of the cylindrical roller, and C denotes COSINE. Once the input-output relation of the Geneva mechanism has been defined, the conjugate points and slot profiles can be determined via the formulation d 0S 0 2 r T d ( 0A2 2 Ar r S ) 0 T =( A2 Ar n) =0, (6) n • dt dt where 0n and 0S are the unit outward normal and surface equation of the slot with respect to frame (xyz)0, respectively. The conjugate point (denoted as θ ) expressed as F θ = − tan −1 ( ) . (7) E dθ dθ where E and F are defined as E = ( R + a1Cθ 2 ) 1 + R and F = − a1 Sθ 2 1 , respectively. dθ 2 dθ 2 The corresponding conjugate profile of the slots on the Geneva wheel can be obtained by 0 0 2 r S= A2 Ar S. That is, rC (θ − θ1 − θ 2 ) + RC (θ1 + θ 2 ) + a1Cθ1    T rS (θ − θ1 − θ 2 ) − RS (θ1 + θ 2 ) − a1Sθ1  0 0 0 0  . (8) S = Sx Sy Sz 1 =   b1 − u   1  

[

]

Fig.3: Geneva wheel with offset curved slot Importantly, the offset alters the shape of the slot, but has no effect on the kinematic characteristics of the mechanism. Figure 3 presents a schematic illustration of the offset concept. As the roller engages with the slot at new point A, the original angle between line 00A and the center line 0 0 01' increases from α to α+∆α, where ∆α is referred to as the offset angle and 01' is the new crank rotation center. The roller then exits the curved slot at point B. In the modified slot design, the axis distance 0 0 01' (denoted as a1 ) and crank length (denoted as R ) are related as follows:

R1 R a1 = = . Sβ S (α + ∆α ) S (π − α − β − ∆α )

(9)

Thus, the geometric profile of the slot with an offset can be obtained by replacing a1 with a1 and R with R in Eqs.(8) and (9).

Kinematics The performance of Geneva mechanisms can be improved by choosing a suitable motion program which incorporates both zero velocity and zero acceleration at the beginning and end of each

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engagement period. In the present study, a modified sine motion curve is employed. The displacement of this motion curve θ2 is the driving crank position, θ1 is the Geneva wheel displacement and θd is the dwell period. The modified sine curve starts from a zero position and rises to a total height of h over the period of the driving crank rotation,τ. The displacement, θ1, associated with the modified sine curve are given as follows:  τ 1 θ − θd π θ2 − θd − S (4π 2 )],0 ≤ θ 2 − θ d ≤ h[ 4 + π τ 4(4 + π ) 8 τ  2 9 4π θ 2 − θ d π τ 7τ π θ2 − θd  S( + − + )], ≤ θ 2 − θ d ≤ , (10) θ1 (θ 2 ) = h[ τ 4( 4 + π ) 3 3 8 8  4+π 4+π τ θ − θ d 7τ 1 h[ 4 + π θ 2 − θ d − S (4π 2 )], ≤ θ 2 − θ d ≤ τ  4+π 4+π τ τ 4( 4 + π ) 8 

Implementation To validate the design methodology presented in Sections 2~4, a Geneva mechanism was constructed with design parameters of α=450, R=120 mm, R1=115 mm, b1=2 mm, λ=10mm, r = 8 mm and N=4. From Eq.(1), parameters a1 and β were obtained as a1=169.564mm and β=42.660. The dwell period of the Geneva wheel is specified as θ2=00 to θ2=137.340. Furthermore, the indexing angle of the Geneva wheel as the driving crank rotates from137.340 to 222.660 is set as 900.Figure 4 shows the slot profile obtained from Eqs. (7) and (8). It can be seen that the profile contains both a singular point and a double-point, and is therefore unsuitable for practical applications.

Fig.4: Curved slots with no offset feature

(a)

(b) Fig.5: Curved slots with offset feature

Figures 5(a) ~ 5(b) illustrate the profiles of curved slots with offset angles of 50 and 70, respectively. (Note that in each figure, the entry and exit points of the driving roller are indicated via the labels A and B, respectively). Given offset angles of ∆α=50or ∆α=70, the singular points and

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double-points disappear, as shown in Figs. 5(a) and 5(b), respectively. It should be noted that the shape of the slot and the relative location of the entry and exit points are both dependent on the magnitude of the offset. The feasibility of the proposed design methodology was confirmed by constructing a mock-up Geneva wheel mechanism with the parameter settings described above. Figure 6 presents photographs of the machining process (Note that readers interested in the problem of generating the NC equations required to produce the corresponding Geneva wheel using a 3-axis machine tool are referred to [7] ). The indexing mechanism was found to perform satisfactorily; thereby confirming the feasibility of the proposed design approach.

Fig.6: Photographs of fabricated Geneva mechanism with curved slots

Conclusions This paper has presented a systematic method for the design of a Geneva indexing mechanism with curved slots. A kinematic model of the indexing mechanism has been derived utilizing the homogeneous coordinate transformation method and conjugate surface theory. In addition, analytical expressions have been derived for the slot profile with and without an offset feature, respectively. It has been shown analytically that the use of an appropriate offset angle eliminates the singular points and double-points on the slot profiles, and therefore improves the control of the indexing wheel. In general, the results have confirmed that the approach proposed in this study provides a suitable basis for the computer-aided design and manufacture of Geneva mechanisms, and thus provides the means to realize a flexible, automatic, cost efficient and controllable production process.

References [1] E.A. Fenton, Geneva mechanisms connected in series, ASME Journal of Engineering for Industry Vol.97 (1975), pp.603-608 [2] C. Y. Cheng and Y. Lin, Improving dynamic performance of the Geneva mechanism using non-linear spring elements, Mechanism and Machine Theory Vol.30 (1995), pp.119-129 [3] R. G. Feston, Y. Zhang and J. Xu, Development of a new Geneva mechanism with improved kinematic characteristics, ASME Journal of Mechanical Design Vol.113 (1991), pp.40-45 [4] H. P. Lee, Design of a Geneva mechanism with curved slots using parametric polynomials, Mechanism and Machine Theory Vol.33 (1998), pp. 321-329 [5] G. Figliolini and J. Angeles, Synthesis of conjugate Geneva mechanisms with curved, Mechanism and Machine Theory Vol.37 (2002), pp.1043-1061 [6] J.-J. Lee and B.-H. Jan, Design of Geneva mechanisms with curved slots for non-undercutting manufacturing. Mechanism and Machine Theory Vol.44 (2009), pp.1192-1200 [7] Jung-Fa Hsieh, Application of homogenous transformation matrix to the design and machining of a Geneva mechanism with curved slots, Proc. Instn. Mech. Engrs, Part C: J. Mechanical Engineering Science Vol.221 (2007), pp.1435-1443 [8] R.P. Paul, Robot Manipulators-Mathematics, Programming and Control. MIT. Cambridge. MA. 1982.

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The study and fabrication of electron field emission module for next-generation multi-beams lithography applications Wen-Shih Lin1a, Tao-Hsing Chen2b and Tsung-Chieh Cheng1c* 1

Department of Mechanical Engineering, National Kaohsiung University of Applied Science, Kaohsiung, Taiwan a

[email protected], [email protected], [email protected]

Keywords:field emission, silicon nanowires, carbon nanotubes,

Abstract In this paper, a single silicon nano-emitter were investigated by means of experiments and simulation models andthe emitters array was fabricated by dry etching using an inductively coupled plasma (ICP) through a three-step process. Besides, in order to understand the field emission phenomenon in nano/micro scale, a novel experimental measurement technique by SEM with nanomotors including the constant voltage and the constant emission modes was developed to measure the accurate field emission properties.The results indicated that etching method is a good way to make the uniform field emitters and the electron field emission from a single nanoemitter is a barrier tunneling, quantum mechanicalprocess. Introduction Advances in research into many vacuum microelectronics devices depend upon the realization of reliable high intensity electron sources. For this reason, the ability to fabricate uniform emitters is an important factor in many vacuum microelectronics applications, including their use as electron sources in various visualization equipment, flat panel displays, electron microscopy, microwave power devices, and especially for the fabrication of next-generation electron beam lithography [1]. Over the past decade, field-emission properties have been studied extensively for various materials and geometrical arrangements, in which performance has been found to strongly depend upon the inherence, morphology, material density, and the sharpness, aspect ratio and surface conditions of the tip, to name a few. Recently, the advent of new nanofabrication techniques has led to the preparation of efficient electron emitters from various one-dimensional systems comprising different elements—including hollow nanotubes, solid nanowires, coaxial cable structures, side-by-side biaxial nanowires, and nanobelts—that can deliver highly bright electron beams from a narrow energy spread. Therefore, hoe to design the easy fabrication, low cost, and high performance field emitter, to understand quantitatively the physical picture of a single field emitter or field emitters array participating in the field-emission process are very important topics. Experiment and Simulation Model In our studies,first, in order to understand the physical picture of field emission phenomena, the field-emission characteristics of a single silicon nano-emitter were investigated by means of experiments and simulation models. The emitters array was fabricated by dry etching using an inductively coupled plasma (ICP) through a three-step process[2].A novel experimental measurement technique by SEM with nanomotorsincluding the constant voltage and theconstant emission modes was developed.In the constant voltage mode, we applieda larger voltage (e.g. 400 V) at the tungsten anode, which wasgreater than the expected turn-on voltage. Then, the tungstenprobe was controlled by the nanomotor to move at a constant speed of 30 nm s− 1 through a longer distance than for the constant emission mode, and we concurrently measured theemission current to determine the approximate position wherethe maximum emission current occurs. In the constantemission mode, we

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moved the tungsten anode through a shorter distance around the approximate position of the maximumemission current determined in the constant voltage mode andmeasured the turn-on voltage at each position to find out wherethe minimum turn-on voltage occurs. By combining thesetwo steps, we can precisely determine the ‘right’ position tomeasure the emission current from a single nano-emitter. Notethat this novel technique can be adapted easily to measure theemission current from other types of nanoscale emitters.Accompanying these measurements,a parallelized 3D PIC code using the finite-element method coupled with a ray-tracing module was also developed and applied to simulate the field-emission process of single emitter[3]. Results and Discussion Figure 1(a) illustrates the steady-state potential distribution along with a snapshot of the emitted electrons. At steady state, there were approximately 3000 electrons in the computational domain. Most of the electrons were emitted from the tip region having very high electric field (up to∼50 Vnm− 1 ). Figure 1(b) shows the comparison between the experimental and simulated I–V curves. In figure 1(b), the simulated emission currents for the case where the space–charge effect was taken into account compared very well with those observed experimentally; conversely, those generated without considering the space–charge effect generally appear much larger than those from the experiments. A reduced emission current, relative to the case that did not account for the space–charge effect, results from the emitted electron clouds near the cathode (tip) surface. This reduction in the emission current reduces the local electric field at the tip surface or equivalently the shielding effect due to the charge particles. Therefore, our experimental and simulation data both clearly demonstrate that the space–charge effect due to the emitted electrons is important in determining the field-emission current from a nano-emitter in the present configuration. Our simulation and experimental results for the turn-on voltage show less than a 9.3% difference. The results also reveal that the field emission from a single silicon tip is a typical barrier-tunnelling, quantum mechanical process.

(a)

(b)

Figure 1. (a) Potential distribution along with snapshot of electrons in the exploded view nearthe nano-emitter tip and (b) Comparison of the experimental and simulatedcurrent–voltage curves (work function = 4.5 eV).

Besides, the theoretically simulation of the effect of space charge on FE nanodevices displaying different geometries, dimensions and work functions of their emitter materials, including diode and triode structures are also investigated as shown in Fig. 2[4]. To study the space-charge-limited FE of an FE nanodiode featuring a nanogap, in this study we derived an analytical model starting from Poisson’s equation. We prepared FE nanodiodes featuring a variety of gap distances and work functions of the cathode. For the integrally gated FE nanotriodes, we proposed a more realistic modified ball-in-sphere model[5] to study the effects of space charge on FE nanotriodes; this model considers the geometry effect and the actual work function of the nanoemitter. By solving the coupled FN equation and Poisson’s equation numerically for spherical coordinates, we investigated the

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influence of space charge on the emission current density of the FE nanotriodes. Specifically, we defined a threshold current density of space-charge limitation to characterize the anti-space-charge abilities of FE nanotriodes. Figure 3(a) reveals that the value of Jthsc decreased upon increasing the dimensions of both the gate aperture and the emitter radius. To verify this behavior, we further examine the potential and electric field distributions (figures 3(b) and (c), respectively) for the FE nanotriodes (1)–(3) under a constant emission current density of 4 × 106 A cm−2. In figure 3(b), when the space charge is taken into consideration, the required gate voltages for the FE nanotriodes (1)–(3) were 42, 22 and 20% greater than those required in the space-charge-free cases, respectively. Because of the presence of space charge, the value of EPoisson was lower than that of ELaplace at the same emission current density. In figure 3(c), the electric fields for the FE nanotriode having values of D and r0 of 50 and 5 nm, respectively, were the strongest, whereas those for the FE nanotriode having values of D and r0 of 500 and 10 nm, respectively, were the weakest. Therefore, we conclude that the increase in the threshold current density can be attributed to the field amplification effect. Obviously, a higher electric field would negate the formation of space charge, thereby lessening its effect and increasing the threshold current density. Therefore, scaling the emitter radius and gate aperture of FE nanotriodes to smaller dimensions will lower the operating voltage and overcome the space-charge effects.

Figure 2. Schematic representations of (a) FE microtriodes possessing microtips as emitters, (b) FE nanotriodes possessing low-dimensional nanomaterials as emitters and (c) the ball-in-sphere model.

○

○

Figure 3. (a) Threshold current densities of space-charge limitation plotted with respect to the dimensions of the gate aperture ( ) and emitter radius ( ). (b) Potentials and (c) electric fields for FE nanotriodes possessing various device dimensions. The solid and dashed lines represent results obtained with and without the consideration of space-charge effects.

Moreover, the well aligned MWCNTs[6] which were grown by MPCVD was also compared with the random MWCNTs which were grown by thermal CVD on the flexible carbon cloth substrate to discuss the structure effect of the CNTs’ field emission properties. Figure 4(a),(b) shows the SEM

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images of these two MWCNT samples by MPCVD and thermal CVD. The results indicated that the MWCNTs grown by MPCVD (MP-CNTs) are well aligned and more uniform than MWCNTs grown by thermal CVD (T-CNTs). Obviously, due to more aligned and uniform CNTs will produce the uniform emission currents through the uniform electric field, in our field emission experiments, the field emission propertie of MP-CNTs is better than T-CNTs. Besides, in our works, we report a study on two-step surface chemical modifications on MWCNTs with the aim of improving the field emission properties of the MWCNTs. In step 1, MWCNTs were modified by 14 M HNO3 at 90 ◦C for 12h for the carboxylation of MWCNTs[7], i.e. caps of closed MWCNTs were removed, forming an open-ended shape. In step 2, the thiolation of MWCNTs was introduced by a method based on the pre-formation of carboxylic bonds of MWCNTs. In this study, the thiolated MP-CNTs depict the lowest turn-on field of 0.2 Vµm− 1 and threshold field of 1.25 Vµm− 1, which are defined as the value of macroscopic fields producing the emission current density of 10 µAcm−2 and 1 mAcm−2, respectively. (a)

(b)

(c)

Figure 4.The SEM images of MWCNTswere grown by (a) MPCVD and by (b) thermal CVD and (c)the SEM images of well aligned silicon nanowires were etched by hydrogen plasma.

Summary In our studies, we found that how to grow the well aligned field emitters is an important key factor for field emission devices but it is hard to form the well aligned uniform field emitters through the “growth” method. For this reason, we demonstrate a new one-step approach to the maskless fabrication of silicon nanowires through hydrogen plasma etching in the absence of a catalyst as shown in Fig.4(c)[8]. The results indicate that during hydrogen plasma etching the silicon substrate was sputtered off and the density of nanowires decreased with increasing the etching time, as a result of some nanowires bundling together, while their lengths increased. Our results indicate that the field emission properties are improved upon increasing the etching time; this process sharpens the nanowires’ geometry and lowers their work function. We hope that these highly uniform with respect to length, diameter, and distribution nanowires display great potential for application within many field emission nanoelectronics devices. References [1] J. M. Bonard, H. Kind, T. Stockli and L. O. Nilsson, Solid-State Electron.45 (2001) 893. [2] T. C. Cheng, K. H. Hsu, P. Y. Chen, W. J. Huang, J. S. Wu, H. T. Hsuehand M. N. Chang, Nanotechnology18(2007) 225503. [3] J. S. Wu and K. C. Tseng,Int. J. Numer. Methods Eng.63 (2005)37. [4] P. Y. Chen, T. C. Cheng, J. H. Tsaiand Y. L. Shao,Nanotechnology20 (2009) 405202. [5] M. Ding, G.Sha and A. I. Akinwande, IEEE Trans. Electron.Devices 49 (2002) 2333. [6] F. T. Chuang, P. Y. Chen, T. C. Cheng, C. H. Chienand B. J. Li, Nanotechnology18(2007) 395702. [7] N. Rajalakshmi, H. Ryu, M. M. Shaijumon and S. Ramaprabhu J. Power Sources 140 (2005) 250. [8] T. C. Cheng, J. Shieh, W. J. Huang, M. C. Yang, M. H. Cheng, H. M. Lin, and M. N. Chang, Appl. Phys. Lett. 88 (2006) 263118.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 268-273 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.268

An Adaptive Parameter Tuning Method with On-machine Weight Identification Function for CNC Machine Tools Shih-Ming Wang1, a, Si-Chi Ouh2,b, and Chuntai Yen3,c 1

Department of Mechanical Engineering, Chung Yuan Christian University, Chung-Li, Taiwan ;

2

Department of Mechanical Engineering, Chung Yuan Christian University, Chung-Li, Taiwan ; 3

Innovative DigiTech-Enable Applications & Services Institute ,Institute for Information Industry,Taipei,Taiwan,105,ROC a

[email protected], [email protected], [email protected]

Keywords: precision machining, inertia effect, friction effect, auto-tuning, weight monitoring.

Abstract. Different inertia effect causes different control errors. To have an optimal control performance, the control parameters of a CNC machine tool should be adaptively tuned based on the variation of the weight of the workpiece in machining process. In this study, simulation based on a theoretical model was made to investigate the influence of inertial effect and friction force on the servo accuracy of a CNC machine tool’s. By using empirical method, an adaptive tuning system that can auto-tune the CNC control parameters based on the detected weight of workpiece was developed. An on-machine weight identification system that can on-machine identify the weight of the workpiece was developed. After integrating the two systems, a control parameter tuning system which can be implanted into CNC controller was developed with the macro executor. Experimental results have shown that the system can effectively improve the accuracy of a machine tool through adaptively tuning control parameters based on the current weight of the machined. Introduction CNC machine tools play an important role in manufacturing industry. For new generation CNC machine tools, high speed and high accuracy have become the necessary characteristics to meet the manufacturing requirement from modern industry. Enhancing the implementation of CNC controller is one of the key factors to achieve high efficiency and high accuracy machining performance. Different workpiece weights give different inertial effect and friction effect to the machine. Different workpiece may have big difference in weight. In addition, workpiece could have big reduction in weight after rough machining and semi-finish machining. In order to obtain accurate machining performance, a CNC machine tool should be able to on-line change control parameters when the workpiece weight changes. However, the commercial CNC controller can only use one set of fixed control parameters set during machine calibration process for all different machining applications. Mei etc. [1] explored the relationship between friction force and the high-speed movement of a platform. Park etc. [2] ussed Bode diagram to adjust the P-I gain values in velocity control loop and P gain value in position control loop. Ohnishi etc. [3] simulated the influence of parameters of a PID controller to system performance. Kuo etc. [4] used Genetic Algorithm to tune the control parameters, and conducted experiments on a SIEMENS 840D controller to prove that the method can automatically identify and adjust control parameters. Kwon etc. [5] conducted experiments to cut a steel block with corner-shape cutting trajectory. In the experiments, different control parameters were used, and two linear displacement sensors were used to measure the corresponding servo errors. Finally, the optimal combination of control parameters was found. In this study, the influence of inertial effect and friction effect on accuracy of servo control was first investigated based on a theoretical control model. Based on the simulation results, the functions of control parameters were discussed. With use of empirical method, the performance curves of

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control parameters that describe the relationships between proper values of parameters and different weights of workpiece were built. The performance curves were converted into G-codes and implanted into FANUC 18iM Controller. When the workpiece weight changes and is detected, the controller will automatically select proper values for the control parameters to obtain better control performance. Experimental results have shown the feasibility and effectiveness of the developed system. Model and Simulation Model of Servo Control System. A servo positioning control system usually contains position control loop and velocity control loop. In the commercial CNC controller, a proportional controller (P-controller) is adopted for position control loop, and a proportional controller and an integral controller (PI controller) are adopted for velocity control loop. In addition, feed forward control is used to enhance its tracking capability and to minimize lag response. The PI controller in velocity loop and feed forward velocity controller (FFV controller) are responsible for velocity control. Because the band width of an inner control loop is 6-10 times higher than an outer control loop, the parameters in the inner control loop are more dominant for inertial and friction force control. Thus, the control functions of parameters in PI controller and FFV controller were investigated in this simulation. Figure 1 shows the control block diagram of a CNC servo system with a controller which is similar to Fanuc 18iM controller. The structure of the system was composed of current loop, velocity control loop, position control loop, and velocity feed-forward control loop. The Friction force (kmg) due to workpiece weight was taken into account in the system. .

Fig. 1 Control block diagram of a CNC servo system Simulation. Based on the block diagram shown in Fig. 1, a simulation with use of Matlab language was conducted to analyze the influence of the weight of a workpiece on the velocity control and positioning control. In the simulation, the servo system drove different weights (50, 500, and 1000 kg) for movement of 18 mm with velocity of 6 m/min. Figures 2 and 3 respectively show the displacement and velocity charts in time domain. It can be seen that 50kg, 500kg and 100kg respectively took 0.39, 0.395 and 0.41 seconds to complete the movement, and 1000kg has largest steady state errors. 1000kg took 0.3-0.4 more seconds to reach the velocity of 0.6 m/min. It concludes that weight influences acceleration of the system. Heavier weight makes the system respond slower. Figure 4 shows that large value of Kp (red line) in PI controller can speed up system response and decrease the steady-state error, but could also cause abnormal oscillation to the system. From Fig. 5, it can be seen that increasing Ki with small value (from 0.1 to 1) could decrease the steady-state

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position errors, but overshoot also occurs. When Ki increases, the steady state errors can be significantly reduced, but it could also cause unstable velocity. Thus, when Ki is tuned, the value of Ki can be properly increased to reduce the stead-state position error, but should be constrained within a range. When Ki is increased, increasing Kp could suppresse the system oscillation due to high value of Ki. However, large Kp could also cause abnormal oscillation to the system. Therefore Ki should be tuned when the value of Kp is still small. Among the gains in PI controller, the gain of FFV controller is more useful for control position overshoot. Decrease of FFV gain value can significantly improve phenomenon velocity oscillation.

Fig. 2 Displacement diagram with different weights

Fig. 4 Position responses with different Kp values

Fig. 3 Velocity diagram with different weights

Fig. 5 Position response with different Ki

Empirical Method. Experiments were conducted to verify the influence of workpiece weight on inertial effects. Furthermore, experiments were conducted to build the performance curves of parameters. Experiments for investigation on influence of Workpiece Weight. A CNC 3-axis machine tool equipping with a FANUC 18iM controller was used. Servo Guide software from FANUC Co. and a cross grid encoder made by Heidenhain Co. were used to measure the feedback signals from the servo motors and movement trajectory to understand the positioning and contour accuracy of the machine. The circle movement trajectories with feedrate of 3000 mm/min were planned. Workpiece with different weights (0, 114, 243, and 357 Kg) were placed on the machine table for the experiments. Figures 6 shows the measured actual trajectories with different workpiece weights. As we can see from the figures, heavier weight caused more peak errors at 0o, 90o, 180o, and 270o on the circle trajectory. For example, when weight is 357Kg, the peak error at 90o is 2 m larger than the weight is

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0kg. This is because slow down(de-accelerating) and speed up(accelerating) occurred at the location, and inertial effect and friction force had more significant influence at this type of movement. Experiments for Performance Curves of Parameters. Parameters P2021 (velocity loop gain), P2092 (pre-FFV gain) in FANUC 18iM controller were selected. By the similar experiments addressed in previous section, proper parameter values which give better contour accuracy were selected for weights 0, 114, 243, and 357Kg. The range for P2021 is from 0 to 2304. In the experiment, P2021 was set as 0, 128, 512, 1024. Figure 7 shows the associated trajectories. It was noted that when value increases, the contour error reduces for 2μm. However, unexpected vibration occurs when P2021 was set to 1024. The range for P2092 is from 0 to 10000. Figure 8 shows the trajectories when P2092 was set as 0, 5000, 9000, and 10000. It was found that when P2092 increases the contour error reduces from 27μm to 1μm. However, the contour error increases when P2092 was set as 10000. Following the similar porcedures, the optimal values of parameters can be decided for different workpiece weights. Experiments were conducted for weights O, 114, 243, and 357 Kg. When optimal parameter values were obtained, curve fitting method was employed to generate the performance curves which are function of workpiece weights. Same experiments were separately made for x, y, and z axis. The performance curves of the three parameters were obtained as following. P2021 for x-axis： y  324.55515  1.1039568x  0.0011551513x 2 .

(1)

for y-axis： y  388.55515  1.1039568x  0.0011551513x 2 . P2092 for x-axis： y  9750.6715  0.41640641x . for y-axis： y  100.13429  0.083281283x .

(2) (3) (4)

where y represents the value of parameter, and x represents workpiece weight. With use of MACRO EXECUTOR, the performance curves were converted as a G-code named G105Q1, and implanted into the CNC controller. If a user adds G105Q1 on the top of a NC program, the controller can automatically determine and reset the values for the three parameters as long as the current weight of a workpiece is known.

Fig. 6 Circle trajectories with different weights On-machine Weight Identification System. To be able to on-machine execute control parameter auto-tuning, the workpiece weight must be on-machine identified. Thus, an on-machine workpiece weight identification system was developed. When a servo motor drives different loads, the motor current are different. According to the characteristics, motor currents were measured when different workpiece weights were used. The measured currents were then curve fitted to obtain the weight prediction equation. Finally, the equation was converted as a G-code named G103W1, and implanted into the CNC controller. When the motor current is detected, the workpiece weight can be predicted through executing G103W1.

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Finally, the system G103W1 was integrated with the system G105Q1 to form an intelligent parameter auto-tuning system that was implanted to FANUC 18iM controller. Experimental Verification. Experiments were conducted to verify the effectiveness of the proposed system. The first experiment was to verify the function of on-line weight identifying system (G103W1). When machining was running, G103W1 was activated. The identified weight was used as input for parameter auto-tuning system (G105Q1) to on-line adjust the three parameters in FANUC 18iM controller. Circle trajectorie was planned to verify the improvement of contour accuracy due to parameters adjustment. The machine carried a 281kg workpiece and moved with feedrate of 3000mm/min. Heidenhain KGM Grid Encoder was used to measure contour accuracy. In Fig. 9, red line is the trajectory with original parameter values, and blue line is the trajectory with the auto-tuned parameter values. It was noted that contour errors at 0o, 90o, 180o and 270o were reduced about 2m. The experimental result has shown that the proposed system can enhance machine’s accuracy through on-line tuning parameters.

Fig. 7 Trajectories with different P2021

Fig. 8 Trajectories with different P2092

Fig. 9 Comparison of circle trajectories Conclusions In this study, simulation based on theoretical model was made to investigate the influence of inertial effect and friction force to CNC machine’s accuracy, and to explore the functions of related control parameters. Empirical method was employed to explore the functions of control parameters in FANUC 18iM controller. Furthermore performance curves of the selected parameters were generated and converted as a G-code named G105Q1 that can be directly implanted to FANUC controller so that the parameter tuning can be automatically executed by the CNC controller. Since the variation of inertial effect and friction force was due to the change of workpiece weight, an on-line weight identifying system was also developed and converted asa G-code named G103W1. Finally G103W1 and G105Q1 were integrated to form an intelligent parameter-tuning system which can be directly implanted in a CNC controller. The experimental results have shown that the system can on-line tune

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the control parameters based on the instantly detected weight of workpiece. Through this on-line control parameter tuning, contour errors caused by inertial effect and friction force of a CNC machine tools can be significantly reduced. Acknowledgement This study is supported by National Science Council of R. O. C. under the grant number NSC 101-2221-E-033 -007, Ministry of Economy Affair, and the Institute for Information Industry subsidized by the Ministry of Economy Affair, R.O.C. under the “III Innovative and Prospective Technologies Project”. References [1] Xuesong Mei, Maosaomi Tsutsumi, Takanori Yamazaki and Nuogang Sun: Study of the friction error for a high-speed high precision table, International Journal of Machine Tools and Manufacture, Volume 41(2001), p.1405-1415. [2] Joon-Ho Park, Tae-Kue Kim, Tae-Sung Yoon and Gun-Pyong Kwak: Systematic Control Parameter Tuning for Actuator in Control Loading System, IEEE International Conference on Industrial Technology (2006). [3] Y.Ohnishi, K. Takao, T. Yamamoto, S. L. Shah and Hiroshima Kure: Design of a PID Controller with a Performance-Driven Adaptive Mechanism, American Control Conference (2007). [4] Lun-Yu Kuo and Jia-Yush Yen: Servo parameter tuning for a 5-axis machine center based upon GA rules, International Journal of Machine Tools and Manufacture, Vol. 41 (2001), p. 1535-1550. [5] H. D. Kwon and M. Burdekin: Adjustment of CNC machine tool controller setting values by an experimental method, International Journal of Machine Tools and Manufacture, Vol. 38 (1998), p. 1045-1065.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 274-278 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.274

Heat Transfer of Oscillating-Move Pin-Fin Heat Sinks with Circular Impinging Jets Tzer-Ming Jeng1,a, Sheng-Chung Tzeng2,b, Chi-Huang Liu3,c, Yu-Xiang Huang4,d 1,2,3,4

Department of Mechanic Engineering, Chienkuo Technology University,No. 1, Chieh Shou N Rd.,Chang Hua 500, Taiwan,R.O.C. a

b

c

[email protected], [email protected], [email protected], d

[email protected]

： Oscillation move, pin-fin heat sink, heat transfer, impinging jet

Keywords

Abstract. This work experimentally investigated the effect of the oscillation move on the heat transfer enhancement of the pin-fin heat sinks with circular impinging jets. The forced convective cooling system usually applies the steady flow to pass through a stationary object. This work mounted the pin-fin heat sinks onto an oscillating platform with the impinging air jets. The experimental results indicate that stroke of the platform moving up and down is too long to enhance the overall heat transfer of the pin-fin heat sinks. 1. Introduction Investigation of fluid flow and heat transfer characteristics of an object in an oscillating flow or of an oscillating-move object in a steady flow has attracted many attentions. This issue is important in lots of practical applications, including sensors mounted in air manifold of auto-engine, heat regenerators for Stirling engines and cryocoolers, and high buildings in stormy conditions. Oscillation-induced heat transport processes maintaining an effective heat transfer enhancement has been demonstrated [1-4]. In addition, the fluid flow and heat transfer behaviors of the oscillating-move objects of various shapes in the nature convective steady flow or forced convective steady flow are explored [5-11]. All of these studies indicated that heat transfer enhancement was increased with the oscillating amplitude and frequency of the object reciprocally moving back and forth. It is because that the oscillating move of the object makes the air flow more unstable and turbulent, and then increases the heat-exchange performance between the object and the fluid flow. Based on the above-mentioned literature survey, the oscillating-move objects were the vertical plate, the circular cylinder and the lid of the cavity. The heat-transfer study of applying the oscillating pin-fin heat sink in the steady flow is few. Therefore, this work will mount the pin-fin heat sinks onto an oscillating platform with the impinging air jets and experimentally investigate the effect of the oscillation on the heat transfer enhancement of the pin-in heat sinks with circular impinging jets. 2. Experimental Method 2.1. Experimental setup An experimental setup, as shown in Fig. 1, was built for the investigations of the heat transfer and fluid flow characteristics. The experimental setup included the air-supplying equipment, the oscillating platform, the test section, the data-acquiring equipment, the smoke generator and the image-capturing equipment. The compressed air was generated by the 5HP air compressor firstly,

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then entered into an 800L steel tank to be reduced the flow impulse as well as flowed through the dryer and filter to be removed the water and impurities, and finally passed through the flow controller to be adjusted the flow rate. Before impinging onto the pin-fin heat sinks of the test section, the air coming from the main pipe would go through a bifurcate-pipe device and then was divided into two equal-flow-rate air flow to leave away from the circular nozzle of 16 mm diameter (D). As shown in Fig. 1, the test section of pin-fin heat sinks was situated on an oscillating platform. This platform can periodically move up and down with variable frequencies. The variable frequencies (f) were set as 0, 10, 30 and 60 Hz. The stroke (S1) of the platform moving up and down is 110mm, respective. The test section, as shown in Fig. 2, was a rectangular block made of the Bakelite. Four aluminum-alloy circular pin-fin heat sinks were installed at the side walls of the test section, respectively. Dimensions of the heat sinks are shown as Fig. 2. Three distances (C) between the heat sinks and the circular nozzle were employed, including 16, 48 and 80 mm (i.e. 1, 3 and 5 times of the nozzle diameter). The spreaders of the heat sinks were adhered with the film heaters by the grease with the high thermal conductivity. The other sides of the film heaters were adhered onto the side walls of the test section. Total twenty T-T-30SLE T-Type thermocouples through the Bakelite block were connected onto the film heaters to measure the heated walls. The film heaters were heated by the DC power supply. The data-acquiring equipment, including the YOKOGAWA MX100 data recorder and the personal computer, was used to record the steady-state temperature data. The criterion of the steady-state data was the change of the temperature within 0.2°C during 15 minutes. Besides, the smoke was obtained by burning the joss stick and collected in a box, and then blown into the test section by coupling with the air flow before performing flow-visualization experiments. The image-capturing equipment included a 60 mW He-Ne laser light-sheet illumination and a CCD camera. After passing through a 5mm cylindrical glass rod, the laser beam became a light sheet. As the light sheet illuminated the annular test section, the smoke reflected the laser light and the smoke trace of the flow could be easily observed.

Fig. 1 Experimental setup and the photo of the test section situated on the oscillating platform

Fig. 2 Dimensions of test section and the pin-fin heat sink (Unit: mm)

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2.2. Data reduction and uncertainty analysis The measured data was used to determine the relevant dimensionless parameters, including average Reynolds number (Re) and average Nusselt number (Nu). Re =

ρ ⋅ Vj ⋅ D µ

(1)

Nu =

qc ⋅ Dh (Tw − T j )k f

(2)

Where Vj is the average velocity of jet flow, D is the diameter of the nozzle, Dh is the hydraulic diameter of the spreader, Tw is the mean wall temperature, Tj is the air temperatures at the nozzle exit, qc is the convective heat flux. The convective heat flux (qc) is estimated to be the difference between the total input heat flux (qt) and the heat flux loss (qloss). qc = qt − qloss = V ⋅ I / A − qloss (3) Where A is the area of the heated surface, as well as V and I are the input voltage and current from the DC power supply to the film heater, respectively. The heat loss (qloss) can be measured at the vertical-plate system with neither pin-fin heat sink nor jet flow. For such condition, the total input heat flux (qt) is divided into two parts: (1) the convective heat flux (qplate) directly from the heated surface to the ambient, and (2) the heat flux loss (qloss) from the heated surface to the ambience through the Bakelite block. (4) qloss = (V ⋅ I / A) − hplate(Tw − T∞ ) = hloss(Tw − T∞ ) The hplate is the heat transfer coefficient of the nature convection from the vertically heated plate surface to the ambient, and T∞ is the ambient temperature. The empirical formula of hplate can be obtained from Molman [12]. 0.59 ⋅ k f h plate = (Gr ⋅ Pr) 0.25 (5) H gβ (Tw − T∞ ) H 3 Gr = (6) 2

ν

The uncertainties of experimental results included the measurement and calculation deviations. The measurement deviation was caused by the errors of the instruments or manual reading, and the calculation deviation was formed by interactive operation of measured parameters. The uncertainties, analyzed by the method of Moffat [13], in average Reynolds number (Re) and average Nusselt number (Nu) were ±3.15% and ±6.75%. 3. Results and Discussion Figure 3 displays the photos of flow visualizations. The operation condition was set as flow rate of 5L/min, oscillating frequency of 5Hz and relative impinging distance (L/d) of 3. Figure 3(a) shows the flow visualization of the stationary system. It shows clearly that the smoke flow was blown from the nozzle, then entered into the pin-fin heat sink, and finally turned 90-degree as well as left away from the sides of the heat sink. Symmetrical vortices appeared at the tip of the pin fins next to the main stream of the air jet. Figure 3(b) displays the flow visualization of the oscillating system moving up and down. It shows that the jets missed impinging onto the normal heat sinks periodically due to the big relative move (S1/H=2.75; S1 is the stroke of the platform moving up and down and H is the height of the heat sink). Figure 4 depicts the Nu as a function of Re for the system moving up and down. The test results indicate that the Nu of the normal heat sink was much higher than that of the lateral one. This result meets the flow visualization. Based on the present arrangement of the impinging jets, only few amount of fluid flow leaving from the normal heat sinks would pass through the side corners of the lateral heat sinks, leading poor heat transfer in the lateral heat sinks. Besides, the decrease of the

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relative impinging distance (L/d) was desired for the increase of the Nu in the stationary normal heat sink, especially for the operation condition of high Reynolds number. The oscillating normal heat sink did not promote the total heat transfer by comparing with the stationary one. It is because that the present oscillation resulted in the jets missing impinging onto the normal heat sinks periodically. However, the effect of L/d on the heat transfer of the oscillating normal heat sinks was insignificant.

Symmetrical line (a) Stationary system

(b) Oscillating system moving up and down Fig. 3 Photos of flow visualizations (Qflow=5L/min, f=5Hz and L/d=3)

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4. Conclusions This work successfully measured the fluid flow and heat transfer behaviors of the pin-fin heat sinks situated on an oscillating-move platform with the impinging jets. The experimental results indicated that the poor heat transfer appeared in the lateral heat sinks by comparing with the normal ones. Besides, the decrease of the relative impinging distance (L/d) was desired for the increase of the Nu in the stationary normal heat sink. The oscillating normal heat sink did not promote the total heat transfer by comparing with the stationary one. Acknowledgement The authors would like to thank the National Science Council of the Republic of China for financially supporting this research under Contract No. NSC 101-2622-E-270-005-CC3. References [1] H. Iwai, T. Mambo, N. Yamamoto and K. Suzuki: Int. J. Heat Mass Transfer Vol. 47 (2004), pp. 4659–4672. [2] K.C. Leong and L.W. Jin: Int. J. Heat Mass Transfer Vol. 48 (2005), pp. 243–253. [3] S.Y. Byun, S.T. Ro, J.Y. Shin, Y.S. Son and D.-Y. Lee: Int. J. Heat Mass Transfer Vol. 49 (2006), pp. 5081–5085. [4] B.N. Hewakandamby: Int. J. Heat Mass Transfer Vol. 52 (2009), pp. 396–406. [5] X.R. Zhang, S. Maruyama, and S. Saka: Int. J. Heat Mass Transfer Vol. 47 (2004), pp. 4439–4448. [6] H. Gomaa and A.M. Al Taweel: Int. J. Heat Mass Transfer Vol. 48 (2005), pp. 1494–1504. [7] Y.-T. Yang and C.-H. Chen: Int. J. Heat Mass Transfer Vol. 51 (2008), pp. 1603–1612. [8] S. Bao, S. Chen, Z. Liu and C. Zheng: Int. J. Heat Fluid Flow Vol. 37 (2012), pp. 147–153. [9] A. Beskok, M. Raisee, B. Celik, B. Yagiz and M. Cheraghi: Int. J. Thermal Sciences Vol. 58 (2012), pp. 61–69. [10] D.Z. Noor, P.R. Kanna and M.-J. Chern: Int. J. Heat Mass Transfer Vol. 52 (2009), pp. 3009–3023. [11] S.S. Mendu and P.K. Das: European Journal of Mechanics B/Fluids Vol. 39 (2013), pp. 59–70. [12] J.P. Holman: McGraw-Hill, Inc., 1997. [13] R.J. Moffat: ASME J. Fluids Engineering Vol. 104 (1982), pp. 250–258.

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Performance Improvement of a Hidden Ceiling Fan Sheam-Chyun Lin a, Ming-Yuan Hsiehb and Cheng-Ju Changc Department of Mechanical Engineering National Taiwan University of Science and Technology 43, Sec. 4, Keelung Road, Taipei, Taiwan 10672, ROC a

b

c

[email protected], [email protected], [email protected]

Keywords: hidden ceiling fan, axial-flow fan, CFD, inhale-return phenomenon, flow pattern.

Abstract. A hidden ceiling-fan is the new design of embedding and hiding itself deeply into the ceiling floor. This design is different from conventional ceiling-fans or circulating fans that usually without an enclosing housing. The majority part of hidden ceiling-fan is embedded in the ceiling floor; hence the enclosing housing will be needed and be created to surround the axial-flow fan. The housing geometric is critical factor for hidden ceiling-fan because the air flow will pass though the horizontal plane of ceiling floor which the inlet and outlet are almost located at same plane. Consequently, the inappropriate design of enclosing housing will cause inhale-return phenomenon. It affects the induced flow performance of a hidden ceiling-fan. Few studies have investigated fan induced flow and its characteristics in a selected space. In this study, computational fluid dynamic (CFD) numerical simulation and experimental investigation were used to predict and valid the flow pattern with different geometric housing and operating conditions. The results showed that the flow pattern has different features as it leaves the fan downward the floor. The unique inhale-return phenomenon probably happens when inappropriate enclosing housing was designed such as high ring-plate and outlet-inlet ratio. Furthermore, the blockage effect will happen if the blockage distance is to short. In conclusion, this systematic design investigation on hidden ceiling-fan not only provides the fan engineer’s design ability to avoid the inhale-return phenomenon, but also the predicting capability on the air flow induced characteristics and performance. Introduction A hidden ceiling-fan is upgraded evolution which inherited all the characteristics from traditional ceiling fans. Generally, ceiling fans are used to circulate or mix air within a space and provide local air movement to enhance thermal comfort of people during warm condition. In most tropical countries, ceiling-fans are extensively used to create an indoor breeze, improve the space air distribution and enhance the feeling of comfort via cooling effect which provided by fans to increase convective evaporative heat loss from the skin. For the economic viewpoint, ceiling-fans have low investment cost, simple in construction, easy to install, and do not need regular maintenance. Especially, they consume a relatively low amount of energy in comparison to air conditioning units, and therefore are used on a large scale worldwide. Even present day with the widespread use of air conditioning units, it has not displaced the ceiling-fan but complemented its usage. For instance, Rohles et al. [1, 2] studied the effectiveness of ceiling-fans in enhancing comfort experimentally by various temperature and air velocity in an environment chamber equipped with a ceiling-fan. The results showed that an air flow from a ceiling-fan with velocity between 0.5 and 1.0 m/s compensates for a 2.8o-3.3oC temperature change. James et al. [3] shown that the additional use of ceiling-fans in air conditioned rooms can lead to substantial savings of energy if ceiling-fans are used in conjunction with higher thermostat set points. A comparative study of commercially available ceiling-fans and a high efficiency fan is given by Schmidt and Patterson [4]. This new fan consists of four blades with tilt angles varying over the length of the blade to adjust the angle of attack for the different speeds at different radii. A hidden ceiling-fan has a lot of advantage with an enclosing housing, but its housing must evaluate carefully and thoughtfully. Because the majority part of hidden ceiling-fan is embedded in ceiling floor, the enclosing housing will be needed and be created to surround the axial-flow fan. Once

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the enclosing housing is created and hidden behind the ceiling floor, the air flow is inhaled from inlet and is expelled from outlet by axial-flow fan. Meanwhile, the air flow will pass though the horizontal plane of ceiling floor which the inlet and outlet are located at same plane. Thus, the air flow pass though the inlet and outlet can be affected each other when structure of enclosing housing is inappropriate design. Then, the air flow is expelled from outlet will directly return to inlet but not downward the floor. This negative effect due to the presence of the flow resistance inside enclosing housing is hereafter referred as the inhale-return phenomenon. Experimental and Numerical Program The hidden ceiling fans available in the market have a tendency to install invisible and thinner as possible. This implies that the whole flow passage inside the enclosing housing has to compress and hide behind the ceiling floor. Obviously, this unfavorable effect can seriously influence the fan’s flow pattern for the cooling of occupant. Within a crowded enclosing housing, the complex problem of flow resistance inside the hidden ceiling fans needs to inspect and improve. As for the performance determination, not only the predicted result of airflow rate is compared with test measurement, but also the visualization of flow pattern at different operating parameter is conducted with the aid of numerical simulation. For the purpose of investigation into the relation between the enclosing housing and the flow pattern, this study chooses a commonly used 356 mm-diameter axis-flow fan with the enclosing housing size of 582(L)*582(W)*192(H) mm3 for demonstrating this research as illustrated in Fig. 1. Furthermore, some of parameters inside the hidden ceiling fan have been set for this research. Experimentally, the fan’s performance is executed via a hot wire anemometer at base of CNS-597 code [5]. The numerical calculation and visualization analysis are carried out using the CFD software Fluent [6]. Also, the calculated flow rate is validated by comparing them with the corresponding experiments. Fig. 2 shows the parameters setting of this disassembled ceiling fan. For investigating the flow pattern and fan evaluation, five parameters are involved in this study which includes various blockage length, ring-plate high, inlet-outlet ratio, various fan rpm and fan guard.

(a) With fan guard (b) Without fan guard Fig. 1 The ceiling fan with different housings. Fig. 2 The disassembled hidden ceiling fan. Performance Measurement Setup. A performance test lab was set-up which hidden ceiling-fan power use, rpm and airflow could be measured. A digital hot wire anemometer (with an accuracy of 0.03% and measurement ranges between 0 and 30 m/s scale reading) was mounted on a tripod to take air velocity measurements. A precision digital watt meter (with a resolution of 0.1 W) was used to measure power consumption, and a hand-held non-contact photo tachometer (with an accuracy of 0.05% and a resolution of 1 rpm) was used to measure fan speed (rpm). Finally, the hidden ceiling-fan was mounted in a large open room with the housing size of 15(L)*15(W)*3(H) m. The hidden ceiling-fan was mounted on the ceiling floor in the center of the room. The air velocities were measured by means of a hot-wire anemometer below the ceiling floor 1 m as the measured plane, beginning at the fan axis r = 0 and then moving radially outward at this measured plane along the radius straight line by placing each points at 50 mm increments apart on a straight line. Basically, points on a straight line can form the circles from the central axis. Each circle will be divided by every

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30 degree to form the 12 measured points because the flow pattern of hidden ceiling-fan is not symmetric as conventional ceiling-fan. In addition, each measured point was averaged, the mean downward velocities of minimum and maximum, for at least two minute at each point. The readings were undertaken at points until the air velocity dropped below 0.1 m/s which the velocity became undetectable. Afterward, by integrating the air velocity over the measured radially disc from each circle averaged, the volumetric flow rate can be numerically obtain in this measured plane. Numerical Scheme. This study simulates the complex flow patterns for the hidden ceiling-fan by utilizing the commercial computational fluid dynamics (CFD) software Fluent [6] to solve the fully three-dimensional incompressible Navier-Stokes equations with the standard k − ε turbulence model. In addition, this model also adapting the multiple reference frame (MRF) mode to deal with the rotating fluid inside the axis fan. MRF mode simulates the rotating fan to produce the energy of airflow which influences the entire flow pattern in the selected room. Under this configuration, the flow pattern visualization at each operating parameter is performed by the steady-state computation. Results and Discussions Performance Evaluation. Fig. 3 demonstrates the flow patterns of the hidden ceiling fan with and without the fan guard condition in the CFD; meanwhile, the horizontal planes below the blade of 0.25m, 0.5m, 0.75m and 1m are chosen to show the airflow distribution. Fig. 3(a) shows that the fan with guard has wider flow distribution with lower scale of velocity. On the contrary, Fig. 3(b) shows that the fan without guard has concentrated flow distribution with higher scale of velocity. For investigating the characteristic of the hidden ceiling fan, table 1 lists the parameters of housing setting. Fig. 4 illustrates performance comparison, a good agreement, between experimental and numerical airflow rate of each parameter as fan speed operating at low speed (1000 rpm). Similarly, the median and high speeds also reveal the same trend.

(a) With fan guard. (b) Without the fan guard. Fig. 3 The flow patterns of the hidden ceiling fan. Airflow Rate (EXP) 1600

) 1400 m cf( 1200 et 1000 aR 800 w ofl 600 ri 400 A 200

1342 1313

1245 1257

1177 1163 1139 1130

Airflow Rate (CFD) 1313

Case A_exp

1313 1311

1163

) 1600 fm c( 1500 tea R 1400 wo 1300 lfr iA 1200

1163 1161

0

0

Case B80_exp

Case B80_cfd 1702 1684

1700

1165

1074

Case A_cfd

1800

0

0

1100

1534 1342 1313 1177

1491

1540 1532

1365 1355

1163

1000 Case Case Case Case Case Case Case Case Case Case Case A B80 B60 B40 B20 C30 C50 C70 D113 D105 D92

Low speed

median speed

high speed

Fig. 4 Performance comparison (1,000 rpm). Fig. 5 Comparison of cases with/without fan guard. Fan-Guard Setting. Fig. 5 illustrates performance comparison between experimental and numerical under with (Case A) and without (Case B80) fan guard conditions at different rotational speed. The result shows that the airflow rates from experiment both setting with and without fan guard

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at median speed are 1534 cfm and 1491 cfm, that increases 43 cfm (2.88%) with fan guard assistance; meanwhile comparison with CFD, the airflow rates from numerical both setting with and without fan guard, are 1365 cfm and 1355 cfm, that increases only 10 cfm (0.73%) with fan guard. Blockage High. Fig. 6 shows that blockage distances are denoted as Case B80, Case B60, Case B40 and Case B20 to demonstrate the blockage effect. As comparing with the numerical data from Fig.4, the various blockage distances show that Case B80 (1163 cfm), Case B60 (1139 cfm), Case B40 (1130 cfm) and Case B80 (1074 cfm) respectively. Fig. 7(a) ~ Fig. 7(e) show the results when the blockage plates were placed 20mm, 40mm, 60mm and 80mm on the top of housing, although the airflow channel is suppressed by blockage plate but the flow rate slight reduced an remained 83.3% of that without the blockage. Furthermore, the blockage effect didn’t invocate the inhale-return phenomenon when suppressed the channel space speeding up the airflow to pass through.

Fig. 6 Schematic blockage distances. (a) Diagonal view of Case B80 (b) Part view of Case B80

(c) Part view of Case B60 (d) Part view of Case B40 (e) Part view of Case B20 Fig. 7 Velocity distributions under various blockage distances. Ring-Plate High. Fig. 8 illustrates that various high ring-plates are denoted as Case C30, Case C50 and Case C70. As comparing with the numerical data from Fig. 4, the various high ring-plates show that Case C30 (1163 cfm), Case C50 (0 cfm) and Case C30 (0 cfm) respectively. Fig. 9(a) ~ Fig. 9(e) show the results that the higher ring-plate causes the inhale-return phenomenon.

Fig. 8 Different high ring-plates. (a) Front view of Case C70. (b) Diagonal view of Case C70.

(c) Part view of Case C30. (b) Part view of Case C50. (e) Part view of Case C70. Fig. 9 Velocity distributions under various high ring-plates. Inlet-Outlet Ratio. Fig. 10 illustrates that various inlet-outlet ratios are denoted as Case D113, Case D105 and Case D92. As comparing with the numerical data from Fig. 4, the various inlet-outlet ratios show that Case D113 (1163 cfm), Case D105 (1161 cfm) and Case D92 (0 cfm) respectively.

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Fig. 11(a) ~ Fig. 11(e) velocity distributions inside the blade passages, the results, show that the inhale-return phenomenon occurs once the inlet area is smaller than outlet area. Form logical concept, the higher reducing inlet area increases the higher flow resistance once the airflow enters inadequate. This means that the airflow can’t be effectively discharge to measured plane by fan blade because the flow resistance has created by blocking passage.

Fig. 10 Various inlet-outlet ratios. (a) Diagonal view of Case D105. (b) Diagonal view of Case D92.

(c) Part view of Case D113. (d) Part view of Case D105. (e) Part view of Case D92. Fig. 11 Velocity distributions under various Inlet-outlet ratios. Concluding Remarks. In summary, the setting of fan guard can widely change the airflow distribution but slightly increase the airflow rate. Also, the inappropriate design of blockage distances will decline the airflow rate. Both fan guard and blockage distances don’t invoke the inhale-return phenomenon. On the contrary, the inappropriate designs of enclosing housing, such as high ring-plate and inlet-outlet ratio, will cause inhale-return phenomenon. Furthermore, all the parameters operated at different rotational speed shown the same trend. References [1] F.H. Rohles, S.A. Konz, B.W. Jones, Ceiling fans as extenders of the summer comfort envelope, ASHRAE Transactions 89 (1A) (1983) 245–263. [2] F.H. Rohles, S.A. Konz, B.W. Jones, Enhancing thermal comfort with ceiling fans, Proceedings of the Human Factors Society (26th Annual Meeting) (1982) 118-122. [3] P.W. James, J.K. Sonne, R.K. Vieira, D.S. Parker, M.T. Anello, Are energy savings due to ceiling fans just hot air?, ACEEE Summer Study on Energy Efficiency in Buildings (1996) FSEC-PF-306-96. [4] K. Schmidt, D.J. Patterson, Performance results for a high efficiency tropical ceiling fan and comparison with conventional fans - Demand side management via small appliance efficiency, Renewable Energy 22 (2001) 169-176. [5] CNS 597, Determination of ceiling fan, Chinese National Standard (1982). [6] Fluent Inc., Fluent 6.2 documentation (2004).

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The Design of Heat Pipe Heat Exchanger for CO2 EGS Jui Ching Hsieh 1, a, David T. W. Lin 2,b , Wei-Mon Yan3,c, and Long Der Shin2,d 1

Industrial Technology Research Institute of Taiwan, No. 195, Sec. 4, Chung Hsing Rd., Hsinchu City, Taiwan

2

Institute of Mechatronic System Engineering, National University of Tainan, No. 33, Sec. 2, Su-Lin St., Tainan, Taiwan 2

Dept. Greenergy Engineering, National University of Tainan, No. 33, Sec. 2, Su-Lin St., Tainan, Taiwan a

[email protected], [email protected], [email protected], d [email protected]

Keywords: Heat pipe, Heat exchanger, Efficiency, EGS

Abstract. The findings of new energy and energy harvester are the important issues for the lacking of fossil energy. For the purpose of the effective usage of supercritical CO2 flowed from the product well of CO2 EGS (Enhanced Geothermal System), an innovative heat pipe heat exchanger (Hx) is designed and practiced in this study. This study presents an innovative Hx of heat pipe for extracting the heat from CO2 or warm gas. By using the heat pipe for cooling gas is the fundamental idea of this Hx. The experimental apparatus of Hx consists a heating blower to blow out hot gas, a circulating cool water device, and a set of heat pipes. The efficiency of Hx is approved as the increasing air velocity and the more fins gradually. This innovative heat pipe exchanger is proofed through our experiment. This heat pipe Hx is suitable for the application of enhanced geothermal system (EGS) and more energy harvesting application. Introduction The findings of new energy and energy harvester are the important issues for the lacking of fossil energy. CO2-EGS is one kind of technology to obtain the geothermal energy. The CO2-EGS has been proved its commercial operation as the flow resistance decreases and heat extraction enhances. The difference between EGS and traditional geothermal system is the heated fluid. The EGS is necessary to pump the fluid from the ground. Therefore, EGS will enlarge the cost of the electric generation. To increase the heat extraction from the heated fluid in the EGS is more important than the one in the traditional geothermal system. The heat exchanger (Hx) is the device that it extracts the heat from the working fluid with high temperature to the one with low temperature. In the application of industry, such as machine factory, petrochemical plants, and food factory, et al., the Hx is popular to use. We can see a lot of applications in the laboratories or factories for cooling, condensing, heating, evaporating, and heat recovering. Recently, most of the studies of Hx are discussed in the design of the geometry, arrangement, working fluid et al.. Heat pipes are the excellent devices for heat removal based on the phase change. The heat transfer efficiency of phase change is better than the one of natural convection and forced convection. Heat pipe has been used to improve the thermal performance of high power LED package [1]. Xiang et al. develop a brand new phase change radiator for the cooling of the high power LED [2]. The thermal performances of heat pipe have been investigated widely, such as the effects of the length of heat pipe’s evaporator section or condenser section [3], the effect of the working fluid [4]. Yau et al. have designed a heat pipe Hx in the air conditional equipment [5]. In addition, Kerrigan et al. design a heat pipe heater to transfer the geothermal energy to home in the colder regions [6]. A series of new design of heat pipe Hx are used to improve the environmental conservation in the operating room of hospital for recycling the waste heat and reducing the air pollution [7-8]. The heat pipe Hx is applied in the power plants for recycling the heat of the exhaust gas in the fuel boiler [9]. According the above-cited study, we know that the advantages of heat pipe are high efficiency and green energy. For the purpose of the effective usage of supercritical CO2 flowed from the product well of CO2 EGS, an innovative heat pipe Hx is designed and practiced in this study. This study presents an innovative Hx of heat pipe for extracting the heat

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from CO2 or warm gas. This study investigates the performances of heat transfer between hot gas and water by the heat pipe Hx. We design a series of experiment to proof the high efficiency of this innovative heat pipe Hx, and the availability on the application of EGS.

Model and Experiment Model. This study investigates the efficiency of the heat pipe Hx. The performances of heat transfer between hot gas and water by the heat pipe Hx is studied. The area of heat dissipation is different on both sides. For the reason of the heat transfer coefficient of gas side is much lower than the water side, the heat transfer area of gas side must enlarge, such as increasing the area of fin or the pressure loss of gas flow. In this study, we should design the suitable area of heat exchange to balance the both sides of heat transfer. The heat of gas is obtained from the heat blower, it can be calculated as below. Q = m
⋅ Cp ⋅ (Tao − Tai )

(1)

here, the mass flow rate of gas is m
, Cp is the specific heat of experimental gas and ∆T = (Tao − Tai ) is temperature difference between the outlet and inlet of the heat blower. The coefficient of heat convection h of the gas-side can be calculated. h = Nu

λ

(2)

Dh 0.8

here, Nu = 0.023 ⋅ Re ⋅ Pr 0.3 , and, Dh is the hydraulic diameter, λ is coefficient of heat conductivity. Therefore, the heat transfer area in the gas-side can be obtained. Q = h ⋅ A ⋅ (Tho − Tci ) (3) here, Tci is the water temperature in the inlet of heat pipe Hx Tho is the temperature of gas in the outlet of heat pipe Hx The heat transfer area of gas-side and water-side should calculate to obtain the balance of the heat transfer for the difference of heat transfer coefficient between water and gas. Finally, the thermal efficiency will be obtained through our experiment ε =

Tco − Tci Thi − Tci

(4)

here, Tco is the water temperature in the outlet of heat pipe Hx Thi is the temperature of gas in the inlet of heat pipe Hx Experiment. The schematic diagram of this experimental system is shown in Fig. 1. It consists of a heat blower, the part of heat pipe Hx, thermostatic water tank, and data logger. Fig. 2 is the photograph of this realistic system of this innovative heat pipe Hx.

Fig.1 The schematic diagram of the experimental system of heat pipe Hx

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Fig. 2 The system of heat pipe Hx According to the evaluation of the heat transfer area calculated from the equations (1-3), an experimental apparatus is done with fifteen heat pipes. Water is used as the working fluid of the heat pipe in this study. The acrylic partitions of the heat pipe Hx are separated as the hot and cold fluid region. The central region is the condenser part of the heat pipe in the water side. The left and right regions are the evaporator part of the heat pipe in the gas side. The schematic diagram and photograph of the heat pipe Hx is shown as Fig. 3. The types of Hx are 15 heat pipes without fin and with 5 fins, and 30 fins. The air is heated by a heat blower then flows into the part of the heat pipe Hx. The water is circulated by the thermostatic water tank and the temperature is set as 20℃. The velocity of air and the temperature variation of air and water will be measured by anemometer and data logger.

(a)

(b)

Fig.3 (a) The schematic diagram of the heat transfer part of heat pipe Hx (b) The photograph of the Hx with 10 fins Results and discussions Throughout the experiment, the temperature difference profiles of Hx with the different air velocity (3~10 m/s) are discussed. The temperature difference profiles of the heat pipe Hx with air velocity are shown in Fig. 4. We observe that the temperature difference of the water between the inlet and outlet of the Hx without fin at 3 m/s is about 2.1℃. In addition, the temperature difference of the air is from 2.9℃ in this case. The variation of the temperature exhibits the heat transfer between the air and water apparently. The temperature difference of water increases from 2.1℃ to 3.4℃ as air velocity is from 3 m/s to 10 m/s. The temperature difference the air decreases from 2.9℃ to 1.4℃ as air velocity increases from 3 m/s to 10 m/s. Here, we observe that the temperature difference between the inlet and outlet in the water side as the air velocity increases. Even the temperature difference of air decrease, the temperature difference of the water still increases as the air velocity increases. Therefore, it is obvious that the heat transfer is excellent as the air velocity is faster. The reason is that the specific heat of water is greater than the one of air.

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Fig. 4 The temperature profiles of the Hx with the air velocity In one word, the efficiency of heat pipe Hx will be affected by the air velocity. The efficiency of heat pipe Hx with the various air velocity is shown in Fig. 5. The efficiency is 11.14% as the air velocity is 3 m/s, and 16.55% as 10 m/s. The efficiency is higher approach 1.49 times as the air velocity increase from 3 m/s to 10 m/s.

Fig. 5 The efficiency of Hx with air velocity Through the Fig. 4, the effect of the fin is exhibited by the variation of the temperature difference. The temperature difference of the water increases from 2.1℃ to 3℃ as the fin number increase from 0 to 30 as the air velocity is 3 m/s. In addition, the temperature difference increases from 3.4℃ to 4.1℃ as the fin number increase from 0 to 30 as the air velocity is 10 m/s. The variation of the temperature exhibits the better heat removal ability contributed by the more fins. The profiles of efficiency of the Hx without fin and with 5 and 30 fins are shown in Fig. 6. The tendency of the efficiency is similar in all of cases. The heat removal is better as the air velocity is faster. The efficiency is 11.14%, 14.08% and 15.0 % as the fin number is 0, 5 and 30 at air velocity is 3 m/s. In addition, the efficiency is 16.55%, 18.8% and 21.35% as the fin number is 0, 5 and 30 at air velocity is 10 m/s. Obviously, the efficiency of Hx is approved as the increasing air velocity and the more fins gradually. Furthermore, the increasing of efficiency is nonlinear as both design parameters. The efficiency increase 1.26 times as the fin number increases from 0 to 5 and 1.06 times as 5 to 30 as the air velocity is 3 m/s. It shows that the optimal fin number with the different operating air velocity exists under the consideration of cost and price.

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Fig. 6 The efficiency of Hx with or without fin Summary For the purpose of the effective usage of supercritical CO2 flowed from the product well of CO2 EGS, an innovative heat pipe Hx is designed and practiced in this study. The results show that the temperature of gas decreases through the heat exchange. The efficiency of Hx is approved as the increasing air velocity and the more fins gradually. Therefore, this innovative heat pipe exchanger is proofed through our experiment. In addition, it shows that the optimal fin number with the different operating air velocity exists under the consideration of cost and price. This heat pipe Hx is suitable for the application of enhanced geothermal system (EGS). More parameters of experiment can be investigated to improve the performance of this heat pipe Hx in future, such as the arrangement of heat pipe, the different thickness of fin, different working fluids and different area of contact of heat pipe (ellipse, circle). The efficiency of heat pipe Hx will increase to obtain the enough heat from the geothermal energy for the effective commercial operation. Acknowledgment The financial support provided to this study by the National Science Council of the Republic of China under Contract No. NSC 102-3113-P-024-001 is gratefully acknowledged. References [1] X. Y. Lu, T. C. Hua, Y. P. Wang, Microelectronics J. Vol.42 (2011), pp. 1257-1262. [2] J. H. Xiang, C. L. Zhang, F. Jiang, X. C. Liu, Y. Tang, Transactions of Nonferrous Metals Society of China Vol.21 (2011), pp. 2066-2071. [3] S. F. Wang, J. J. Chen, Y. X. Hu, W. Zhang, Applied Thermal Engineering Vol.31 (2011), pp. 2367-2373. [4] S. C. Wong, Y. C. Lin, J. H. Liou, Int. J. Thermal Sciences Vol.52 (2012), pp. 154-160, 2012 [5] Y. H. Yau, M. Ahmadzadehtalatapeh, Applied Thermal Engineering, Vol.30 (2010), pp. 77-84. [6] K. Kerrigan, H. Jouhara, G.E. O’Donnell, A.J. Robinson, Simulation Modelling Practice and Theory Vol.19 (2011), pp. 1154-1163. [7] M. Ahmadzadehtalatapeh, Y. H. Yau, Energy and Buildings Vol.43 (2011), pp. 2344-2355. [8] S. H. Noie-Baghban, G. R. Majideian, Applied Thermal Engineering Vol.20 (2000), pp. 1271-1282. [9] L. L. Vasiliev, Applied Thermal Engineering Vol.25 (2005), pp. 1-19.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 289-293 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.289

Optimization of Circular Diamond Saw Blades with Annular Slots Wei-Hsin Gau1, Kun-Nan Chen2,a and Yunn-Lin Hwang3 1

Department of Mechatronic Engineering, Huafan University, New Taipei City, 223, Taiwan.

2

Department of Mechanical Engineering, Tungnan University, New Taipei City, 22202, Taiwan.

3

Department of Mechanical Design Engineering, National Formosa University, Yunlin County, 632, Taiwan. a

[email protected]

Keywords: Circular saw blade, Resonance, Sizing optimization, Annular slot, Modal testing, Finite element analysis.

Abstract. Circular diamond saws rotating in high speed are widely used to cut hard materials, and narrow slots on saw blades are sometimes used to reduce the blades’ vibration and noise. Sizing optimization of the annular slots on saw blades is investigated in this paper. First, an accurate finite element model representing an actual saw blade is obtained by model updating. Then, sizing optimization on two types of annular slots is performed to maximize the frequency separation between the finite element analysis results and the saw blade’s operational speed, and to reduce the possibility of structural resonance. Optimization results demonstrate great improvements in frequency separation from the rotating speed of 500 Hz for the optimized models. Introduction Working in high speed, circular diamond saws are widely used to cut, dice or groove hard materials such as ceramics, optical glasses, rock, metal and electronic materials. The advantage of using diamond saws is that they can cut high aspect ratio work-pieces very efficiently. In the electronics industry, the machining speed of diamond saws for cutting Si wafers of thickness 200 µm can be more than three times as fast as that of UV lasers [1]. In particular, to cut wafers with thickness in millimeters, abrasive diamond saws are the only logical choice. Some diamond saw blades have radial or/and annular slots symmetrically distributed about the center hole. These narrow slots are used to increase the thermal dispersion efficiency of the blade and to reduce vibration and noise when the blade rotates in high speed. Fig. 1(a) shows a common circular diamond saw blade, and Fig. 1(b) demonstrates a saw blade mounted on a sawing machine by clamping the blade with two flanges during a cutting operation. A saw blade in operation can produce a high level of noise and even cause severe noise pollution in the work place. When the rotation speed is at or near one of the natural frequencies of the blade, resonance occurs and vibration and noise levels increase dramatically. Although they may weaken the blade structure, slots on a blade can decrease the vibration and noise intensity. Singh [2], through experimentation, observed the effects of radial slots on idling blades and found that radial openings destroyed the continuity of vibrational mode shapes of the blades, and sound wave transmission was also obstructed due to geometrical discontinuity. As a result, both vibration and noise levels were significantly diminished. Chen and Chang [3] proposed a two-stepped procedure for the optimum design of circular diamond saw blades, in an attempt to reduce the possibility of structural resonance. In step one, an accurate finite element (FE) model representing an actual saw blade is acquired by incorporating experimental and finite element analysis (FEA) frequencies to update the blade FE model. In step two, shape optimization of the radial slots on the blade, based on the updated geometrical parameters obtained in step one, is performed to maximize the frequency separation between the FEA results and the saw’s operational speed. Other research works about circular saw blades include: Ishihara et al. [4] studied the dynamic behavior of thermally loaded circular disks based on plate bending theories; and Schajer and Steinzig [5] employed Electronic Speckle Pattern Interferometry (ESPI) to measure the natural frequencies and mode shapes of saw blades.

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This paper studies the influences of annular slots on the dynamic characteristics of circular diamond saw blades, and investigates the sizing optimization of several types of the annular slots with the frequency separation between the FEA results and the saw’s operational speed as the objective function to be maximized. The sizing optimization of the annular slots is performed on finite element models that are derived from an experimentally updated model. The optimization results should provide improved designs for saw blades that produce minimal vibration and noise during operation. The finite element analysis and the sizing optimization are carried out by the use of the commercial software ANSYS and the ANSYS Parametric Design Language (APDL).

Fig. 1. (a) Circular diamond saw blade, and (b) clamping of the blade in a sawing machine. Research Methods Experimental Modal Testing. A circular diamond saw blade with a center hole diameter of 22 mm, an outer diameter of 230 mm and 16 radial slots was tested to extract its natural frequencies and mode shapes in a modal testing experiment. In the test setup, the blade was suspended by two thin strings to simulate a free-free boundary condition, and a miniature instrumented impact hammer and a miniature accelerometer were used to provide input force and measure response signal. Fig. 2(a) shows the blade’s test grid and the accelerometer was fixed at grid point No. 193. The impact hammer stroke each grid point three times and the frequency response functions were averaged. The test results including the test frequencies, damping coefficients and the mode shapes are shown in Fig. 3. Finite Element Analysis. The blade body and tip are measured to have thicknesses of roughly 2 mm and 2.6 mm, respectively. Also, the blade is measured at 531 grams. Finite element models for the blade in two different boundary conditions (BC) are created using the ANSYS software with SHELL93 elements: a free-free BC (Fig. 2(b)) and a fixed BC (Fig. 2(c)). The model with the free-free BC will be used later for model updating, and the one with the fixed BC simulating a saw blade clamped by two flanges on a sawing machine (Fig. 1(b)) will be modified to investigate the effects of annular slots. Fig. 4 displays the FEA frequencies and mode shapes of the first model, in which Mode (0,2), for example, symbolizes a mode with 0 nodal circle line and 2 nodal diameter lines. Note that due to structural symmetry most modes will appear in pairs (orthogonal pairs) but only one mode from each pair of the symmetrical modes is shown. Comparing the test and the FEA results in Fig. 3 and Fig. 4 reveals that although each two corresponding frequencies disagree quite significantly, their mode shapes match rather well. Further, when a saw blade revolves, rotation stiffening effects will take place. Faster the blade rotates, higher the frequencies increase. Finite element analysis of a saw blade rotating in high speed must take account of the stiffening effects.

Fig. 2. (a) Test grid, and finite element grid of the saw blade (b) in a free-free boundary condition, and (c) in a fixed boundary condition.

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Fig. 3. The test frequencies, damping coefficients and the mode shapes of the saw blade.

Fig. 4. FEA frequencies and mode shapes of the initial model. Model Updating. Applying FEM to analyze a structure requires the geometrical and material properties of the structure as input parameters. A small error in input parameters may produce large errors in the structural responses. To obtain a more accurate and reliable finite element model of a structure, the FE model updating has been an active research area [6,7]. Usually combined with an optimization technique, an FE model updating procedure modifies the FE model and seeks to minimize the difference between the analysis and the experimental results. The updated FE model is considered to be a better model for future dynamic response predictions or design modifications. The model updating process begins with experimental measurements of the natural frequencies and mode shapes of the structure tested. The FE model of the structure is created and then analyzed. Since the values of the finite element input parameters are often not precise, it is very likely that the measured and the predicted results will show a significant discrepancy. By carefully comparing the experimental and FEA mode shapes, matching modes are correctly paired, which is important since the order of the FEA modal data can be different from that of the measured data. By defining the error vector as a vector containing the relative differences between the experimental and FEA natural frequencies, an optimization problem can be formulated as to minimize the length of the error vector: 1

 m 2 Minimize e =  ∑ ei2  ,  i =1  fa− fe Subject to ei = i e i fi

(1) i = 1,…, m ,

mT − M ≤ ε ,

X jL ≤ x j ≤ X jU

(2) (3)

j = 1,…, n ,

(4)

where fi is the natural frequency for the matched mode i; the superscripts a and e represent FEA and experimental results, respectively; mT represents the total mass of the blade model, M the measured mass and ε a small positive value; xj is the jth FE input parameter and XjL and XjU denote its upper and lower bounds, respectively; m is the number of modes included in the optimization process; and n is the number of FE input parameters to be updated. This optimization problem is solved to yield a set of updated parameters, and then the results are checked for convergence. If converged, the process can be stopped; otherwise, FEA is once again performed using the updated parameters to produce a new set of modal data leading to the next iteration, and the procedure is continued in an iterative way. Since the blade tips are embedded with diamond grids, they have very rough surfaces. And the blade body is usually coated with a thick layer of paint, which makes the exact thickness of the blade body difficult to determine. Therefore, in this study, the tip thickness, denoted as x1, and the blade thickness, x2, are set as the updating parameters. In addition, to reduce the risk of introducing further modeling errors while applying boundary conditions, the modal testing experiment of the blade was conducted under a free-free boundary condition, and so is the finite element model constructed.

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Sizing Optimization. After the FE model is updated, the sizes of the annular slots on a saw blade can be optimized by maximizing the frequency differences between the blade’s natural frequencies and the saw’s operational speed. The shape optimization problem is formulated as follows: 1

Maximize

 r  f a − ω 2  2  ∑  i   , i =1  ω  

Subject to X jL ≤ x j ≤ X jU

(5) j = 1,…, s ,

(6)

where ω is the saw’s operational rotation speed; xj in this step represents the sizing parameters of the radial slots; and r and s represent the number of frequencies and design parameters included in the optimization process, respectively. To maximize the objective function defined in Eq. 5 is to enforce the blade’s natural frequencies to separate from the saw’s operational speed as far as possible. Therefore, the possibility of structural resonance can be minimized. Two types of annular slots are examined in this paper. Fig. 5(a) displays the 3 parameters (r, θ and w) defining a Type A slot, while Fig. 5(b) exhibits the 4 parameters (r1, r2, θ and w) for a Type B slot. Fig. 6(a) demonstrates saw blades with 3, 4, 5 and 6 Type A slots, and Fig. 6(b) shows a saw blade with 4 Type B slots. Blades shown in Fig. 6(a) can be used to study the effects of the number of openings on the dynamic characteristics of a blade. The saw blades mounted on a sawing machine are simulated by a fixed boundary condition as shown in Fig. 2(c).

Fig. 5. Design parameters for (a) Type A slots and (b) Type B slots.

Fig. 6. (a) Saw blades with 3, 4, 5 and 6 Type A slots, and (b) saw blade with 4 Type B slots. Results and Discussion The Updated Model. Applying the updating scheme with m=4, M=531 grams, ε=2 grams and n=2 (x1: tip thickness and x2: blade thickness), the updating process converged in 30 iterations. The final updated tip and blade thicknesses are 1.57 mm and 0.97 mm, respectively. There are significant discrepancies between the test and the initial model’s FEA frequencies. The updating technique reduces the disagreements dramatically, from more than 37% the most to less than 5%. Sizing Optimization for Type A Slots. Type A slots have 3 design variables (s=3), there are 2 frequencies included (r=2), and the operational speed is assumed to be 500 Hz (ω=500 Hz). Based on the updated geometrical parameters obtained in the last section, blade models with 3, 4, 5 and 6 Type A slots are clamped by a pair of flanges of 40 mm in diameter and then optimized using the sizing optimization scheme described earlier. The results are given in Table 1, which clearly shows that all optimized models produce natural frequencies well above or below the operational speed, and the improvements on the objective functions are significant. Therefore, the possibilities of structural resonance on the blades are greatly reduced. Among the 4 cases, a blade with fewer slots yields a better initial model with a greater objective function value. However, improvements from the sizing optimization are comparable for all cases.

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Table 1. Initial and optimal values for models with Type A slots. Status 3 slots 4 slots 5 slots 6 slots

Initial value Optimal value Initial value Optimal value Initial value Optimal value Initial value Optimal value

r [mm] 65.00 74.61 65.00 63.21 65.00 60.71 65.00 60.59

Design variable w [mm] 3.00 4.65 3.00 3.56 3.00 2.85 3.00 2.80

θ [°] 60.00 64.99 50.00 54.99 40.00 49.99 30.00 39.96

Freq. diff. (relative to 500 Hz) Mode 1 [%] Mode 2 [%] -13.98 4.21 -17.13 10.17 -12.37 5.41 -14.56 10.50 -10.14 6.96 -14.40 10.54 -7.74 8.10 -11.84 11.08

Obj. function f 0.146 0.199 0.135 0.180 0.123 0.179 0.112 0.162

Sizing Optimization for Type B Slots. For Type B slots, there are 4 design variables (s=4). A blade with 4 Type B slots is optimized, and the results are given in Table 2. Again, improvement in frequency separation (from 500 Hz) is obvious. Table 2. Initial and optimal values for the model with 4 Type B slots Status Initial value Optimal value

r1 [mm] 35.00 25.01

Design variable r2 [mm] W [mm] 20.00 3.00 21.81 1.87

θ [°] 70.00 70.21

Freq. diff. (relative to 500 Hz) Mode 1 [%] Mode 2 [%] -8.26 8.00 -13.74 10.01

Obj. function f 0.115 0.170

Stress Analysis. Although there is a concern that the annular slots may weaken the blade structure, stress analysis on the blades in cutting condition has revealed that the von Mises stresses of these saw blades with multiple openings are still much less than the allowable stress of 270 MPa. The largest maximum von Mises stress (σmax=23.2 MPa) occurs in the blade with 6 Type A slots. Summary In this paper, sizing optimization of the annular slots on circular diamond saw blades has been described. First, an accurate FE model representing an actual saw blade is obtained by incorporating measured and FEA frequencies to update the blade FE model. Then, sizing optimization on two types of annular slots, based on the updated geometrical parameters, is performed to maximize the frequency separation between the FEA results and the saw blade’s operational speed, and to reduce the possibility of structural resonance. Numerical results have demonstrated that the FEA frequencies of the updated model are in excellent agreement with the experimental data, and that FEA frequency separation from the rotating speed of 500 Hz has been greatly improved with two types of annular slots showing comparable outcomes. Stress analysis has also been performed and has revealed that the von Mises stresses of these designs are all within safe range. References [1] M. Mizuno, T. Iyama, B. Zhang, Analysis of the sawing process with abrasive circular saw, J. Manuf. Sci. Eng. 130(1) (2008), Paper no. 011012. [2] R. Singh, Case history: the effect of radial slots on the noise of idling circular saws, Noise Control Engineering Journal. 31(3) (1988) 167-172. [3] K.N. Chen, C. Chang, Optimum design of diamond saw blades based on experimentally verified finite element models, Computer-Aided Design & Applications. 9(4) (2012) 571-583. [4] M. Ishihara, Y. Ootao, N. Noda, Analysis of dynamic characteristics of a rotating, thermally loaded circular saw subjected to tensioning over a double annular domain, Journal of Solid Mechanics and Materials Engineering. 4(8) (2010) 1155-1166. [5] G.S. Schajer, M. Steinzig, Sawblade vibration mode shape measurement using ESPI, J. Test. Eval. 36(3) (2008) 259-263. [6] J.L. Zapico-Valle, R. Alonso-Camblor, M.P. Gonzalez-Martinez, M. Garcia-Dieguez, A new method for finite element model updating in structural dynamics, Mech. Syst. Sig. Process. 24 (2010) 2137-2159. [7] K.N. Chen, Model updating and optimum designs for V-shaped AFM probes, Eng. Optim. 38(7) (2006) 755-770.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 294-298 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.294

Effects of Metal Hydride Absorption in Reactor with Annular Finned Tube Heat Exchanger Yap Yong-Soon1,a; Peng Chi-hung2,b and Wang Chi-Chang3,c 1,2,3

Department of Mechanical and Computer-Aided Engineering, Feng Chia University, Taichung City, 407, Taiwan

a

[email protected], [email protected], [email protected]

Keywords: metal hydride; hydrogen heat and mass transfer; annular fins heat transfer

Abstract This study analyzed and discussed the hydrogen storage reaction in the metal hydride LaNi5 hydrogen storage tank with internally fined heat tube. As the heat transfer and hydrogen storage efficiency of internal temperature control system are better than external temperature control, this study created a hydrogen storage simulation method to discuss the effect of thermistor fins on hydrogen storage. The results showed that the fins have significant effect on increasing the hydrogen storage efficiency, and the hydrogen storage time decreases as the thermistor fluid velocity increases, but the drawback is not apparent when the fluid velocity reaches a threshold. Introduction At present, as for metal hydride hydrogen storage, the weight ratio of hydrogen storage is better than that of compression hydrogen storage. It is safe, its reaction is reversible, and the hydrogen storage reaction can proceed without changing the temperature and pressure largely. Thus, most current studies on hydrogen storage techniques focus on metal hydride hydrogen storage. In 1995, Jemni and Nasrallah first discussed heat and mass transfer of hydrogen absorption and release behaviors of two-dimensional metal hydrogen storage tank [1,2]. After a series of validation [3]-[7], most of the present metal hydrogen storage theories use macroscopic homogeneous assumed conditions to avoid handling the solid-gas mixing problem of metal alloy and hydrogen, so as to develop various governing equations meeting porous metal hydrogen storage material. Therefore, this study examined annular finned hydrogen storage tanks of internal temperature control, and analyzed the hydrogen storage efficiency. The findings can serve as references to future studies on hydrogen storage tank. Mode Definition and Method (1) Geometrical model The geometrical model used in this paper is divided into two parts. The inner tube fluid temperature controlled hydrogen storage tank is shown in Figure 1. The internal temperature controlled annular finned hydrogen storage tank is shown in Figure 2. The hydrogen storage tank shell and the fins are made of stainless steel (AISI-304). The schematic section of three-dimensional internal temperature controlled annular finned hydrogen storage tank is shown in Figure 3. (2) Mathematical architecture of metal hydride reaction zone According to previous studies [1] and [2], besides the exothermic and endothermic chemical reaction processes in the process of hydrogen absorption and release, the material and heat and mass transfer theories should be considered, so as to describe the variation of hydrogen absorption and release rate with the temperature and pressure inside the tank shell.

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(2.1) Energy Equation (ρCp )e

∂T 1 ∂  ∂T  ∂2T
[∆H −T(Cp,g −Cp,s )] = ker  + ke 2 − m ∂t r ∂r  ∂r  ∂z

( ρ C p ) e = ε ( ρ C p ) g + (1 − ε )( ρ C p ) s , k e = ε k g + (1 − ε ) k s

(1) (2)

where subscripts g , s and e denote the equivalence of gas, solid and solid-gas mixing. ( ρC p ) e and ke are equivalent heat capacity and equivalent heat transfer coefficient respectively. m



>0, represents hydrogen absorption behavior, while m
0 , for p g > p eq ,a m
= C a exp  − ln  R T  P  sat g    eq , a 

(7)

The above equation is the metal hydride hydrogen storage reaction expression, where ρ sat represent the metal density after the metal alloy absorbs and releases hydrogen completely respectively,
 is the metal hydride hydrogen storage activation energy,  is the metal hydride hydrogen storage constant. When the pressure inside the tank is greater than the equilibrium
>0) and releases heat. pressure Peq ,a , the metal hydride stores hydrogen (i.e. m (3) Mathematical Model of cooling fins and internal heat-tube wall The material of cooling fins, thermistor wall and metal internal bladder is stainless steel (AISI-304). In order to increase the heat transfer efficiency, the fins are fixed to the inner thermistor wall, the heat is transferred to the central fin radially, and the metal powder far from the cooling fins can transfer heat via metal internal bladder. The heat transfer area is enlarged greatly, then the expected hydrogen storage time is shortened greatly. The energy equation of cooling fins and thermistor wall and metal shell, where subscript w represents the physical characteristic of metal region, is expressed as follows. ∂T 1 ∂  ∂T  ∂  ∂T  (8) ρ w C p,w =  kwr +  kw  ∂t

r ∂r 

∂r 

∂z 

∂z 

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(4) Initial condition and material parameter settings The analysis module set initial conditions and material parameters are shown in Table 1. Table.1 Initial conditions and material parameters of hydrogen storage

Numerical Results and Discussion (1) Validation of hydrogen absorption behavior In order to validate the correctness of the mathematical model of this paper, the model discussed by Jemni et al. [10] is considered, as shown in Figure 4. The temperature change at the center in the hydrogen storage process obtained by the model of this paper is compared with that of Jemni in Figure 5. It is observed that the numerical analysis model built in this paper matches the experimental result of Jemni, suggesting that the mathematical model of this paper can be used as a correct analysis tool. (2) Effect of fins on hydrogen storage efficiency The effect of fins on the hydrogen storage efficiency can be observed in Figure 6. The hydrogen storage saturation time of the hydrogen storage tank with fins is shorter than that of the hydrogen storage tank without fins by 6100 sec. As shown in Figure 7, the hydrogen storage tank with fins is cooled to 340 K at 1000 sec (measuring point is at r=3 cm, z=4.1 cm inside hydrogen storage tank), whereas the hydrogen storage tank without fins is cooled to 340 K until 8000 sec. According to the inlet volume flow rate in Figure 8, the inlet volume flow rates of the two tanks reach the maximum flow of 0.3 L/s and 0.25 L/s with instantaneous entry of pressure at the beginning. They decrease to 0.025 L/s within 10 seconds of initial hydrogen storage reaction, and then hydrogen storage is stable. The above analysis shows in the hydrogen storage process, as the metal hydride hydrogen storage releases heat, more heat should be taken away by the fluid in thermistor, and the fins can enlarge the heat transfer area. When the heat is transferred only by thermistor wall, the heat is transferred slowly, and the surplus heat will cause reaction delay. (3) Effect of thermistor fluid flow rate The temperature and metal density distribution of hydrogen storage tank with annular fin in the hydrogen storage process is shown in Figure 9. The assumed thermistor fluid temperature is 293 K. As the hydrogen storage process releases heat, the thermistor must give cryogenic fluid to let the metal hydride reach the hydrogen storage reaction temperature. Therefore, the hydrogen storage tank inlet pressure increases to 10 Bar instantaneously at the beginning of hydrogen storage reaction, and the metal hydride density increases by degrees from 7164 Kg/m3 . As compared with the hydrogen storage process without fins in Figure 10, the variation and distribution of temperature field and metal hydride density with time are closely related to fins, suggesting that the fins actually can change the temperature distribution and hydrogen storage rate in the hydrogen absorption process. Second, in order to discuss the effect of thermistor operating fluid flow rate on the hydrogen storage efficiency, Figure 11 shows the effects of the operating fluid in thermistor at six velocities on the hydrogen storage reaction process. As seen, when the fluid velocity is high, the heat

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generated by metal hydride is more likely to be carried away. However, when the fluid velocity is higher than 5 m/ s , the rates of internal temperature drop are very close to each other. Figure 12 shows that when the water flow rate is higher than 5 m/ s , the metal hydride hydrogen storage saturation periods are very close to each other. The saturated hydrogen storage weight ratio is reached at 1400 sec.

Conclusions According to the analysis of the metal hydride powder hydrogen storage tank with annular fins, in the hydrogen storage process using water as operating fluid, the hydrogen storage saturation time is much shorter than the hydrogen storage tank without fins. In addition, when the operating fluid flow rate increases, the hydrogen storage time is shortened relatively. However, when the flow rate of operating fluid is higher than 5 m/s, the hydrogen storage saturation time is approximately fixed at 1300 sec and it no longer decreases. This suggests that the flow rate of operating fluid still should be considered moderately while aiming to shorten the hydrogen storage time, so as to avoid the operating fluid driving pump consuming excessive energy.

Acknowledgement Thanks for the subsidy of the outlay NSC100-2628-E-035-009-MY2 given by National Science Council, the Republic of China, to help us finish this special research successfully. H2

Fig.1 Inner tube fluid temperature controlled hydrogen storage tank

Fig.2 Internal

Fig.3 3-D internal

temperature controlled

annular finned

annular finned

hydrogen storage

hydrogen storage tank

tank

1.4

Fig.4 Experimental diagram of hydrogen storage tank

350

0.3

1.3 1.2

°C °C

Hydrogen Flow Rate (L/s)

1

Temperature (k)

330

0.9 0.8

320

0.7 0.6

Fin Tank No-fin Tank

310

0.5 0.4

300

Fin Tank No-fin Tank

0.3 0.2

Fin Tank No-fin Tank

0.25

1.1

Weight Ratio (Wt%)

°C

340

0.2

0.15

0.1

0.05

290

0.1 0

0

2000

4000

6000

8000

10000

Time (s)

Fig.5 Validation of temperature change at center in hydrogen storage process

280

0

0

2000

4000

6000

8000

10000

Time (s)

0

25

50

75

100

Time (s)

Fig.6 Effect of fins on

Fig.7 Effect of fins

Fig.8 Effect of fins

hydrogen storage

on internal

on inlet hydrogen

saturation time in

temperature change

volume flow rate

hydrogen storage

in hydrogen storage

within 100 sec.

process

process

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350

1.4 1.3

V=0.1m/s V=0.5m/s V=1m/s V=5m/s V=40m/s V=100m/s

Temperature (k)

330

1.2 1.1

Weight Ratio (Wt%)

340

320

310

1 0.9 0.8 0.7 0.6

V=0.1m/s V=0.5m/s V=1m/s V=5m/s V=40m/s V=100m/s

0.5 0.4 0.3

300

0.2 0.1

290

0

2000

4000

6000

8000

10000

Time (s)

0

0

500

1000

1500

2000

2500

Time (s)

Fig.9 Metal hydride

Fig.10 Metal hydride

Fig.11 Variation of

Fig.12 Variation of

temperature and

temperature and

temperature with time

hydrogen storage

density profiles in

density profiles in

of different water

weight ratio with

hydrogen tank with

hydrogen tank without

velocities in

time of different

annular fins (A) 100

fins (A) 100 sec (B)

hydrogen storage

water velocities in

sec (B) 700 sec

700 sec

process

process

Reference [1] Jemni, A.,Nasrallah, S. B., Study of two-dimensional heat and mass transfer during absorption in a metal-hydrogen reactor,International Journal of Hydrogen Energy, Vol. 20,pp.43-52,1995. [2] Jemni, A.,Nasrallah, S. B., Study of two-dimensional heat and mass transfer during desorption in a metal-hydrogen reactor, International Journal of Hydrogen Energy, Vol. 20,pp.881-891,1995. [3] Kikkinides, Eustathios S., Georgiadis, Michael C., Stubos, Athanassios K.,On the optimization of hydrogen storage in metal hydride beds,International Journal of Hydrogen Energy, Vol. 31,pp. 737-751,2006. [4] Kikkinides, E. S.,Georgiadis, M. C.,Stubos, A. K., Dynamic modelling and optimization of hydrogen storage in metal hydride beds, International Journal of Hydrogen Energy, Vol. 31,pp. 2428-2446, 2006. [5] Mellouli, S.,Askri, F., Dhaou, H., Jemni, A., Ben Nasrallah, S., Numerical study of heat exchanger effects on charge/discharge times of metal-hydrogen storage vessel, International Journal of Hydrogen Energy, Vol. 34, pp. 3005-3017, 2009. [6] Askri, F., Jemni, A., Ben Nasrallah, S., Study of two-dimensional and dynamic heat and mass transfer in a metal-hydrogen reactor, International Journal of Hydrogen Energy, Vol. 28, pp. 537-557, 2003. [7] Aldasa, K.,Matb, M. D.,Kaplanb, Y., A three-dimensional mathematical model for absorption in a metal hydride bed, International Journal of Hydrogen Energy, Vol. 27, pp. 1049-1056, 2002. [8] Zhou, Li.,Zhou, Yaping., Determination of compressibility factor and fugacity coefficient of hydrogen in studies of adsorptive storage,International Journal of Hydrogen Energy, Vol. 6, pp. 597-601, 2001. [9] http://webbook.nist.gov/chemistry.National Institute of Standards and Technology,Standard reference database, 2005. [10] Jemni, A., Nasrallah, S. B., Lamloumi J.,Experimental and theoretical study of a metal-hydrogen reactor,International Journal of Hydrogen Energy, Vol. 24,pp. 631-644,1999.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 299-303 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.299

Magnetic assisted laser percussion drilling Chao-Ching Ho1, a, Guan-Ru Tseng1,b, Yuan-Jen Chang1,c, Jin-Chen Hsu1,d and Chia-Lung Kuo1,e 1

No. 123, Sec. 3, University Rd., Douliou Yunlin, 640 Taiwan

a

b

c

[email protected], [email protected], [email protected], d e [email protected], [email protected]

Keywords: Laser, Magnetic field, Reflective Surface, Micromachining, Laser percussion drilling.

Abstract. In this paper, feasibility of laser percussion drilling on highly reflective materials i.e., Al5052 using an assisting magnetic field was explored. During the laser percussion drilling, the Lorentz force generated by the assisting magnetic field affects the laser-induced plasma and results in significant influence of the laser percussion drilling. The magnetic field simulation was performed to investigate the field strength of the L-shaped magnetic permeable metals. The influences of magnetic field and the laser radiation energy on the penetration depth and inlet diameter were examined. Introduction Laser percussion drilling has gained great attention in the industry due to its wide range of industrial applications and capability to process various materials, high operating speeds and accuracy. However, laser percussion drilling encounters difficulty in applications with a highly reflective target surface such as aluminum, which reflects the optical energy and dramatically reduces the processing efficiency [1, 2]. It lengthens the drilling time, increasing the cost of the process and decreasing the yield. Several solutions have been proposed to overcome this issue. Thawari et al. use high power pulsed Nd:YAG laser to provide enough energy to penetrate the highly reflective surface without reducing the yield of the process, but efficiency remains low [3]. Gu et al. report that shorter wave-length lasers improve absorption by the reflective material, thereby providing a higher cutting speed [4]. Zhu et al. utilize an ultra-fast pulsed laser, such as a femto-second laser, to provide high cutting speed without the effect of reflectivity from surfaces [5]. Both methods require expensive short pulsed laser equipment, which increases the cost of machining. In this paper, the effect of the magnetic field with the influence of different laser power on laser percussion drilling was explored. The magnetic field simulation was performed to determine the paired numbers of the permanent magnets for the L-shaped magnetic permeable metals. The penetration depth and inlet diameter are measured and examined. Magnetic Field Simulation Pairs of NdFeB permanent magnets with L-shaped magnetic permeable metals were selected for all experiments since the gap between the two portions of the magnets provided a pathway to the laser beam, as depicted in Fig. 1. Finite element (FE) method is one of the most used numerical simulation techniques to study the magnetic field distribution during laser processing. To understand how the magnetic field of the L-shaped magnetic permeable metals distributed, a finite-element simulation with COMSOL software was conducted. A mesh model is constructed in order to simulate the distribution of magnetic field lines, and the simulated result is shown in Fig. 2. In order to find out relation between the effect of magnet size and the distance between the workpiece and magnet on the effectiveness of magnetic field strength, The corresponding FE simulated magnetic field was performed along x-direction with the ± 0.75 mm movement from the origin, then move a step of 0.1 mm along z-direction and finally stop at 0.6 mm in z-direction. The preliminary simulation was

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performed to predict the strength of the magnetic field with the same gap distance of 1.5 mm between the paired L-shaped magnetic permeable metals but the different paired numbers of the magnets. Workpiece

One pair

(Al 5052)

Permanent magnet (φ10x5 mm)

Two pairs

Permeability material (SUS 420)

Fig. 1. The simulated result of the permanent Fig. 2. The simulation of the distribution of magnet with the gap distance of 1.5 mm between magnetic field lines with the different paired two L-shaped magnetic permeable metals. numbers of the magnets.

Fig. 3. The cross-section view of a magnetic Fig. 4. The cross-section view of a magnetic field simulated by the model with the one paired field simulated by the model with the two paired permanent magnets. permanent magnets. From the simulation with gap distance, 1.5 mm of one paired permanent magnets, the magnetic strength from the origin o is stronger (i.e., 1823 Gauss) than the position of 0.6 mm (i.e., 1111 Gauss) in z-direction, as shown in Fig. 3. From the simulation with gap distance, 1.5 mm of two paired permanent magnets, the magnetic strength from the origin o is stronger (i.e., 3439 Gauss) than the position of 0.6 mm (i.e., 2113 Gauss) in z-direction, as shown in Fig. 4. From the simulations, we observe that the magnetic strength is influenced by the paired numbers of magnets and the distance between the workpiece and magnet. Therefore the magnetic strength is stronger at the upper position of the workpiece and the L-shaped magnetic permeable metals with the two paired permanent magnets have a higher magnetic strength. The reason is the magnetic field line was influenced by the gap distance between the L-shaped magnetic permeable metals, and the much stronger magnetic field strength with the shorter distance between the North and South of the magnet.

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Experimental Setup The setup for studying the effect of magnetic field was shown and the isometric view was shown in Fig. 5. The whole experimental setup was established on a Sodick AP1L Micro Precision EDM machine. A fixture connected the holders of the optical components, a mirror and a lens, to the column of the EDM machine. The mirror reflected the laser to the sample while the lens with a Z-axis-stage focused the laser onto the workpiece. The workpiece was made of aluminum 5052 (i.e., Al 5052) with a thickness of 0.6 mm. A 120 mm focal length lens was used for focusing. The L-shaped magnetic permeable metals were placed at 0.5 mm below the workpiece. The distance between the paired L-shaped magnetic permeable metals were 1.5 mm. The field strength was measured by a digital gauss meter. The laser beam was focused on the surface of the workpiece. The influences of the magnetic field on the penetration depth and diameter were studied. Aluminum (i.e., Al5052) was used as the target material in these experiments. The laser source was a Nd:YAG laser (LOTIS, LS-2134UTF) which provided four harmonic modes, i.e., four different wavelengths. The 532 nm wavelength with pulse mode was used in all of our experiments. The maximum energy of a single pulse was 200 mJ in the experiments, while the maximum frequency was 15 Hz. The pulse width was around 6 ns.

Fixture Permanent magnets

L-shaped magnetic permeable metals Fig. 5. Isometric view of the setup for studying the effect of magnetic field. The laser drilling parameters are listed in Table 1. In these experiments, the penetration depth is determined after a couple of hours of careful grinding along vertical planes of the workpiece until the drilled cavity is made visible. The penetration depth and the diameter of holes and the thickness of

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recast are investigated by optical microscopy (OM). All the experiments were performed in air without additional process gas. The penetration depth and diameter were determined by taking the average of data from three separate drilling holes of the same workpiece. Experimental results of the effect of applying magnetic field on the percussion drilling holes are shown in Figs. 6 and 7. Table 1. The laser machining parameters.

1

Item

Parameter

Wavelength

532 nm

Frequency

15 Hz

Pumping lamp energy

20 J

Radiation energy

200 mJ

Focal length

120 mm

Process time

3s

Permanent magnet (Magnetic flux)

2.84 kG

No. of pulse (200 mJ)

1,10,20,30,40,45

10

20

30

40

45

Pulse 1 101 µm

Pulse 10 123 µm

Pulse 20 156 µm

Pulse 30 175 µm

No. of pulse Pulse 40 181 µm

46

236

Penetration depth

413

496

600

Pulse 45 185 µm

600

Fig. 6 The profile images of the drilled holes with the magnetic field applied at different number of laser pulse, where the radiation energy of the laser was 200 mJ.

Fig. 7 The inlet diameter images of the drilled holes with the magnetic field applied at different number of laser pulse, where the radiation energy of the laser was 200 mJ.

Conclusion This work showed the feasibility of using a magnetic field to influence the behavior of the plasma plume during laser percussion drilling. The depths of the drilled holes by the assisting L-shaped magnetic permeable metals were deeper than those in the normal case. It is due to the effect of the Lorentz force that the plume particle could be lifted upwards and circulated outwards to the sidewall from the center of laser beam. Therefore, the expanding of laser-induced plasma plume increases the removal rate of material on the sidewalls. In the future work, the external electric field employed to assist the laser percussion drilling will be investigated. Acknowledgement The work was supported by the National Science Council, Taiwan, R.O.C. NSC 101-2221-E-224-008.

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References [1] J. Wendland, P. M. Harrison, M. Henry, and M. Brownell, in: Proceedings of ICALEO (2005). [2] Y.-J. Chang, C.-L. Kuo, and N.-Y. Wang: J Laser Micro Nanoen. Vol. 7 (2012), p. 254 [3] G. Thawari, J. Sundar, G. Sundararajan, and S. Joshi: J. Mater. Process. Technol. Vol. 170 (2005), p. 229 [4] E. Gu, C. Jeon, H. Choi, G. Rice, M. Dawson, E. Illy, et al.: Thin Solid Films. Vol. 453 (2004), p. 462 [5] X. Zhu, D. Villeneuve, A. Y. Naumov, S. Nikumb, and P. Corkum: Appl. Surf. Sci. Vol. 152(1999), p. 138

Applied Mechanics and Materials Vols. 479-480 (2014) pp 304-308 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.304

An electric wheelchair with function of climbing up and down a step Ren-Chung Soong1, a, Sun-Li Wu2,b and Jui-Min Lee3,c 1, 2, 3

No.1821, Jhongshan Rd., Lujhu Dist, Kaohsiung City 82151, Taiwan (R.O.C.)

a

b

c

[email protected], [email protected], [email protected]

Keywords: wheelchair, electric wheelchair, climbing-stair

Abstract. A new electric four-wheel wheelchair with function of climbing up and down a step is proposed. Each wheel has four telescopic rods driven by a ratchet mechanism which makes them stretchable. They retract into each wheel during the wheelchair moves on the flat roads. They stretch out of each wheel to overcome a step obstacle during the wheelchair encounters the steps and thresholds. The center of gravity and angular position of the seat relative to the horizontal axis can be adjusted simultaneously during climbing up and down a step or moving on the uphill or downhill road sections. The actual test of climbing up and down a height 15 cm step has been done successfully on condition of carrying a weight 85 kg person. This new electric wheelchair makes users more safe and scopes of activity of the elderly and those with disabilities wider. Introduction In general, electric wheelchairs or scooters do not have the function of climbing up and down a step obstacle. And the center of gravity and the angular position of their seats relative to horizontal axis also can not be adjusted when encounter different road conditions. These two disadvantages make users feel unsafe during driving on the uphill or downhill road sections and limit the moving scopes of these two mobility devices for the elderly and those with disabilities. Usally, the seat angular position relative to horizotal axis of a wheelchair is not adjustable, but the seat back is. Therefore, the seats charactered with angular position adjustable function are rare. Zhao proposed a linkage seat mechanism driven by a linear actuator to adjust its angular position[1]. Soong et al. Also presented a linkage seat mechanism but driven by a set of screw-nut mechanism and a motor[2]. The climbing-stair mechanisms of wheelchair can be grouped into two categories according to the ways to climb up and down stairs. The First category is called as the type of auxiliary apparatus[3-9]. The devices of this type are use of mechanisms installed on wheels or frame such as linkage mechanisms or auxiliary wheels to climb up and down stairs. The second category is called as the type of building a temporary road[10-13]. The devices of this type are use of movable roads that are stored in wheelchair during driving on flat roads and released during climbing up and down stairs such as tracks. In this paper, we propose a new electric wheelchair with function of climbing up and down a step. And the center of gravity and angular position of its seat relative to horizontal axis are adjustable simultaneously during moving on the uphill or downhill road sections. These two special designs will make users feel safety and scopes of activity of the elderly and those with disabilities wider. And the prototype test of climbing up and down a height 15 cm step on condition of carrying a weight 85 kg person is implemented to verify the feasibility and effectiveness of this invention. Design of the wheel A wheel with four telescopic rod sets is shown in Fig. 1(a). Each set is comprised of a rod, a spring, a linear bearing, a rack and a ratchet. The telescopic rods are forced retracting into each wheel like a general wheel by ground reaction force during the wheelchair moves on the flat roads. They are pushed out of each wheel to overcome step obstacles by a push link which is driven by a cam as shown

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in Fig. 1(b) during the wheelchair encounters the steps or thresholds. By controlling these two cams, the telescopic rods can be released for needs of overcoming a step obstacle. The retreated and stretched states of a prototype wheel are shown in Fig. 1(c), respectively.

(a)

(b) Fig. 1 Formation of the wheel

(c)

Design of the seat A new seat, which the center of gravity and angular position relative to horizontal axis can be adjusted simultaneously, is shown in Fig. 2(a). This new seat mechanism is comprised of a link with six rollers, a set of ballscrew and nut driven by a motor and two fixed guiding tracks in both sides of the frame. By controlling the ballscrew, the center of gravity and angular position of the seat relative to the horizontal axis can be adjusted simultaneously. The adjustable range of the angular position relative to vertical axis of the seat is ±20°as shown in Fig. 2(b). The prototype of seat is shown in Fig. 2(c).

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(a)

(b)

(c) Fig. 2 Formation of the seat mechanism

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Prototyping and actual test A prototype of this new electric wheelchair has been made as shown in Fig. 3(a). The actual test of the wheels to climb up and down a height 15 cm step also has been done on condition of carrying a weight 85 kg person, the consecutive decomposition actions are shown in Fig. 3(b) and Fig. 3(c) respectively. These tests shown that this new mobility device can easily overcome a step obstacle and always keep the seat in horizontal position and adjust the center of gravity of the seat forward and backward simultaneously during climbing up and down a step or moving on the uphill or downhill road sections to make users more safe.

(a)

(b)

(c) Fig. 3. The prototype and actual test

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Conclusions A new electric wheelchair with function of climbing up and down a step was presented. A new seat, its center of gravity and angular position relative to the horizontal axis could be adjusted simultaneously, was also proposed in this paper. The prototype test of climbing up and down a height 15 cm step had been done successfully on condition of carrying a weight 85 kg person. This actual test verified the feasibility and effectiveness of this invention. There were two main advantages of this new mobility device. One was that make users more safe during driving on the uphill or downhill road sections or encountering a step obstacle, the other one was that make scopes of activity of the elderly and those with disabilities wider. Acknowledgments: The author is grateful to the National Science Council of the Republic of China (TAIWAN, R.O.C.) for supporting this research under grant NSC 101-2218-E-244-001 References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13]

Y. H. Zhao, Taiwan Patent M271565. (2004) R. C. Soong, S. L. Wu, W. H. Lee, Taiwan Patent M322817. (2007) R. Cox, U. S. Patent 4,200,161. (1985) J. Wild, U. S. Patent 5,423,563. (1995) H. S. Lai: On the Improved Design of A Step-climbing Mechanism (National Cheng Kung University Department of Mechanical Engineering Thesis, Taiwan, 2003) K. C. Chan, Taiwan Patent 301, 605. (1996) H. Kluth, U. S. Patent 4,569,409. (1986) I. Jayne, U. S. Patent 4,618,155. (1986) F. Bihler and A. Abele, U. S. Patent 4,556,229. (1985) N. Rembos, U. S. Patent 4,962,941. (1990) C. H. Kao, Taiwan Patent 204, 495. (1993) T. Quigg, U. S. Patent 5,158,309. (1992) M. Feliz, U. S. Patent 4,566,551. (1986)

Applied Mechanics and Materials Vols. 479-480 (2014) pp 309-313 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.309

The Meshing Efficiency Analysis of Coupled Planetary Gear Reducer Long-Chang Hsieh 1,a, Hsiu-Chen Tang 2,b 1

Dept. of Power Mechanical Engineering, National Formosa University 64 Wun Hua Rd., Huwei, Yunlin 63208, Taiwan 2

Institute of Mechanical & Electro- Mechanical Engineering 64 Wun Hua Rd., Huwei, Yunlin 63208, Taiwan a

b

[email protected], [email protected]

Keywords: Kinematic analysis, latent power theorem, train value equation, coupled type planetary gear reducer.

Abstract. This paper focus on the meshing efficiency analysis of coupled planetary gear reducer. First, according to the concept of train value equation, the kinematic analysis of coupled planetary gear reducers is carried out. Then, based on the latent power theorem, the meshing efficiency of coupled planetary gear reducer is derived. The coupled planetary gear reducer has the following characteristics: 1. There is a problem of power circulation, 2.Larger reduction ratio makes less meshing efficiency, and 3.For the same reduction ratio, larger value |ξ42| (|ξα|) will get better meshing efficiency. Introduction Planetary gear trains were the subject of intensive research directed at kinematic analysis [1-2], kinematic design [3-6], efficiency analysis [7-9], and patents [10-11]. Few studies focused on the efficiency analysis of coupled planetary gear trains. This paper focus on the meshing efficiency of coupled planetary gear reducer. Fig. 1 shows a coupled planetary gear train which is a planetary gear train with two sun gears (including ring gears) and two carriers (planet arms). 2012, Hsieh and Chen [11] proposed this coupled planetary gear reducer to have high reduction ratio and got the Taiwan patent right (M428280).

Fig. 1

Coupled planetary gear reducer (Taiwan Patent No. M428280) [11]

Kinematic Analysis For a planetary gear train, let us denote the first sun gear as i, the last sun gear as j, and the carrier (arm) as k, respectively. The relationship among ωi, ωj, and ωk can be expressed as : ωi − ξ ji ω j + (ξ ji − 1)ωk = 0

(1)

The coupled planetary gear reducer shown in Fig. 1 has two sun gears and two carriers, it is a planetary gear train with two train circuits. The coupled planetary gear reducer is coupled by two train circuits. According to the research of Hsieh, Lee, and Chen [4], the coupling relationship can be expressed as Fig. 2, Fig. 3(a), 3(b), and 3(c) are three examples of coupled planetary gear reducers with reduction ratios of 50, 100, and 99, respectively.

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Fig. 2

The coupling relationship of coupled planetary gear train shown in Fig 1

(a) Rr=50 (b) Rr=100 (c) Rr=99 Fig. 3 Three examples of coupled planetary simple gear reducer Let (2, 4; 5) and (2, 4; 7) are the 1st and 2nd train circuit of this coupled planetary gear train shown in Fig. 1(a), and ξ42=-2.76923 (ξ4’2’=-2.57143) be the train value of ring gear 4 (4’) to sun gear 2 (2’). According to Eq. (1), the two train value equations can be rewritten as:

ω2 + 2.76923 ω4 − 3.76923 ω5 = 0 ω 2 + 2.57143 ω 4 − 3 .57143 ω 7 = 0

(2) (3)

Based on Eq. (2) and Eq. (3), by eliminating the variable ω4, we get:

ω 2 + 49 ω5 − 50 ω7 = 0

(4)

For the coupled planetary gear reducer shown in Fig. 3(a), 1st carrier 5 is fixed, coupled sun gear 2 is adjacent ot input shaft, and 2nd carrier 7 is adjacent to output shaft, according to Eq. (4), its reduction ratio (Rr) is:

Rr =

ωin ω = 2 = 50 ωout ω7

(5)

Based on the same above process, the coupled planetary gear reducers shown in Fig. 3(b) and 3(c), their reduction ratios (Rr) are 100 and 99.

Latent Power theorem For a train circuit with sun gear i, ring gear j, and carrier k, let Ti, Tj, and Tk be the torques of members i, j, and k, respectively, according to the torque balance, we have: Ti + Tj + Tk = 0

(6)

The latent powers of sun gear i and ring gear j relative to carrier k ( Pik and Pjk ) are defined as: Pik = Ti × (ωi − ωk )

(7)

Pjk = Tj × (ω j − ωk )

(8)

Let ηijk ( ηkji ) be the meshing efficiency of planetary gear train if the latent power is transmitted from sun gear i (ring gear j) to ring gear j (sun gear i) when carrier k is relatively fixed. Based on the concept of latent power, the relationship among Pik and Pjk can be expressed as:

− Pjk = Pik × ηijk for Pik ≥ 0 and Pjk ≤ 0 k i

k j

−P = P ×η

k ji

k i

k j

for P ≤ 0 and P ≥ 0

(9a) (9b)

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Subsititute Eq. (7)~(8) into Eq. (9a)~(9b), we get:

Tj = −(ξ ji ηijk )Ti for Pik ≥ 0 and Pjk ≤ 0 Tj = −

ξ ji η

k ji

Ti for Pik ≤ 0 and Pjk ≥ 0

(10a)

(10b)

Meshing Efficiency For the coupled planetary gear reducer shown in Fig. 3(a), ξ42= -2.76923, ξ4’2’= -2.57143, according to Eq. (2)~(5), we get ω2=50ω7, ω5=0, and ω4= -0.3611ω2= -18.05556ω7.

(a). 2nd train circuit For the 2nd train circuit of coupled planetary gear reducer shown in Fig. 3(a), the relationship of angular velocities is ω2>ω7>0>ω4. Since 2nd carrier 7 is output and ω7 >0, we get T70. Then, based on the Equ. (8), the latent powers of ring gear 4’ relative to 2nd carrier 7( P47' ) can be expressed as:

P47' = T4' × (ω4 −ω7 ) < 0

(11)

According to Eq. (9a), we have:

− T4' ×(ω4 −ω7 ) = T2' × (ω2 −ω7 )× η72'4'

(12)

For the gear manufacturing, if the gears are manufactured by shaving, the meshing efficiency of external (internal) gear pair is 0.98 (0.99), then η 27'4' = 0.99 × 0.98 = 0.9702 . According to the Eq. (12), we have:

T4 ' = 2.4948 T2'

(13)

For the 2nd train circuit, sun gear2’, ring gear4’, and 2nd carrier 7 rotate about the same axis, we have T2 ' + T4' + T7 = 0 . Then, , we have:

T2' = − 0.28614 T7 > 0

(14)

T4' = − 0.71386 T7 > 0

(15)

Since ω2>ω7>0>ω4, according to Eq. (14) and Eq. (15), we get:

P2' = T2' × ω2 > 0

(16)

P4' = T4' × ω4' < 0

(17)

Based on Eq. (16) and (17), the power flow of 2nd train circuit can be drawn as Fig. 4(b).

(a) 1st train circuit (b) 2nd train circuit (c) Complete power flow Fig. 4 The power flow of 3K-type planetary gear reducer

(b). 1st train circuit Since ring gear 4 and ring gear 4’ are coupled together to be the is free link, we have:

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T4 = −T4' < 0

(18)

For the 1st train circuit of coupled planetary gear train shown in Fig. 3(a), the relationship of angular velocities is ω2>ω5=0>ω4. According to the Equ. (18) and ω2>ω5=0>ω4, the latent powers of ring gear 4 relative to 1st carrier 5 ( P75 ) can be expressed as:

P45 = T4 × (ω4 − ω5 ) > 0

(19)

According to Eq. (9b), we have:

− T2 ×(ω2 −ω5 ) = T4 ×(ω4 −ω5 )×η542

(20)

5 = 0.99 × 0.98 = 0.9702 , according to the Eq. (20), we have: For 1st train circuit, ξ42=-2.76923 and η 42

T4 = 2.85429 T2 or T2 = 0.35035 T4

(21)

Based on Eq. (15), Eq. (18), and Eq. (21), we get; T2 = 0.25001 T7 < 0

(22)

According to Eq. (14) and Eq. (22), the input torque Tin=Ti1+Ti2 can be expressed as: Tin = T2 + T2' = −0.03604 T7 > 0

(23)

Based on the Eq. (23), the meshing efficiency of the coupled planetary gear reducer can be obtained as:

ηm = −

Pout P P ω 1 1 1 =− 7 =− 7 × 7 = × = 27.748 × = 55.50% Pin Pin Pin ω2 0.03604 R r 50

(24)

If the gears are manufactured by grinding, the meshing efficiency of external (internal) gear pair is 0.99 (0.995). Then, the meshing efficiencies ηijk and ηkji can be regarded as 0.99×0.995=0.985. Base on the above process, the meshing efficiency of the coupled planetary gear reducer is ηm=71.32%. For the coupled planetary gear reducers shown in Figs. 3(a), 3(b), and 3(c), the meshing efficiencies of the coupled planetary gear reducers are summarized as follows:

[Example 1] Fig. 3(a), Rr=50 Fig. 3(a) shows a 2K-2H type planetary gear reducer with Rr=50, ξ42=ξα=-2.7692, ξ4’2’ =ξβ =-2.5714. 1. If η624 = η62' 4' = 0.9702 , we get its meshing efficiency is ηm=55.50%. 2.

If η624 = η62' 4' = 0.9850 , we get its meshing efficiency is ηm=71.32%.

[Example 2] Fig. 4(b) , Rr=100 Fig. 3(b) shows a 2K-2H type planetary gear reducer with Rr=100, ξ42=ξα=-2.6667, ξ4’2’ =ξβ =-2.5714. 1. If η624 = η62' 4' = 0.9702 , we get its meshing efficiency is ηm=37.85%. 2.

If η624 = η62' 4' = 0.9850 , we get its meshing efficiency is ηm=54.84%.

[Example 3] Fig. 4(c) , Rr=99 Fig. 3(c) shows a 2K-2H type planetary gear reducer with Rr=99, ξ42=ξα=-3.6667, ξ4’2’ =ξβ =-3.5. 1. If η624 = η62' 4' = 0.9702 , we get its meshing efficiency is ηm=43.75%. 2. If η624 = η62' 4' = 0.9850 , we get its meshing efficiency is ηm=60.81%. The meshing efficiency of coupled planetary gear reducer with Rr=100 (Fig. 3(b)) is much less than coupled planetary gear reducer with Rr=99 (Fig. 3(c)). Hence, when we design this coupled planetary gear reducer, we must choose the larger |ξ42| (|ξα|) as possible.

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Conclusion This paper focuses on the meshing efficiency analysis of coupled planetary gear reducer. Three coupled planetary gear reducers with high reduction ratios (50, 100, and 99) are used as examples to illustrate the process of analysizing meshing efficiency. This coupled planetary gear reducers have the following characteristics: 1. There is a power circulation in this coupled planetary gear reducer. 2. Basically, larger reduction ratio makes less meshing efficiency. 3. For the same reduction ratio, larger value |ξ42| (|ξα|) will get better meshing efficiency. 4. The better quality of gears (manufactured by grinding) will produce much better meshing efficiency.

Acknowledgements The authors are grateful to the National Science of the Republic of China for the support of this research under NSC 100-2221-E-150-013. The authors are also grateful to the HIWIN Technologies Corp. of the Republic of China for the support of this research under 100AF10.

References [1] L.C. Hsieh, H.S. Yan and L.I. Wu: Journal of the Chinese Society of Mechanical Engineers, Vol. 10, (1989), No. 2, pp.153-158 [2] M.C. Tsai and C.C. Huang: Journal of Mechanical Design, Vol. 132, (2010), 065001. [3] W.M. Hwang and Y.L. Huang: Configuration design of six-speed automatic transmissions with two-degree-of-freedom planetary gear trains, Transactions of the Canadian Society for Mechanical Engineering, Vol. 29, (2005), No. 1, pp. 41-55 [4] L.C. Hsieh, H. S. Lee and T.H. Chen: Materials Science Forum, Vol. 505-507, (2006), pp. 1003-1008 [5] C.G. Lu and Q.H. Duan: The unit analysis method of 3K type planetary gear train, Journal of Machine Design and Research, Vol. 25, (2009), No. 6, pp.22-24 [6] L.C. Hsieh and H.C. Tang: submitted to Journal Advanced Materials Research (2013). [7] Jose M.del Castillo: Mechanism and Machine Theory 37, (2002), pp.197-214 [8] L.C. Hsieh and T.H. Chen: Advanced Materials Research, Vols.317-319, (2011), pp.2226-2229 [9] L.C. Hsieh and T.H. Chen: Journal of Advanced Science Letters, Vol. 12, (2012), pp34-39 [10] Y. Arai, T. Ouchi and H. Umezawa, U.S. Patent No. 07325780. (2008) [11] L.C. Hsieh and T.H. Chen, Taiwan Patent No. M428280. (2012)

Applied Mechanics and Materials Vols. 479-480 (2014) pp 314-318 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.314

A Study On the Optimization design of BOP Gantry Crane By ANSYS Hyun-Ji Kim1,a, Chang-Kweon Jeong2,b, Yong-Gil Jung3,c and Sun-Cheol Huh3,d† 1

Graduate School of Department of Mechanical and Energy Engineering, Gyeongsang National University 2 DMC co., LTd 3 Department of Mechanical and Energy Engineering , Gyeongsang National University

a

b

c

d

[email protected], [email protected], [email protected], [email protected]

Keywords: Offshore structure, Drillship, Offshore crane, Gantry crane, BOP

Abstract. BOP (Blow-out preventer) Gantry Crane is a crane which is used to move BOP stack saved in Drilling Platform to BOP trolley. However, such offshore plant equipment has not been developed in Korea but a lot of loyalty has to be paid to overseas companies. Thus, domestic production of it is necessary. In this research, ANSYS was used to apply into analysis of rolling and pitching due to wave, wind load due to Drillship, and the crane's self-weight and structural analysis was implemented. Moreover, Simulation X was used for control system design, and sub system was modeled and hydraulic system analysis was implemented. Introduction Recently, offshore plant industry is in the spotlight. Offshore plant means design, production, installation, and operation of drilling equipments such as Drillship, LNG-SPSO, or LNG-FSRU for digging up crude oil, natural gas or other energy in the deep sea instead of land. As the offshore plant market develops, the market of offshore equipment is expected to expand, too, but only the minimum number of companies produce a portion of products in Korea compare to the world market. It is necessary to improve Korean technology by making domestic offshore plant equipments as soon as possible (Yong-gil Jung et al. 2011). At present, up to 55 ton level (Main Hoist : 275mT × 2) is being commercialized in case of professional manufacturer in other country, and the performance is none in Korea. BOP Gantry Crane is the essential equipment of Drilling System Package for Drillship/Rig. It is used to move BOP stack in Drilling Platform using BOP Trolley. In here, BOP(Blow-out Preventer) Stack is a safety device that controls Drillship's mining work so oil, gas, or water is not gushed out from the ocean oil well. Fig. 1 shows the structure of Drillship equipment. BOP Gantry Crane is installed at the end of after drill floor on upper side of Moonpool of a Drillship. It moves back and forth of the rail toward the direction of PORT/STBD of the Drillship. In this research, as a domestic making of BOP Gantry Crane which is an offshore plant equipment, pressure system using for system control, Simulation X is implemented and ANSYS is used for optimal design of Crane to implement structure analysis.

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Fig. 1 Drilling system package

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(a) BOP Gantry Crane (b) CATIA Modeling Fig. 2 BOP Gantry Crane

Structure and analysis conditions 2.1 Structure of BOP Gantry Crane BOP Gantry Crane is a crane looks like a door or a bridge. It consists of jib, trolley, and hoist. A rail is in the bottom and it moves on it. Fig.2 is modeling of BOP Gantry Crane using CATIA. The crane used in this research is 300ton, 25m of height, and 16-20mm of plate thickness. It may have bucking since due to small structure of plate area compared to the overall length, so supplementary material is designed additionally. Unnecessary parts are eliminated in order to see the change of structure when it is loaded and it is modeled simply at maximum. Crash test was implemented to see conflict or duplicate occur at the CATIA between supplementary material, crane plate, and each part. 2.2 Application condition of dynamic figures BOP Gantry Crane operates on Drillship/Rig, so dynamic figures should be applied on the operation weight in order to reflect continues movement of the boat.

(1) The general equation that calculates dynamic figures follows equation (1) if there's no other assigned dynamic figure value. In here Cv is dynamic figure and Vr is hoisting speed. The equation of other dynamic figure values depend on the offshore plant structure is on Table 1. BOP Gantry Crane is an equipment of Drillship, so dynamic figure 1.6 is applied according to the Drillship dynamic figure calculation equation in table 1. Table 1 Onboard lift dynamic coefficients Crane Mount on

Dynamic Coefficient Cv

Fixed Structure

1.33

Spar

1.33 + 0.003 x Hsig ≥ 1.4

Semisubmersible

1.33 + 0.0007 x Hsig x Hsig ≥ 1.4

Drillship, FPSO

1.33 + 0.0012 x Hsig x Hsig ≥ 1.4

Hsig : sea significant wave height for the load chart in question (ft)

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2.3 Application scheme of BOP Gantry Crane‘s Rolling / Pitching BOP Gantry Crane operates on Drillship/Rig so the motion of Drillship should be applied on the analysis model. Fig 3 shows rolling and pitching values of Drillship according to the height. Flare L (EL=35.4) value is applied to consider rolling and pitching.

Fig. 3 Rolling & pitching degree of drillship 2.4 Wind load application scheme of BOP Gantry Crane Follow equation (2) to calculate wind load. Wind load means the load that occurs on the structure when wind hits the structure. BOP Gantry Crane is used in sea so maximum wind speed 72km/h is applied which the structure may get in ocean. F = 0.0473 * Vz² * Cs * A According to equation (2), if the load on BOP Gantry Crane is F, then the equation is F = 0.0473 x (72km/h)² x 1 x (69.725x10⁻⁶)km² = 17.1 N.

(2)

2.5 Outline of BOP Gantry Crane hydraulic system Hydraulic system of BOP Gantry Crane consists of Main winch, Aux winch, Winch trolley, and Stack device. In this research, sub modeling was designed which is a process to review the appropriateness of circuit logic before modeling the overall circuit. In the sub model, Aux winch, Winch trolley, and Stack device are structured as the circuit. Fig 4 is the picture of sub circuit modeling. (a) Aux winch consists of hydraulic motor, winch, brake valve, counter balance valve, shuttle valve, puppet valve, and brake valve. The line related to external brake is eliminated from the modeling. (b) Winch trolley consists of hydraulic motor, puppet valve, counter balance valve, shuttle valve, and external brake. Damping of rotating axis is considered. (c) consists of four hydraulic cylinder and a counter balance valve. The cylinder is installed vertically in consideration of gravity.

(a) Aux winch modeling

(b) Winch trolly modeling (c) Stack device modeling Fig. 4 Sub circuit modeling

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2.6 Structure analysis of BOP Gantry Crane Fig. 5 shows restraint conditions applied to the crane. Hex dominant mesh was applied, 119408 of elements, and about 451839 of nodes were produced. 84 contact regions are created as bonded between connection parts of each structure and supplementary material. In order to express 200ton of operation load, multiplication value 320ton of dynamic figure 1.6 is applied to the force as 80ton for each on A, B, C and D parts of fixed part on in the main winch. In order to put self-weight F of the crane, standard earth gravity is applied as -Z direction. In order to express maximum load on the structure according to rolling of pitching in the Drillship, 435.89 mm/s² acceleration is applied to G as ax, ay, and -az (counter gravity direction). The wind load H on the Drillship was applied with 17.1N toward Y direction according to the wind load calculation formula. Pin hole part in the bottom of crane and E is connected with traveling device which moves as the rail, so fixed support was applied.

Fig. 5 Boundary condition for BOP Gantry Crane Analysis results 3.1 Analysis conditions and results of hydraulic system sub modeling Fig 6 shows analysis results of sub circuit modeling. The black dotted line shows analysis results when safety valve was not used. The red line is the graph when safety valve was operate. (a) It shows at it takes a lot of time to stop the load on the Aux winch if safety valve was used but the difference can be neglected enough. counter torque prevention and soft speed reduction with the inertia of hydraulic motor was possible. (b) Winch trolley shows that simultaneous use of safety valve when stopping the winch reduces surge pressure on the hydraulic motor. So it can improve the longevity of motor and overall system stability. (c) In case of stack device, Because the counter balance valve implements as a safety valve at the neutral mode, the stack device cylinder is fixed at a certain location.

(a) Aux winch result

(b) Winch trolly result Fig. 6 Result of sub circuit modeling

(c) Stack device result

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3.2 Analysis results of crane structure Fig. 7 shows structure analysis results of BOP Gantry Crane. Stress value is about 160Mpa which maximum was measured at the lower corner of leg connection part. The structure change amount due to wind load, rolling, and pitching was about 7.14mm. However, the safety figure of analysis result was 2.24 which shows it was designed safely.

(a) Equivalent stress (b) Equivalent stress (c) Deformation (d) Deformation Fig. 7 Result of structure analysis for BOP Gantry Crane Conclusion Optimization design for domestic production of BOP Gantry Crane as a Drillship/Rig equipment was implemented in this research. Hydraulic system was designed to control the crane system, and ANSYS program was used for structural analysis, and the following results were found. (1) As the result of Crane hydraulic system, BOP Gantry Crane analysis model was developed and the movement of stack device, Aux winch, and winch trolley system were understood. Using SimulationX which is a commercial software, the design of new hydraulic circuit, correction of existing circuits, and future developments of parts may be conducted using the BOP Gantry Crane hydraulic system. (2) As the result of optimization design for crane structure analysis, safety figure was 2.24 which as higher than 1.5 of regulated safety figure. Thus, the structure was designed safely. 3D modeling and the analysis results may be used for future BOP Gantry Crane technology development for making of actual model. References [1] K.P.Park, J.H.Cha and K.Y.Lee : Lifting Design Analysis of a Floating Crane considering the Dynamic Behavior of Elastic Booms. KSNVE, p207-208 (2010) [2] S.H.Shin, J.K.Kim, C.K.Song, B.K.Kim, T.H.Bae and J.M.Kim : Structural Evaluation of the 300 Ton Goliath Crane. Volume 35 of KSME, 11, p.1515-1520 (2011) [3] S.S.Lee, H.W.Lee, C.H.Park, K.T.Park and M.H.Lee : The Study of 3-Dimension Dynamic Characteristics of Gantry Crane . KSPE, p.708-712 (2000) [4] Andrzej Urbaś, Marek Szczotka and Andrzej Maczyńki : Analysis of Movement of the BOP Crane under sea weaving conditions. Journal of theoretical and applied mechanics Warsaw, 3, p. 677-701. (2010) [5] William E. Singhose, Lisa J. Porter and Warren P. Seering : Input Shaped Control of a Planar Gantry Crane with Hoisting. Proceedings of the American Control Conference, New Mexico, p97-100. (1997)

Applied Mechanics and Materials Vols. 479-480 (2014) pp 319-323 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.319

Stress Distribution Analysis of Different Types of Blade for a Fermentation System Cheng-Chi Wang a, Po-Jen Cheng b , Kuo-Chi Liuc Far East University, No.49, Zhonghua Rd., Xinshi Dist., Tainan City 74448, Taiwan a

b

c

[email protected], [email protected], [email protected]

Keywords: Stress, Fermentation, Blade

Abstract. Fermentation system is widely used for food manufacturing, materials processing and chemical reaction etc. Different types of blade in the tank for fermentation cause distinct stress distribution on the surface between fluid and blade, and appear various flow fields in the tank. So, this paper is mainly focused on analyzing the stress field of blades under different scales of blade with fixing rotational speed. The results show that the ratio of blade length to width influences stress distribution on the blades. At the same time, the inclined angle of blade is also the key parameter for the consideration of design and appropriate design will decrease the maximum stress. The results provide an effective means of gaining insights into the stress distribution of fermentation system.

Introduction The original study of fermentation system is applied for the way of cultivating and producing acetone by tanks [1]. The most common problem that arose at the initial stage of the culture was the contamination of the antibacterial bodies. Without the help of appropriate tanks, the ones with lids were used at the outset; they could not be used, however, to proceed with steam-pasteurization under normal stress, so the kind of cylinder-shaped iron tanks with lids on the tops and semispherical bottoms were employed instead, and the pressurized steam-pasteurization was implemented. The selections of appropriate fermentation tanks and fluids are the key of success during the process. Therefore, the design and choice of fermentation system has become highly significant. As far as the culture of microbes is concerned, the conditions of growth environment and the process should be treated differently according to different kinds of microbes; hence, the difference among the microbial systems should be taken into consideration when designing and manufacturing the fermentation tanks, so as to attain the optimal results under the suitable environment and conditions. Not only can the yield of microbes be greatly increased by the use of large-sized fermentation tanks, but the quality can be controlled to be stable with the steady provision of microbes, and the time span of culture can be substantially shortened, which can help save both time and energy [2]. Fermenting is the most extensively applied unit operation, the relations of which with the principles of hydrodynamics, thermal conductivity, chemical reactions and so forth make it a complex existence. Fermenting can be applied to various and sundry production processes. In industries, for instance, it is utilized during the manufacturing process of numerous products to evenly separate the different chemical compounds to produce the assorted products that serve in different functions, such as adhesive, food products and so on [3]. The quality of products is influenced by the act of fermenting throughout the manufacturing process; if it fails during the manufacturing process, the products will end up being unsatisfactory, discordant in quality or unbalanced in constituents, which will not match up with our expectation [4]. There are some common requirements of fermentation process which are determined by characteristics of products. It is also necessary to a fermenting tank throughout the process considering convectional circulation, and diffusion. So, the analysis of blades, rotational speed and the viscosity of fluid flow, will have different influences on different fermenting processes as well [5, 6].

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Geometric Design of the Fermentation System Specification of a Fermentation Tank. The fermentation system employed in the experiment, as shown in Fig. 1, includes a sealed cylindrical tank (without the passages that connect the inside and outside of the tank itself) whose diameter is 1.14m long, and the surface of the exterior wall is set to be non-slip. The relative specifications and the details of the dimensional parameters are shown in Table 1. The baffles and blades are placed symmetrically; and the blade is set to rotate counterclockwise at the constant speed of 10 rpm for the simulation process. Table 1. Geometric parameters of a fermentation system Parameters

Size [m]

Parameters

Size [m]

Diameter of tank (T) Tank height (H) Blade length (Wa) Blade width (Wb) Blade thickness (Wc)

1.14 1.50 0.112 0.015 0.07

Distance of the Impeller to the top (H1) Distance of the Impeller from the bottom (H2) Baffle length (La) Baffle width (Lb) Baffle height (Lh)

0.75 0.75 0.095 0.025 1.50

Fig. 1. Specification of the fermentation system. Boundary Conditions. In this study, a cylindrical tank is used and shown in Fig. 1. The inside wall of tank is assumed as no-slip boundary. In Table 2 shows the scales of blade for numerical simulation. Table 2. Scales of blade Blade length (Wa)

Blade width (Wb)

RW(Wa/Wb)

0.112m

0.015m 0.025m 0.035m 0.045m

7.5 4.48 3.2 2.5

Blade width (Wb)

Blade length (Wa)

RL(Wa/Wb)

0.015m

0.1425m 0.1275m 0.112m 0.0975m

9.5 8.5 7.5 6.5

Numerical Simulation Results Influence of Different Sizes of Blade-Fixed Length and Altered Width of Blade. Fig. 2 shows us stress distributions of blade with different width of 0.015m(Rw=7.5), 0.025m(Rw=4.5), 0.035m(Rw=3.2), and 0.045m(Rw=2.5). In Fig. 2, we analyze the stress generated onto the YZ surface of the blade, and the result shows that the absolute maximum stresses of these four cases are 3.975×10-4, 4.128×10-4, 2.831×10-4, and 3.381×10-4, respectively. Also, all maximum stresses occurs at the outer side away from the rotor.

Applied Mechanics and Materials Vols. 479-480

(a)Rw=7.5

(b) Rw=4.5

(c)Rw=3.2

(d)Rw=2.5

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Fig. 2. Distribution of stress in accordance with different widths of blade. Fig. 3 shows that the stress distribution on the XY surface of blade with different Rw, and the stress data calculated from the coordinate of (0.094,0.77)to (0.206,0.77). The results reveal that absolute stress of Rw=7.5 and 3.2 decreases suddenly at Y=0.14m. But absolute stress of Rw=4.5 and 2.5 stablizes from increasing situation at Y=0.14m. So, Y=0.14m is the key point of blade.

Fig. 3. Stress curves with different values of Rw Influence of Different Sizes of Blade-Fixed Width and Altered Length of Blade. Fig. 4 shows that stress of blade with different length of 0.0975m(RL=6.5), 0.112m(RL=7.5), 0.1425m(RL=9.5). In Fig. 4, the stress is analyzed and generated onto the XY surface of the blade, and the result shows that the absolute maximum stress of RL =6.5 is 0.125 occurred at the interval of X[0.14,0.16] away from the rotor shown in Fig.4(a). But, the maximum stress transfer to X[0.13,0.14] and the value decrease to 2.3×10-3 shown in Fig. 4(b). And in Fig. 4(c), when RL increases to 9.5, the maximum stress occurs at the outside of blade X[0.2,0.22].

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(a)RL=6.5

(b) RL=7.5

(c)RL=9.5

Fig. 4. Distribution of stress in accordance with different lengths of blade. Fig. 5 shows that the stress distribution on the outer of blade with different RL, and the stress data calculated from the coordinate of Y[-0.007,0.007]. The results reveal that absolute stress of RL =6.5 is the greatest than all the other cases and the maximum absolute stress occurs at Y=-0.007. 0.00 -0.01 -0.02 -0.03

)a(p 力壓

-0.04

9.75 11.2 12.75 14.25

-0.05 -0.06 -0.07 -0.08 -0.09 -0 .008

-0. 006

-0.00 4

-0.002

長度(m) 0.0 00

0.00 2

0 .004

0.0 06

0.00 8

Fig. 5. Stress curves with different values of RL Influence of Different Inclined Angles of Blade. The inclined angle of blade influences the uniform situation of fermentor, and the thermal stress caused by the friction between blades and fluid and also influenced by the inclined angle of blade. Different inclined angles will induce different effects including reaction phenomenon, reactive heat, and thermal stress. So, it is necessary that the influence of inclined angle of blade should be analyzed. The results shown that as the inclined angle of blade is 30°, the stress distribution exists two different areas including positive and negative stress areas shown in Fig.6(a). When the angle is further increased to 60°, the stress distribution reveals that the minimum stress occurs near the rotor shown in Fig.6(b). From Fig. 7, the stress distribution under different angles shows that the blade induced the suddenly positive stress at X=0.04m and then decreased to cause negative stress at X=0.08m when the angle equals to 60°. For the other three cases, the stress distributions are more stable and it is obtained that the larger inclined angle will cause the more variation.

(a)inclined angle=30°

(b)inclined angle=60°

Fig. 6. Distribution of stress in accordance with different inclined angles of blade.

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Fig. 7. Stress curves with different inclined angles of blade. Conclusion. From the simulation results, it is shown that the scales of the blades influence the stress distribution induced by fluid for a fermentation process. As the fluid flow to hit the blade, it causes different types of stress areas under specified parameters of blade scales. While the Rw is increased, it doesn’t mean that the absolute stress is increased. But, it is interesting that the stress varies suddenly at Y=0.14m for all cases. It is also obtained that the maximum stress acting on the blade for lower RL of the blade. And, for considering the influence of inclined angles of blade, the stress variations acting on the blade are increased for larger angles. The numerical results can be the guideline for the design of fermentor in a fermentation process to prevent the thermal stress induced by inappropriate blade scales. Acknowledgments. The financial support of this research by National Science Council of the R.O.C., under Grant NSC-98-2622-E-269 -004 -CC3 & 102-2622-E-269 -008 -CC3 is greatly appreciated. References [1] J. J. H. Hastings: Economic Microbiology Vol. 2 (1978), p. 31 [2] V. Buwa, A. Dewan, A.F. Massar, and F. Durst: Chemical Engineering Science Vol. 61 (2006), p. 2815 [3] M. Li, G. White, D. Wilkinson, and K.J. Roberts: Industrial Engineering and Chemistry Research Vol. 43 (2004), p. 6534 [4] S.C. Byung, B. Wan, S. Philyaw, K. Dhanasekharan, and A.R. Terry: Industrial Engineering and Chemistry Research Vol. 43 (2004), p. 6548 [5] A.R. Khopkar, G.R. Kasat, A.B. Pandit, and V.V. Ranade: Chemical Engineering Science Vol. 61 (2006), p. 2921 [6] Y. Bao, Z. Hao, Z. Gao, L. Shi, and J.M. Smith: Chemical Engineering Science Vol. 60 (2005), p. 2283

Applied Mechanics and Materials Vols. 479-480 (2014) pp 324-328 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.324

Optimal Design of the Single-mode Piezoelectric Actuator S. J. Changa, and J. Chenb EM334B, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R.O.C. a

[email protected], [email protected]

Keywords: Piezoelectric, Actuator, Asymmetric, Electrodes.

Abstract. The general operation of a piezoelectric ultrasonic actuator is to convert the cyclic motion of the piezoelectric plate to a linear motion at the rotor or slider. The conventional piezoelectric ultrasonic actuator has two symmetric exciter electrodes on the front surface and each electrode covers one half of the front surface. The rear surface has only one electrode that severs as a common drain. In this paper, the design and simulation of the novel single-mode piezoelectric actuator with asymmetric electrodes were presented. The accomplishment of this study is to find the optimal dimensions of the piezoelectric plate and the asymmetric electrodes, and the stator tip on the piezoelectric ultrasonic actuator would have the larger vibrating amplitude. From the simulation experiment results, the optimal dimensions of the piezoelectric plate are 20×10×1 mm with 12 mm exciter electrode length, and the vibrating amplitude is from 0.73µm increasing to 0.91µm. Introduction The piezoelectric ultrasonic actuator was widely used in the industry. This is due to their outstanding characteristics such as large output torques, no gearbox or brake mechanism required, bearing-less, quick response, no backlash, high positioning resolution, absence of magnetic fields, simple structure, linear direct driving, small volume, low power consumption and high positioning accuracy. More and more applications of the piezoelectric ultrasonic actuators were found in the daily life such as the light pick-up element application [1], atomizing devices, medical micro-nebulizer [2-4] and the zooming/image stabilization system in the digital camera [5-6]. Many kinds of piezoelectric ultrasonic actuator were developed for certain application in recent years. However, the core characteristics required of actuators are the same. Actuators at these scales require high output forces, accuracy, low response times, a simple design and simple operation [7]. A single-mode piezoelectric actuator for ultrasonic linear motor was developed in 2005 [8]. The friction element, as the driving tip, was attached at the midpoint of the long edge of the piezoelectric plate. The two-dimensional standing wave would occur at the midpoint of the long edge of the piezoelectric plate when the actuator was excited asymmetrically. The superposition of the two-dimension standing wave would produce the cyclic motion. With a proper preload, the piezoelectric actuator would push the linear slider. Piezoelectric ultrasonic actuators would have better performance if the stator tip on the piezoelectric ultrasonic actuator would have the larger vibrating amplitude. Design Concepts The conventional piezoelectric actuator with symmetric electrodes and the linear stage driven by it are shown as Fig. 1(a). The actuator consists of a piezoelectric plate polarized in the Z direction and a friction element (driving tip) attached on the long edge of the piezoelectric plate. The electrodes are on the large surfaces (X-Y planes) of the plate. There are two symmetric exciter electrodes on the front surface and each electrode covers one half of the front surface. The rear surface has only one electrode that severs as a common drain. The driving tip is attached on the long edge of the piezoelectric plate. The basic design concepts of the piezoelectric actuator with asymmetric electrodes and the linear stage driven by it are shown as Fig. 1(b). Comparing with conventional piezoelectric actuator in Fig.

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1(a), the electrodes on the front surface of the piezoelectric plate are divided into A, B and C three areas. The rear surface still has only one electrode that severs as a common drain, and the driving tip is attached on the long edge of the piezoelectric plate. Y

Z

Y

driving tip X

electrode A

Z

driving tip X

electrode A

electrode B

electrode B

electrode C

(a)

(b)

Fig.1. The linear stage driven by the piezoelectric actuators. The detailed method for the simulation in this study including three steps: modal analysis, harmonic analysis, and design parameters optimization. First, the exciting frequency of the piezoelectric actuator can be fine by the modal analysis. Second, the harmonic analysis can show the amplitude of driving tip of the piezoelectric actuator. Finally, the design parameters optimization process can find the optimal parameter combination can be obtained. The PZT material properties were provided by the manufacturing company of PZT in Taiwan (Eleceram Technology Co., Ltd. and Internet Web is www.eleceram.com.tw). Those material properties as d31, electromechanical coupling coefficient, quality factor, and density were 171 pm/v, 0.34, 1800, and 7.75 g/cm3, respectively. The vibration mode of piezoelectric actuator and the motion trajectory of the driving tip are shown as Fig.2. The point P is the location for the driving tip to be attached. From the simulation results, it is found that the motion trajectory of point P is the elliptical trajectory. The driving tip should have the larger vibrating amplitude to make the piezoelectric actuator with better operating characteristics. Thus, it is very important to find the optimal dimensions of the piezoelectric actuator to make the driving tip have the larger vibrating amplitude. P

(a)

(b)

Fig.2. (a) The vibration mode of piezoelectric actuator. (b) The motion trajectory of the point P. Simulation Experiments Taguchi method, kind of design of experiment, is a statistical method developed by Genichi Taguchi to improve the quality of a product or a manufacturing process. It has been used to improve quality of products for a long time. It usually uses the lowest cost to obtain the best quality by tools such as S/N ratio and orthogonal arrays. By this method, the product quality is insensitive to variance caused by “noise factors” and an optimal parameter combination can be obtained. In this study, the Taguchi method is used to find out the optimal design factors of the piezoelectric actuator has the larger elliptical cyclic motion on the stator tip. By the simulation experiments, the optimal parameter combination can be obtained [9].

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In this study, “the vibrating amplitude of the stator tip on the piezoelectric plate” is chosen to be the quality characteristics. By a brainstorming in early design stage, all possible design parameters that affect the “vibrating amplitude of the stator tip on the piezoelectric plate” were considered. The four chosen control factors and their levels for the experiment are shown in Table 1. Table 1 The Control Factors and Levels Table (Original Design) Factor\Level Length Width Thickness Electrode Length

Level 1 12 mm 8 mm 1 mm 0.4 L

Level 2 16 mm 10 mm 1.5 mm 0.5 L

Level 3 20 mm 12 mm 2 mm 0.6 L

In this study, the quality characteristic is larger-the-better. We seek to maximize the vibrating amplitude of the stator tip on the piezoelectric plate to attain piezoelectric actuator with asymmetric electrodes to have better performance. The larger-the-better S/N ratio is based on the reciprocal of the smaller-the-better loss function. The derivation of the larger-the-better type S/N ratio is based on the following ideas: (1) quality characteristics or response values are continuous and nonnegative, (2) the desired value of the response is infinite, and (3) the goal is simply to minimize the reciprocal of mean and variance simultaneously. The larger-the-better S/N ratio is defined by: 1 n 1  S/NLTB = − 10log  ∑ 2  (1)  n i=1 yi  The factor effects responses are listed in Table 2 and Table3. After the parameter optimization experiments, the optimal assembly of control factors and levels in X-direction and Y-direction are both B3 C2 D1 E3 by S/N ratio response Table. Among of the factors and levels, all the factors are considered as the significant factors. The third level of factor B is 20 mm (the length of piezoelectric plate). The second level of factor C is 10 mm (the width of piezoelectric plate). The first level of factor D is 1 mm (the thickness of piezoelectric plate). The third level of factor E is 12 mm (the electrode length of piezoelectric plate). Table 2 The S/Nx Ratio Response Table Factors Levels 1 2 3

Length(B)

Width(C)

Thickness(D)

Electrode(E)

-163.40 -145.15 -144.90

-150.53 -150.62 -152.29

-144.32 -154.85 -154.27

-157.38 -150.34 -145.72

Table 3 The S/Ny Ratio Response Table Factors Levels 1 2 3

Length(B)

Width(C)

Thickness(D)

Electrode (E)

-142.58 -137.74 -136.35

-138.72 -137.75 -140.18

-134.45 -139.00 -143.20

-146.24 -138.02 -132.40

The optimal assembly of control factors B, C, D, E is B3 C2 D1 E3, and it is also the 17th experiment in the L18 orthogonal array experiments. Since the optimal assembly of control factors is the 17th experiment in the L18 orthogonal array experiments. Another assembly of control factors B3 C2 D1 E2 is chosen to be the assembly of control factors of confirmation experiment. The predicted results (S/N ratio) of the assembly of control factors are: η x − predict = η x + (η xB 3 − η x ) + (η xC 2 − η x ) = (−144.90) + (−150.62) − (−151.147) = −144.37

(2)

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η y − predict = η y + (η yB 3 − η y ) + (η yC 2 − η y )

327

(3)

= (−136.35) + ( −137.75) − ( −138.89) = −135.21

The predicted and the confirmation simulation experiment results are all listed in Table 4. The results are in the Table quite similar. It means the experiments results are reliable. Table 4 Confirmation Experiment Table X-Original X-Optimal Y-Original Y-Optimal

Experiment S/N -124.025 -126.674 -128.748 -124.560

Predicted S/N -144.531 -144.371 -137.574 -135.211

The original and optimal experiment results (vibrating amplitude of the stator tip on the piezoelectric plate in the X-direction and Y-direction) are shown as Fig.3 (a) and Fig.3 (b) respectively. After the simulation experiments and the optimal process, the vibrating amplitude of the stator tip on the piezoelectric plate in the X-direction is from 0.63µm reducing to 0.54µm and the vibrating amplitude of the stator tip on the piezoelectric plate in the Y-direction is from 0.37µm to 0.73µm. The total vibrating amplitude is improved by 0.18µm (from 0.73µm to 0.91µm).

(a) (b) Fig.3. (a) The experiment results of original design. (b) The experiment results of optimal design. Fixed Points of the Piezoelectric Plate The motion amplitudes along the length of piezoelectric plate are shown as Fig.4(a). The driving tip should be put on the points which have the maximum vibrating amplitude to make the piezoelectric actuator has better performance. In addition, the fixed devices of the piezoelectric actuator should be located on the points with the minimum vibrating amplitudes. After seeking in the Fig.4(a), the location of 10 mm is chosen to set the driving tip and the locations of 4 mm and 16 mm are chosen to set the two fixed points. The detail dimensions of the piezoelectric actuator are shown as Fig.5. The dimensions of the piezoelectric plate are 20×10×1 mm and the dimensions of electrodes on the front surface of the piezoelectric plate are 8 mm, 4mm, and 8mm. The P is the point to locate the driving tip and F1 and F2 are the points to locate the fixed devices. Conclusions In this paper, the design and simulation of the novel piezoelectric actuator with asymmetric electrode were presented. The main purpose of this study is to find the optimal design factors of the piezoelectric plate have the largest vibrating amplitude of the stator tip on the piezoelectric actuator. From the simulation experiment results, the main factors to inflect the vibrating amplitude of the

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stator tip on the piezoelectric actuator are the length of the piezoelectric plate and the length of the electrode. The optimal dimensions of the piezoelectric plate are 20×10×1 mm with 12 mm electrode length. The vibrating amplitude of the stator tip on the piezoelectric actuator in the X-direction and Y-direction are 0.63µm and 0.37µm respectively. After the design optimization process, the vibrating amplitude of the stator tip on the piezoelectric actuator in the X-direction and Y-direction are 0.54µm and 0.73µm respectively. In other words, the motion amplitude is from 0.73µm increasing to 0.91µm (improved by 0.18µm). P 8 mm 4 mm 8 mm 4 mm

16 10 mm

Y Z

X

F1 20 mm F2

1 mm

(a) (b) Fig.4. (a)The vibrating amplitudes in the X-direction and the Y-direction along the length of piezoelectric plate. (b)The detail dimensions of the piezoelectric actuator with asymmetric electrode. Acknowledgment The authors would thank National Science Council (NSC) for the financial supports to the project (granted number: NSC 101-2221-E-224-009). References [1] Takehiro Takano, Yoshiro Tomikawa, Manabu Aoyagi, Toshiharu Ogasawara, and Akira Yabuki, Ultrasonic linear motors for application to driving a light pick-up element, Ultrasonic Symposium (1993) 445-448. [2] Sheng-Chih Shen, Yu-Jen Wang, Yung-Yue Chen, Design and Fabrication of Medical Micro-Nebulizer, Sensors & Actuators, A, 144 (2008) 135–143. [3] C. T. Pan, J. Shiea and S.C. Shen, Fabrication of an integrated piezo-electric micro-nebulizer for biochemical sample analysis, Journal of Micromechanics and Microengineering, 17 (2007) 659-669. [4] S.C. Shen, A new cymbal-shaped high power microactuator for nebulizer application, Microelectronic Engineering, 87 (2009) 89-97. [5] S. J. Chang, Y. J. Wang, Y. C. Chen, and T. F. Wu, U.S. Patent 7,800,65. (2010) [6] Won-Hee Leea, Chong-Yun Kanga, Dong-Soo Paik, Byeong-Kwon Ju, Seok-Jin Yoon, Butterfly-shaped ultra slim piezoelectric ultrasonic linear motor, Sensors and Actuators, A 168 (2011) 127-130. [7] B. Watson, J. Friend, and L. Yeo, Piezoelectric ultrasonic micro/milli-scale actuators, Sensors & Actuators, A, 152 (2009) 219–233. [8] Oleksiy Vyshnevskyy, Sergej Kovalev, and Wladimir Wischnewskiy, A Novel, Single-Mode Piezoelectric Plate Actuator for Ultrasonic Linear Motors, IEEE Transaction on Ultrasonics, Ferroelectrics, and Frequency Control, 52 (2005) 2047-2053. [9] Shyang-Jye Chang, Yung-Yue Chen, and Henry Wu, Design and Simulation of the Novel Piezoelectric Actuator with Multiple Driving Tips, Advanced Science Letters, 8 (2012) 317-321.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 329-332 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.329

The Design of Multiple Function Acoustic Horns for Ultrasonic Welding of Plastic Kuen-Ming Shu 1, a, Yu-Jen Wang2,b and Chi-Wei Chi3,c No.64, Wunhua Rd., Huwei Township, Yunlin County 632, Taiwan 1,2,3 a

National Formosa University b

[email protected], [email protected],[email protected],

Keywords: Ultrasonic welding, Multiple function acoustic horns, Finite element analysis.

Abstract.The acoustic solid horns are the important parts in high power ultrasonic vibrating systems, and its design is critical to the quality and the efficiency of ultrasonic welding. The using of multiple function acoustic horn can reduce machining time very effectively. This paper performs the analysis and design of multiple function acoustic horns for ultrasonic welding of plastic by employing ANSYS finite element software. Firstly, the theoretical dimensions of the horns are calculated. Moreover, their natural frequencies and amplitudes are obtained through the simulations of ANSYS. Experiments are currently being set up to verify the validity of the analytical results. Introduction Ultrasonic horns are device commonly used for augmenting the oscillation displacement amplitude provided by an ultrasonic transducer. The device is necessary because the ultrasonic amplitudes provided by the ultrasonic transducers them selves are insufficient for most practical applications of power ultrasound. Maximum achievable ultrasonic amplitude depends, primarily, on the properties of the material from which an ultrasonic horn is made as well as on the shape of its longitudinal cross-section. Commonly, the horns are made from titanium alloys, such as Ti6Al4V, aluminum alloys or powdered metals. The most common and simple to make transitional section shapes are conical and catenoidal. An ultrasonic horn is a tapering metal bar commonly used for augmenting the oscillation displacement amplitude provided by an ultrasonic transducer operating at the low end of the ultrasonic frequency spectrum. The device is necessary because the amplitudes provided by the transducers themselves are insufficient for most practical applications of power ultrasound (M. Roopa Rani et al, 2013). Another function of the ultrasonic horn is to efficiently transfer the acoustic energy from the ultrasonic transducer into the treated media (Peshkovsky et al, 2007), which may be solid or liquid. Ultrasonic welding is the process of adhesive two parts together by ultrasonic vibration (Pandey, P. C et al.1980).This process replaces the costly, time-consuming, conventional method of glue adhesive or nailing process. It is one kind of recent development refining methods, has the operation easily, the partial hot melt merit, but because the technical stratification plane is high, for example the horn design needs to have the specialized technology and so on question prevent it from widely used. The aim of this paper is to design and fabricate a multiple function acoustic horns for plastic ultrasonic welding. Acoustic horn select Three shapes of acoustic horn can be widely found in practice, they are the conical shape, the stepped shape, and the exponential shape respectively. To preventing stress concentration due to the abrupt change of cross section, a fillet will be made for the stepped shape. The design of an acoustic horn depends on the determination of the resonance length. The length must equal to the multiple of half wavelength of the system. The computation for an exponential

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shape horn is the easiest among three different shapes. Also, the horn of this shape has better amplitude than the others. Analysis of Conical Horns The resonance length of an acoustic horn depends on the areas of input and output end, wavelength constant, etc. The resonance equations and amplitude magnifications of conical horns, stepped horns, and stepped horn - two cylinders connected with a conical are presented.

Fig. 1 Conical horn - the larger cross section connected by a cylinder Fig. 1 depicts the profile of a conical horn connected with a cylinder on its larger cross section. Its resonance length L is defined as the total length of the horn, i.e., L = l 1 + l 2, where l 1 and l 2 are the lengths of the cylinder section and the conical section, respectively. l 1 can be obtained by(Simakawa, 2001): α l2 tan αl1 =

(

2 2 2 S1 S 2 − 1 −  S1 S 2 (αl2 ) + S1 S 2 − 1  tan αl2   , S1 S 2 • αl2 αl2 + S1 S 2 − 1 tan αl2

)

(

[

(

) ]

)

(1)

Finally, the amplitude magnification M can be calculated by: M =

S1 S 2 •

cos α l 1 • cos α l 2 α l2 +

(

α l2

)

S 1 S 2 − 1 tan α l 2

.

(2)

whereα (=ω/c) is the wavelength constant, M is the amplitude magnification, and S1 and S2 are the cross section areas of the input end and output end, respectively. A conical horn connected with a cylinder on its smaller cross section. Its resonance length can be calculated by: 2 2 αl1 S1 S1 − 1 −  S1 S2 (αl1 )2 + S1 S2 − 1  tan αl1   tan αl2 = αl1 S1 S2 • αl1 − S1 S2 − 1 tan αl1

(

)

[

(

(

)

) ]

(3)

A stepped horn with two cylinders connected by an exponential curve is shown in Fig. 2 Let l 1 = λ/4, and the profile be an exponential curve in section l 2. If the length of l 2 is reduced, then the profile will approach a typical stepped horn. On the contrast, if the length of l 2 is increased and the length l 3 is shorten, then the profile will approach an exponential curve. After having calculated D1 and S ⁄S , then we can find the dimensions 2and l 3.

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Fig. 2 Stepped horn - two cylinders connected with an exponential curve The design of acoustic horn for plastic ultrasonic welding The horn for plastic ultrasonic welding is designed as two cylinders connected by an exponential curve. Only a few studies on this type of horns can be found in the literature. This work computed the theoretical dimensions according to the diameter ratios of commercial horns. Their dimensions and amplitude magnification are listed in Table 1. Also, their natural frequencies obtained by the modal analysis are shown in Table 2. Table 1 The dimensions and amplitude magnification of exponential shape horn.

Dimensions (mm) D1 D2 L1 L2 R amplitude magnification

Value 75 27 65 28 45 3.1

Table 2 Natural frequencies of exponential shape horn Horn Mode

frequency (Hz)

1st modes

12368

2nd modes

9612

3rd modes

14324

4th modes

8510

5th modes

19512

The finite element analysis was performed by using the commercially available code ANSYS, it is one of the most flexible and powerful tools available for solving the horn design problems (Lin, Y.H. 1996, Lin, Z. C. 2000, Lu, P.C. 1999).According to the requirement of finite element analysis approach, the horn has to be divided into simple, homogeneous, discontinuous finite nodes. As shown in Fig. 3, the element of Solid95 is adopted in analysis, it is a cubic element with 20 nodes, and it has three degrees of freedom. Without lowering the accuracy of computation, it allows irregular shapes of horns to be analyzed, and it also has superior compatibility of deformation. Moreover, it can also be applied on the curved boundary with plasticity, creeping, expansion, stress strengthening, large deformation, and even a body with failure (M.Nad, 2010).

Fig. 3 Finite element model of exponential shape horn

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The natural frequencies of the horn computed by equation are closer to the operating frequency 20 kHz. Experiments are currently being set up to verify the validity of the analytical results. Fig. 4 shows the real horn made by aluminum. Due to its high strength and stability in properties, the A7075-T651 aluminum alloy is used as the horn material, its properties are elastic modulus E = 71.7 GPa, Poisson ratio µ= 0.33, and mass density ρ = 2810 kg/m3. These horns are set on the specialized station for ultrasonic welding round and rectangular shape plastic as shown in Fig. 5.

Fig. 4 Real aluminum horn

Fig. 5 Ultrasonic welding specialized station

Summary Theoretical and numerical analysis was conducted to study the performance of multiple functions ultrasonic horns for welding round and rectangular shape plastic .From the results of analysis, the natural frequency of the horn designed by the equation is close to the operating frequency of the machine. The horn designed by the proposed method will use less material and trial & error time. Real aluminum horns are made and be approved working effectively on the ultrasonic welding specialized station. Acknowledgement The support of the National Science Council (Taiwan), under Grants (101-2622-E-150-009-CC3), is gratefully acknowledged. References [1] Lin, Yih-Hwang, and Tsai, Yau-Kun, “Nonlinear free vibration analysis of Timoshenko beams using the finite element method,” Journal of the Chinese Society of Mechanical Engineers, Vol. 17(1996), p. 609-615. [2] Lin, Zone-Ching, and Fung, Chih-Lang, “Hot rolling analysis with consideration of the contact deformation between strip and roll,“ Journal of the Chinese Society of Mechanical Engineers, Vol. 21 (2000), p. 459-472. [3] Lu, Pai-Chuan, Using adjoint variable method in the shape optimization under fatigue life constraints, Journal of the Chinese Society of Mechanical Engineers, Vol. 20(1999), No. 3, pp. 237-245 [4] M. Nad, Ultrasonic horn design for ultrasonic machining technologies, Applied and Computational Mechanics 4 79–88(2010). [5] Pandey, P. C. and Shan, H. S., Modern machining processes’ Tata, McGraw-Hill, New York (1980). [6] Peshkovsky, S.L. and Peshkovsky, A.S., "Matching a transducer to water at cavitation: Acoustic horn design principles", Ultrason. Sonochem., 14: p. 314–322,(2007). [7] M. Roopa Rani, R. Rudramoorthy. “Computational modeling and experimental studies of the dynamic performance of ultrasonic horn profiles used in plastic welding”, Ultrasonics 53 763– 772 (2013) [8] Simakawa M., The principles and practices of ultrasonic engineering (in Chinese), Fu Han Co., Taipei, pp. 113 (2001)

Applied Mechanics and Materials Vols. 479-480 (2014) pp 333-337 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.333

Five-Axis NC Program Conversion for Inclined Plane Machining Hsin-Yu Cheng1, a, Yung-Chou Kao2,b 1

Department of Computer Science & Information Engineering, Far East University, Tainan, Taiwan 2

Department of Mechanical Engineering, University of Applied Sciences, Kaohsiung, Taiwan a

[email protected], [email protected]

Keywords: Inclined surface machining, NC program transform, 5-axis machine tools

Abstract Machining processes on an inclined plane include mostly hole making, profiling, and pocketing. It comprises of 80% - 90% cutting process in five-axis machining and is therefore very important in multi-axis machining work. However, five-axis machining processes are normally difficult to introduce and to use because five-axis CAD/CAM and post-processor are normally demanded to generate five-axis NC program even though it is for the 2D contour machining on a plane with inclined angle. Therefore, this paper studies the inclined plane machining methods and extends traditional three-axis milling machining processes and methods so as to directly convert 2-1/2 and three-axis NC program into five-axis machining program to ease the application of five-axis machining processes. This study integrates the developed three-axis NC program interpreter, inclined plane coordinates transformation, and post-processor to simply the inclined plane NC programming. Two-dimensional NC program on a plane can be converted into five-axis NC program on the inclined-plane by the proposed methodology. Case study has been utilized to verify the utilization and correctness of the proposed methodology Introduction Five-axis machine tool has two more rotational axes than that of three-axis one. It is capable of conducting machining processes on mechanical component with complex geometry and is also very suitable for the machining of component that needs multi-directional machining. For example, simultaneously five-axis movement could be used for the machining of turbine-blade, impeller wheel, and workpiece that has under-cut geometry. Rule-surface that has tapered angle could be machined via five-axis flange cutting with very high cutting efficiency. Synchronously five-axis movement machining could also be used to eliminate the static problem in three-axis machining. Furthermore, the setup and re-setup tasks [1] could be reduced because special fixtures are not needed during the whole machining processes. The machining precision could therefore be enhanced. This has resulted in high efficiency on inclined plane machining processes such as hole-making, profiling, and pocketing. The inclined-plane machining consists of 80% - 90% cutting process in five-axis machining, for example, the hole-making processes include drilling, reaming, and boring. Fig. 1 illustrates an example showing machining on inclined surface [2]. Fig. 1(a) shows five-axis simultaneously machining and Fig. 1(b) shows a 3+2 axis control that can be used for heavy duty cutting. Fig. 1(d) shows another example that can shorten overhang length and is more suitable for heavy duty cutting than that in Fig. 1(c). This means that 3+2 axis control could sometimes be adopted to replace simultaneously five-axis movement machining with more efficient and more cost-effective cutting strategies. The machining on an inclined-plane through five-axis NC program could be achieved by a three-axis NC program if the coordinates system could be transformed so that the cutter is in perpendicular to the inclined plane. This means five-axis NC program generated by a five-axis CAD/CAM could be replaced by the three-axis NC program created by a three-axis CAD/CAM through appropriate coordinate’s transformation. It also means a five-axis NC machining process could be achieved by integrating a three-axis NC and coordinate transformation. This has resulted in a solution to machine geometry on an inclined plane by combining 2-1/2 axis or three-axis NC program and coordinate’s transformation. This is the proposed methodology of this paper.

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Generally, CNC operators and CAD/CAM engineers are more familiar with three-axis milling machining functions than that of five-axis CAD/CAM functions. Furthermore, five-axis CAD/CAM and related post-processor are more expensive than three-axis CAD/CAM; therefore, the proposed methodology could reduce the machining process cost for the machining on an inclined plane.

(a) simultaneously five-axis machining

(b) more suitable for (c) longer tool length (d) shorted tool length heady duty by changing is needed in via 3+2 axis control to 3+2 axis control Fig. 1 Example machining postures of cutters on inclined plane

In general, a CNC operator is familiar with 2-1/2 axis NC programming and a CAD/CAM engineer is very familiar with three-axis NC programming by using three-axis CAD/CAM software. This paper proposes that a 2-1/2D NC program for machining the 2-1/2D geometry such as a hole, pocket, and profile could be written by considering the inclined plane as a general 2D plane. The 2-1/2D NC program could then be converted into a five-axis NC program automatically by the developed methods. The developed methods include NC program interpreter, inclined plane definition, inclined plane coordinate transformation, cutter location file (CLF in APT format) interpretation, and five-axis post-processor. This means most of the five-axis machining processes could be achieved by 3+2 axis machining if the cutter could be transformed to be in perpendicular to the inclined plane and the cutter could then be driven on the inclined plane coordinate system. Advanced CNC such as FANUC 31i and Siemens 840D five axis controllers already have supported inclined plane definition. However, how it was achieved has not been published yet. The authors have studied the APT program interpreter for five-axis machining [3] and exchangeability of different APTs for 5-axis machine tool applications [4]. A middle file was proposed for the exchangeability before using the postprocessor to convert CLF (in APT format) into five-axis NC program. This paper therefore converts a NC program into the middle file so that post-processor can convert the middle file into a NC program for the other five-axis machine tool. The postprocessor in converting CLF file in workpiece coordinate system into NC program has been studied by various researchers [5, 6] since 1990s. However, it seems that there is no published research related to converting 2-1/2D NC program into five-axis NC program for the machining on inclined plane. If the inclined plane could be defined, the post-processor could be used to convert a 2-1/2D NC program into five-axis NC program, and therefore, it is not necessarily to use a generally expensive five-axis CAD/CAM for the generation of the NC program in machining the 2D contours on the inclined plane. However, two modules should be developed to achieve the afore-mentioned functionalities: “definition of inclined plane” and “post-processor”. The definition of inclined plane and post-processor will be described in the following sections. Inclined plane definition The definition of inclined plane includes five types in this paper: (1) Euler angle, (2) Rotation angle Roll-Pitch-Yaw, (3) Three points, (4) Two vectors, and (5) Projection angle. These definition are describes as follows. Euler angle. Definition of inclined plane based on Euler angle is accomplished by (1) rotating the workpiece coordinate system along the Z-axis for α angle, (2) rotate the new workpiece coordinate system along new X axis for β angle, and (3) rotate the new workpiece coordinate system another γ angle along new Z axis. For example, if point A, as shown in Fig. 2, is the origin of the work coordinate system and AB is the X axis, then the “origin of inclined plane” can be set

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to be (16.6581,0,12), as shown in Figure 4, and the “Rotation angle” for the Z-X-Z Euler angle will be Z=60°, X=63.43495°, and Z=0° after the Set OK button is clicked. However, there are 12 rotation ways in Euler angle transformation although the most common one in commercial CNC controller is ZXZ. Rotation angle Roll-Pitch-Yaw. The Roll-Pitch-Yaw definition is similar to Euler angle method but rotates along the axis of the orginal work coordinate system. There are generally six rotational sequences, XYZ, XZY, YXZ, YZX, ZXY, and ZYX to adapt to various inclined plane. Three points. A plane can be defined by three points that are not in the same line. For example, if the coordinates of A, B, and C points, as shown in Fig. 2, are (X1, Y1, Z1), (X2, Y2, Z2), and (X3, Y3, Z3), as shown in Figure 5, the inclined plane ABC could be defined by assuming A is the origin, AB is the X-axis direction. Two vectors. A plane can be defined by two vectors that are not parallel to each other. If the first vector is in X axis direction, the Z axis direction can be created by multiplying the first vector and the second vector. The Y axis direction could then be created by multiplying Z axis direction vector and the X axis direction vector. Projection angle XYYZ. If the inclined plane origin is set at point C, as shown in Fig. 2, and the X axis direction in the same as AB , the inclined plane ABC could then be defined by rotating X axis for 60° along Y axis, and rotate Y axis -30° along the original Z axis. Z

Y

C

(0,0,0)

A

B

X Fig. 2 Inclined plane

Fig. 3 Plane by Euler Angle

Fig. 4 Plane by Three points

NC Program Conversion To simply the five-axis NC program creation and reduce the cost in training technicians for writing five-axis NC program, this paper proposes to follow the traditional three-axis NC program creation process. Firstly, define the inclined plane and secondly generate the three-axis NC program on the inclined plane coordinate system (IPCS). That is to say, consider the inclined plane as a normal flat plane such as a XY plane. Thirdly, convert the three-axis 2D/3D NC program into toolpath data (cutter location), and fourthly convert the toolpath data on the IPCS into work coordinate system (WCS). Finally, post-process the toolpath data on the WCS to generate five-axis NC program. NC program interpretation. the NC program interpretation function is used to convert 2D/3D NC program on the IPCS into toolpath data on the same IPCS. Figure 8 shows the flowchart of the NC interpretation. The interpretation starts by using “Read NC_Block()” function to read in NC block one by one and then separate G code and M code by the function of “DeGcode()”. The function “G_motion()” could be used to get tool movement data accordingly. Work coordinate system toolpath conversion. The major purpose in converting the 2-1/2D 3D NC program on inclined plane into five-axis NC program is to simplify the five-axis NC program creation process. That is to say, a five-axis machine tool operator can generate a five-axis NC program based on the use of the three-axis NC program generation methods that the operator was familiar with. The operator only needs to generate the three-axis NC program on the IPCS, creates the toolpath data on the IPCS after interpreted the NC program, and then post-process the toolpath to generate the five-axis NC program on the WCS. To accomplish these conversions, a transformation matrix A should be obtained according to the definition of an inclined plane 1 on the WCS could then be calculated by multiplying the firstly; the toolpath data 1 with the transformation matrix A , as shown in equation (1). NC program data

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1 =A 1 (1) For example, if the Euler angle is used for the inclined plane definition and the rotation sequence are relative to X, Y, and Z axis respectively. The rotation sequences would become: rotate ϕ angle along the X axis (represented by R( φ ,X)), rotate θ angle along Y axis (represented by R( θ ,Y)), rotate φ angle along Z axis (represented by R( ϕ ,Z)), and then translate to the origin (X0, Y0, Z0) that can be represented by T(X0,Y0,Z0). Then, the transformation matrix [A] could be expressed as in equation (2). A = R( φ ,X) R( θ ,Y) R( ϕ ,Z) T(X0,Y0,Z0) 0 0  cosθ 0 sinθ 0 cosϕ − sinϕ 0 0 1 0 0 X 0 1 0 0 cosφ − sinφ 0  0 1 0 0 sinϕ cosϕ 0 0 0 1 0 Y 0         =  0 sinφ cosφ 0 − sinθ 0 cosθ 0  0 0 1 0 0 0 1 Z0          0 1  0 0 0 1  0 0 0 1 0 0 0 1  0 0 cosθ cosϕ - cosθ sinϕ sinθ X 0  cosθ sinϕ + sinφ sinθ cosϕ cosφ cosϕ − sinϕ sinθ sinϕ − sinφ cosθ Y 0   =  (2) sinφ sinϕ − cosφ sinθ cosϕ sinφ cosϕ + cosφ sinθ sinϕ cosφ cosθ Z 0    0 0 0 1  Five-axis post-processor. The NC post-processor is to convert the toolpath data on the IPCS into the toolpath data on the WCS. Inverse kinematics is then adopted to convert the toolpath in WCS into the five-axis NC program. Since there are varieties of five-axis machine tool configuration, this paper uses the most common table-rotating/tilting type, as shown in Fig. 5, for explanation. The tool axis vector K K K and tool tip position Q Q Q could then be calculated via homogeneous transformation ans be expressed as shown in equation (3) and (4) K K K = sin∅ sin∅ cos∅ sin∅ cos∅ (3)

Q Q Q

cos∅ P + sin∅ cos∅ P + sin∅ sin∅ P + sin∅ D + L = −sin∅ P + cos∅ cos∅ P + cos∅ sin∅ P + cos∅ D + L −sin∅ cos∅ + cos∅ P + D + L

(4)

From equation (4), the P , P , and P can be obtained as in equation (5), (6), and (7). P = (Q − L )cos∅ − Q − L sin∅ P =(Q − L )sin∅ cos∅ + Q − L cos∅ cos∅ − (Q − L )sin∅ − D cos∅ P = (Q − L )sin∅ sin∅ + Q − L sin∅ cos∅ + (Q − L − D )cos∅ − D sin∅ When ϕ = 0 and ϕ = 0 ⟹ Q Q Q

(5) (6) (7)

= X Y Z , then, the

(X, Y, Z) in NC program could be obtained from equation (5)~(7), as the followings. X = L + P ，Y = L + P + D ，Z = L + P + D The angle A and C could also be calculated as follows. A = ϕ = cos (K ) , C = ϕ = tan (K /K )

Zw

Zt

C

Yw

+

Xw

+

+

+

+

+

Yt

Xt

A

Fig. 5 The kinematic relationship of a table-rotating/tilting type

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Implementation and Verification To realize the proposed methods, the example in Fig. 1(a) is adopted and its dimension is shown in Fig. 6. If the Euler angle is used for the inclined plane definition, the rotation sequence is YXY, and the origin is (38, 75.0). Then, the transformation would be rotate 0° along X axis and then rotate 44.744° along Y axis. Fig. 7 shows the eight more holes are copied. Conclusion This paper proposed a method to generate five-axis NC program based on the three-axis NC program defined on the inclined plane coordinate system, that is to 7. Euler angle say, by considering the inclined Fig. 6. An example to Fig. realize the proposed transformation and NC plane as a flat plane. The user program conversion could use the proposed system to methods easily generate the 3+2 axis NC program without the need to use expensive five-axis CAD/CAM system. Although the proposed functions are also supported by high end CNC controllers such as Fanuc 31i and Siemens 840D, how the functions are accomplished have not been published yet. The proposed methodology includes definition of inclined plane, NC interpretation in converting NC program into toolpath data, and conversion of the toolpath data into the toolpath data on work coordinate system The 3+2 axis NC program could then be generated by post-processor and an example has been used to verify the correctness of the proposed methods successfully. High end CNC controller is generally much more expensive and has more convenient value-added functions than that of the low-end CNC. Furthermore, expensive five-axis CAD/CAM software is not necessarily to be used in order to generate five-axis NC program on an inclined plane. The developed methods could be integrated with lower-end CNC to enhance the value of five-axis machine tool such as the drilling center. Acknowledgments The authors appreciate the grant support from the National Science Council in Taiwan by the grant NSC 101-2221-E-151-005 and also the support from the Technology Development Program of the Ministry of Economic Affairs (MOEA) by the grant 101-EC-17-A-05-S1-211. Reference: [1] Xavier Pessoles & Yann Landon & Stéphane Segonds and Walter Rubio, “Optimisation of workpiece setup for continuous five-axis milling: application to a five-axis BC type machining centre”, Int J Adv Manuf Technol (2013) 65:67–79, DOI 10.1007/s00170-012-4151 [2] T. Moriwaki, “Multi-functional machine tool”, CIRP Annals-Manufacturing Technology Vols. 57 (2008) pp. 736–749. [3] Hsin-Yu Cheng, Jo-Peng Tsai and Yung-Chou Kao, “The development of an APT program interpreter for 5-axis machining”, Advanced Materials Research Vols. 482-484 (2012) pp 2247-2252. [4] Hsin-Yu Cheng, Yung-Chou Kao, “Studies on the exchangeability of different APT interpreters for 5-axis machine tool applications”, Applied Mechanics and Materials Vols. 284-287 (2013) pp 1924-1928. [5]Y.H. Jung, D.W. Lee, J.S. Kim and H.S. Mok, “NC post-processor for 5-axis milling machine of table-rotating/tilting type”, Journal of Materials Processing Technology, Vols. 130–131 (2002) pp 641–646. [6] C. H. She, Z. T. Huang, “Postprocessor Development of a Five-axis Machine Tool with Nutating Head and Table Configuration”, International Journal of Advanced Manufacturing Technology, Vol. 38, No. 7-8, (2008) pp.728-740

Applied Mechanics and Materials Vols. 479-480 (2014) pp 338-342 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.338

The Impact of Bicycle Suspension on Pedaling Forces Yung-Sheng Liu1, a, Tswn-Syau Tsay2,b, Tsai-Chu Wang3,c , and Chi-Fan Liu4,d 1

Feng Chia University,100 Wen-Haw Rd.,Taichung 407, Taiwan, ROC

2

Asia University, 500, Lioufeng Rd., Wufeng, Taichung Taiwan 41354, ROC 3

Feng Chia University,100 Wen-Haw Rd.,Taichung 407, Taiwan, ROC

4

Feng Chia University,100 Wen-Haw Rd.,Taichung 407, Taiwan, ROC

a

b

[email protected], [email protected],

c

d

[email protected], [email protected]

Keywords: ADAMS, LifeMOD, Multibody, Bicycle suspension system.

Abstract. Front and rear suspensions are commonly equipped on bicycles for the purpose of riding comfort especially for mountain bicycle. Suspension system includes damper for shock absorbing and spring for rebounding. Therefore suspension system would increase bicycle riding effort since damper dissipates energy. ADAMS/LifeMOD are proposed in this research to establish a bicycle-human integrated multibody dynamic model to investigate the impact of bicycle suspensions on cyclist’s leg muscle forces under various pedaling conditions. Muscles studied include adductor magnus, rectus femoris, vastus lateralis and semitendinosus. Pedaling conditions include riding on flat road, over a road bump, and climbing slope. The results indicate that suspension system increases the pedaling forces of vastus lateralis and semitendinosus. However suspension system decreases the pedaling forces of adductor magnus and rectus femoris. The integrated model built in this research may be used as reference for designing bicycle suspension systems. Also, the results of this study may be used as a basis of leg weight training to strengthen certain muscles for long-distance off-road cyclists. Introduction The purpose of installing front/rear suspension systems on a bicycle is to provide the cyclist more comfortable experience when riding on soil and gravel road or other uneven surfaces. To understand the performance of bicycle suspension system Waechter, et al. [1] developed a 2-D lumped-masses dynamic system model to simulate off-road bicycle pedaling. Wang and Hull [2] developed a 2-D multibody model to simulate a cyclist riding suspension bicycle and study the reduction of vibration. Yang [3] suggested the spectral density function of cushion’s acceleration as an index to investigate bicycle riding comfort. Rankin and Neptune [4] analyzed the configuration of bicycle seat, the seat tube angle, and pelvic orientation to obtain the maximum crank power. Kooijman, et al. [5] installed several sensors on an experiment bicycle. Data collected from sensors are employed to verify a three dimensional benchmarked bicycle model. The results from experiment and 3-D model were very close when both the speed and frequency are low. Dynamic analysis software ADAMS and human body model LifeMOD are employed in this research to build up a bicycle-human integrated multibody dynamic model for simulating bicycle riding. The software is widely used on human body dynamics study. For example, Lee et al. [6] used the software to analyze impulse force on human body from rifle shooting. Kenny et al. [7] used the software to analyze golf driving. A golfer swing model built by ADAMS/LifeMOD was conducted by Tucker et al. [8]. Besides, the software extends to the study of the impact force of Taekwondo side kick [9], modeling boat rower [10], and modeling cyclist to explore the leg forces and joint loads [11]. In medical related research, ADAMS/LifeMOD was used to analyze the spine spacer dynamics of using Dynesys dynamic stabilization system implanted in the vertebra [12], and to dynamically simulate the human thoracolumbar [13]. ADAMS/LifeMOD has drawn much attention to be an effective tool for dynamic modeling of integration mechanical devices and human body.

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Front fork suspension and/or rear suspension system are installed to bicycles for the purpose of riding comfort especially for mountain bicycles. Suspension system includes damper for shock absorbing and spring for rebounding. Therefore suspension system would increases bicycle riding effort since damper dissipates some pedaling energy. In this research a 3-D full suspension bicycle model is built by ADAMS, and a human body model is built by LifeMOD. Then the bicycle model and the human model are integrated as a multibody dynamic model. The integrated model is employed to simulate the motion of a cyclist riding bicycle under various pedaling conditions and analyze the impact of suspension systems on the cyclist's leg muscle forces. Muscles studied include adductor magnus, rectus femoris, vastus lateralis and semitendinosus. Pedaling conditions include riding on flat road, over a road bump, and climbing slope. Methods ADAMS is a multibody dynamic software developed by MDI (Mechanical Dynamics, Inc.). It can be used for modeling a complex mechanical system as a “virtual machine.” LifeMOD is a three-dimensional computer model of human body developed by LifeModeler, Inc. This model consists of 19 segments for skeleton which are connected by 18 joints (Fig. 1(a)). Muscles are modeled by spring-damper complexes (Fig. 1(b)). In order to save the computing load, the present study only includes the lower limb muscular system. LifeMOD contains a database for the spring stiffness and damping coefficient based on input parameters (height, weight, etc.). The joints properties in LifeMOD are based on the Hybrid III dummy

Fig. 1 (a) LifeMOD segments and joints, (b) LifeMOD muscles system (red lines)[14] In this research a 23 years old male subject with 176 cm height and 70 kg weight is modeled by LifeMOD as the cyclist. This cyclist model is then imported into ADAMS and integrated with a bicycle model. Then adjust the human body model position and joints angles to fit the riding posture (Fig. 2). Hands, hip and feet are linked with bicycle handles, saddle and pedals respectively by using bushing joints. Bushing joints have the same stiffness and damping properties as muscles. Road conditions include flat road, a 15 cm height bump on road, and climbing 10° slope as shown in Fig. 2.

Fig. 2 Bicycle riding on different road conditions

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The bicycle model is equipped with front fork suspension and rear suspension as shown in Fig. 3(a) and (b). The spring stiffness and damping coefficient of the front fork suspension are 18 N/mm and 0.6 N*s/mm respectively, and of rear suspension are 36 N/mm and 1.2N*s/mm respectively.

Fig. 3 (a) front fork suspension

(b) rear suspension

After setting up the model, an inverse dynamic simulation of bicycle riding is implemented by ADAMS. During inverse dynamic simulation, a motion driver is equipped at the bicycle crank and makes the bicycle pedalling itself. The leg muscles (spring-damper complexes) contraction histories will be recorded in inverse dynamic simulation. Then the motion driver will be removed and the muscle contraction histories are employed to perform a forward dynamic simulation. During forward dynamic simulation, the bicycle will be pedalled by human model to reproduce the motion history and therefore the human body motion and muscle forces would be analyzed by ADAMS. Bicycle speed in dynamic analysis is 10 km/h. Results and Discussion The simulation results show that for climbing slope, both front and rear suspensions do not have much influence on pedaling effort as shown in Fig.6 and Fig. 9. For riding on flat road and over bump, suspension systems cause increased pedaling forces of vastus lateralis as shown in Fig. 4 and Fig. 5 and also of semitendinosus as shown in Fig. 7 and Fig. 8.

(a) No suspension (b) Front fork suspension equipped (c) Rear suspension equipped Fig. 4 Pedaling forces of vastus lateralis for riding on flat road

(a) No suspension (b) Front fork suspension equipped (c) Rear suspension equipped Fig. 5 Pedaling forces of vastus lateralis for riding over bump

(a) No suspension (b) Front fork suspension equipped (c) Rear suspension equipped Fig. 6 Pedaling forces of vastus lateralis for climbing slope

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(a) No suspension (b) Front fork suspension equipped (c) Rear suspension equipped Fig. 7 Pedaling forces of semitendinosus for riding on flat road

(a) No suspension (b) Front fork suspension equipped (c) Rear suspension equipped Fig. 8 Pedaling forces of semitendinosus for riding over bump

(a) No suspension (b) Front fork suspension equipped (c) Rear suspension equipped Fig. 9 Pedaling forces of semitendinosus for climbing slope Table 1 shows the comparisons of pedaling suspension bicycle with rigid (non-suspension) bicycle. A"+" sign means pedaling force increased, a"-" sign means pedaling force decreased compared with pedaling a rigid bicycle, and “—” indicates no significant difference between pedaling suspension or non-suspension bicycle. Table 1 Comparisons of forces of muscles under various conditions. Lower body Adductor Rectus Vastus Semitendlnosus Road/shock absorber with front suspension Flat with rear suspension Road with front suspension Over a with rear suspension Bump Climbing with front suspension Slope with rear suspension

Magnus

Femoris

Lateralis

— -23% — -8% — —

— -14% -33% +26% -20% —

+20% +60% +50% +25% — —

+17% — +14% — +7% −8%

The results also show that climbing a 10° slope needs to pay a lot more pedaling effort compared with riding on flat road as shown in Fig. 4, Fig. 6, Fig. 7, and Fig. 9. Conclusions Based on this research ADAMS and LifeMOD may efficiently and effectively simulate bicycle riding and study the human body dynamics. This study shows the increase on pedaling effort with bicycle suspension systems. Further work may analyze the effect of bicycle suspension on comfort of

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human body corresponding to the road unevenness. The results of this study together with further work will be useful for bicycle suspension system design. The results of this study may be used as a basis of leg weight training to strengthen certain muscles for long-distance off-road cyclists. Also simulation of bicycle riding by using ADAMS/LifeMOD may analyze the joint loads of cyclist and therefore to avoid sport injury. References [1] M. Waechter, F. Riess and N. Zacharias, A Multibody Model for the Simulation of Bicycle Suspension Systems, Vehicle System Dynamics. Vol.37(1), (2002), 3-28. [2] E.L. Wang and M.L. Hull, A Dynamic System Model of an Off-road Cyclist, Journal of Biomechanical Engineering-Transactions of the ASME. Vol.119(3), (1997), 248-253. [3] M.-H. Yang, A study on comfortable effect of a bicycle rider with different dampers, Mechanical Engineering, National Cheng Kung University, Master thesis (2008). [4] J.W. Rankin and R.R. Neptune: The Influence of Seat Configuration on Maximal Average Crank Power During Pedaling, A Simulation Study, Journal of Applied Biomechanics. Vol.26(4), (2010), 493-500. [5] J.D.G. Kooijman, A.L. Schwab and J.P. Meijaard, Experimental validation of a model of an uncontrolled bicycle, Multibody System Dynamics. Vol.19(1-2), (2008), 115-132. [6] Y.S. Lee, Y.J. Choi, K.H. Han, J.W. Chae, E.J. Choi and I.W. Kim: A study on the human impulse characteristics with standing shooting posture, Key Engineering Materials - Advances in Fracture and Strength. Vol.297-300(2005), 2314-2319. [7] I.C. Kenny, E.S.B. Wallace, D. and S.R. Otto, Validation of a full-body computer simulation of the golf drive for clubs of differing length, in The 6th International Conference on the Engineering of Sport. 2006: Olympic Hall, Munich, Germany. [8] C.B. Tucker, I.C. Kenny and R. Anderson: Development of a large-scale golfer computer model to study swing kinematics, Procedia Engineering. Vol.2(2010), 34-39. [9] J.H. Lee, Lee, Y.S., and Han, K.H.: A study on impact analysis of side kick in Taewondo, International Journal of Modern Physics B. Vol.22(9-11), (2008), 1760-1765. [10] S. Serveto, S. Barré, J.-M. Kobus and J.-P. Mariot: A three-dimensional model of the boat-oars-rower system using ADAMS and LifeMOD commercial software, Proc. IMechE. Vol.224(2010), 75-88. [11] Y.S. Liu, T.S. Tsay and T.C. Wang: Muscles Force and Joints Load Simulation of Bicycle Riding Using Multibody Models, Procedia Engineering. Vol.13(2011), 81-87. [12] S.M. Kim, I.C. Yang, S.Y. Lee and S.Y. Cho: Dynamic simulation of universal spacer in Dynesys dynamic stabilization system for human vertebra, Transactions of Nonferrous Metals Society of China. Vol.19(2009), 238-242. [13] K.T. Huynh, I. Gibson, W.F. Lu and B.N. Jagdish: Simulating Dynamics of Thoracolumbar Spine Derived from LifeMOD under Haptic Forces, World Academy of Science, Engineering and Technology. Vol.64(2010), 278-285. [14] Information on http://www.lifemodeler.com/LM_Manual/modeling_segments.shtml.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 343-347 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.343

Development of a Virtual Milling Machining Center Simulation System with Switchable Modular Components Chen-Lung Wei1,a, Hsin-Yu Cheng2,b, Chi-Yuang Yu3,c, and Yung-Chou Kao4,d 1,3

Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan

2

Department of Computer Science & Information Engineering, Far East University, Tainan, Taiwan 4

Department of Mechanical Engineering, University of Applied Sciences, Kaohsiung, Taiwan a

[email protected], [email protected], [email protected], d [email protected],

Keywords: Virtual machine tool, Virtual controller, HMI, Virtual Reality.

Abstract. The application of traditional three-axis milling machine center is very popular and the related application technology is also much matured resulting in mechanical components to be machined with good quality. Machine tool has therefore become an inevitable facility in precision manufacturing. Furthermore, the pursuit of higher precision machining has thus demanding five-axis machine tool to be adopted owing to its flexibility and capability in machining more precise mechanical components in shorter time. However, one of the key factors for the popularity in smooth introduction of five-axis machine tool would be based on a very user friendly learning and teaching environment. This is partly because two more rotational axes in a five-axis machine tool could generate very complex toolpath movement that is out of the imagination of a general operator. Furthermore, the price of an industrial five-axis machine tool is not normally affordable by an educational institute; to the worse, the maintenance cost is also very high. There is very high risk for a novice to collide during the learning process and this will generally cause big worry of a teacher. This paper aims for the development of a virtual machining center simulation system with switchable modular components to ease the learning process in getting acquainted with a five-axis machine tool. A five-axis machine tool consists generally of two modules: (1) CNC controller and Operation panel, and (2) machine tool hardware. The developed system will provide the novice with four CNC controller with operation human machine interface (HMI), and three typical types of five-axis machine tool, Head-Head (HH), Head-Table (HT), and Table-Table (TT), are also supported. The developed modularized and switchable machining center simulation system has been successfully developed and is very helpful to both learner and teacher

Introduction The machine tool and machining industry are demanding higher precision and shorter cycle times in these years. This is a need not only market-led but also industry-led. For example, aero-space, mold and die, bio-mechanical, and automotive industries are requesting more precision machined components that are characterized to have more complex geometry and more difficult to machine. The mechanical components include turbine blade, engine component, artificial hip stem, artificial knee joint, artificial dental implant and crown, to name only a few. These have resulted in the adoption of five-axis machining facility in resolving the limitation of traditional three-axis machine center’s capabilities. For example, concave geometry is very difficult to cut by using a three-axis machine center unless customized fixture are designed and implemented. While a five-axis machine tool could be used to easily conquer such a problem so as to be able to machine a concave component in one machine with the need to re-measure the program zero point. Five-axis machine tool has two more rotational axes than a typical three-axis one. These rotational axes enable the five-axis machine to have more degree of freedom (DOF) in movement and to have better capabilities in making more complicated shapes such as freeform geometry by five-axes

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synchronously movement. However, this has induced difficulties in maintenance, operation learning, and higher investment cost, etc. The maintenance cost could be reduced by appropriate training to the maintenance engineers while the higher investment cost seems to be a must at the moment. Therefore, a good environment is expected to ease the learning curve for both learner and teacher. The application of virtual reality (VR) has been used [1] in assisting the learning the operation training of machine tool and shown very effective potential. This paper is thus aimed for the development of a virtual machining center simulation with switchable modular components to help a novice in learning the operation of a five-axis machine tool. The toolpath movement could be simulated according to an NC program and collision detection function is supported to alert the user if collision occurs. A five-axis machine tool consists generally of two modules: (1) CNC controller and Operation panel, and (2) machine tool hardware. Three basic configurations of five-axis machine tool are established including Head-Head (HH), Head-Table (HT), and Table-Table (TT). Furthermore, four CNC controller HMIs are created to help a learner to get acquainted to different operation interfaces. That is to say, there would have totally twelve combinations in mapping three machine types and four CNC HMIs. General speaking, a five-axis machine tool consists of only one CNC HMI and one machine hardware; and thus, the developed system provides a learner with more varieties of configuration through switchable modules. Researches on virtual CNC simulation has been studied and potential application and effectiveness have been reported. For example, five-axis NC toolpath simulation had also been studied by Chin-yu Chang [2]. Hong-Chin Haung [3] has studied the technology of a five-axis virtual machine tool system. This system can simulate five-axis motion based on NC toolpath; Yuan-pei Hou [4 ] researched the dental crown machining by five-axis machine tool. Chienhung Kuo [5] adopted OpenGL to demonstrate virtual five-axis mechanism system; and Ming-Chang Chang [6] has also developed three major types of five-axis milling machine of Head-Head (HH), Head-Table (HT), and Table-Table (TT) configuration and showed the virtual machine based on OpenGL, as shown in Fig. 1. Furthermore, VR-based multi-axis machine tool simulation systems for both learning and training have been conducted with very promising results. For example, The authors have developed VR-based CNC milling machine learning and training assistance system on three-axis machine center [7], as shown in Fig. 2. A review paper has also been published by Aini Abdul Kadir [8] on virtual machining. This means virtual machine tool has been paid great attention in learning, training, and tool path verification. However, one of the key bottlenecks in using a five-axis CNC milling machine is the risk of collision. A typical CAD/CAM process is shown in Fig. 3. Therefore, this paper focuses on Fig. 2 A VR three-axis CNC milling Fig. 1 An HH virtual providing a user with three machine learning and training system five-axis machine tool [6] five-axis machine tool configurations (HH, HT, and TT) and four CNC operation panels to ease the operation learning of various five-axis machine tools. An NC program can be simulated by the developed system and collision detection between the cutter and the fixture could be verified as well. Adopted Technologies Microsoft Visual Studio 2010. The Microsoft Visual Studio 2010 C# programming language. This environment provides an integrated development environment (IDE) to be able to integrate Visual Basic, C++, and C# for the development of software running in all the Microsoft environment.

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Virtual Reality (VR). The concept of Virtual Toolpath creation in CAD/CAM software such as Catia Reality (VR) has been widely accepted and Output cutter location (CL) file in neutral implemented for education assistance in specific file format such as APT source file in Catia domain. The virtual five-axis machining centers in this development are created by EON Studio Post-processing that is a product supported by EON Reality. Both OpenGL and Direct 3D technologies were used Post-processor for fivePost-processor for ... axis machine A five-axis machine N in EON Studio and mimic effects could be easily created to emulate a real machining center. Focus of this paper Event-driven algorithm, as shown in Fig. 4, is NC program simulation and verification before implemented by EON Studio. That is to say, an real machine operation “out event” could be sent by C# and the created virtual machine tool (VMT) could be actuated by Fig. 3 A general CAD/CAM process for CNC listening to the “in event” from C#. The “out event” such as the collision signal from the VMT could then be sent out to C#. The C# will react to and process Out Event In Event the “out event” once it is received. A general five-axis machine tool consists of three Virtual Machine Tool linear axes (X, Y, and Z) and two rotational axes. The (VMT) C# In EON Studio rotational axes could be any two combinations out of the totally three rotational axes. These rotational axes include In Event Out Event A (rotation about X axis), B (rotation about Y axis), and C (rotation about Z axis). Therefore, a five-axis machine Fig. 4 The event-driven algorithm in could be (1) XYZAB, (2) XYZBC, and (3) XYZAC. A the developed system five-axis machine tool is categorized as Head-Head (HH) type, as shown in Fig. 5, when both rotational axes are attached on the spindle, Head-Table (HT) type, as shown in Fig. 6, when one of the rotational axes is attached on spindle and the other is attached on machine table, and Table-Table (TT) type, as shown in Figure 7, when both rotational axes are attached on machine table.

Fig. 5 An HH type five-axis machine tool

Fig. 6 An HT type five-axis machine tool

Fig. 7 A TT type five-axis machine tool

Fig. 8 The real HT five-axis machine

Construction of VR machine. The 3D geometry model of the VR five-axis machines in this development were created in Solidworks software and then STL file format was adopted for the data exchange between Solidworks and the adopted VR software EON Studio. The constructed HT VR machine is shown in Figure 9 and its hierarchical relationships between modular components of the five-axis machine are shown in Figure 10. When Y axis moves, the X axis, C axis, and workpiece will all move as well. Z axis movement will also cause both B axis and Spindle to move as well.

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Construction of VR controller HMIs. The VR controller panel is used as the HMI to control the VR machine. The HMI was coded in Microsoft Visual Studio C# 2010. There are four VR controller panels in this paper (1) LNC, as shown in Fig. 11, (2) FANUC, as shown in Fig. 12, (3) Mitsubishi, as shown in Fig. 13, and (4) Heidenhain, as shown in Fig. 14.

Fig. 11 LNC panel example

Workpiece Spindle and Tool

C axis

B axis

X axis

Z axis

Y axis Machine Bed

Fig. 9 The VR HT five-axis machine

Fig. 12 FANUC example

Fig. 10 Hierarchical relation of the HT five-axis machine

Fig. 13 Mitsubishi example

System flowchart. The initial interface of the system is shown in Fig, 15 and the flowchart of the developed system is shown in Fig, 16. A snapshot of the LNC HMI in operation is shown in Fig. 17. The event-driven algorithm is illustrated Fig. 14 Heidenhain controller Fig. 15 Initial interface of in Fig. 18. The process center is panel example the developed system designed to process all the events actuated during the developed system, for example, the “click” signal and the “mouse” buttons triggered by the user. Both virtual CNC hand-wheel, as shown in Fig. 19, and real CNC hand-wheel, as shown in Fig. 20, is supported to drive the VR machine tool in this development. Start Initialize Window Form

Choose type of VR machine

Choose VR controller

Actuate VR machine Display VR machine

Display VR controller

Display VR Handwheel

Switch to real Handwheel

Fig. 16 System flowchart of the developed system

Fig. 17 The LNC HMI in operation

Return message

Process center

Send message

Events processing Send event

Invoke appropriate methods and/or classes

VR Machine

VR controller

VR operation panel

VR Handwheel

Real Handwheel

Fig. 18 The event-driven algorithm in this development

Fig. 19 The virtual CNC hand-wheel

Fig. 20 A real CNC hand-wheel

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Discussion and Conclusion The developed virtual machining simulation system is to be used by a novice before the operation of a real five-axis machine tool. The developed system has the following characteristics: 1. The VR machine, as shown in Figure 9, was created according to the real machine. The virtual operation has been designed according to the real operation. That is to say, once the learner is familiar with the VR system, the gap to operate the real machine could be minimized. Unexpected breakdown such as accidental collision could be reduced. 2. NC program could be simulated in the developed system and collision detection function could be used to ensure a collision free toolpath for safe operation. 3. Three typical types of five-axis machine configuration (HH, HT, and TT) have been implemented according to the mechanical modules so that a learner can use this system to get acquainted with different five-axis machine configurations without the need to use real machines. 4. Four different CNC controller panels were created and can be selected by the user according to his or her own preferences. Acknowledgments: The authors appreciate the grant support from the National Science Council in Taiwan by the grant NSC 101-2221-E-151-005 and also the support from the Technology Development Program of the Ministry of Economic Affairs (MOEA) by the grant 101-EC-17-A-05-S1-211. References [1] Yung-Chou Kao, Jo-Peng Tsai, Hsin-Yu Cheng, Chia-Chung Chao, “Development of a Virtual Reality Wire Electrical Discharge Machining System for Operation Training”, 2010 International Journal of Advanced Manufacturing Technology, Online Published, 2010/9/21, DOI 10.1007/s00170-010-2939-1, Springer (2010) [2] Chin-yu Chang, “NC Path Simulation And Collision Detection Based On The Five-Axis CNC Gear Profile Grinding Machine”, Master Thesis, Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taiwan, (2011) [3] Hong-Chin Haung, “A Study of the Technology of Five-Axis Virtual Machine Tool System”, Master Thesis, Department of Mechanical Engineering, National Chung-Cheng University, Taiwan, (2007) [4] Yuan-pei Hou, “The Research on Dental Crown Machining by 5-Axis Machine Tools”, Master Thesis, Department of Mechanical Engineering, National Chung-Cheng University, Chiayi, Taiwan, (2009) [5] Chienhung Kuo, “Applying OpenGL for Development of Multi-axis Virtual Mechanism System”, Master Thesis, Department of Mechanical Engineering, National Chung-Cheng University, Taiwan, (2011) [6] Ming-Chang Chang, “Development of OpenGL-based Virtual HH, HT, TT Five-axis Milling Machine Motion Simulation System”, Master Thesis, Graduate Institute of Mechanical and Precision Engineering, National Kaohsiung University of Applied Sciences, Taiwan, (2011) [7] Yung-Chou Kao and Hsin-Yu Cheng, “A Smart Virtual Vertical Three-axis Machining Center Simulator”, Automation 2009, The 10th International Conference on Automation Technology, June 27-29, 2009, National Cheng-Kung University, Tainan, Taiwan, R.O.C. (2009) [8] Aini Abdul Kadir, Xun Xu, and Enrico Hämmerle, “Virtual machine tools and virtual machining A technological review”, Robotics and Computer Integrated Manufacturing Volume: 27, Issue: 3, June, 2011, pp. 494-508. (2011)

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Hysteretic Nonlinear Characteristics and Stochastic Bifurcation of Cantilevered Piezoelectric Energy Harvester Jia Xu 1, a, Zhi-Wen Zhu 1, 2, b 1

College of Mechanical Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, P.R.China

2

Tianjin Key Laboratory of Nonlinear Dynamics and Chaos Control, 92 Weijin Road, Tianjin 300072, P.R.China a

b

[email protected], [email protected]

Keywords: piezoelectric energy harvester, hysteretic nonlinearity, stochastic bifurcation.

Abstract. Hysteretic nonlinear characteristics and stochastic bifurcation of cantilevered piezoelectric energy harvester was studied in this paper. Piezoelectric ceramics was adhesively bonded on the substrate of cantilever beam to make piezoelectric cantilever beam. Von de Pol difference item was introduced to interpret the hysteretic phenomena of piezoelectric ceramics, and then the nonlinear dynamic model of piezoelectric cantilever beam subjected to axial stochastic excitation was developed. The stochastic stability of the system was analyzed, and the steady-state probability density function and the joint probability density function of the dynamic response of the system were obtained. Finally, the conditions of stochastic Hopf bifurcation were determined. Numerical simulation shows that stochastic Hopf bifurcation appears when bifurcation parameter varies, which can increase vibration amplitude of cantilever beam system and improve the efficiency of piezoelectric energy harvester. The results of this paper are helpful to application of cantilevered piezoelectric energy harvester in engineering fields. Introduction Piezoelectric ceramics is a kind of smart material. It can be used to convert mechanical energy into electrical energy, which is known as piezoelectric effect. Based on this effect, piezoelectric energy harvester can be designed to gather vibration energy of structures. Compared with the other types of power generation system, piezoelectric energy harvester has many advantages, such as small size, high electro-mechanical conversion efficiency, long service life, and low cost, which cause it be applied as green energy widely. DuToit designed MEMS-scale piezoelectric mechanical vibration energy harvesters firstly [1]. Erturk developed the mechanical model of cantilevered piezoelectric vibration energy harvesters [2]. Priya proposed the criterion for material selection in design of bulk piezoelectric energy harvesters [3]. Liao studied parameters optimization and power characteristics of piezoelectric energy harvesters with an RC circuit [4]. Although many advances were obtained, the modeling problem limits the application of cantilever piezoelectric energy harvester in industry fields. In order to optimize piezoelectric energy harvester effectively, it is necessary to build a model in high accuracy to describe the nonlinearities and the electro-mechanical strongly coupling characteristics of piezoelectric energy harvester, which depends on physical model of piezoelectric ceramics. For the hysteretic characteristics of piezoelectric ceramics, most of the piezoelectric ceramics models were shown as equations with subsection function or double integral function, and were hard to be analysed in theory [5-9]. Usually, research results could only be obtained by numerical or experiment method [10,11]. In this paper, hysteretic nonlinear theory was introduced to develop a new kind of continuous piezoelectric ceramics model, and then nonlinear characteristics and stochastic bifurcation of cantilevered piezoelectric energy harvester can be analyzed in theory.

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Hysteresis Nonlinear Model of Piezoelectric Energy Harvester

Fig.1 The voltage-displacement curve of piezoelectric ceramics

Fig.2 The structure of strain-MFI of cantilevered piezoelectric energy harvester

The voltage-displacement curve of piezoelectric ceramics was shown in Fig.1. Obviously, there is hysteretic nonlinearity in piezoelectric ceramics. In this paper, improved Von del Pol hysteretic model was introduced to describe the hysteretic nonlinear characteristics of piezoelectric ceramics. The voltage-displacement curve of piezoelectric ceramics can be shown as follows: u = a1 x + a2 x 2 + a3 x 3 + (a4 x − a5 x 2 ) x
(1) where u is voltage, x is strain, ai (i=1,2,3,4,5) are coefficients. The structure of cantilevered piezoelectric energy harvester was shown in Fig.2. It can be simplified as piezoelectric cantilever beam. The dynamic equation of piezoelectric cantilever beam subjected to axial stochastic excitation can be obtained as follows according to Hamilton's principle: 1
x
+ 2ζ m x
− kx − ϑ 2u + ϑ 2α1 xu + ϑ 2α 2u 2 − α 3 x 2 + α 4 x 3 = exς (t ) 2

(2)

where ζ m is damping, k is stiffness, ϑ and α i (i=1,2,3,4) are coefficients, e is intensity of stochastic excitation, ς (t ) is Gauss white noise. Substituting Eq.1 into Eq.2, we obtained:
x
+ A1 ( x) x
+ A2 ( x) x
2 − B1 x + B2 x 2 + B3 x3 + B4 x 4 + B5 x5 + B6 x 6 = exς (t ) (3) where A1 ( x) = 2ζ m − ϑ 2 (a4 x − a5 x 2 ) + ϑ 2α1 (a4 x − a5 x 2 ) x + ϑ 2α 2 a1 (a4 x − a5 x 2 ) x + ϑ 2α 2 a2 (a4 x − a5 x 2 ) x 2 + ϑ 2α 2 a3 (a4 x − a5 x 2 ) x 3 1 1 2 A2 ( x) = ϑ 2α 2 (a4 x − a5 x 2 ) 2 , B1 = k + ϑ a1 , B2 = ϑ 2 (α1a1 − a2 + α 2 a12 ) − α 3 , 2 2 1 1 B3 = ϑ 2 (α1a2 − a3 + a1a2 ) + α 4 , B4 = ϑ 2 (α1 + α 2 a22 + α 2 a1a3 ) , B5 = ϑ 2α 2 a2a3 , B6 = ϑ 2α 2 a32 2 2

Stochastic Stability of the System Let x = q , x
= p , Eq.3 can also be shown as follows: q
= p  2 2 3 4 5 6  p
= − A1 (q ) p − A2 (q) p + B1q − B2 q − B3 q − B4 q − B5 q − B6 q + eqς (t )

(4)

The Hamiltonian function of Eq.4 can be shown as follows: H=

1 2 1 1 1 1 1 1 ( p − B1q 2 + B2 q 3 + B3q 4 + B4 q 5 + B5 q 6 + B6 q 7 ) 2 2 3 4 5 6 7

(5)

According to the quasi-nonintegrable Hamiltonian system theory, the Hamiltonian function H(t) converges weakly in probability to an one-dimensional Ito diffusion process. The averaged Ito equation about the Hamiltonian function can be shown as follows:

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dH = m( H )dt + σ ( H )dB(t )

(6) where B (t ) is standard Wiener process, m( H ) and σ ( H ) are drift and diffusion coefficients of Ito stochastic process, which can be obtained in stochastic averaging method: 1 1 1 1 m( H ) = −ζ m HR − ϑ 2α1a 4 R 2 − ( ϑ 2 a5 + ϑ 2α 2 a1a4 ) R 3 + ϑ 2α 2 ( a2 a5 − a3 a 4 ) R 5 + 2e 2 DHR (7) 4

σ 2 (H ) =

8

4

16

2 2 e DHR 2 2

(8)

where R is the solution of the following equation: 1 1 1 1 1 1 − B1q 2 + B2 q 3 + B3q 4 + B4 q 5 + B5q 6 + B6 q 7 = H (9) 2 3 4 5 6 7 Based on quasi-nonintegrable Hamiltonian system theory, the largest Lyapunov exponent of a linearized system is defined as follows: 1 t

(10)

λ = lim ln Z (t , z0 ) t→∞

The linearized Ito differential equation can be shown as follows after the system was linearized in the trivial solution H=0: (11) dH = m′(0) Hdt + σ ′(0) HdB(t ) Then the associated largest Lyapunov exponent is 1 2ϑ 2α1a4 − e 2 D 2 1/ 2 ′ ′ (12) λ = lim ln H = m (0) − [σ (0)] / 2 / 2 = t →∞ t 4(k + ϑ 2 a1 ) Now the local stochastic stability of the system can be discussed as follows: 1) The trivial solution H=0 is locally asymptotic stable if and only if λ < 0, which means 2ϑ 2α1a4 < e 2 D ; 2) The trivial solution H=0 is locally asymptotic unstable if and only if λ > 0, which means 2ϑ 2α1a4 > e 2 D ; 3) Bifurcation should appear near the trivial solution H=0 if and only if λ = 0, which means

{

}

2ϑ 2α1a4 = e 2 D

The largest Lyapunov exponent can only estimate the local stability. In this paper, the boundary classification method was used to analyze the global stability of the trivial solution of the system. Generally, the boundaries of diffusion process are singular, and the boundary classification is often determined by diffusion exponent, drift exponent and character value . When H → 0 : m( H ) → O( H ) , σ 2 ( H ) → O( H 2 ) So 2 α l = 2 , βl = 1 , cl = 2ϑ α2 1a4

De

where α l is diffusion exponent, βl is drift exponent, cl is character value, l is left boundary. Thus, the left boundary H= 0 belongs to the first kind of singular boundary. According to the classification for singular boundary , we obtained: c 1) The left boundary H=0 is repulsively natural if l >1; c 2) The left boundary H=0 is strictly natural if l =1; c 3) The left boundary H=0 is attractively natural if l 90μV) were rejected. The EEG recording was conducted in a sound-attenuated room. In auditory oddball conditions, participants kept their eyes closed. ERPCOH is considered an important method of understanding the nature of brain connectivity [10, 11]. The main implications of ERPCOH analysis, which applies time-frequency methods, can be found in the work of Delorme and Makeig [10]. If x and y represent two signals from two electrode sites, the ERPCOH is defined as ERPCOH x , y  f , t  =

where for n trials, whereas

Fi y  f , t 

*

Fi x  f , t 

x y 1 n Fi  f , t  Fi  f , t   n i 1 Fi x  f , t  Fi y  f , t 

*

(1)

is the spectral estimate of trial i at frequency f and time t on the signal x,

is the complex conjugate of

Fi y  f , t 

. The ERPCOH analysis reflects the

event-related response of the cortico-cortical connections to a stimulus and represents the degree of phase synchronization between two channels [12]. The magnitude of ERPCOH varied between 0 (absence of synchronization) and 1 (perfect synchronization). Previous studies have demonstrated that high coherence corresponds to stronger functional connectivity, which relates to attention, cognitive information processing, and neural communication [13]. A sliding temporal Hanning window of 256 points was used to obtain 1 Hz frequency resolution and 4 ms time resolution. To avoid possible edge effects for the ERPCOH measure, a frequency band range from 3.9 Hz to 50 Hz was used in the time-frequency domain. Time-frequency representations of the ERPCOH data were used in the theta, alpha-1, alpha-2, beta-1 (13–20 Hz), beta-2, and gamma bands. Early and late components of ERPs were 80-140 ms and 280-450 ms. ERPCOH was analyzed using the EEGLAB version 9.0 [10] under Matlab 7. The statistical data were tested by analysis of variance (ANOVA) and student’s paired t test using SPSS 12.0. A p-value of .05 was considered significant. Results In the ERP waveforms, parietal P3 amplitudes and adult group latency were found to be larger and shorter than the child groups. The mean and standard deviation of the reaction times, response accuracies, parietal P3 amplitudes, and latencies were 368 ± 50 ms, 97.7 ± 6.8%, 10.7 ± 3.2 μV, and 356 ± 28 ms for adults, 417 ± 42 ms, 96.6 ± 5.1%, 6.5 ± 2.0 μV, and 375 ± 49 ms for 11-year-old children, and 422 ± 69 ms, 74.5 ± 21.2%, 4.0 ± 2.8 μV, and 396 ± 56 ms for 7-year-old children. For the early component, ANOVA (Scheffe’s test) showed no significant differences in amplitudes and latencies among the groups [F [2, 51] = 0.95; p = .39 and F [2, 51] = 0.19; p = .83]. For the late component, amplitudes increased with increasing age (F [2, 51] = 24.25; p < .001), and latencies were prolonged in the younger participants (F [2, 51] = 7.64; p < .001). As mentioned, the response

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accuracies of the adult group and the 11-year-old children (97.7 ± 6.8% vs. 96.6 ± 5.1%, respectively) were significantly higher than the 7-year-old children (74.5± 21.2 %; p < .01, in all cases). To calculate the mean ERPCOH values for each group responding to the target stimuli, the ERPCOH values are represented in various bands. The higher value reflects stronger coherence (connectivity). For the early component (see Fig. 1(A)), both the 7-year-old children and 11-year-old children had lower ERPCOH values in alpha-1 and alpha-2 bands than the adults. The 11-year-old children had higher ERPCOH values than the 7-year-old children in the theta, beta-2, and gamma bands, but also higher values than the adults in the gamma band. For the late component (see Fig. 1(B)), the connection tendency was the same as that in the early component.

Fig. 1: Mean ERPCOH values for 7-year-old children, 11-year-old children, and adults responding to the target stimulus in various frequency bands. The frequency bands were estimated (A) From 80 ms to 140 ms (the N1 component) (B) From 280 ms to 450 ms (the P3 component). Vertical bars indicate 95 % confidence intervals. The current research measured the number and strength differences of the connections between two areas of the brain in adults and 11-year-old children. The connections were found to be higher in 11-year-old children than those in adults in the theta, beta-2, and gamma bands, but lower than those in adults in the alpha-1 and alpha-2 bands in the early component (see Fig. 2(A)). The findings indicated a strong connectivity in 11-year-old children in the gamma band, primarily occurring between the frontal and temporal/parietal electrodes of the left hemisphere. Connectivity for the theta band occurred primarily between the left frontal and posterior, and between the left inferior temporal and the right posterior temporal electrodes. A decrease in phase coherence was also observable primarily between the left and right hemispheres, along the left-right brain axis for 11-year-old children in the alpha-1 and alpha-2 bands. For the late component (Fig. 2(B)), the significance of these two group differences in connection was the same as those in the early component, but diminished for the 11-year-old children only in the theta band.

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Fig. 2: Summary of significant ERPCOH differences (t-test, p < .05) between 11-year-old children and adults. The frequency bands were estimated (A) From 80 ms to 140 ms (the early component) (B) From 280 ms to 450 ms (the late component) responding to the target. Green and red lines denote that the mean values of adults and 11-year-old children are high. The numbers of significant phase coherence are denoted in the boxes below each pattern. To compare the extent to which connectivity may have occurred in the 11-year-old children and 7-year-old children, this work measured the number and strength differences of the connections between two sites of the brain in the two groups (see Fig. 3(A)(B)). The mean ERPCOH values were lower in the 7-year-old children in all frequency bands, with the most significant immaturities occurring in the theta, beta-2, and gamma bands. These findings suggest that little connectivity had occurred related to brain maturation in 7-year-old children.

Fig. 3: Summary of significant ERPCOH differences (t test, p < .05) between 7-year-old children and 11-year-old children. The frequency bands were estimated (A) from 80 ms to 140 ms (the early component) (B) From 280 ms to 450 ms (the late component) responding to the target. Red and blue lines denote that the mean values of 11-year-old children and 7-year-old children are high. The numbers of significant phase coherence are denoted in the boxes below each pattern.

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Discussion This study investigated whether age-related changes affect ERPs and ERPCOH of brain oscillations. Some studies have found a similar significant increase in N1 and P3 peak amplitude and an decrease in N1 and P3 peak latency with advancing age [14]. However, the literature on age-related differences in N1 and P3 components during childhood is inconsistent [15]. In the current samples, the children had a larger variance of ERP amplitudes in anterior areas, particularly in the prefrontal cortex. One explanation for this may be that evidence of frontal lobe functions is still relatively immature in myelination [16], resulting in less efficiency in decision making. This study assumed that if the immature frontal lobes in 7-year-old children have difficulty eliciting an early negativity over anterior scalp sites, then an ERP component would evidence by very different patterns of frontal electrophysiological activity, which consistently elicited N400 and P600 components during a continuous recognition memory task [17]. The 7-year-old children may be associated with more negative effect, thus leading to a decrease in response accuracies. Recent research has found an association between aging-related increases in bilateral frontal activity during cognitive tasks, aging-related declines and compensatory processes [18]. However, these studies assumed that increased activity in the elderly would coincide with enhanced behavioral performance. Older children, when performing auditory oddball tasks have been found to have increased amplitude and enhanced phase-locking [6] in the theta and alpha-1 bands, if better cognitive performance arises through oscillatory connections. The current findings show clear differences of phase coherence in the theta, beta-2, and gamma bands, particularly during the early component for each of the two groups. Although the 11-year-old children had lower ERPCOH than the adults in the alpha-1 and alpha-2 bands, they performed as well as their adult counterparts, probably resulting from increased connections. When comparing the 11-year-old children with the 7-year-old children, whereas the 11-year-old children tended to have increased ERPCOH in the theta, beta-2, and gamma bands, the 7-year-old children had the lowest ERPCOH in these frequency bands. The long-range coupling between oscillators of theta activities [19] and phase coherence of the gamma band [20] have also been interpreted as indicating the integration of cortical information underlying cognitive processing in the brain [19]. These phenomena represent long-range integration in theta, beta-2, and gamma bands and increased activities in these bands suggest an increase in intra- and inter-areal association connections for 11-year-old children. This occurred at the early stage, which has been previously associated with early attention-related processing in the working memory [8], possibly reflecting an associative mechanism which best represents children's brain maturation. Conclusions This study found decreased connection in alpha-1 and alpha-2 bands among both 7-year-old children and 11-year-old children. Increased connection was also found in the theta, beta-2, and gamma bands and in the maintained ability to distinguish target tones during the early component in 11-year-old children, but not in 7-year-old children, suggesting a tendency toward age-related

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association connections among 11-year-old children that is immature in 7-year-old children. Further study is worthwhile to investigate and differentiate between normal people and patients with various neurological conditions, such as dyslexia and ADHD. Acknowledgments The authors would like to thank the National Science Council, Taiwan, ROC, for financial support for this research under contract No. NSC 99-2112-M-017-001-MY3 and No. NSC 99-2511-S-017-004-MY3. References [1] E. Ornitz, Developmental aspects of neurophysiology, Child and adolescent psychiatry: A comprehensive textbook (1996) 39-51. [2] M.C. Ho, C.Y. Chou, C.F. Huang, Y.T. Lin, C.S. Shih, S.Y. Han, M.H. Shen, T.C. Chen, C. Liang, M.C. Lu, C.J. Liu: Neuroscience Letters 507 (2012) 78-83. [3] J.J. Eggermont, and C.W: Acta Oto-Laryngologica 123 (2003) 249-252. [4] W. Klimesch, P. Sauseng, S. Hanslmayr, W. Gruber, and R. Freunberger: Neuroscience and Biobehavioral Reviews 31 (2007) 1003-1016. [5] Z.A. Gaál, R. Boha, C.J. Stam, M. Molnár: Neuroscience Letters 479 (2010) 79-84. [6] J. Yordanova, V. Kolev: Journal of Psychophysiology 23 (2009) 174-182. [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20]

S.A. Hillyard, R.F. Hink, V.L. Schwent, T.W. Picton: Science 182 (1973) 177-180. R. Naatanen, T. Picton: Psychophysiology 24 (1987) 375-425. C. Başar-Eroglu, E. Başar, T. Demiralp, M. Schurmann: International Journal of Psychophysiology 13 (1992) 161-179. A. Delorme, S. Makeig: Journal of Neuroscience Methods 134 (2004) 9-21. S. Makeig, S. Debener, J. Onton, A. Delorme: Trends in Cognitive Sciences 8 (2004) 204-210. O. David, L. Harrison, K.J. Friston: Neuroimage 25 (2005) 756-770. B. Güntekin, E. Başar: Cognitive Neurodynamics 4 (2010) 107-118. S.J. Johnstone, R.J. Barry, J.W. Anderson, S.F. Coyle: International Journal of Psychophysiology 24 (1996) 223-238. V. Mueller, Y. Brehmer, T. von Oertzen, S.-C. Li, U. Lindenberger: BMC Neuroscience 9 (2008) 18. A. Toga, P. Thompson, E. Sowell: Trends in Neurosciences 29 (2006) 148-159. P.E. Engelhardt, Ş. Barış Demiral, F. Ferreira: Brain and Cognition 77 (2011) 304-314. R. Cabeza, N.D. Anderson, J.K. Locantore, A.R. McIntosh: Neuroimage 17 (2002) 1394-1402. P. Sauseng, J. Hoppe, W. Klimesch, C. Gerloff, F.C: European Journal of Neuroscience 25 (2007) 587-593. E. Rodriquez, H. George, J. Lanchaux, J. Martinerie, B. Renault, F. Varela: Nature 397 (1999) 430-433.

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In-Plane Electromagnetic Generator Fabricated on Printed Circuit Board Technology C.T. Pan1, 2, a, F.T. Hsu1, b, C.C. Nien3, c, Z.H. Liu1, d, Y.J. Chen1, e and P.H. Chen1,f 1

Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-Sen University, Kaohsiung 804, Taiwan 2

Center for Nanoscience & Nanotechnology, National Sun Yat-Sen University; National Science Council Core Facilities Laboratory for Nano-Science and Nano-Technology in Kaohsiung-Pingtung area, Taiwan 3

Industrial Technology Research Institute, Logistics & Energy Efficiency Service Division, Service Systems Technology Center a

[email protected], [email protected], [email protected], [email protected], [email protected], f [email protected]

d

Keywords: energy harvester, PCB, electromagnetic, finite element analysis.

Abstract. Small and efficient energy harvesters, as a renewable power supply, draw lots of attention in the last few years. This paper presents a planar rotary electromagnetic generator with copper coils fabricated by using printed circuit board (PCB) as inductance and Nd-Fe-B magnets as magnetic element. Coils are fabricated on PCB, which is presumably cost-effective and promising methods. 28-pole Nd-Fe-B magnets with outer diameter of 50 mm and thickness of 2 mm was sintered and magnetized, which can provide magnetic field of 1.44 Tesla. This harvester consists of planar multilayer with multi-pole coils and multi-pole permanent magnet, and the volume of this harvester is about 50x50x2.5 mm3. Finite element analysis is used to design energy harvesting system, and simulation model of the energy harvester is established. In order to verify the simulation, experiment data are compared with simulation result. The PCB energy harvester prototype can generate induced voltage 0.61 V and 13.29mW output power at rotary speed of 4,000 rpm. Introduction In last decades, there has a lot of research in microelectronics technology. These application and devices can be used on industrial, wireless sensor network and bio-medical industry. Nevertheless, how to power these devices is a big problem. Battery is the most common and popular way to solve this problem, but it has many disadvantages, such as short lifetime, large dimension and difficult to replace it. Thus, developing a self-power source to replace conventional batteries draws a lot of attention. Scavenging ambient energy and converting it into electrical power is a potential way to substitute conventional energy sources. Classified by transduction types [1], there are many kinds of generators, piezoelectric, electromagnetic, electrostatic, etc. Electromagnetic generators have many advantages over other generators, such as high sensitivity, supply sufficient power and easily combined with other devices [2]. Electromagnetic generators are mainly driven by two ways: vibration and rotation. There are lots of vibration energy harvesters have been developed. Some of them were with yoke [3], and some of them were without yoke and either makes coil or magnet vibrate [4]. The principle of vibration energy harvester is converting mechanical vibration to electrical power. Most of them put permanent magnet on the mass cube, when relative motion occurs between magnets and coil, coil will generate electromotive force [5]. However, air resistance is another reason to decrease the vibration amplitude. Wang et al presents a structure with air channel to reduce air pressure [6], but vibration energy harvester still have many limitations.

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Though many research focus on broadening the operation frequency, output electrical power is still limited by natural frequency and periodic vibration source [7-10]. Rotation energy harvester is a feasible way to solve these problems. Rotation energy harvesters don’t have to operate under certain frequency; furthermore, gear box can be used to multiply or divide rotation speed into wanted number. Besides, unlike vibration harvester, rotation harvester don’t need extra space to vibrate, so rotation energy harvester also save a lot of space which is really important for decreasing the dimension of energy harvester. Nowadays, rotation energy harvesters have been developed to multi-pole magnet and multi-layer structure [11-15]. Some previous research present planar micro generator fabricated by low temperature co-fired ceramic (LTCC) process [12]. However, LTCC has some fatal defects, such as expensive and fragile. Raw materials of LTCC energy harvester are ceramic and silver. Also, LTCC fabrication should be done under demanding conditions, such as vacuum and high temperature (850°C). Those two reason makes LTCC process pretty expensive. In addition, since it is an energy harvester, it should scavenging ambient motion. Therefore, the harvester should be placed at a location with lots of motion and vibration, such as bicycle and door knob. If energy harvester is made of ceramics, it means very delicate and brittle. It will leads to very limited life time and usefulness. In this study, a planar rotary electromagnetic generator with copper coils fabricated by printed circuit board is presented. Printed circuit board (PCB) for computer main board is a well established industry; therefore, this PCB-based harvester could find its high potential for integration with IC related industry. Moreover, PCB is made of plastic and copper, both materials are quite cheap. This is also a big advantage for industrial and mass production. Finite element analysis has been used for optimizing the design. The generator has been fabricated and tested. This harvester system is about 50x50x2.5 mm3 in volume. The simulation result agrees well with experimental result. Design and Fabrication Design and Simulation. The energy harvester comprises of a magnetic element and a magnetic-inducing coils. The magnetic member has a magnetic pole face. Considering multi-poles, area, shape and line width of coil, the optimal design are listed as follows. Magnetic pole face has a plurality of N and S magnetic poles that are evenly arranged in an interlaced manner. That is to say, 14 N and 14 S magnetic poles are laid side by side to form a 28 poles magnetic member, as shown in Fig. 1. The copper coil is composed of 22 fan-shaped segments. Each segment is composed of copper coil. Copper coil have line width of 200µm, gap between lines are 100 µm and 35µm in thickness, as shown in Fig. 2. When rotation is applied to the energy harvester, the magnetic member and the magnetic-inducing member can generate electric power by relatively motion, according to Faraday’s law of induction. This is a multi-pole coil, if we connect 22 poles directly, it would have some current offsetting problems. In order to solve this problem, every pole next to each other should generate current in opposite directions. It means if a pole generate clock-wise current through the coil, the pole next to it should generate counter clock-wise current through the coil. That way, the generated current can accumulate through each coil, rather than neutralize by opposite direction current. The simulation model of PCB energy harvesting system is shown in Fig. 3. The solution type is set as magnetic transient. Motion type is rotation around global Z axis. Coil terminal excitation has one conductor. The material of coil is copper and Nd-Fe-B permanent magnet can provide magnetic field of 1.44 Tesla. The mesh operation of coil and magnet are limited to 5,000 elements. Time step is 0.25ms. The simulated induced electromotive force is 0.19, 0.353, 0.568, 0.71V at rotary speed of 1000, 2000, 3000 and 4000 rpm, respectively.

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Fig. 1 Schematic view of 28 pole magnet, (a) 14 Fig. 2 (a) Top (b) Schematic view of 1 pole PCB N and 14 S are laid side by side (b) 28 poles coil. magnet form a magnetic member.

Fig. 4 Fabrication process of Nd-Fe-B magnet. Fig. 3 The simulation model of energy harvesting system, (a) Top view (b) Schematic view. Fabrication. This harvester consists of planar multi-pole coils and multi-pole permanent magnet. First, raw materials are melted and casted into ingots. After crushing and milling, anisotropic magnetic field orientation direction is applied to the ingot. The magnet is sintered under heat treatment and pressure. Then, the magnet is cut and grinded into the wanted shape and size. Fig. 4 shows the fabrication process of magnet. 28-pole Nd-Fe-B magnets with outer diameter of 50 mm with thickness of 2 mm are fabricated, which can provide magnetic field of 1.44 Tesla, as shown in Fig. 5. The fabricated magnet has been measured by Vibrating Sample Magnetometer (VSM) and result is shown in Fig. 6. Coil fabrication process is shown in Fig. 7 (a-d). First, positive photo resist were spun coated on the substrate. Second, the mask was placed on the substrate, followed by exposure to ultraviolet light for 40 seconds to transfer the patterns on mask to photoresist. After the exposure, the board was put into sodium carbonate developer to wash away the unwanted parts. Last, the circuit board is immersed into the bath of ferric chloride etchant at 60°C for 40 minutes. The PCB coil completes when the uncovered copper are all removed. Fig. 8 shows 22 poles copper coil fabricated by PCB technology. Gap between PCB coil and Nd-Fe-B magnet set as 100 µm. The volume of energy harvesting system is about 50x50x2.5 mm3.

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Fig. 6 Result of VSM measurement. Fig. 5 (a) One pole of Nd-Fe-B permanent magnet (b) 28 poles of Nd-Fe-B magnet form a magnetic member.

Fig. 7 Fabrication process of PCB coil, (a) coating (b) UV light exposing (c) developing (d) Fig. 8 22 poles copper coil fabricated by PCB technology. etching and stripping.

Application and Result Induced voltage and output power of the prototype energy harvester are measured. In Fig. 9, the applied torque comes from right hand side. Angular velocity will multiply by coaxial reduction gearbox (25:1), and make coaxial magnetic member rotate at same angular velocity ω. Fig. 10 shows the relationship between simulation and experiment result. The tendency of experiment data agrees with the simulation result. The inaccuracy might caused by the inexact gap between coil and magnet. Since it is a rotation energy harvester, the rotary speed is critical for output power. Generally, high speed motion is not common in daily life; thus, a reduction gearbox can be used to multiply the rotary speed from ambient motion, such as opening door. The selection of reduction gearbox depends on what kind of electric devices are going to be driven. Nevertheless,

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gearbox has high reduction ratio result in high angular velocity and output power, but needs bigger torque to make it work. Fig. 11 shows that the rotary speed is highly relevant with its output power. This energy harvester can generate 13.29mW at rotary speed of 4,000 rpm with load resistance 19Ω.

Fig. 9 Coaxial reduction gearbox can multiply input angular velocity.

Fig. 10 Comparison between simulation and experiment result.

Fig. 11 Experiment result of output power.

Conclusion The design, fabrication, simulation and application of planar rotary energy harvester are presented. Finite element analysis is used to simulate the design and optimize the energy harvester. This energy harvester consists of 28 poles Nd-Fe-B sintered permanent magnet and 22 poles coil fabricated by PCB technology. The entire energy harvester is about 50x50x2.5 mm3 in volume. The prototype energy harvester has the output power of 13.29mW at rotary speed of 4,000 rpm. According to the experiment result, there is a high positive correlation between output power and rotary speed. Thus, using a gearbox to multiply the rotary speed is an effective way to improve the output power. References [1] P.D. Mitcheson, E.K. Reilly, T. Toh, P.K. Wright, E.M. Yeatman, Performance limits of the three MEMS inertial energy generator transduction types, Journal of Micromechanics and Microengineering, 17 (2007) 211-217. [2] D.P. Arnold, F. Herrault, I. Zana, P. Galle1, J.W. Park, S. Das, J.H. Lang, M.G. Allen, Design optimization of an 8W, microscale, axial-flux, permanent-magnet generator, Journal of Micromechanics and Microengineering. 16 (2006) 290-297. [3] S. Kulkarni, S. Roy, T. O’Donnell, S. Beeby, J. Tudor, Vibration based electromagnetic micropower generator on silicon, Journal of Applied Physics. 99 (2006) 511-513.

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[4] S. Kulkarni, E. Koukharenko, R. Torah, J. Tudor, S. Beeby, T. O’Donnell, S. Roy, Design, fabrication and test of integrated micro-scale vibration-based electromagnetic generator, Sensors and Actuators A: Physical. 145 (2008) 336-342. [5] P.H. Wang, X.H. Dai, D.M. Fang, X.L. Zhao, Design, fabrication and performance of a new vibration-based electromagnetic micro power generator, Microelectronics Journal. 38 (2007) 1175-1180. [6] P.H. Wang, H.T. Liu, X.H. Dai, Z.Q. Yang, Z.Z. Wang, X.L. Zhao, Design, simulation, fabrication and characterization of a micro electromagnetic vibration energy harvester with sandwiched structure and air channel, Microelectronics Journal. 43 (2012) 154-159. [7] I. Sari, T. Balkan, H. Kulah, An electromagnetic micro power generator for wideband environmental vibrations, Sensors and Actuators A: Physical. 145 (2008) 405-413. [8] C. Serre, A. Perez-Rodrıguez, N. Fondevilla, E. Martincic, S. Martınez, J.R. Morante, J. Montserrat, J. Esteve, Design and implementation of mechanical resonators for optimized inertial electromagnetic microgenerators, Microsyst Technol. 14 (2007) 653-658. [9] C. Serre, A. Perez-Rodrıguez, N. Fondevilla, J.R. Morante, J. Montserrat, J. Esteve, Linear and non-linear behavior of mechanical resonators for optimized inertial electromagnetic microgenerators, Microsyst Technol. 13 (2007) 1655-1661. [10] J. Yang, Y.M. Wen, P. Li, X.Z. Dai, A magnetoelectric, broadband vibration-powered generator for intelligent sensor systems, Sensors and Actuators A: Physical. 168 (2011) 358-364. [11] C.T. Pan, T.T. Wu, Simulation and fabrication of magnetic rotary microgenerator with multipolar Nd/Fe/B magnet, Microelectronics Reliability. 47 (2007) 2129-2134. [12] C.T. Pan, Y.J. Chen, Application of low temperature co-fire ceramics on in-plane micro-generator, Sensors and Actuators A: Physical. 144 (2008) 144-153. [13] C.T. Pan, Y.J. Chen, S.C. Shen, Simulation and analysis of electromagnetic in-plane microgenerator, Journal of Micro-Nanolithography MEMS and MOEMS. 8 (2009) 031304. [14] A.S. Holmes, G. Hong, K.R. Pullen, Axial-Flux Permanent Magnet Machines for Micropower Generation, Journal of Microelectromechanical System. 14 (2005) 54-62. [15] S.M. Hosseini, M.A. Mirsalim, M. Mirzaeil, Design, Prototyping, and analysis of a low cost axial-flux coreless permanent-magnet generator, Transations on Magnets. 44 (2008) 75-80.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 530-534 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.530

Wide Area Input Stabilizer for Damping of Power System Inter-area Oscillation Van-Dien Doan, Ta-Hsiu Tseng and Pei-Hwa Huang Department of Electrical Engineering, National Taiwan Ocean University, Taiwan [email protected] Keywords: Power system stability, eigenanalysis, power system stabilizer, phasor measurement.

Abstract. The main objective of this paper is to report the small signal stability analysis of Vietnam Power System which has a longitudinal network structure with the consideration of power system stabilizer (PSS) in operation to enhance the damping of inter-area oscillation by using local as well as remote feedback signals via phasor measurement unit (PMU). Both methods of frequency domain and time domain analyses are used to investigate the performance of the power system. The study results show that by proper selection of PSS installation locations and remote feedback signals, power oscillations on the tie-line will be reduced and the system stability is thus improved. Introduction Interconnection of power systems has been proving an efficient operation pattern in techniques, economics and environments. It is becoming a backbone in power system which supports to transport energy with less cost from the generation center over long distance to the load center as well as to exchange the power between the regions or countries. However, the stability of the power system becomes also more complex, especially the power systems, which must always work under stressed conditions in the deregulated competitive environments. Low frequency electromechanical oscillations are one of the potentially dangerous effects on power system stability. They are inherent in the weak interconnected power systems during contingencies and can be classified into local modes and inter-area modes which refer to the rotor oscillations associated with generators within the same area and with generators located in some different areas, respectively [1,4]. Inter-area modes are associated with machines in one part of the system oscillating against those machines in other parts of the system. As compared to the local mode oscillation, the oscillation caused by an inter-area mode often has a lower frequency and less damping, with more generators involved from different regions [3,8]. For many years, PSS is still considered as the best option in terms of cost and damping oscillation performance. PSS has been used to add damping to electromechanical oscillations in order to increase the power transfer or maintain working stable modes in the network. Method of Eigen-analysis Small-signal stability analysis with the method of eigenanalysis has proven as the most effective analysis tool for power system low-frequency oscillations. This method provides not only information related to destabilizing mechanism but also identify clearly areas which has potential instability problems. In this method the system is linearized about an operating point. The following steps constitute the procedure for analyzing power system oscillations [1,4]. • Step 1 Linearize the power system at the operating point and obtain the linearized form of the system. • Step 2 Calculate system eigenvalues from the linearized form of the system. Check the damping of each eigenvalue and designate the poorly damped oscillation mode as the critical mode of the system. • Step 3 Perform detailed eigenanalysis for the poorly damped oscillation mode, including the eigenvalue, the frequency and the damping ratio, and the corresponding eigenvector elements (the mode shape) as well as the associated state participation factors.

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•

Step 4 Conduct time-domain simulations for the identified critical mode by applying typical and necessary disturbances to the system for making comparison with the result obtained from frequency-domain eigenanalysis. Both the time domain simulation and the frequency domain analysis, i.e. the method of eigenanalysis, are used in the task of system analysis. The small signal stability of the system under study is investigated by the method of eigenanalysis for finding the damping, frequency, and mode shape of the critical inter-area mode of oscillation. The PSS is to be investigated in detail. Time domain simulations will then be conducted to verify the effectiveness of installing PSSs [3]. Phasor measurement units and multi-input power system stabilizer PMU has developed in the last few years to become a powerful tool to observe, protect and control large power system under abnormal operations. PMU allows a global view of the power system by providing synchronous phasor information from different locations of power system such as voltage, current, angle, frequency in real time and control signals at high speed via modem telecommunication to the controllers [2,7]. Most of the conventional PSSs are designed with single-loop structure and utilizes local input signals such as accelerating power or frequency deviation, rotor speed deviation as feedback signals. Under global observability of power system it seems to be limited since inter-area oscillation is a global dynamic phenomenon. The combining one or more remote signals with local signals to design of PSS may be a better choice for enhancement damping of inter-area oscillations. Fig. 1 and Fig.2 describes details about functional block diagram of dual-input PSS [3,9].

Fig. 1. Dual-input Power System Stabilizer type IEE2ST.

Fig. 2. Dual-input Power System Stabilizer type PSS2A. Characteristics of the study system In this paper, the stability analysis is focused on the Vietnam Power System which has a longitudinal network structure [5,6]. The system eigenvalues are to be calculated from the normal operating condition, with neither power system stabilizer or damping controller installed nor the occurrence of the contingency. All generators are modeled in detail of which the governors and exciters are represented by models in accordance with the actual generators in Vietnam Power System. With the status quo that hydro power plants of large capacity are located mainly in the north and thermal power plants of large capacity are situated mainly in the south, the system is to be investigated with the scenario in the rainy season and power is being transmitted from north to south through two EHV tie-lines. The power transfer is about 1185MW in total. The eigenvalues and damping ratios of the system are to be calculated by eigenanalysis method and the low-frequency oscillation mode associated with a complex conjugate pair of eigenvalues -0.467±j3.233 is a mode having a relatively low oscillation frequency (0.514 Hz). The damping ratio (ζ) of the mode is specified by ζ = - σ/√(σ2+ω2) = 0.1429 that determines the decay rate of the oscillation amplitude where σ and ω denote the real part and imaginary part of the eigenvalue,

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respectively. It is a poorly damped oscillation mode. This mode is thus designated as the critical oscillation mode. For more detailed analysis of the interaction between generators of this mode, the mode shape is depicted as shown in Fig. 3. It is found that this critical mode demonstrates an inter-area mode shape with northern generators as a group oscillating against the group of southern generators. Fig. 4 decribes the participation rate of generators in oscillation.

Fig. 3. Mode shape of the critical inter-area mode.

Fig. 4. Participation rate of generators in oscillation. In order to evaluate the effects of low frequency oscillation on the power system, time domain simulations have been conducted to verify the results of the linear analysis. A fault is applied to disturb the system on bus 500 of Hoa Binh hydro power plant with eight generating units in the northern area and then cleared after 80ms (4 cycles). Fig. 5 describes the speed oscillation of generators without PSSs. Fig. 6 is responses of active power on tie-lines. From Fig. 6, it can be observed that the active power of tie-lines swing strong and the system damping is not sufficient since the oscillation persists up to 10 seconds. The main reason in this case could be that, under the scenario considered, a large flow of power (1185MW) through tie-lines in such system with a longitudinal structure is likely to excite an electromechanical mode with poor damping. Inter-area oscillation with dual-input PSS Based on participation factors in Fig. 4, generators have the largest participation factors will be considered to install PSSs. Thus, the generator Huoi Quang (1110) is equipped with a PSS of type IEE2ST. The generator of Tra Vinh (9520) and Mong Duong (2530) are equipped with a PSS of type PSS2A.

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Fig. 5. Speed oscillation of generators without PSSs.

Fig. 6. Responses of active power on tie-line without PSSs. The local signals of PSSs are speed signals on the shafts of the generators meanwhile the remote signals of PSSs are to be collected from different 500kV buses along the power system, respectively. Time domain simulation for each PSS with different combinations of input signals are conducted by applying a fault similar to case without PSSs which are presented in the previous section. Fig. 7 is the responses of active power oscillations of generators when PSSs installed in both areas with remote signals from bus 880 (Daknong) in the central area. Fig. 8 is the responses of active power oscillations on tie-lines. The various results with eigenanalysis are summarized in Table 1. Table 1. Eigenvalues and damping ratio at different remote buses. Location of PSS Remote Bus Eigenvalue D. Ratio Case and local signal 1 9250-1110,2530 210 -0.301± j3.213 0.093 2 9250-1110,2530 880 -0.249± j0.906 0.265 3 9250-1110,2530 990 -0.294± j3.281 0.089 4 9250-1110,2530 210 - 990 -0.232± j3.332 0.069 From Table 1, it is observed that the combination of the locals and remote signals which obtained from bus 880 (Daknong) will provide the best performance of damping in the system. After PSSs are installed the characteristics of inter-area oscillation changed significantly. Besides that, in time domain simulation, the responses in Fig. 8, for which the PSSs are installed in both areas with the remote signal from bus 880 yield also the most damping in the system. This is consistent with the eigenvalues shown in Table 1. And we can make an observation that the PSSs employs remote bus voltage as one of the input signals will also improve the system damping

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Fig. 7. Active power oscillations of generators with remote signals from bus 880.

Fig. 8. Responses of active power on tie-line with remote signals from bus 880. Conclusions This paper has focused on inter-area oscillation damping improvement using PSS with wide area input signals in a longitudinal power system. Based on the method of eigenanalysis to specify the installation place of PSS; the use of local as well as remote signals which obtained via the phasor measurement unit for dual-input PSS, the inter-area oscillation is well damped. Both eigen-structure analysis and time domain simulation are conducted to verify the effectiveness of proposed dual-input PSS in improving the stability of the power system. References [1] G. Rogers: Power System Oscillation (Kluwer Academic, Norway 2000). [2] M.E. Aboul-Ela, A.A. Sallam, J.D. McCalley and A.A. Fouad: IEEE Trans. on Power Systems, Vol. 11, No. 2 (1996), pp. 767-773. [3] P.H. Huang and T.H. Tseng: Journal of Computational Information Systems, Vol. 6, No. 14 (2010), pp. 4683- 4690. [4] P. Kundur: Power System Stability and Control (McGraw-Hill 1994). [5] T.D. Hoang, A.T. Nguyen and T.T. Nguyen: EPU-CRIS International Conference on Science and Technology (2011), pp. 1-5. [6] Q.T. Tran, A.T. Tran, D.S. Lam, A.T. Tran, B. Nguyen, H.A. Nguyen, R. Feuillet and C. Praing: IEEE PES Transmission and Distribution Conference and Exposition, Vol. 2 (2003), pp. 729-735. [7] Y. Kitauchi, H. Taniguchi, T. Shirasaki, Y. Ichikawa, M. Asano and M. Banjo: Trans. of IEE Japan, Vol. 122-B, No. 1 (2002), pp. 137-144. [8] Y.Y. Hsu, S.W. Shyue and C.C. Su: IEEE Trans. on Power Systems, Vol. 2, No.1 (1987), pp. 92-98. [9] X. Yang and A. Feliachi: IEEE Trans. on Power Systems, Vol. 9, No. 1 (1994), pp. 494-500.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 535-539 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.535

Development of Serial-Connected High Step-Up DC-DC Converter with Single Switch Van-Tsai Liua and Chien-Hao Hsub Department of Electrical Engineering National Formosa University, Yunlin County, 632, Taiwan a

[email protected], [email protected]

Keywords: High voltage gain, Coupled-inductor, Clamp Circuit, Voltage-lift capacitor

Abstract The proposed converter is integrated by boost circuit, voltage lift capacitor, and coupled-inductor techniques to achieve high step-up voltage and has several advantages. First, the circuit is controlled by one single pulse width modulation (PWM). Second, the converter consists of active clamp circuit to recycle the leakage inductance and send to output capacitor so that the voltage spike on active switch is suppressed and efficiency is also improved. Third, by using the winding of secondary boost circuit, and voltage lift capacitor techniques, the high voltage gain can be achieved without more than 50% duty ratio, and the slope compensation circuit can also be simplified. Finally, a 1k W prototype converter is implemented, to verify the performance of the proposed converter with input voltage 48V, output voltage 400V, and output power 1k W is also achieved. The highest efficiency is 92.96% at 400W, and the full-load efficiency is up to 90.48%. Introduction In the future, the demand of high step-up conversion technique is gradually increased according to the growth of battery-powered applications and low-voltage renewable sources. High step-up DC-DC converters are required to have a large conversion ratio, high efficiency, and small volume. With a high step-up conversion techniques are required in many applications, such as hybrid systems for electric vehicles, high-intensity discharge lamp ballasts for automobile headlamps, fuel-cell energy conversion systems, photovoltaic conversion systems, and battery backup systems for uninterruptible power supplies. Previous research on various converters for high step-up voltage gain and increase the conversion efficiency has been investigated. In practice, conventional boost converter cannot achieve high step-up voltage gain at extreme duty ratio, the efficiency and voltage gain is affected by the active switch, rectifier diode and the resistances of the inductors. The extreme duty ratio not only causes very large current ripples and increases conduction losses but also causes strict diode reverse recovery problem. The flyback converter is a very simple structure with a high step-up voltage gain and an electrical isolation, it can rely on adjusting the turn ratios of transformer to achieve high voltage gain and circuit isolation but the voltage spike will destroy the active switch due to the leakage inductance of transformer. Although high-withstand voltage active switch and

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snubber circuit can be used to solve the problem but will result in low efficiency and increase the cost. Many researches using resonance have presented a zero-voltage and zero-current switching (ZVZCS) converter that performs zero-voltage switching (ZVS) and zero-current switching (ZCS). However, the auxiliary circuit for the resonance circuit increases the complexity of the circuit and its cost. Some resonant converters with an auxiliary switch, the main switch achieves soft switching, while the auxiliary switch executes hard switching [1]. These converters cannot improve the system’s efficiency due to the switching losses of the auxiliary switch [2]. In order to increase the voltage gain, a number of existing topologies applicable to high step-up converters by using switched-capacitor, voltage-lift and coupled-inductor techniques. The integrated boost-flyback converter was presented [3]. With low duty ratio, it can achieve high voltage gain by increasing the turn ratios or adding secondary winding stages. The leakage inductance is recycled to output capacitor during turn off period, and the efficiency can be improved. Moreover, the voltage stress on switch can be reduced. A novel high step-up converter uses the coupled-inductor and switched-capacitor techniques have been proposed. Based on the demands of high voltage gain, using serial-connected converter can achieve higher voltage gain. This converter is a combination of voltage-lift capacitor technique [4], switched-capacitor technique [5], the cascaded boost technique [6] and the coupled-inductor technique [7]. Analysis of the Proposed Converter under Continuous Conduction Mode (CCM)

Fig. 1 Proposed high step-up DC-DC converter Fig. 1 shows the proposed high step-up DC-DC converter. The circuit is consisting of DC input voltage Vin, active switch S1, input-inductor Lin, a two-windings coupled-inductor of primary-side winding N1 and secondary winding N2, clamped capacitor CO2, clamped diode D3, voltage-lift capacitor C2, rectifier diodes D1, D2, D4 and D5, first stage boost capacitor C1, output capacitor CO1, CO2 and output load resistor RO. To analyze the steady-state characteristics of the proposed converter under CCM operation, the leakage inductors of the coupled-inductor, winding resistance and the transient characteristics of the active switch S1 are neglected, all capacitors are extremely large and the voltages across the capacitors are treated as constant. The coupled-inductor is modeled as a magnetizing inductor Lm

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and an ideal transformer. The turn ratio of coupled-inductor n is equal to N2/N1, where N1 is the primary-side winding turns, and N2 is the secondary-side winding turns. During the active switch S1 is turned on, the following equations can be written as VLin = Vin VLm = VC1 VC 2 = n ⋅ VLm = n ⋅ VC 1 The change in inductor current is written as follows while switch S1 is turned on Vin ⋅ DTs , 0 ≤ t ≤ DTS Lin V ∆iLm ( on ) = C 1 ⋅ DTs , 0 ≤ t ≤ DTS Lm During the turn off period, the following equations can be written as VLin = VC1 − Vin ∆iLin ( on ) =

(1) (2) (3)

(4) (5)

(6) (7) VLm = VCO 2 − VC1 (8) VCO1 = VN 2 + VC 2 = n ⋅ (VCO 2 − VC 1 ) + n ⋅ VC1 By the volt-second balance principle, the voltage across input inductor Lin and coupled-inductor Lm is shown as

∫

DTS

∫

DTS

0

0

Vin dt + ∫

TS

DTS

VC1 dt + ∫

TS

DTS

(VC1 − Vin ) dt = 0 (VCO 2 − VC1 ) dt = 0

The output voltage VO can be express as VO = VCO1 + VCO 2 By substituting, the ideal voltage gain of this proposed converter is given by V (1 + n ) M CCM = O = Vin (1 − D ) 2

(9) (10) (11) (12)

Experimental Results A prototype circuit is implemented in the laboratory to demonstrate the practicability of the proposed converter. The specifications are shown in Table 1. The experimental voltage and current waveforms at different loads are presented in this section. According to Fig. 2(a), while the output voltage VO= 400 V, the voltage on the active switch can be clamped to achieve low voltage stress. Fig. 2(b) presents the input-inductor and coupled-inductor current iLin, iLm and active switch voltage VGS of the proposed converter which are operating in CCM because the current is not equal to zero when the switch is turned on. The rectifier diodes and clamp diode of the current iD1, iD2 and iD3 are shown in Fig. 2(c). The inrush current across iD3 is caused by the leakage inductance of the coupled-inductor while the active switch is turned off. Furthermore, the leakage inductance energy is recycled to the output capacitor CO2 so that can improve the efficiency of the converter. Fig. 2(d) shows the current through switch and rectifier diodes waveforms iDS, iD4 and iD5.

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Table 1 Vi

48 VDC

Vo

400 VDC

Po

1k W

fs

43k Hz

MOSFET S1

IXFN160N30T

Diode D1,D2

DSSK 60-02A

Diode D3, D4, D5

20CTH03FP

Coupled-inductor turn ratio

1:1.3

Input inductor

36.33 uH

Magnetizing inductor

145.34 uH

Leakage inductor

1.36 uH

Capacitor C1

200 V/2000 uF

Capacitor C2

450 V/180 uF

Capacitor CO1, CO2

250 V/820 uF

Fig. 2 Experiment results under full-load PO = 1k W

Conclusion This paper proposed a high step-up dc-dc converter with coupled-inductor, active clamp circuit and voltage-lift techniques. The steady-state analyses of voltage gain and boundary operating condition are discussed. Finally, a prototype circuit of the proposed converter is implemented in the laboratory. Fig. 3 shows the conversion efficiency under different output powers of the proposed converter, the experimental result shows that the maximum efficiency is 92.96% at 400 W and the

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full-load efficiency is 90.48% that confirm high step-up voltage gain can be realized. The voltage stress on the active switch is 192 V, so that the low voltage ratings and low RDS(ON) switch can be selected. 95,00%

Efficiency(%)

93,00%

91,00%

89,00%

87,00%

85,00% 0

200

400

600

800

1000

POUT (W)

Fig. 3 Experimental conversion efficiency

Reference [1] J. H. Kim, D. Y. Jung, S. H. Park, C. Y. Won, Y. C. Jung, and S. W. Lee: High efficiency soft-switching boost converter using a single switch. Journal of Power Electronics Vol. 9-6(2009), p. 929–939. [2] P. Das, B. Laan, S. A. Mousavi, and G. Moschopoulos: A nonisolated bidirectional ZVS-PWM active clamped DC-DC converter. Power Electronics, IEEE Transactions Vol. 24-2(2009), p. 553–558. [3] K. C. Tseng and T. J Liang: Novel high-efficiency step-up converter. Electric Power Applications, IEE Proceedings Vol. 151-2(2004), p. 182-190. [4] G. Hua, C. S. Leu, Y. Jiang, and F. C. Y. Lee: Novel zero-voltage transition PWM converters. Power Electronics, IEEE Transactions on Vol. 9-2(1994), p. 213–219. [5] Y. P. Hsieh, J. F. Chen, T. J Liang and L. S. Yang: Novel high step-up DC–DC converter with coupled-inductor and switched capacitor techniques. Industrial Electronics, IEEE Transactions on Vol. 59-2(2012), p. 998-1007. [6] L. Huber and M. M. Jovanovic: A design approach for server power supplies for networking applications. Applied Power Electronics Conference and Exposition, 2000. APEC 2000. Fifteenth Annual IEEE Vol. 2(2000), p. 1163–1169. [7] S. K. Changchien, T. J. Liang, J. F. Chen and L. S. Yang: Step-up DC-DC converter by coupled-inductor and voltage-lift technique. Power Electronics, IET Vol. 3-3(2010), p. 369-378.

CHAPTER 6: Energy and Power Engineering

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Application of TRACE and FRAPTRAN in the Spent Fuel Pool of Chinshan Nuclear Power Plant Jong-Rong Wang1, a, Hao-Tzu Lin1,b, Wan-Yun Li2,c, Shao-Wen Chen2,d and Chunkuan Shih 2,e 1

Institute of Nuclear Energy Research, Atomic Energy Council, R.O.C., 1000, Wenhua Rd., Chiaan Village, Lungtan, Taoyuan, 325, Taiwan

2

Institute of Nuclear Engineering and Science, National Tsing-Hua University, 101 Section 2, Kuang Fu Rd., HsinChu, Taiwan a

b

c

d

[email protected], [email protected], [email protected], [email protected], e [email protected]

Keywords: BWR, Spent fuel pool, TRACE, FRAPTRAN.

Abstract. In the nuclear power plant (NPP) safety, the safety analysis of the NPP is very important work. In Fukushima NPP event, due to the earthquake and tsunami, the cooling system of the spent fuel pool failed and the safety issue of the spent fuel pool generated. In this study, the safety analysis of the Chinshan NPP spent fuel pool was performed by using TRACE and FRAPTRAN, which also assumed the cooling system of the spent fuel pool failed. There are two cases considered in this study. Case 1 is the no fire water injection in the spent fuel pool. Case 2 is the fire water injection while the water level of the spent fuel pool uncover the length of fuel rods over 1/3 full length. The analysis results of the case 1 show that the failure of cladding occurs in about 3.6 day. However, the results of case 2 indicate that the integrity of cladding is kept after the fire water injection. Introduction The safety analysis of the nuclear power plant (NPP) is very important work in the NPP safety. Especially after the Fukushima NPP event occurred, the importance of NPP safety analysis has been raised and there is more concern for the safety of the NPPs in the world. Because the earthquake and tsunami occurred, the cooling system of the spent fuel pool failed and the safety issue of the spent fuel pool generated in Japan’s Fukushima NPP. In this study, the safety analysis of the spent fuel pool for Chinshan NPP was performed by using TRACE and FRAPTRAN which also assumed the cooling system of the spent fuel pool failed. The geometry of the Chinshan NPP spent fuel pool is 12.17 m × 7.87 m × 11.61 m and the initial condition is 60 ℃ (water temperature) / 1.013 × 105 Pa. Besides, the total power of the fuels is roughly 8.9 MWt initially. TRACE is an advanced thermal hydraulic code and is developed by U.S. NRC for NPP safety analysis [1]. The development of TRACE is based on TRAC, integrating RELAP5 and other programs. One of the features of TRACE is its capacity to model the reactor vessel with 3-D geometry. It could support a more accurate and detailed safety analysis for NPPs. TRACE offers the greater simulation capability than other old codes, especially for events such as LOCA. However, TRACE can’t perform the detailed calculation in the fuel rods. FRAPTRAN is a Fortran language computer code that calculates the transient performance of light-water reactor fuel rods during reactor transients and hypothetical accidents such as loss-of-coolant accidents, anticipated transients without scram, and reactivity-initiated accidents [2]. FRAPTRAN calculates the temperature and deformation history of a fuel rod as a function of time-dependent fuel rod power and coolant boundary conditions. There are two cases considered in this study. Case 1 is the no fire water injection in the spent fuel pool of Chinshan NPP. Case 2 is the fire water injection while the water level of the spent fuel pool uncover the length of fuel rods over 1/3 full length. Two steps considered in this research, the first

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step is the thermal hydraulic analysis of the spent fuel pool by using TRACE. The second step is the fuel rod analysis of the spent fuel pool by using FRAPTRAN and TRACE’s results. By using the TRACE analysis results as the input data of FRAPTRAN, FRAPTRAN can calculate the cladding temperature, hoop stress/strain, oxide thickness of cladding of the fuel rods. Methodology The SNAP v 2.2.1, TRACE v 5.0p3 and FRAPTRAN v 1.4 were employed in this research. SNAP is a graphic user interface program that processes the inputs and outputs of TRACE and FRAPTRAN. The process is shown in Fig. 1. First, TRACE performs the thermal hydraulic analysis of the spent fuel pool. Fig. 2 (a) shows the TRACE model of the spent fuel pool. In this model, the vessel and channel components of TRACE were used to simulate the pool and fuels. The heat source of the spent fuel pool was the decay heat of the fuels and was simulated by a power component of TRACE, which used the power table to simulate the power varying during the transient. The decay heat data of the fuels come from the reference [3]. Besides, this model also had the simulation of the heat conduction between the racks of the fuels and the pool. One heat structure component of TRACE was used to simulate the heat exchange in the spent fuel pool and the fuels’ racks. The geometry of the spent fuel pool is 12.17 m × 7.87 m × 11.61 m and the initial condition is 60 ℃ (water temperature) / 1.013 × 105 Pa. The total power of the fuels is roughly 8.9 MWt initially. After the TRACE analysis, FRAPTRAN input deck is established by the TRACE’s results (ex: power, coolant conditions, heat transfer coefficients history data) and fuel rod geometry data. Fig.2 (b) shows the fuel rod model of FRAPTRAN. The fuel rod is divided into 23 nodes from bottom to top. Subsequently, FRAPTRAN performs the fuel rod analysis. Then, we check the cladding surface / fuel centerline temperature of TRACE and FRAPTRAN in order to avoid the inconsistency in the temperature trend of TRACE and FRAPTRAN. Finally, the analysis results (ex: cladding strain/stress, gap pressure, oxide data, etc.) of the fuel rod are obtained from FRAPTRAN output file.

Fig. 1 The flow chart of the analysis of spent fuel pool.

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Fig. 2 (a) The TRACE model of the spent fuel pool, (b) The Fuel rod model of FRAPTRAN. Results In this research, after the cooling system of the spent fuel pool failed, this transient began. The heat source of the spent fuel pool was the decay heat of the fuels. In case 1, no fire water added into the spent fuel pool during the transient. Before the uncovered of the fuels occurred, the heat of the fuels was removed by the evaporation of pool water. After the uncovered of the fuels occurred, the film-boiling of the fuels may be generated. Fig. 3 show the cladding temperature and water level results of TRACE. The initial water temperature of the pool is 60 ℃. After the cooling system of the spent fuel pool failed, the time of the water temperature which reached 100 ℃ was roughly 2.9 hour. Subsequently, the water dries out, which lead to the water level uncover the fuel rods. Finally, the metal-water reaction of the fuels occurred in 3.6 day. The metal-water reaction makes the cladding temperature sharply rise and may generate the break of the cladding of the fuel rods. The above phenomenon may cause the safety issue of the fuels. Fig. 3 also shows the cladding temperature of FRAPTRAN for case 1 which is consistent with the result of TRACE. By using the TRACE analysis results as the input data of FRAPTRAN, FRAPTRAN can calculate the fuel rod performance in detail. Fig. 4 and 5 depict the analysis results of fuel rod using FRAPTRAN. Fig. 4 shows that the metal water reaction energy of case 1 can be observed after 3.6 day. The oxide thickness also increases after 3.6 day. According to 10 CFR 50.46 rule [4], the increasing oxide thickness of cladding should be less than 17%, but Fig. 4 shows the cladding oxide thickness is over the critical value. Fig. 5 shows the cladding hoop strain results of case 1. The cladding hoop strain of the fuel rod node 21 rises sharply after 3.6 day. Fig. 5 also shows the cladding hoop stress results of case 1. The cladding hoop stress drops abruptly to zero after 3.6 day. Besides, the radial gap of the fuel rod node 21 also increases after 3.6 day. Combining the above results, we think that the failure of cladding occurs in about 3.6 day. Fig. 6 shows the water level results of case 2 using TRACE. In case 2, the fire water added into the spent fuel pool after the water level of the spent fuel pool uncover the length of fuel rods over 1/3 full length. Therefore, in about 2.9 day, the fire water injected into the spent fuel pool. Subsequently, the water level raised. Fig. 6 and 7 show the analysis results of fuel rod using FRAPTRAN. Fig. 6 depict that the cladding temperature of case 2. When the uncover length of fuel rods is over 1/3 full length, the cladding temperature increases. After the fire water injection, the cladding temperature decreases. So the peak can be observed in 2.9 day. The peaks also can be observed in Fig. 7. The variation of cladding temperature affects the cladding hoop strain/stress.

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16

4000

Fuel Top

TRACE FRAPTRAN

3000 Cladding Tempterature (K)

Water level (m)

12

8

4

2000

1000

0

0

0

50000

100000

150000 200000 Time (sec)

250000

300000

350000

0

50000

100000

150000 200000 Time (sec)

250000

300000

350000

Fig. 3 The water level and cladding temperature of case 1. 0.0016 1.60E-02 1.40E-02

0.0012

1.20E-02

0.001

Oxide Thickness (mm )

Metal Water Reaction Energy (kW )

0.0014

0.0008 0.0006 0.0004

1.00E-02 8.00E-03 6.00E-03 4.00E-03

0.0002 2.00E-03

0 0

50000

100000

150000

200000

250000

300000

350000

0.00E+00 0

Time (sec )

50000

100000

150000 200000 Time (sec)

250000

300000

350000

Fig. 4 The metal water reaction energy and oxide thickness of case 1.

Cladding Hoop Strain

5.00E-01

4.00E-01

3.00E-01

2.00E-01

1.00E-01

0.00E+00 0

50000

100000

150000 200000 Time (sec)

250000

300000

350000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

3.00E+01

2.50E+01 Cladding Hoop Stress (MPa )

6.00E-01

2.00E+01

1.50E+01

1.00E+01

5.00E+00

0.00E+00 0

50000

100000

150000 200000 Time (sec)

250000

Fig. 5 The cladding hoop strain and stress of case 1. (Node 23 is the fuel rod top; node 1 is the fuel rod bottom)

300000

350000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

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16 Fuel Top

6.00E+02 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

12

Cladding Outside Temperature (K )

Water level (m)

5.00E+02

8

4

0

4.00E+02

3.00E+02

2.00E+02

1.00E+02

0.00E+00 0

50000

100000

150000 200000 Time (sec)

250000

300000

0

350000

50000

100000

150000 200000 Time (sec)

250000

300000

350000

Fig. 6 The water level and cladding temperature of case 2. (Node 23 is the fuel rod top; node 1 is the fuel rod bottom) 2.00E-03

1.95E+01

1.60E-03

Cladding Hoop Strain

1.40E-03 1.20E-03 1.00E-03 8.00E-04 6.00E-04 4.00E-04 2.00E-04 0.00E+00

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

1.95E+01 1.94E+01 Cladding Hoop Stress (MPa )

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

1.80E-03

1.94E+01 1.93E+01 1.93E+01 1.92E+01 1.92E+01 1.91E+01 1.91E+01 1.90E+01

0

50000

100000

150000 200000 Time (sec)

250000

300000

350000

0

50000

100000

150000 200000 Time (sec)

250000

300000

350000

Fig. 7 The cladding hoop strain and stress of case 2. (Node 23 is the fuel rod top; node 1 is the fuel rod bottom) Conclusion This study has developed the TRACE and FRAPTRAN models of the spent fuel pool successfully. In this study, there are two cases considered. Case 1 is the no fire water injection in the spent fuel pool. Case 2 is the fire water injection while the water level of the spent fuel pool uncover the length of fuel rods over 1/3 full length. The analysis results of the case 1 show that the failure of cladding occurs in about 3.6 day. However, the results of case 2 indicate that the integrity of cladding is kept after the fire water injection. This study’s results can help to evaluate the safety issue of the Chinshan NPP spent fuel pool. References [1] U.S. NRC, TRACE V5.0 Theory Manual, Division of Safety Analysis, Office of Nuclear Regulatory Research (2010). [2] K.J. Geelhood, W.G. Luscher, C.E. Beyer, J.M. Cuta, FRAPTRAN 1.4: A Computer Code for the Transient Analysis of Oxide Fuel Rods, NUREG/CR-7023, Vol. 1, PNNL-19400, Vol. 1, , USA (2010). [3] AREVA NP Inc., Startup and Operations Report Chinshan Unit 1 Cycle 24, ANP-2772(P) Revision 0 (2008). [4] U.S. NRC, 10CFR50.46c, ML110970044 (2011).

Applied Mechanics and Materials Vols. 479-480 (2014) pp 548-552 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.548

LAPUR6 Stability Analysis on Power/Flow Map of Lungmen ABWR Hao-Tzu Lin1, a, Jong-Rong Wang1, b, Kuan-Yu Chen2,c, Shao-Hsuan Chen2,d and Chunkuan Shih 2,e 1

Institute of Nuclear Energy Research, Atomic Energy Council, R.O.C., 1000, Wenhua Rd., Chiaan Village, Lungtan, Taoyuan, 325, Taiwan

2

Institute of Nuclear Engineering and Science, National Tsing-Hua University, 101 Section 2, Kuang Fu Rd., HsinChu, Taiwan a

b

c

[email protected], [email protected], [email protected], d e [email protected], [email protected]

Keywords: ABWR, Stability, LAPUR6.

Abstract. This research aims at investigating the instability phenomena on the power-flow operating map of Lungmen nuclear power plant (NPP). Lungmen NPP is the first ABWR (Advanced Boiling Water Reactor) and under construction in Taiwan. It consists of two identical units with 3926 MWt rated thermal power and 52.2×106 kg/hr rated core flow. In this research, decay ratios (the stability index) are calculated by LAPUR6. LAPUR6 is an analyzing core instability computer code based on the frequency domain approach. Before investigating the stability on Lungmen NPP operating map, some additional state points are carried out for validating with the SIRIUS-F experimental data [1]. LAPUR6 results are consistent with the SIRIUS-F experimental data. Besides, LAPUR6 results of Lungmen NPP operating map show that the Lungmen NPP will not encounter core-wide or regional instability under normal operating or RIP trip event. Introduction Boiling water reactors (BWRs) may encounter some stability and safety problems due to the presence of steam in the BWRs’ core. The mechanism of these instability phenomena is related to a coupling between thermal-hydraulics and neutron kinetics. These instabilities could be classified as in-phase (core-wide mode) and/or out-of-phase (regional mode) instability [2]. Normally, these instability problems occur under high power and low flow condition. Some researchers [3,4,5] mention that at high power/flow ratio condition, two-phase pressure drop and void reactivity coefficient are very important and considered primary for BWR stability analysis. And C.L. Hsieh [6] indicated that smaller pressure drop ratio (two phase pressure drop/single phase pressure drop) could lead to smaller decay ratio. Advanced boiling water reactor (ABWR) has several improvements than general BWRs. Some of the improvements could cause larger single-phase pressure drop and lower the pressure drop ratio. Before a fuel reload is executed, stability analyses are performed to guarantee that parameters such as core-wide decay ratio, regional mode decay ratio, and channel decay ratio are within safety limits [7]. Fuel vendors provide instability boundaries on power-flow operating map by ODYSY code to assure the safe reactor operating. In Taiwan, we make a parallel examination by NRC certified code, LAPUR6, to verify venders’ results. In order to provide more detail information, we used LAPUR6 code to investigate the stability phenomena on power-flow operating map of Lungmen nuclear power plant, especially for high power/flow ratio region. Besides, LAPUR6 also performed the analysis of the SIRIUS-F experiment. LAPUR6 results compared with the SIRIUS-F experimental data [1]. Methodology LAPUR6 is a computer code that analyzes core stability of boiling water nuclear reactors. It uses frequency domain approach to calculate decay ratios. SIMULATE-3, based on the three-dimensional

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iterative nodal method, is a neutronic code that generates three-dimensional distributions of a nuclear reactor core. Fig. 1 depicted the analytic procedures of LAPUR6 methodology in this study. There are two modes of instabilities calculated by LAPUR6: core-wide mode instability and regional mode instability. Core-wide mode instability is characterized by its overall core region oscillation behaviors. On the other hand, regional mode instability shows local oscillations. Basically, LAPUR6 is divided into two separate programs, LAPURX and LAPURW. LAPURX solves the steady state governing equations of coolant and fuels. And LAPURW is programmed to calculate the dynamic equations of coolant, fuels, and core neutronics in frequency domain. Because of the differences in neutronic models between LAPUR6 (point kinetics) and SIMULATE-3 (3-D), it is necessary to process some of their inputs and outputs. PAPU code, developed by Polytechnic University of Valencia, Chemical Engineering Department [8], transfers results from reactivity perturbation calculations (density and Doppler reactivity coefficient) and other dynamic nuclear parameters [9] to prepare the input file for LAPURW. EXAVERA-200, developed by our own team, collects and processes thermal-hydraulic and power distributions from SIMULATE-3 to obtain some information such as axial power profile, radial power fraction, and channel contraction coefficients into formats compatible with LAPURX inputs. Two output files, LAPURX.OUT and LAPURW.OUT, are then obtained from LAPUR6. At the end of LAPUR calculations, users should try to examine results (core pressure drops, channel flow, and core density reactivity coefficient) to check if they are consistent (within the preset acceptable error percentages) with results from SIMULATE-3 to ensure that their errors are within the limits prescribed. The error limits for core pressure drops, channel flows, and core density reactivity coefficient are 2%, 10%, and 1% respectively. If the accuracy is not met, new density reactivity coefficient, pressure drop, and flow distribution are assumed and new iterations are repeated until converging.

Fig. 1 Simplified flow chart of LAPUR6.0 methodology.

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Applied Science and Precision Engineering Innovation

Results Before studying the stability phenomena on power-flow operating map of Lungmen NPP, we analyzed the same state points performed by Masahiro Furuya [1]. In this reference, an experimental facility SIRIUS-F simulated the performances of forced circulation ABWR. SIRIUS-F is a full-height facility with artificial void-reactivity feedback system for simulating core-wide and regional stabilities of the ABWR. It used real-time analysis conducted for thermal-hydraulics, neutronics, and thermal conduction to simulate void-reactivity feedback. The experimental ranges of SIRIUS-F are shown in Fig. 2 with two hatched rectangles: (1) the minimum pump speed line including the maximum power point, and (2) the natural circulation line including the maximum power point.

Fig. 2 ABWR Power-Flow Operating Map and SIRIUS-F Experimental Ranges [1]. The resonance frequencies and regional decay ratios, calculated by LAPUR6, agree well with experiment data (shown in Fig. 3). And the regional mode is the dominant oscillation mode of analysis state points. It shows the same trend as experiment result, proving that LAPUR6 has the capability to analyze ABWR stability phenomena. 1

0.6

42% Flow Rate 0.5

0.8

Decay Ratio

Resonance Frequency

42% Flow Rate

0.6

0.4

0.4 0.3 regional stability (Experiment)

regional stability (Experiment)

0.2

regional stability (LAPUR6.0)

0.1

regional stability (LAPUR6.0)

0.2

core-wide stability (LAPUR6.0)

0

0

0.6

0.65

0.7

0.75

Core Thermal Power

0.8

0.85

0.6

0.65

0.7

0.75

0.8

0.85

Core Thermal Power

Fig.3 The comparison of experiment data and LAPUR6 results. In Lungmen cycle 1 load design, the core has only one type of fuel (GE-14). In this study, all fuel assemblies are lumped into 200 regions by the location on core configuration shown for quarter-core form in Fig. 4. The color performed on this figure is based on the relative assembly power fraction. According to the LAPUR6 requirements, the sum of relative power in each region is required not to exceed 20%. This requirement guarantees a good description of the radial power shape, especially for the high power channels. The highest relative power in this study was below 1%. All the calculating processes in the methodology were included in DRASM-200 except SIMULATE-3 code. DRASM-200 is an interface program, developed by our own team, and carries out the LAPUR6 input files setting processes and converging iterations automatically. Lungmen NPP incorporates some design features to improve the stability performance, such as smaller inlet orifice, wider control rod pitch, and more steam separators, and assure that it is more

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stable than the current operated BWR. Fig. 5 shows the decay ratio distribution on the power-flow operating map. Because of the expected large decay ratios on the high power/flow region, we set more analysis state points between natural circulation line and minimum pump speed line. On the other region of operating map, we chose the intersection points of rod lines and pump speed lines as analysis state points. Totally, about 150 state points were analyzed in this research. In Fig. 5, the decay ratios on most of the power-flow operating map are quite small (DR ∆ > ∆ > ∆ ). This monotonic magnitude changes at various ammonia dosage rates have a significant implication on the application of the SNS. Specifically, the amplitude of the SNS signal at a perturbed dosage frequency can be used for direct interpretation of the true NOx emission in applications where ammonia is involved. Fig. 6 shows the close-up view of the NOx response in Fig. 3 when the pump speed is 0.2 rev/s. The main frequency (0.2 Hz) and its corresponding magnitude can be clearly observed in Fig. 6. Moreover, discretization distortions (small amplitude steps) resulted from digitization of the continuous data during data acquisition can be clearly observed. They are responsible for the higher harmonics existing in the spectrums shown in Fig. 4.

0.2

0.5

1

1.5

2

3 urea pump flow rate=0.193(g/s) and speed=0.3(rev/s)

2 1 0 0

30 20

0.3

0.5

1

1.5

2

urea pump flow rate=0.255(g/s) and speed=0.4(rev/s)

10 0 0

0.4 0.5

1 Frequency (Hz)

1.5

2

Fig. 4. Spectral analysis of NOx sensor signals.

Conclusions In an effort to explain the oscillating behaviors of the NOx sensor signals with respect to various urea dosages and to find solutions to the cross-sensitivity of the Smart NOx Sensor (SNS) to ammonia, spectral analysis is conducted by using Fast Fourier Transform (FFT). The SNS requires decoding following the SAE J1939 protocol and thus higher harmonics induced by the discretization are

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observed in the spectrums. Moreover, the cross-sensitivity of the SNS to ammonia concentration for higher-than-stoichiometric ammonia dosage results in oscillating NOx sensor signal at lower frequencies. As a result, the SNS signal cannot be interpreted in a straight-forward way as it is not clear whether excess NOx or NH3 is present [4]. On the other hand, the amplitude of the SNS signal at a perturbed dosage frequency can be used for direct interpretation of the true NOx emission in applications where ammonia is involved. In this specific case, the ammonia dosage is inherently perturbed by the reciprocating motion of the urea pump in the SCR system. The periodic fluctuations of the ammonia dosage and the nonlinear characteristics from ammonia dosage to NOx downstream SCR result in oscillating NOx sensor readings with different amplitudes at corresponding pump speeds.

350 NOx Sensor Signal 300

NOx (ppm)

250

200

150

100

50 300

320

340

360

380

400

Time (s)

Fig. 5. Nonlinear curve of NOx downstream SCR with respect to perturbed ammonia dosage ratios.

Fig. 6. Zoomed view of Fig. 3.

Acknowledgments: The authors would like to thank the funding support from Bureau of Energy, Ministry of Economic Affairs, Taiwan, R.O.C., under contract 102-D0107. References [1] J. W. Patrick and K. M. Thomas, “NOx-basic mechanisms of formation and destruction, and their application to emission control technologies.” Fuel, vol. 73, September (1994). [2] R. Moos, “A Brief Overview on Automotive Exhaust Gas Sensors Based on Electro ceramics.”Int. J. Appl. Ceram. Technol., 2 (5), PP.401-413, (2005). [3] R. Moos, “Catalysts as Sensors—A Promising Novel Approach in Automotive Exhaust Gas Aftertreatment.”Sensors, PP. 6773-6787, (2010). [4] L. Guzzalla and C. H. Onder, Introduction to Modeling and Control of Internal Combustion Engine System. Springer, (2004). [5] M. Mrosek, H. Sequenz, R. Isermann, “Identification of Emission Measurement Dynamics for Diesel Engines”, IFAC World Congress, pp.11839-11844, (2011). [6] J. Wang, K. Zhang, D. Wang, D. Xu, B. Zhang and Z. Zhao. “Synthesis and Nox Gas Sensing Properties of In1.82ni0.18o3 Electrospun Nanofibers,” FISITA, Vol. 194, pp 231-239, (2012). [7] SAE J1939-71, “Surface Vehicle Recommended Practice”, JUN (2006). [8] Brigham, E. Oran, “The fast Fourier transform and its applications.” Englewood Cliffs, N.J.: Prentice Hall. ISBN 0-13-307505-2 (1988).

Applied Mechanics and Materials Vols. 479-480 (2014) pp 724-728 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.724

Design of photo diode sensors for measuring solar light orientation Yong-Nong Chang 1,a, Hung-Liang Cheng 2,b , Shun-Yu Chan 3,c and 1

Yu-Siang Shen 1,a

Department of Electrical Engineering, National Formosa University, Yunlin County, 63201, Taiwan 2 3

Department of Electrical Engineering, I-Shou University, Kaohsiung, Taiwan

Department of Electrical Engineering, Cheng Shiu University, Kaohsiung, 83347, Taiwan a

[email protected], [email protected], [email protected]

Keywords: solar energy, photo diode, geometric space transformation, solar orientation azimuth

Abstract. In this paper, the photo diode sensors are used to realize the solar light detector for measuring the relative solar orientations. The proposed solar light detector comprises five photo diode sensors which are positioned on the front, back, left, right, and upper sides, respectively, on a cubic structure and cubic light-measuring detector is constructed. Accordingly, the photo sensors located on five facets can detect solar light from various directions and measure the incident solar power. Therefore, the relative solar azimuth and elevation angles can be measured precisely. The experimental results have confirmed the validity of the developed system. Introduction Solar energy has always been the cleanest, pollution free, and sustainable energy resource for human being. Being abundant and inexhaustible, solar power is the most natural energy source [1]. In recent years, all the developed countries are devoted to harnessing and developing solar power, as is considered to be the most important green energy. Harnessing and collecting solar power to transform into electricity or heat is always being the most important application of solar energy. Research has been focusing on solar-light tracking system to guide and adjust the solar panels toward the optimal direction and promotes the transformation efficiency. A well-designed solar tracking system can lead to optimal solar panel azimuth and elevation angles, thus maintaining good transformation efficiency [2]. With regards to solar power applications, a comprehensive solar energy information and sensor is indispensable. Despite that the related technologies about solar tracking systems have been developed by previous researches, there still exist several problems to be improved [2]. To take electronic perpetual calendar as an example, orientation corrector (calibrator), i.e. expensive electronic compass for instance, is the prerequisite for setting up reference orientation and measurement accuracy. Therefore, this study will aim at developing a light orientation solar sensor. By means of, theoretically, utilizing the combination of incident light measured from front, back, left, right, and top facets of cubic detector, the relative orientation and energy of solar light can be calculated based on the geometric vector space and coordinate transformation[3,4,5]. In this study, the instant relative azimuth angle and elevation angle are measured and recorded through the usage of SOC (system on chip) technology for further explorations. Implementation of light power detector The proposed solar cubic light-measuring detector comprises five photo diode sensors which are positioned on the front, back, left, right, and upper sides, respectively, to measure the incident sunlight coming from different orientation and elevation angles. Due to inevitable minute errors arisen from photo diode device, all sensors must be corrected and calibrated prior to the measurement. In this study, the corrections of sensor are accomplished by using operation amplifier circuit as shown in Fig.1. By adjusting the voltage gain of OP Amp, every sensor is corrected to

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possess the identical error. Therefore, the precision of azimuth and elevation angles measured by the proposed power detector can be promoted, accordingly. 50K£[

103

100K£[ Vo

103

Photo diode

510£[

Fig. 1. Correcting circuit of solar light sensors

In this research, the design and implementation of solar orientation detection is based on the changing azimuth and elevation angles which would affect the incident power to sensors. Therefore, the test can be performed based on the sunlight variation during day time in a sunny day. The solar power will be measured and analyzed according to different azimuth and elevation angles at different time instants in a day. By making use of horizontal sensor, the measured data are substituted into the geometric space transformation equations. In this way, the solar power information corresponding to front, back, left, right direction can be calculated by the usage of coordinate transformation equations. Using SOC technology, the transformation equations are programmed and burned into the chip. The azimuth and elevation angles of sunlight are displayed on the LCD panel and recorded. Next, the generated photo current resulted from incident light will pass through shunt impedance and creates milli-volt scale voltage (mV). For obtaining large enough readable voltage data for single-chip, high voltage gain amplifier must be utilized to boost the measured voltage to a large-enough scale for single chip. The derivations of geometric space transformation between Sun and sensor In this study, the incident light vector is decomposed into four coordinates as shown in Fig. 2. In Fig. 2, five sensors are mounted on the top side (T for Top side), front side (F for front side), right side (R for right side), left side (L for left side), and back side (B for back side) respectively. In this structure, sensors B, R and T can absorb the sunlight of the first quadrant, sensor B, L and T can absorb the sunlight of the second quadrant, sensor F, L and T can absorb the sunlight of the third quadrant, and sensor F, R and T can absorb the sunlight of the fourth quadrant. The incident sunlight vectors ought to belong to one of these four quadrants based on the comparison results of photo power from various orientations. In case of PR>PL, PB>PF, the incident light source is justified to be coming from the first quadrant; as PL>PR, PB>PF, the incident light source is justified to be coming from the second quadrant; when PL>PR, PF>PB, the incident light source is justified to be coming from the third quadrant, and while PR>PL, PF>PB, the incident light source is justified to be coming from the fourth quadrant. In a three dimension vector space , the right direction is generally defined to be Y axis, the back direction is defined to be X axis, and the top direction is defined to be Z axis. By means of coordinate transformation, the mathematical relationship between sensor and solar light source can be derived. In the meanwhile, the azimuth angle and elevation angle can be evaluated.

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Z

Top sensor Back sensor Right sensor Left sensor Front sensor

II III

X(Front)

I

Y(Right)

IV

(B)

(L)

(R)

(F)

Fig. 2. Sensors on five sides

For obtaining the relative locations and angles between every sensor and incident sunlight, in Fig.2, the space geometric coordinate transformation is used to achieve the associated coordinate quantities of all sensors. In Fig.3, the sunlight is assigned to be located at (x,y,z) relative to the top side horizontal sensor. In this geometry, the distance (γ) between horizontal sensor(T) and solar light source, elevation angle (φ') and azimuth angle (α') are illustrated as follows:

x

y

Fig. 3. Geometric space transformation

According to Fig. 3 , the coordinate transformation can be expressed as follows:  X = r sin φ′ cos α′ 
Y = r sin φ′ sin α ′ Z
= r cos φ′ 


(1)

Where φ':the angle between light source and Z axis α':the angle between light source projection on the XY plane and X axis γ:the distance between light source and origin Substituting the measured data of sensors on the five sides into the above-mentioned equations, it is seen that the measured solar power of individual sensor associated with the horizontal angle φ' and vertical angle α' can be described as follows: (1) The measured quantity of right side sensor is equivalent to rotating about X axis with angle 90°. In this way, the sensed photo power of right side direction PZR and maximum power Pmax gives PZ R = Pmax sin ϕ ′ sin α ′ = Pmax cos ϕ R

(2) (2) The measured quantity of left side sensor is equivalent to rotating about X axis with angle -90°, this means θx =-90°，θz =0°. By doing so, the sensed photo power of left side direction PZL and maximum power Pmax is PZ L = -Pmax sin ϕ ′ sin α ′ = Pmax cos ϕ L

(3)

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(3) The measured quantity of front side sensor is equivalent to rotating about Y axis with angle 90°. In this way, the sensed photo power of front side direction PZF and maximum power Pmax gives PZ F = − Pmax sin ϕ ′ cos α ′ = Pmax cos ϕ F

(4) (4) The measured quantity of back side sensor is equivalent to rotating about Y axis with angle -90°. By doing so, the sensed photo power of left side direction PZB and maximum power Pmax is PZ = Pmax sin ϕ ′ cos α ′ = Pmax cos ϕ B B

(5) (5) The measured quantity of horizontal sensor is equivalent to rotating about Z axis with angle 0°. In the same way, the sensed photo power of horizontal direction PZU and maximum power Pmax is PZU = Pmax cos ϕ ′ = Pmax cos ϕ U

(6) When the light falls on the first quadrant of XY plane, the parameters φ', α', Pmax can be obtained based on the above-listed equations. According to Eq. 2 and Eq. 5, elevation angle α' can be conducted to be: PZ PZ

R

=

B

sin α ′ cos α ′

= tan α ′ ⇒ α ′ = tan

− 1 PZ R PZ

(7)

B

Based on Eq. 5 and Eq. 6, the incident azimuth angle φ' can be found out: PZ

B

=

PZ

U

sin ϕ′ cos α′ cos ϕ′

= tan ϕ′ sin α′ ⇒ ϕ′ = tan

−1

PZ

B

PZ sin α′

(8)

U

Substituting this calculated φ' into Eq. 9, the maximum power Pmax gives: P max

=

PZ

U

cos ϕ ′

(9)

Experiment results On May 4th, 2011, the sunlight azimuth and elevation angle measurements were conducted outdoors from 10:00 A.M. to 04:00 P.M. Table 1 lists the photo powers measured by sensors of different sides. It can be clearly seen that the measured powers absorbed by diverse sides are different due to changing incident orientation angles at various time instants. Therefore, the measured solar powers absorbed by all sides are substituted into the above-listed corresponding equation to accomplish the calculations of associated azimuth angles and elevation angles as illustrated in Table 2 and Table 3. By inspecting Table 2, it can be observed that the calculated azimuth angles approximate to the true ones very well. The error angles fall within 9°. Table 3 shows the measured elevation angles are in good correspondence with the true ones as well. Table 1 Solar power measured by different sides( unit: W/m2) side

right

left

front

back

top

10:00

446

81

178

89

730

time instant

11:00

268

124

208

127

773

12:00

141

168

211

130

819

13:00

108

314

157

130

789

14:00

92

473

122

132

719

15:00 16:00

84 73

557 514

100 78

149 168

586 386

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Applied Science and Precision Engineering Innovation

Table 2 Contrast of measured azimuth angles with true ones Time instant 10:00

measured azimuth angle(α') 77.00°

True azimuth angle(α') 74.10°

error 4.65°

11:00

59.00°

60.00°

1.00°

12:00

18.40°

15.11°

-3.29°

13:00

-76.00°

-67.23°

8.77°

14:00

-85.90°

-81.48°

4.42°

15:00

-86.80°

-89.00°

-2.20°

16:00

-100.60°

-94.70°

5.90°

Table 3 Contrast of measured elevation angles with true ones 10:00

measured elevation angle(φ') 60.90°

True elevation angle(φ') 58.80°

error 3.79°

11:00

76.30°

75.52°

-0.78°

12:00

82.50°

82.01°

-0.49°

13:00

71.70°

72.24°

0.54°

14:00

58.60°

58.98°

0.38°

15:00

46.50°

45.30°

-1.20°

16:00

36.40°

31.58°

-4.82°

Time instant

CONCLUSIONS In this study, a simple cubic sensor for measuring solar orientation is developed based on sensors of five sides and equations via geometric space transformation. The proposed system not only drastically reduces the complexity of mechanical mechanism of sunlight tracking system but also breakthroughs the limited measuring range problem for those consisting of thermistors. In consequence, maintenance cost can be greatly curtailed. The experiment has confirmed the validity of the developed system. Even though the developed solar detector has successfully accomplish the orientation measurement, there still exist many problems to be overcome and solved. Because the experiment is performed outdoors, there are many uncontrollable factors that can influence the accuracy of the developed system. For examples, the sunlight passing through the atmosphere inevitably undergoes the dispersion phenomenon and light falling on rough surface will experience the problem of diverse reflection. Both phenomena will affect the justification of light sensors. Consequently, further study will cover these factors to enhance the availability of cubic solar light detector. Acknowledgment This research is supported by the National Science Council, R.O.C. under contract NSC 102-3113-P-214 -001. References [1] H.A. Krishna, N.K. Misra and M.S. Suresh: submitted to Journal of IEEE Transactions on Aerospace and Electronic Systems (2011) [2] C. Alippi and C. Galperti: submitted to Journal of IEEE Transactions on Circuits and Systems I (2008) [3] T. Wu and Ronglin Li and M.M. Tentzeris: submitted to Journal of IEEE Antennas and Wireless Propagation Letters (2011) [4] M. Danesh and J.R. Long: submitted to Journal of IEEE Transactions on Microwave Theory and Techniques (2011) [5] M. Perenzoni and L. Gonzo: submitted to Journal of Electronics Letters (2010)

Applied Mechanics and Materials Vols. 479-480 (2014) pp 729-736 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.729

Singularity Avoidance for a Redundant Robot Using Fuzzy Motion Planning Chih-Jer Lin1, a, Chii-Ruey Lin2,b , Shen-Kai Yu3,c, Cheng-Chin Han4,d 1,4

Graduate Institute of Automation Technology, National Taipei University of Technology, Taipei Taiwan, R.O.C. 2 Department of Mechanical Engineering, National Taipei University of Technology, Taipei, Taiwan, R.O.C. 3 Graduate Institute of Mechanical and Electrical Engineering, National Taipei University of Technology, Taipei, Taiwan, R.O.C. a [email protected], [email protected], [email protected], d [email protected] Keywords: Redundant Robot; B-Spline; Motion Planning; Generalized Inverse; Fuzzy Inverse Kinematic Mapping; Singularity Robustness

Abstract The purpose of this study is to design a redundant robot meeting the specific task and tracking the specific trajectory. Although the Moore-Penrose pseudo-inverse kinematic is commonly using to solve the inverse kinematic problem, it cannot solve the singularity exists in some situations that the rank of Jacobian matrix is not full rank for the redundant robot. Thus, a fuzzy motion planning algorithm is proposed to solve the inverse kinematic with singularity. Finally, we can obtain the position of five axes robot manipulator using fuzzy motion planning mapping method, and the errors of the singular points are approximately to zero. The results prove the fuzzy inverse kinematic mapping method can robust singular point when the tracking path with singular points. 1. Introduction Commonly, automatic technology has been used to reducing the production cost, increase productivity and improving quality of the product in industry since 1980; Besides, the technique commonly has been applied for various fields which are like military technology, space technology, medical equipment and home services to improve human life and quality. For those words, the robot arm is a very useful technique due to the fact that range of work space could be flexible and wide. So, the obstacle avoidance and motion controlling is never stopped present. Five degree of freedom (DOF) robot arm with obstacle avoidance using fuzzy controller has be purposed in this paper. It consists of several links, revolute joint and motor. Generally, the desire trajectory is used to describe in Cartesian coordinate system, and the link angle is described in joint coordinate. However, the kinematics analysis is divided into two parts: forward kinematics and inverse kinematics. With coordinate transform problem, various methods of formulation have been proposed. The most commonly used is the 4×4 homogeneous transformation matrix that proposed by Denavit and Hartenberg[28,29,30]. The method describes Eq.1. =

0

−

0

−

0

−

0 1

(1)

The forward kinematic is used to find the location and orientation of end effector relative to the base coordinate system, and it is determined by a serial of D-H translation matrix (Eq.1) which indicates the relationship between end effector coordinate and the base coordinate. As a result (Eq.2): = (2) In the inverse kinematics, the problem is how to find the joint angle when the location of end effector in the task space is given. Some researchers present solving the inverse kinematics problem, such as the null-space methods[1-2], singular value decomposition SVD method[3], singularity-isolation plus compact quadratic SICQP method[4], the new singularity avoidance NSA[5], and the fuzzy inverse kinematic mapping FIKM method[6] to solve the problem. Since

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Applied Science and Precision Engineering Innovation

the singularities can be decomposed into position singularities and orientation singularities, the NSA method can deal with the position singularities and orientation singularity separately. The FIKM method is to simplify the computation and replace the Moore-Penrose pseudo-inverse kinematic (PIKM) [7] method which called the generalized inverse method of the inverse kinematic problem with singularities for the redundant robots; For example, Whitney[8] proposes a method called resolve motion rate control which describes a relationship between Cartesian coordinate and joint coordinate, and the most important thing is the transform of Jacobian matrix. On the other hand, Wu and Pual[9] propose resolve motion force control which increases robustness of robot arm in environment. The purpose of those methods is to find out the control parameters in ∂f (θ )
Rm , J (θ ) = ∈ R m ×n . the limited time. Hence, the relationship is defined x
= J (θ )θ
, where x∈ ∂θ J (θ ) is the matrix of Jacobian, which represent the relationship between velocity vector of end effector and vector of joint angle, so reverse x
= J (θ )θ
can get θ
= J + (θ ) x
, where J + represent the Jacobian matrix of pseudo inverse, which is defined J + (θ ) = J (θ )T ( J (θ ) J (θ )T ) −1 . In the Inverse processing, the inverse matrix J = 0 is not solved as θ =0 or θ = j ×180 , that is called the robot manipulator is at singular posture. However, there is no guarantee that the kinematic singularities are avoided due to the usage of the inverse matrix. Hence, we use the method of fuzzy inverse kinematic mapping to solve the singular problem. Finally, this paper is organized that chapter1 gives introduction of the kinematics, and chapter 2 describes the fuzzy inverse kinematics mapping method, and then chapter 3 implements the fuzzy inverse kinematics and discusses the experimental result, and last gives a conclusions of this paper. 2. Fuzzy Inverse Kinematics The Moore-Penrose pseudo-inverse kinematic is commonly using to solve the inverse kinematic problem, but it cannot solve the singularity exists in some situations that the rank of Jacobian matrix is not full rank for the redundant robot. However, the problem becomes more complicated for the control of redundant robot in real-time. Hence, this paper proposes a fuzzy motion planning algorithm which is used to solve the inverse kinematic with singularity which was proposed by Schacherbauer and Xu in 1993[10].The Chih-Jer Lin and Chieh-Li Chen [11] implement on a transputer-based parallel processing system to solve the motion planning problem of the redundant robot with singularity by using this method. Basic concept Considering a planar robot with one link in x-y plane and the position of the end effector can be described as  x = l cos θ (3)   y = l sin θ Linearization around a specific joint θ yields the following forward kinematic Eq.3: = = =− , where (4) = = = From the Eq.4, we can observe the values of c and c are the elements of the Jacobian matrix J which is illustrated in Eq.5. − = = = (5) Hence, we can use the fuzzy rules such as PM=“positive medium”, NL=“negative large” and NS=“negative small” that a simple rule for the inverse kinematic can be formulated as Eq.6. If dx is PM and c_x is NL then dθ is NS. (6) Fuzzy Mapping Model According to the typical Fuzzy Logic Controller, we establish the Fuzzy Kinematics Mapping Controller as Fig.1

Applied Mechanics and Materials Vols. 479-480

731

Fig.1 The structure of Fuzzy Inverse Kinematic Mapping Controller. where, denotes desired path from trajectory planning, and is the element of Jacobian matrix. , is given following (Fig.2-4): The membership function of , and

Fig2.

Membership Function

Fig.4

Fig.3



Membership Function

Membership Function

The fuzzy rule table through human intuition and experience for the Fuzzy Inverse Kinematic Mapping is given in Table 1. dx

Table1 Fuzzy rule-base of Fuzzy Inverse Kinematic Mapping Controller c

NB

NM

NS

NVS

ZE

PVS

PS

PM

PB

NM

PB

PM

PS

PVS

ZE

NVS

NS

NM

NB

NS

PVB

PB

PM

PS

ZE

NS

NM

NB

NVB

ZE

ZE PS

NVB

NB

NM

NS

ZE

PS

PM

PB

PVB

PM

NB

NM

NS

NVS

ZE

PVS

PS

PM

PB

Determination of In the section, we discuss the detail how to weight the fuzzy mapping result to obtained the through the column and row weighting. The resulting is obtained by using the fuzzy mapping for each combination of and . We denoted the formulated as Eq.7. = , , , (7) where FM stands for the fuzzy mapping using the membership functions defined in Figs 3.4 and 3.5 and the fuzzy rule-base of Table 2. Because the of each combination of and is not the same, so we need to adjust the weight of and use the superposition principle obtain . the actual At first, we define the weights as Eq.8. To obtain the actual output , we have to weighting the in the direction of column and row which are defined as Eq.9

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Applied Science and Precision Engineering Innovation =

(8) = ∑ ,and Wcsum = ∑ W (9) where it represents the effects of sum in row i of each joints and similarly which is the sum in column j over all Cartesian coordinates. Hence, we can use each yield approximately and it can be formulated as Eq.10 (10) Using the contributions of each to should be weighted by some factor, such that the sum of the contributions is close to dx (Eq.11) ∑

a c dθ

dx , where a =

∑

…

=∑

…

(11)

After the row weighting, the effective joint angle change is formulated as Eq.12 On other hand, we can obtain the m form the jth joint of the robot. We can sum these values with column weights so that the final solution can be obtained which is formulated as Eq.13. = (12) =∑

, where

are chosen under the following assumption: starting from a particular The weights considering , the change in is the highest for the where the largest. To keep errors small, the averaged should be closest to those corresponding is large. Hence, the has a new defined as Eq.14. =

, and

=

(13)

and is the whose (14)

Finally, summarizing the weighting scheme, we find the results of the fuzzy mapping can be weighted through row-weighting and column weighting to obtain the effective joint change . 3. Experiments and Results In this paper, we design a robot which has redundancy degrees of freedom. The architecture system of five joints robotic manipulator is divided into host and controlled terminal called target(Fig.5). The robotic mechanism consists of the robotic manipulator and gripper. The robotic manipulator is controlled by actuators associated with reducers, which are two smart motors, two AC servo motors and one DC brushless servo motor as following Fig.6. The parameter of DH matrix gives following table2, and the forward kinematics equation is given following Eq.15.

Fig.5 System structure diagram.

Fig.6 (a) Five D.O.F. mechanism robot manipulator by solidworks. (b) The entity of redundant robotic manipulator

Applied Mechanics and Materials Vols. 479-480

deg

mm

mm

733

deg

Table2 Kinematic parameters of the redundant robot manipulaor Joint

0

1 2 3 4 5

90 0

0

65

300

0

426.98

−90

0

313.6

−263 0 0

-54.35

 x  c1a2 − s1a1 + L2 c1c2 + L3c1c23 + L4 c1s234 + L5c1c234 c5 − L5 s1s5   y  = s a + c a + L s c + L s c + L s s + L s c c + L c s  2 1 2 3 1 23 4 1 234 5 1 234 5 5 1 5   1 2 1 1  z    L1 + L2 s2 + L3 s23 − L4 c234 + L5 s234 c5

(15)

Considering the redundant robot manipulator in 3 D.O.F., we setup the change of is relative to and the coordinate of is always parallel with the base coordinate whose degree is always zero. Hence, we should only consider about the position of the end of third link of the redundant robot manipulator whose kinematic model is formulated as Eq.16 −

=

(16)

where = , = , = the equation (16), we can obtain Eq.17 =

−

Define Eq.18

− −

=

=

−

, =

0

−

=

− −

,

=

,

− −

=

− −

,

=

. Derive (17)

and denote the element of Jacobian matrix as

(18)

By Using the Fuzzy Inverse Kinematic Mapping method, we can obtain the through row and column weighting each which is derived from the fuzzy mapping relation between each and by using the Fig 2-4 and Table 1. In order to let the robot have a good path tracking results, the diagram of the combination of Fuzzy Inverse Kinematic Mapping and generalized inverse Method is setting as the Fig.7.

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Applied Science and Precision Engineering Innovation

YES

NO

θ

j

= θ oj + d θ

j

X = f (θ )

Fig.7 The block diagram of combination of Generalized Inverse and Fuzzy Inverse Kinematic Mapping

Straight Line experiment In the straight line experiments which divide into two robot kinematic model equation (15) and (16) track the assign path without obstacles in task space. At first, we use the robotic kinematic model equation (16) and generalized inverse method track a straight in x-y plane. We set the initial position of the end efector as the initial path starting point and the initial angular of each joints are =0 , = 90 and = −180 . The sampling time is 0.001s. The motion time is 10s. The robotic manipulator is move from the end position of third link 65, 263,186.62 to the position of destination 465, 663, 186.62 . The experiment results are shown in Fig 8-10.

Figure 8 (a)The posture of the center link of 3D.O.F. robotic manipulator. (b) The posture of the center link of five axes redundant robotic manipulator. -5

100

8

x 10

7 6 0

Tracking errors(mm)

The angle of each joints (degree)

50

-50

-100

-200

0

1

2

3

4

5 time(sec)

6

7

8

9

4 3 2

joint1 joint2 joint3

-150

5

1

10

0

0

1

2

3

4

5 time(sec)

6

7

8

9

10

Figure 9 (a)The response of the joint angle of 3 D.O.F. robot in straight line. (b)The tracking errors of 3D.O.F. robot in straight line.

Applied Mechanics and Materials Vols. 479-480

100

2.5

x 10

735

-5

2

0

Tracking errors(mm)

The angle of each joints (degree)

50

-50

-100

joint1 joint2 joint3 joint4 ioint5

-150

-200

0

1

2

3

4

5 time(sec)

6

7

8

9

1.5

1

0.5

0

10

0

1

2

3

4

5 time(sec)

6

7

8

9

10

Fig.10 (a) The response of the joint of five axes redundant robotic manipulator in straight line. (b) The tracking errors of five axes redundant robotic manipulator in straight line.

From the Fig.10(b), we can observe the movement of robot in the straight experiment. These tracking errors of kinematic model are approximately to zero. Hence, the robot has a good performance in tracking the assign path in experiment. Singularity path experiment In path with singular experiment, we consider about the 3-link planar robot in x-y plane and the forward kinematic model of the 3-link planar robot is as Eq.19 =

Where, =5 , =5 and =1 .We use the above robotic kinematic model equation (19) and fuzzy inverse kinematic mapping method track a path with singular in x-y = 10, = 10 and = 10 for the fuzzy plane. We set up the scaling factor such as inverse kinematic mapping in the singularity path experiment. The path has three singular point are 0,11 , 0,0 and 0, −11 .We set the initial position of the end effector as the initial path starting point and the initial angular of each joints are =0 , = 0 and = 0 . The sampling time is 0.001s. The motion time is 10s. The robotic manipulator is move from the end position of third link 0, 11 to the position of destination 0, −11 . The experiment results are shown in Fig 11. (19)

250

15 actual path motion planning path

0.7

joint1 joint2 joint3

200

Y(mm)

5

0

-5

-10

-15 -2

0.6

150

0.5 Tracking errors(mm)

The angle of each joints (degree)

10

100

50

0

2

4

6 X(mm)

8

10

12

-100

0.3

0.2

-50

0

0.4

0.1

0

1

2

3

4

5 time(sec)

6

7

8

9

10

0

0

1

2

3

4

5 time(sec)

6

7

8

9

10

Fig.11(a)The results of fuzzy inverse kinematic mapping method. (b)The response of the joint angle in singular path. (c) The tracking errors in singular path

Form the Figure 13(c), we can observe the errors of the three singular points are approximately to zero. The results prove the fuzzy inverse kinematic mapping method can robust singular point when the tracking path with singular points. Summary Generally, the generalized inverse method is widely applied to calculate the inverse kinematic problems. Although it can promise the solution with , it cannot solve the situation in singular point due to the fact that the absolute value of Jacobian matrix is approximately to zero, and the rank is not full. Hence, the fuzzy inverse method proposed by this paper replaces the generalized inverse to solve the singular problem. As the result, the fuzzy inverse kinematics mapping method can robust singular when the robot meets singular in the tracking path. On the other hand, to contrast between the fuzzy inverse kinematics mapping method and generalized inverse method, the tracking is always approximately to zero at singular point closely. Finally, the method proposed in this paper is successfully verified on the five axes robot manipulator.

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References [1]T. Yoshikawa, "Manipulability of robotic mechanism," Int. J. Robot. Res., vol. 4, no. 2, pp. 3-9, Summer 1985 [2]R.V. Mayorga and A. K. C. Wong, "A singularities avoidance method for the trajectory planning of redundant and non-redundant robot manipulators," Proc. IEEE Int. Conf. on Robotics Automat., 1987, pp. 1707-1712. [3]Y. Nakamura and H. Hanafusa, "Inverse kinematic solution with singularity robustness for the manipulator control," J. dynamic Sys. Measur. Control, 10(8), 163-171, 1986. [4]F.-T. Cheng, T.-L. Hour, Y.-Y Sun, and T.-H. Chen, "Study and resolution of singularities for a 6-DOF PUMA manipulator," IEEE Trans. Syst., Man., Cybern. B, vol. 27, pp. 332-343, Apr. 1997. [5]F.-T. Cheng, J.-S. Chen, and F.-C. Kung, "Study and Resolution of Singularities for a 7-DOF Redundant Manipulator," IEEE Transactions on Industrial Electronics, vol. 45, no. 3, pp. 469-480, June 1998. [6]Schacherbauer, A., Xu, Y. S."Fuzzy Inverse Kinematic Mapping for a Redundant Robot," Computers in Industry, vol. 22, pp.159-168, August 1993. [7]Whitney, D.E., "Resolved motion rate control of manipulators and human prostheses," IEEE Trans., Man-Machine Systems, MMS-10, pp.45-53, 1969. [8]Baillieul, J., Hollerbach, J.H.. and Brockett, R., 1984 December 12-14, “Programming and control of kinematically redundant manipulators,” 23rd IEEE Conf. on Decision and Control, LasVegas, Nevada. [9]A. egeois “Automatic supervisory control of the configuration and behavior of multibody mechanism,” IEEE Trans. Syst. ,Man, Cyern., vol.SMC-7. No.12, pp.868-871, Dec.1997 [10]Schacherbauer, A., Xu, Y.S. “Fuzzy Inverse Kinematics Mapping for a Redundant Robot,” Computers in Industry, vol.22, pp.159-168, August 1993. [11]Chih-Jer Lin and Chieh-Li Chen, “Motion Planning of Redundant Robots with Singularities Using Transputer Based Fuzzy Inverse Kinematics Method, “ICIC, vol. 4114, pp. 140-145

Applied Mechanics and Materials Vols. 479-480 (2014) pp 737-741 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.737

An Output based Adaptive Iterative Learning Control with Particle Swarm Optimization for Robotic Systems Ying-Chung Wang 1, a, Chiang-Ju Chien 2,b , Chi-Nan Chuang 3,c 1

Department of Electronic Engineering, Huafan University, New Taipei City, 223, Taiwan

2

Department of Electronic Engineering, Huafan University, New Taipei City, 223, Taiwan

3

Department of Electronic Engineering, Huafan University, New Taipei City, 223, Taiwan a

[email protected], [email protected], [email protected]

Keywords: Robotic systems, AILC, a sliding window of measurements, PSO algorithm.

Abstract. We consider an output based adaptive iterative learning control (AILC) for robotic systems with repetitive tasks in this paper. Since the joint velocities are not measurable, a sliding window of measurements and an averaging filter approach are used to design the AILC. Besides, the particle swarm optimization (PSO) is used to adjust the learning gains in the learning process to improve the learning performance. Finally, a Lyapunov like analysis is applied to show that the norm of output tracking error will asymptotically converge to a tunable residual set as iteration goes to infinity. Introduction In recent years, iterative learning control (ILC) became a more effective control approach when robotic systems performing a repeated tracking control task. The acceleration error of joint variable is used to construct the D-type ILC [1] for robotic systems. Unfortunately, a simple Lipschitz continuous condition on the plant's nonlinearity is necessary. In addition, the acceleration measurement is the major disadvantage of D-type ILC. On the other hand, the P-type ILC [2] using velocity feedback to design the controller, the requirement of acceleration measurement is removed. But more restrictive assumptions and more complicated control structures are needed for technical analysis. Without using the restrict Lipschitz condition on the plant's nonlinearity, the Lyapunov-like approach is applied to analyze the stability and convergence. However, the design of the AILC still require that the joint velocities are measurable. In this paper, we propose an output based AILC for robotic systems with repetitive tasks. Since the joint velocities are not measurable, a sliding window of measurements and an averaging filter approach are introduced to design the AILC. Besides, the PSO algorithm [3] is used to adjust the learning gains in the learning process to improve the learning performance. In addition, we apply a Lyapunov like analysis to show that the norm of output tracking error will asymptotically converge to a tunable residual set as iteration goes to infinity. Finally, a simulation example is used to verify stability, convergence and the control performance of the proposed AILC systems Problem Formulation In this paper, we consider an uncertain robotic system with n rigid bodies which can perform a given task repeatedly over a finite time interval [0, T ] as follows: D(q j )q

j + B(q j , q
j )q
j + F (q j , q
j ) = u j (1) where j ∈ Z + denotes the index of iteration number and t ∈ [0, T ] denotes the time index. We note that the time index t will be omitted unless otherwise specified. The signals q j , q
j , q

j ∈ R n are respectively the generalized joint position, joint velocity and joint acceleration vectors. D(q j ) ∈ R n×n is the inertia matrix, B(q j , q
j ) ∈ R n× n is the centripetal plus Coriolis force vector, F (q j , q
j ) ∈ R n is the gravitational plus frictional forces and u j ∈ R n is the joint torque vector. It is noted the inertia

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matrix D(q j ) is assumed to be positive definite and bounded for all t ∈ [0, T ] and iteration j ≥ 1 as 0 < m1I ≤ D(q j )) ≤ m2 I where m1 , m2 > 0 and I is an n × n identity matrix. Since the inverse of inertia matrix exists for all joint variables, the dynamis of the robotic system as follows q

j = − D −1 (q j )[ B (q j , q
j ))q
j + F (q j , q
j ) = u j (2) j j −1 j j j j j j n j −1 j n× n Let f (q , q
) = − D (q )[ B (q ), q
)q
+ F (q , q
)] ∈ R and b(q ) = D (q ) ∈ R . If we choose the

output jΤ

variable

jΤ Τ 2

jΤ

jΤ Τ

as jΤ

y j = q j ∈ Rn

and

the

state

variable

as

jΤ Τ

X j = [ x1 , x ] = [ y , y
] = [q , q
] ∈ R 2 n , then we have the following state-space form :

X
j = AX j + B[ f ( X j ) + b( X j )u j ] y j = CΤ X j

(3)

where

0 I  0  A= , B =  , C Τ = [I 0]  0 0  I  Here 0 < b( X j ) ≤ m1I . In this paper, we assume that only system output y j is measurable for controller design. Let the desired state trajectory be defined as X d = [ ydΤ , y
dΤ ]Τ . Now, given a specified desired output trajectory y d , t ∈ [0, T ] and a possible initial resetting error yd (0) ≠ y j (0) for all j ≥ 1 , the control objective for the robotic systems doing a repeatable task is to force the system output y j to follow y d as close as possible.

Derivations of controller and error model At first, let the output error e j = y d − y j , then we derive the time derivative of e j as follows: e

j =
y
d − f ( X j ) − b( X j )u j = − K cΤ E j +
y
d + K cΤ E j − f ( X j ) − b( X j )u j

(4)

where K c = [k2c I , k1c I ]T ∈ R 2 n× n is the feedback gain matrix such that the characteristic polynominal Τ

Τ

of Ac = A − BK cT is Hurwitz and E j = X d − X j = [e j , e
j ]Τ ∈ R 2 n is the state tracking error vector. The tracking error dynamics will satisfy E
j = Ac E j + B[− f ( X j ) − b( X j )u j +
y
d + K cΤ E j ] (5) e j = CΤE j If f ( X j ) and b( X j ) are exactly known and state vector X j is measurable, we can use the following certainty equivalent controller u*j = b −1 ( X j )[− f ( X j ) +
y
d (t ) + K cΤ E j ] (6) j j j j such that E
= A E . This implies E = 0 for all t ∈ [0, T ] and j ≥ 1 if E (0) = 0 . However, the c

ideal certainty equivalent controller (6) can not be achieved because f ( X j ) and b( X j ) are assumed to be unknown and X j is not available for measurement. To solve the design problem, we add and subtract the term b( X j )u*j in (5) such that E
j = Ac E j + B[b( X j )u*j − u j + (1 − b( X j ))u j )] (7) j Τ j e =C E Now based on the results given in [4], we know that the smooth nonlinear function b( X j )u*j can be Τ

approximated by a typical FNN (for example the FNN in [5]) W j O ( 3) (η j ) which is constructed by the silding window of measurement η j as the network input. Here O (3) (η j ) ∈ R M is the basis function of the FNN with M being the number of rule nodes, and W j ∈ R M × n is the weight matrix of

Applied Mechanics and Materials Vols. 479-480

739

the output layer. According to the universal approximation theorem [5] and Lemma 1 in [4], there will exist an optimal weight matrix W * such that b( X j )u*j ( X j ) = W *ΤO (3) (η j ) + δ j , where δ j is the approximation error satisfying δ j (t ) ≤ δ * in a certain compact set. Theefore, (7) can be rewritten as E
j = Ac E j + B[W *Τ O (3) (η j ) + δ j − u j + (1 − b( X j ))u j ]

(8) e j = CΤE j The explicit expression of e j in (8) in time domain with a filtered version can be rewritten as follows e j = H ( s )[W *Τ O ( 3) (η j ) + δ j − u j + (1 − b( X j ))u j ]

=

 1  *Τ 1 1 W [O (3) (η j )] − [u j ] + δ mj , δ mj =  ( s )  L( s ) L( s ) 

where H ( s ) = C T ( sI − Ac ) −1 B ≡

1 ( s ) L( s)

I=

1 ( s +λ ) L ( s )

1 L(s)

[(1 − b( X j )u j + δ j ]

(9)

I and L(s ) being any Hurwitz polynomial of the

first order. According to the output tracking error model (9), we define an augmented signal as  1  j 1 y aj = v − [u j ], y aj (0) = 0 (10)  ( s)  L( s)  where v j is an auxiliary input to be designed later. Then, design an auxiliary error signal as eaj = e j − y aj , eaj (0) = e j (0) − y aj (0) = e j (0) = ε j Substituting (9) and (10) into (11), we can find an auxiliary error model as  1  *Τ 1 eaj = [O (3) (η j )] − v j + δ mj  W ( s)  L( s) 

(11)

(12)

Define normalization signal m j [6] as follows:

mj =

δ2 δ 1 + u j , m j ( 0) > 2 s + δ1 δ1

[

]

(13)

where δ1, δ 2 > 0 and δ1 < δ * . Here δ * is the is the least positive contant such that 1 / L ( s − δ * ) is a stable system. In practical, δ 1 can be chosen as small as possible. According to the definition of δ mj in (9) and by using Lemma 3.1 in [6], we can prove that j j * j * * * m  δ m (t ) ≤ θ1 m + θ 2 = [θ1 , θ 2 ]  ≡ θ *ΤY j , θ1* , θ 2* > 0 (14) 1  The time-domain state space representation of (12) is rewritten as Τ 1 e
aj = −λeaj + W * [O (3) (η j )] − v j + δ mj (15) L( s) To overcome the uncertainty from initial output tracking error, a new signal eφj is introduced as:

 ej  eφj = eaj − φ j sat  aj , φ j = ε j e − λt , λ > 0 φ 

where sat

( ) is defined as the saturation function in [6] and φ e aj ( t )

φ j (t )

j

(16)

is the width of boundary layer. Note

that φ j is designed to decrease along time axis with the initial condition chosen as φ j (0) = ε j for jth iteration, 0 < ε j e − λT ≤ φ j (t ) ≤ ε j , ∀t ∈ [0, T ], j ≥ 1 . Using a similar technique in [6], let us differentiate 12 (eφj ) 2 with respective to time t :

 1d j 2 Τ Τ 1 (eφ ) ≤ −λ (eφj ) 2 + eφj W * [O (3) (η j )] − v j + δ mj  2 dt L( s )   Now based on the error model (17), we design u j and v j as follows

(17)

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Applied Science and Precision Engineering Innovation

uj = vj =W j

Τ

L( s ) vj F n −1 (τs )

[ ]

(18)

1 [O (3) (η j )] + sat L( s )

( )θ e aj

φ

jΤ

Τ

Y j + eφjY j Y j

j

(19)

where W j is the weight matrix of the FNN and θ j is control parameter vector . Here, 1 = (τs +11) 2 with τ > 0 being a small constant that is referred to as an averaging filter. If we define the F (τs ) ~ ~ parameter error as W j = W j − W * and θ j = θ j − θ * and substitute (19) into (17), we have Τ ~ Τ Τ 1 d j 2 1 ~ Τ (eφ ) ≤ −λ (eφj ) 2 − eφj W j [O (3) (η j )] − eφj θ j Y j − (eφj ) 2 Y j Y j (20) 2 dt L( s) Finally, a set of adaptive laws is necessary and given as follows, W j = W pj −1 + β j eφj

Τ

1 L(s)

[O (3) (η j )], W pj −1 = proj (W

j −1

)

θ j = θ pj −1 + β j eφj Y j , θ pj −1 = proj (θ j −1 )

(21) (22)

where proj denotes projection mechanism [5], β j is the adaptive learning gains. Here, we define the upper and lower bounds of β j as β max and β min , i.e., β min ≤ β j ≤ β max .

4. ANALYSIS OF STABILITY AND CONVERGENCE 1 Fact 1: Choose a Lyapunov-like function Vaj = (eφj ) 2 , then we can use a similar argument as in [6] 2 and the proof given in Lemma 1 of [6] to show that eφ1 ,W 1 ,θ 1 , v1 , u1 ∈ L∞e [0, T ] . Fact 2: Define the positive functions V j (T ) and V pj (T ) as V j (T ) =

∫

T

0

1 ~ jΤ ~ j  ~ jΤ ~ j 1 j  2 tr{W W } + 2 θ θ  dt , V p (T ) =  

∫

T

0

1 ~ jΤ ~ j  ~ jΤ ~ j 1  2 tr{W p W p } + 2 θ p θ p  dt  

(23)

T

Using a similar technique in [6], we can further show that lim ∫ (eφj ) 2 dt = 0 and lim (eφj (T ))2 = 0 . j →∞ 0

Lemma 1: The AILC ensures that all i.e., eφj , eaj , yaj , e j ,η j , E j ,W j ,θ j , v j , u j ∈ L∞e [0, T ] .

the

internal

j →∞

signals

are

bounded,

Proof : By using a similar technique analysis in Fact 1 and [6], the result of Lemma 1 is achieved.. Theorem 1: The AILC guarantee the tracking performance and system stability as follows: (T1) lim (eφj ) 2 = 0 , t ∈ [0, T ] (T2) lim eaj ≤ e − λtε ∞ , t ∈ [0, T ] (T3) lim e j ≤ e − λt ε ∞ + τk , t ∈ [0, T ] j →∞

j→∞

j →∞

Proof : Based on a similar technique in [6], (T1), (T2) and (T3) are achieved. To further improve the learning performance, the PSO algorithm [6] is adopted for tuning the adaptive learning gains. Due to the page limitation, the PSO procedure is briefly described as follows: Step 1. Initialization. Step 2. Determination of Fitness function. Step 3. Selection and Memorization. Step 4. Modification of Velocity and Position. Step 5. Stopping Rule. Simulation Example In this example, we apply the AILC to robotic system [6]

 D11j  j  D21

D12j  q

1j  − hq
2j  + D22j  q

2j   hq
1j

− h(q
1j + q
2j ) q
1j  u1j    j= j 0  q
2  u 2 

Applied Mechanics and Materials Vols. 479-480

741

The control objective is to let q j = [q1j , q2j ]Τ tracking the desired trajectory qd = [ q d 1 , q d 2 ]T = [sin(t ), cos(t )]T over a finite time interval [0,15] . In Fig. 1, we show the better learning performance at the 5th trials. -2

0

10

10

-10

(b) 10

(a) -3

10

1 (c)

0.5

2

4

200

1 (d)

0

5

10

0.5 (f)

0

5

10

2 (h)

0

5

10

50 (j)

0

5

10

15

3

4

5

0

5

10

15

0

5

10

15

0

5

10

15

0

5

10

15

0 -2

15

2

0 -0.5

15

1

0 -1

15

0 -200

10

5

0 -2

(i)

3

0 -0.5

(g)

2

0 -1

(e)

-20

1

0 -50

Fig. 1. (a) supt∈[ 0,15] | eφj1 | versus j ；(b) supt∈[ 0,15] | eφj2 | versus j ；(c) e a51 (solid line) and φ 5 (dotted lines) versus time t ；(d) ea52 (solid line) and φ 5 (dotted lines) versus time t ；(e) e15 versus time t ； (f) e 25 versus time t；(g) q15 (solid line) and q d1 (dotted line) versus time t；(h) q 25 (solid line) and q d 2 (dotted line)；(i) u15 versus time t ；(j) u 25 versus time t

Conclusions Since only joint position is measurable, a sliding window of measurements and an averaging filter approach are used to design the AILC for compensation of the unknown certainty equivalent controller. Since the optimal control parameters are unknown, all the parameters are tuned by adaptive law with PSO. Finally, we show that all adjustable parameters and the internal signals remain bounded and the output tracking error asymptotically converge to a tunable residual set as the iteration number goes to infinity.

Acknowledge This work is supported 101-2221-E-211-0008.

by National

Science

Council,

R.O.C.,

under

Grant

NSC

References [1] T.J. Jang, C.H. Choi and H.S. Ahn, Iterative learning control in feedback systems, Automatica, Vol. 31 (1995), No. 2, pp. 243-248. [2] B.H. Park, T.Y. Kuc and J.S. Lee, Adaptive learning of uncertain robotic systems, Int. J. Contr., Vol. 65 (1996), No. 5, pp. 725-744. [3] A. I. Selvakumar and K. Thanushkodi, A new particle swarm optimization solution to nonconvex economic dispatch problems, IEEE Trans. Power Systems, Vol. 22 (2007), No. 1, pp. 42-51. [4] Anthony J. Calise, Naira Hovakimyan and Moshe Idan, Adaptive output feedback control of nonlinear systems using neural networks, Automatica, Vol. 37 (2001), pp. 1201–1211. [5] Y. C. Wang, C. J. Chien, and D. T. Lee, A hybrid adaptive scheme of fuzzy-neural iterative learning controller for nonlinear dynamic systems, International Journal of Fuzzy Systems, Vol. 7 (2005), No. 4, pp. 147-157. [6] Y.-C. Wang and C.-J. Chien. An observer based adaptive iterative learning control for robotic systems,. 2011 IEEE International Conference on Fuzzy Systems, (2011).

Applied Mechanics and Materials Vols. 479-480 (2014) pp 742-746 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.742

Distributed Control Intelligent Robotic Gripper Shiuh-Jer Huang1,a, Wei-Han Chang1,b, Jui-Yiao Su2,c and Yan-Chen Liu2,d 1,

Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, 106, TAIWAN 2

Industrial Technology Research Institute, Chutung, Hsinchu, 31040, Taiwan

1

[email protected]; [email protected]; [email protected]; 4 [email protected]

Keywords: intelligent gripper, force control, anti-slip scheme and fuzzy sliding mode control.

Abstract. An intelligent gripper is designed with embedded distributed control structure for overcoming the uncertainty of grasped object mass and soft/hard features. An efficient model-free intelligent fuzzy sliding mode control strategy is employed to design the position and force controllers of gripper, respectively. Experimental results of pick-and-place soft and hard objects with grasping force auto-tuning and anti-slip control strategy are shown by pictures to verify this distributed system performance. The position and force tracking errors are less than 1 mm and 0.1 N, respectively. Introduction During robotic pick-and-place operation, the main function of gripper is to apply appropriate force for grasping and lifting an object to avoid the risk of object slippage and any possible object damage. For grasping and manipulating fragile or slippery objects, the slip onset determination between robot gripper and grasped object is an essential procedure for object dexterous safe handling [1]. This slip symptom is also an important information for determining the appropriate grasping force to prevent unexpected slippage or object crushing. This end-effector grasping force monitoring function is an important feature for establishing robotic compliance to execute further intelligent grasping, assembly and human-interaction applications. However, multi-degree force control of achieving desired robotic compliance has been known to be a complicated control problem. They also need an expensive multi-degree torque/force sensor. Actually, many robotic operations do not need too complicate hybrid motion control structure. They only need to monitor the grasping force at specified positions instead of fully position/force hybrid motion control. Hence, robotic end-effector motion control and gripper force control can be designed based on its own control kernel individually and operated in sequence with a switching signal. For stable grasping and manipulating object, the gripper controller should have quickly respond capability to prevent object falling when slip occurs. If the slip onset can be predicted before it actually occurs, the gripper controller can be worked more efficiently and robustly. Generally, the concept of friction cone has been used for slip prediction, where the static/dynamic friction coefficient is used as a threshold. When the ratio between the friction and normal force is less than this threshold, grasping contact is considered stable [2]. However, this ratio is a function of the dynamic interaction between fingers and objects, it varies with the changes of acceleration and disturbing force applied on the objects [3]. Some fingertip sensors [4] and Polyvivylidene fluoride (PVDF) sensor [5] were developed to detect the applied normal force and slip. Neuro-fuzzy controller was employed to manipulate intelligent gripper [6]. Here, an intelligent distributed gripper system is designed with gripper opening and grasping force monitoring alternately for safe and stable grasping objects with obvious hardness difference. The grasping force control error and robot position error were monitored directly by using an intelligent fuzzy sliding mode controller (FSMC). This intelligent gripper will be installed on a 5 DOF robot. During pick-and-place operation, the 5 DOF Mitsubishi robot is manipulated to a specified position by FPGA based control system first. Then the intelligent gripper is activated by a signal from FPGA to estimate the object hardness and specify the gripper grasping force based on Arduino embedded control system and FSMC force controller.

Applied Mechanics and Materials Vols. 479-480

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Intelligent Gripper System Design Gripper is the object grasping device installed in robotic end-effector. Its motion DOF and complexness depend on the working functions specification. Although, two fingers or parallel jaw gripper has function limitation, it is easy to design and implement for most of the industrial pick-and-place automation operations. Here, an embedded control parallel jaws gripper is designed for objects with obvious hardness difference pick-and-place operation. The embedded gripper system includes two gripping jaw pieces, force sensitive resistive (FSR) sensor, one DC servo motor driving mechanism with Arduino control kernel for gripper opening and grasping force monitoring. Arduino Nano 328 is chosen as the embedded control kernel for driving the DC servo motor and monitoring the contact force of FSR force sensor installed in gripper jaw. The intelligent gripper system structure is shown in Fig. 1

Fig. 1 The embedded gripper control system structure. Since, the FSR voltage output is not linear with respect to applied force, an off-line calibration should be done to find the mapping function between measured output voltage and contact force. After 30 samples experiments with standard weight, a transfer function had been found based on Matlab curve fitting tool box. F = 3 .99V 7 − 51 . 62V 6 + 261 . 83V 5 − 654 .42V 4 + 835 . 6V 3 − 503 . 6V 2 + 138 . 3V + 2 . 13

(1)

Gripper Intelligent Judging Strategy For intelligent pick-and-place operation, the gripper should have capability to estimate the object hardness for setting suitable grasping force to safe/stable operation, and prevent slippage on-line corresponding to object characteristic diversity. Hence, the following algorithms are developed and implemented on the gripper control kernel. (A) Object hardness estimation and grasping force selection When the gripper contact force reaches 0.1 N, the controller is switched to position control for manipulating the gripper backward 0.5 mm and recorded the object/gripper center position. Then, the gripper is closed step by step with 5 counter pulses (0.1mm) interval change and the FSR contact force is measured simultaneously. The object stiffness can be roughly estimated from measured contact force variation divide by the position step change based on Hook’s law. After 10 times step change experiments, the object hardness can be roughly estimated as the average of those calculated values. The object hardness estimation flow chart is plotted in Fig. 2(a). Based on experimental results, Fig. 3, the estimated spring constant average values for soft pad, toothpaste and USB case are 20.25, 3.44, and 54.5 N/mm, respectively. Then, the appropriate grasping force command can be specified for certain pick up objects candidate based on their hardness estimation values. (B) Slip detection and anti-slip control strategy Since the gripper jaws have FSR contact force sensor only without slip sensor, the object slip phenomena should be detected from the normal grasping force variation. When 4 N force is set for gripper to grasp a volumetric cylinder and marbles are thrown into cylinder one-by-one. The FSR measuring force record is shown in Fig. 5. The volumetric cylinder has about 12 mm downward slippage. It can be observed that the contact force has obvious high frequency variation with respect to volumetric cylinder slippage. Hence, the slip phenomena can be detected form the normal contact

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Applied Science and Precision Engineering Innovation

force variation. When contact force variation is larger than the maximum change rate of force control for three continue time steps, it is judged as slip occurring. Then the anti-slip control strategy is activated to change the grasping force specification with a suitable incremental value, i.e. 0.5N. The anti-slip control strategy flow chart is shown in Fig. 2(b). After introducing the anti-slip scheme, the gripper grasping volumetric cylinder does not have obvious slipping down phenomena during continuous drawing in marbles.

Fig. 2 Control flow chart of (a) object stiffness estimation and (b) anti-slip control.

Fig. 3 Objects stiffness on-line estimation results. Model-free Intelligent control Since, it is difficult to establish an appropriate dynamic model for the model based controller design, especially for the onboard microprocessor, the sliding mode concept is combined with fuzzy control strategy to design a model-free fuzzy sliding mode controller (FSMC) for intelligent gripper stable grasping control. Based on the Lyapunov theorem, if a control input u can be selected to satisfy the sliding surface reaching condition s ⋅ s
< 0 , the control system will converge to origin of the phase plane. Then, the control input u can be designed in an attempt to satisfy the inequality s ⋅ s
< 0 based on this qualitative analysis. The relating theory about the convergence and stability of the adaptation process for the minimization of s
s can be found in ref. [7]. This approach is a novel gain scheduling 1D fuzzy sliding mode control structure with 11 fuzzy rules only. Experimental Results For evaluating this intelligent gripper dynamic control performance, it should be installed in robotic manipulator wrist for practical implementation experiments. The retrofitted robot with Atera Stratix system-on-a-programmable-chip (SOPC) control structure was chosen as test plant. This distributed control structure can monitor the end-effector position and grasping force individually in sequence. The sampling frequency in these experiments was 100 Hz.

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745

Case (A): Gripper force control for grasping object with different stiffness The gripper is assigned to grasp and pick up banana fruit, toothpaste with opened cap, and USB case. The controller should have strategy to estimate object hardness and adjust/monitor the grasping force automatically to prevent damage the objects. The appropriate grasping force can be found based on the contact force/gripper opening change relationship and an intelligent selection program. The experimental results of contact force monitoring are shown in Fig. 4 (a), (b) and (c), respectively. It can be observed that this FSMC controller spends less than 0.1sec to settle down the specified contact force with steady state error less than 0.1 N for grasping soft frangible objects and hard object with appropriate grasping force.

Fig. 4. The grasping force control monitoring for (a) sponge cake, (b) toothpaste and (c) USB case.

Fig 5 FSR measuring force record.

Case (B): Intelligent gripper and robot end-effector integration for objects pick and place, and anti-slip stable operations The robot end-effector is planned to move from the basis coordinate origin (0, 0, 0) to 2 different Cartesian space coordinates for pricking and placing soft banana fruit with on-line intelligent grasping scheme. 9 pictures of these sequent operations are shown in Fig. 6. Secondly, the robot end-effector is planned to move from the basis coordinate origin (0, 0, 0) to 4 different positions for pricking and placing 200g weigh and foam rubber. During this experiment, both on-line stiffness estimation and anti-slip control strategies are integrated to successfully complete this job. 8 pictures of these objects stable pick-and-place sequent operations are shown in Fig. 7. The force control record of pick-and-place 200g weight is shown in Fig. 8. It can be observed that the controller is judging the object stiffness during 0.2 ~0.8sec and then specified a grasping force 4 N to pick up it. When the robot arm starts to move, the object slip phenomenon is detected at time 1.3 sec based on high frequency oscillation of contact force. Then, the control kernel of this intelligent gripper increases the grasping force setting with 0.5 N step change gradually. Finally, the stable grasping force 6N is reached for further dynamic handling without slippage.

Conclusions An embedded intelligent gripper is designed with Arduino control kernel for robotic intelligent gripper positioning and grasping force control, respectively. An actuating signal is employed to switch the control kernels in sequence for monitoring the end-effector position and gripper grasping force individually. 1D model-free fuzzy sliding mode controller was designed for each joint to execute intelligent end-effector motion control and intelligent gripper stiffness estimation and anti-slip force control, respectively. The experimental results show that this intelligent gripper can dexterous pick-and-place various objects with stiffness estimation to specify appropriate grasping force and the grasping force control error is less than 0.1 N. In addition, the anti-slip control strategy can adjust the grasping force on-line to avoid the object slide or falling during dynamic operation.

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Acknowledgements The authors would like to thank Industrial Technology Research Institute for part of the financial support of this research.

Fig. 6 Sequential pictures of intelligent gripper pick-and-place soft banana with stiffness estimation and grasp force selection.

Fig. 7 Sequential pictures of intelligent gripper pick-and-place hard weight and soft sponge with stiffness estimation and anti-slip control.

Fig. 8 Force control record of pick-and-place 200g weight with anti-slip scheme.

References [1] A. Bicchi, IEEE Transactions on Robotics and automation, Vol. 16, (2000). p. 652. [2] X. Song, H. Liu., J. Bimbo. and L. D. Seneviratne, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, (IROS 2012), p. 4511. [3] de Wit C. Canudas d, H. Olsson, K. Astrom and P. KLischinsky, IEEE Trans. On Automatic Control, Vol. 40, (1995), p. 419. [4] W. Friedrich, P. Lim and H. Nicholls, Proceedings on the 2000 IEEE Int. Conf. on Robotics and Automation, (2000), p. 1982. [5] B. Choi., H. Choi and S. Kang, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, (IROS 2005), p. 2638. [6] A. M. Zaki, A. M. Soliman, O. A. Mahgoub and A. M. El-Shafei, Proceedings of the 2010 Int. Conf. on Modelling, Identification and Control, (2010), p. 710. [7] G. C. Hwang and S. C. Lin, Fuzzy Sets Systems, Vol. 48, (1992) p.279.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 747-752 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.747

A Laboratory-Based Smart Grid Sensor Network Testbed Long-Fung Cheung, King-Shan Lui, Kenneth Kin-Yip Wong, Wing-Kin Lee, Philip Wing-Tat Ponga Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong a

[email protected]

Keywords: Sensor Network, Smart Grid, Testbed

Abstract. A laboratory-based sensor network testbed for Smart Grid was developed at the Smart Grid and High Power System Laboratory of The University of Hong Kong. The setup is featured by a scaled transmission-line model, visualization of sensor measurement, optical communication network, and integration with global positioning system (GPS). The transmission-line model consists of a power cable and towers in which various types of sensors including magnetic sensors, infrared sensors, strain gauges, and accelerometers are installed to monitor the condition of the transmission line and the transmission towers. Magnetic sensors and infrared sensor are employed as advanced sensors which can provide more accurate and comprehensive information of the transmission line. The sensor data is transferred to the computer for analysis and visualization. Graphical user interface (GUI) was designed in LabVIEW to integrate the data acquisition and display of measurement results including cable position, inclination and vibration of the tower, frequency and waveform of the cable current. The host computer also forms an IP network with five remote computers, via optical fiber and optical interface card, for testing various communication protocols. The topology and connectivity of the network is graphically displayed. The sensor network is integrated with GPS and can perform synchronized measurement with the GPS timing. This sensor network testbed provides a platform for the implementation testing, experimentation, and feasibility evaluation of new sensor applications under test in Smart Grid. Introduction Smart Grid is an idea of modernizing the power grids to overcome the existing limitations, shortcomings, challenges of the power systems. Due to environmental issues, the expansion of transmission grid has been stagnant for decades which largely constrain the delivery of renewable energy. The ever-interesting cost of fossil fuel is pushing the usage of alternative energy. More and more customers voice out the need of transparency and liberty in the power market, high quality/price ratio electricity, and freedom to interact with the grid. The existing infrastructure is aging while the load demand keeps on growing. To prevent possible decline in reliability, the grid needs to equip with the latest technology such as wide-area measurement and self-healing capability [1]. As a result, many countries are pushing forward the Smart Grid. Slootweg et. al. [2] defines Smart Grid as a common denominator for a wide range of developments that make medium and low voltage grids more intelligent and flexible than they are nowadays. The development of Smart Grid can improve utilization of renewable energy, promote interactive power market, and enhance compatibility and reliability. Sensors play an important role to make the grid smarter [3]. Smart Grid will need information more than simply voltage and current. A variety of sensors will be used to detect environment around the facilities and condition of the infrastructure [4]. Advanced sensors are necessary because of their superior sensitivity, accuracy, and compatibility. Since developmental testing may present interruption or reliability threat to a live power system, a testbed for experimenting various kinds of sensing technologies and communication protocols in Smart Grid is needed for testing in an isolated fashion. Gang et al. [5] designed a Smart Grid testbed to enable the research community to analyze their designs and protocols in lab environment. Qiu et al. [6] built a real- time cognitive radio network for Smart Grid. Nevertheless, their testbeds do not provide a real transmission model for experiments. To the best of our knowledge, we are the first to develop a testbed for studying transmission line in

748

Applied Science and Precision Engineering Innovation TABLE I. SENSOR RESPONSES IN VARIOUS EVENTS Strain Sensor

Accelerometer (Vibration)

Accelerometer (Tilting)

Temperature Sensor

Magnetic Sensor

Normal

Normal

Normal

Normal

Normal

Normal

Sagging

Increase

Normal

Normal

Increase

Galloping

Increase

Low frequency, High amplitude

Oscillating

Normal

Explosion

Increase

Sharp Increase

Oscillating

Temporary Increase

Tower Collapse

Sharp Increase, Then zero

No Information

Appreciable tilt 0-90 degree

No Information

Electrical Fault

No Information

No Information

No Information

No Information

Change magnetic waveform distribution

in field or

smart grid. Our test bed is designed to perform sensor testing, concept verification, simulation on sensor network, intra system communication, and wide area synchronization. Our design features visualization, multi sensor network, use of advanced sensors, networking control, and GPS monitoring. The sensor network employs various types of sensors to provide multi-type information to the host computer. The uses of optical communication and IP network enhance compatibility and scalability of the setup. The control system processes the sensor data to visualize the transmission line infrastructure and display complicated charts in real time. GPS is deployed to perform synchronization. All components of this testbed are commercially available, and researcher can build their own setup easily. Testbed Features A. Platform with Multiple Advanced Sensors A complete sensing solution for all the transmission system conditions requires multiple types of sensors [7]. Table I shows the responses of accelerometer, temperature sensor, strain gauge, and magnetic sensor in sagging, tilting, explosion, tower collapse and electric fault. Different type of sensor is sensitive to different kinds of scenarios. For example, electrical fault can only be sensed by magnetic field sensor while tower collapse can be sensed by both strain sensor and accelerometer. Therefore, a sensor network with multiple types of sensors is essential for comprehensive monitoring of the transmission line. Our setup includes a multi-sensor network consisting of strain gauges, accelerometers, infrared sensors, and magnetic sensors. The advanced magnetic sensing technology is adopted because a magnetic sensor is sensitive to all types of abnormal events. As shown in Table I, the magnetic field waveform and distribution are sensitive to sagging, galloping, explosion, collapse, and electrical fault. Thus the magnetic field can signify these abnormal events. Due to its extensive sensing ability, it can be used as a universal sensor. In addition, the magnetic field measured by the magnetic sensor can be used to find out the cable position and perform power quality analysis which is difficult to achieve by conventional sensors. The advanced temperature sensing technology is also applied in the setup. The infrared sensor can measure the cable temperature without physical contact with the high-voltage cable, which makes installation and maintenance easier and safer. Furthermore, it is equipped with a laser tracking device to measure temperature of a galloping cable. B. Visualization of Measurement Information Visualization of the measurement information is a key component of the setup because it conveys abstract information in intuitive ways and thus enables users to perceive and understand large amount of information instantaneously [8]. The monitoring part of our setup is highly visualized in order to enhance situational awareness and reduce cognitive demand on the operators. The graphical user interface (GUI) displays the measurement and analysis results of the electrical and spatial information of the transmission line in the forms of images, diagrams, and charts. The magnetic field waveform is presented in graphs while the power quality analysis calculated by performing Fourier Transform on the magnetic waveform is presented in a spectrum.

Applied Mechanics and Materials Vols. 479-480

Fig. 2 Laboratory setup of the testbed: transmission towers, transmission line, and sensors are indicated by red arrows.

749

Fig. 1 Schematic diagram of the setup.

C. Integration with Global Positioning System (GPS) Our setup is integrated with GPS for providing position and time. As a result, the synchronization accuracy of the sensor network can be boosted from 1 millisecond up to 1 microsecond which is 1000 times better than the current standard [9]. The time provided by the GPS enables time synchronization for wide area measurement. The geographical coordinates obtained from the GPS is fed to the Google Earth to provide satellite aerial map of the sensor network location in the GUI. Hardware Architecture A. Transmission Line, Sensors, and Electrical System The laboratory setup of the testbed is established in the Smart Grid and High Power System Laboratory at the University of Hong Kong (Fig. 1). Figure 2 illustrates the schematic diagram of the transmission line model and the associated sensors. The setup consists of a power transmission line suspended by the two towers and connected to a power source. The sensor network includes several types of sensors: magnetic sensors, infrared sensors, strain gauges, and accelerometers. Each end of the transmission line is installed with one set of strain gauges and one accelerometer. Another accelerometer is mounted on each tower. The transmission line is 3 meters long. The height of each tower is adjustable. In normal situation, the degree of sagging at the mid-span of the transmission line is 0.08 m measuring from the horizontal level of the tops of the towers. The cross section of the transmission line is 35mm2. Two magnetic sensors are placed on each side of the transmission line at the mid-span on the ground level. The vertical and horizontal distance between each magnetic sensor and the cable are 0.35m and 0.6m respectively. An infrared sensor is placed 0.15m horizontally from the transmission line. Figure 2 shows the dimension of the single phase system. The power source used is FOSTER PCITS 2000/2. The current supplied is 50 Hz sine wave , either 2000A at 0 – 3V or 1000A at 0 – 6V, with current resolution 1A. B. Sensor Data Transmission and Network Connection A data-acquisition (DAQ) card (National Instruments NI USB 6211 M) establishes a link between the host computer (monitoring station) and the sensors (Fig. 3). It collects the analog data from the sensors, converts them into digital form, and sends them via USB hub to the host computer which plays the role of a monitoring station that analyzes the information from sensors and monitor the transmission line. There are 16 analog input channels with +/-10V voltage range (16 bits) with high sample rate of 250k sample per second. In order to provide a platform for testing and implementing communication protocols, there are five computers simulating other monitoring stations and they are connected with the actual monitoring station by optical communication links. Fig. 4 shows the schematic diagram of this monitoring station network. Between the host and each of other five monitoring stations, there are optical fibers and optical interface cards (OLYCOM OM910-FE/S25).

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The optical interface cards convert digital signals into optical signals in order to be conveyed by the optical fibers. These interface cards are capable of operating at 100Mbps, providing a network throughput of 200Mbps in full-duplex mode. The single-mode optical fibers are connected to the optical interface cards with the FC/PC connectors.

Fig. 4 Illustration of the monitoring statin network. The host computer is connected to five other monitoring station computers via optical link. Fig.. 3 Illustration of the sensor network. The sensors are connected to the computer via the DAQ card.

Testbed in Operation The GUI of the monitoring station is shown in Fig. 5. The diagram labeled by (1) is the position chart indicating the position of the mid-span of the transmission line. The position is derived from the magnetic field measured by the two magnetic sensors based on the Biot-Savart Law. As the transmission line is monitored by the two magnetic sensors, there are two magnetic waveforms displayed in the graphs labeled by (2). The inclination diagrams (3) show the front and side views of Tower 1 and Tower 2 and users can observe if there is any inclination for the transmission towers. The inclination is calculated from the tilting angle values measured by the accelerometers mounted on the transmission towers. The diagram (4) is the three-dimensional monitoring of the transmission line derived from the titling angle values measured by the accelerometers mounted on the transmission line. The spectrum (5) is the power quality analysis by taking Fourier Transform with the magnetic field measured by the magnetic sensors. The GUI also provides numerical measurement information in the panel labeled by (6). The numerical information including the cable temperature measured by the infrared sensor, cable tension measured by the strain gauges, magnitude of the electric current carried by the transmission line as determined by inverse calculation from the magnetic field measured by the two magnetic sensors, and the exact values of the tower inclinations. If these values exceed certain pre-determined safety levels, the corresponding warning indicators are lit up to alert the operators. When there is strong vibration to the tower due to, for example, explosion by terrorist sabotage, the oscillation is sensed by the accelerometers mounted on the transmission towers and the corresponding “Shocked” indicator is lit up to alarm the operators. As such, all the abnormal events listed in Table I can be effectively monitored in this sensor network testbed.

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Summary The laboratory-based sensor network testbed is featured by a platform with multiple advanced sensors, a GUI visualizing the measurement information, and integration with GPS. The monitoring station has access to all the sensor data and it can carry out further analysis to provide monitoring of the transmission line. The system can detect various electrical and spatial abnormal events of the transmission line including cable sagging and galloping, tower collapse and explosion, and electrical faults. Moreover, it is equipped with GPS receiver and can perform time synchronization for wide area measurement. This setup provides a comprehensive platform for experimenting various sensor network scheme and protocols for Smart Grid.

Fig. 5 GUI of the monitoring station. The interface includes (1) position chart, (2) magnetic field waveform, (3) inclination of Tower 1 and 2, (4) three-dimensional monitoring of the transmission line, (5) power quality analysis spectrum, and (6) numerical measurement information panel. The setup is sponsored by HKUICEE (Initiative on Clean Energy and Environment of the University of Hong Kong) which is displayed in the upper left corner.

References [1] X. S. Zhou, L. Q. Cui, and Y. J. Ma, “Research on Smart Grid Technology”, 2010 International Conference on Computer Application and System Modeling, vol. 3, pp. 599 – pp. 603, Nov 2010 [2] H. Slootweg, B.V. Enexis, “Smart Grids - The Future or Fantasy?”, Smart Metering – Making It Happen, 2009 IET, pp. 1 – 9, Feb 2009 [3] Yang et al., “A Survey on Technologies for Implementing Sensor Networks for Power Delivery Systems”, IEEE Power Engineering Society General Meeting, pp.1-8, Jun 2007

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[4] Leon et al., “Application of sensor network for secure electric energy infrastructure,” IEEE Trans. on Power Delivery 22 (2007) 1021 [5] L. Gang, D. De, and W.Z. Song, “SmartGridLab: A Laboratory-Based Smart Grid Testbed”, 2010 First IEEE International Conference on Smart Grid Communications, pp. 143 – 148, Oct 2010 [6] Qiu et al., “Towards a Real-Time Cognitive Radio Network Testbed: Architecture, Hardware Platform, and Application to Smart Grid”, 2010 Fifth IEEE Workshop on Networking Technologies for Software Defined Radio Networks, pp.1, Jun 2010 [7] Information on: http://www.the-infoshop.com/report/nan99531-sensor-for-smart-grid.html [8] Xu et al., “3D Visualization of Power System State Estimation”, IEEE Electrotechnical Conference 2006, pp. 943-947, May 2006 [9] van As et al., “A GPS based time-stamping and scheduling system for wide area power system measurements”, IEEE Africon Conference in Africa 2002, vol. 2, pp. 853 – 857, Oct 2002

Applied Mechanics and Materials Vols. 479-480 (2014) pp 753-757 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.753

Discoid and Asymmetrical Micro-satellite Propulsion Mode Attitude Control with Great Mass Change and without Angular Rate Sensor Ho-Nien Shou Department of Aviation & Communication Electronics, Air Force Institute of Technology, Kaohsiung, 820, Taiwan [email protected] Keywords: attitude control, unscented kalman filter, coarse sun sensor, earth horizon sensor

Abstract. The center of mass of the micro-satellite can offset due to fuel consumption in the course of propulsion, with the interference of external orbital environment such as gravity gradient torque and solar radiation torque. If the structural shape is discoid and asymmetrical, the attitude control may be difficult. The only solution is to design a robust controller, so that the attitude pointing of the satellite can meet the mission requirements with the interference of internal parameter perturbation and external disturbance. This study applied the robust control theory H∞ control law in the design of Formosat-3 propulsion mode attitude control, and carried out cross validation of the feasibility of the controller by time domain and frequency domain stability analyses. This study used H∞ controller as the experimental result. The time domain performance indexes (e.g., rise time, maximum overshoot and stabilization time) of the designed H∞ controller were consistent with the robust stability margin of stable performance index of frequency domain. Meanwhile, in order to reduce the weight and manufacturing cost of satellite, in the design of satellite attitude angular rate determination, the project used unscented kalman filter (UKF) algorithm, coarse sun sensor (CSS) and earth horizon sensor (EHS) as measurement components to obtain the satellite attitude without rate gyro. The research method and procedures in this study are applicable to any shaped and asymmetrical satellites with large mass variation and without angular rate sensor. The attitude sensors include three-axis magnetometer, horizon sensor, CSS as the analytic platform for stability of attitude control. Introduction The stability analysis of discoid and asymmetrical satellite propulsion mode attitude control with large mass change in the paper developed a real-time dynamic simulation system based on the experience in previous studies and the technology developed from annual plan. The attitude control processor was used to test the processor-in-the-loop, in order to be used in the micro-satellite system. The establishment of this analytic method and control technique is very important for controlling the micro-satellite attitude stabilization in any shape with large mass change. The basic attitude sensors of satellite include attitude sensors and attitude rate sensors. The attitude sensors include sun sensor, horizon sensor, magnetometer and star tracker. The attitude rate sensor is only the gyro. The gyro is very expensive, and unreliable in terms of reference point drift and main measurement error source. It is likely to be faulty than attitude sensors. As the satellite technology is generalized, the satellite price needs to reduce. In addition, as the software and algorithmic techniques develop, processing the attitude data by software to obtain attitude rate information becomes mature, thus, the gyro is certainly the first component that engineers aim to remove. Therefore, the gyro-less design is the research trend in recent years. 1).The gyroless satellite attitude determination algorithm provided by the UKF is used in this study. The filtering algorithm does not need to carry out linear approximation of the measure equation, while it can improve the attitude determination performance of satellite at large attitude angles effectively. The algorithm has higher convergence as the robust tracking is adopted. The simulation result shows that the algorithm can increase the attitude estimation convergence rate of gyroless satellite in initial

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attitude tumbling and three-axis stabilization effectively, and can implement attitude tracking in high speed rotation. The algorithm has concise linear structure. The computing load meets real-time requirement. The structure is simple, and the requirement for hardware configuration is not strict. It is especially applicable to low-cost micro-satellites. 2).The satellite attitude control has robust performance design issue with internal parameter perturbation and external disturbance. The mass center of satellite offsets due to fuel consumption in the course of propulsion, causing internal parametric variation. If the configuration is asymmetrical, the attitude control may be difficult. The micro-satellite is disturbed by external disturbances of gravity gradient torque and solar radiation torque in orbital motion. A robust controller is thus designed to render the attitude pointing meet the mission requirement. 3).The geomagnetic environment in the near-earth space is an important resource available for satellites. The magnetometer implements attitude computation by observing the geomagnetic field intensity vector. It is the attitude determination means commonly used by low orbit micro-satellites. The magnetometer is fixed in three-axis direction of the body coordinate system, and can detect the size and orientation of magnetic field at the same time. Moreover, it can compute the attitude after comparison with the magnetometer on the satellite. The measurement of earth orientation vector is implemented by the earth horizon sensor. This measuring method uses the infrared radiation of earth to measure the orientation of the satellite in relation to local horizon. At present, the technique implemented in Formosat-3 is static wide field of view (FOV). The earth sensor can obtain the nadir orientation, the FOV of sensor is required strictly for low-orbiting satellites, and the implementation cost shall be low. The sun azimuth vector is the third available reference vector. The sun sensor measures the orientation of sun sight in sensitive coordinate system according to the solar radiation intensity difference when the attitude changes. This method is the most extensively used attitude determination method. The sun can be approximately regarded as a point source with high intensity, and varying with time. These characteristics guarantee the simple sensing principle, easy design and production, light structure and conveniently implemented attitude determination. The coarse sun sensor (CSS) for sun vector, or called sun sensor implements omnidirectional viewing, but the sun sensor is unavailable in earth's shadow area. The sun sensor, EHS and magnetometer are used in this study as direct observation equation. 4).The measurement often has errors. The attitude filtering algorithm can reduce the effect of measurement errors on the entire control loop to increase the accuracy. In some states, some sensors fail or the measurement accuracy declines severely, the attitude information cannot be obtained completely, and the single-point deterministic attitude computation is no longer tenable. The filtering processing is required to be imported into the attitude determination loop to enhance the robustness of the system. This study used unscented Kalman filter algorithm to implement six-dimensional attitude estimation output of two/three observation vectors without angular rate sensor. The numerical simulation showed that its performance meets the requirement. The remainder of this paper is organized as follows: Section 2 presents the micro-satellite attitude control model; Section 3 introduces the unscented kalman filtering and algorithm; Section 4 describes the measurement reference model; Section 6 analyzes the attitude determination subsystem; and Section 7 offers the conclusion. Micro-satellite Attitude Control Model Micro-satellite Thrust-torque Deduction. Fig. 1 (a) and (b) show the discoid and asymmetrical micro-satellite, the four thrust nozzles of the micro-satellite are in the x-z plane at inclination α , the nozzles point to y-direction, laid in square at intervals of d . The fuel tank is at the x-z plane l of the nozzle, and is at − y distance from the centroid position of the micro-satellite. The Formosat-3 micro-satellite body coordinates are shown in Fig 1 (c). ∆α , ∆d and ∆l represent the uncertainty of nozzle inclination, relative distance between nozzles and the fuel tank centroid position offset respectively. The nozzle thrust direction and the force arm generated torque are deduced as follows

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dx

−y

3

4

y

α

x

x dz

dy

x-z plane

1

(a)

(b)

2

(c)

z z

Fig. 1 Geometric graph of micro-satellite
1 1


F1 = − sin (α + ∆α ) ex + cos (α + ∆α ) ey + sin (α + ∆α ) ez 2 2



r1 = ( d x + ∆d x ) ex − ( l + ∆l ) ey + ( d z + ∆d z ) ez

where

(1) (2)

∆d x ∆d z ∆l ≤ 0.2 , ≤ 0.2 , ≤ 0.2 and ∆α ≤ 0.2 . dx dz l α

(3)

If α + ∆α is very small, the torque τ u can be deduced as follows τ u  x τ u y  τ u z

     =  r1 × F1  

  r2 × F 2

 u1   − β 1∆  u   r4 × F 4   2  =  − β 2 ∆ u3     β 3 ∆ u4 

  r3 × F3

− β 1∆

β 2∆ − β 3∆

β 1∆ − β 2∆ − β 3∆

u 

β 1∆   1  u − β 2 ∆   2  = β u  u3  β 3 ∆   

(4)

u4 

where βi∆ = βi + ∆β i , i = 1, 2,3 On/Off-modulated Thrust Control.

(5) xˆ0 , P0

M command k=1

Ts → ton ,i M thruster

χi ,k ,Wi m , Wi c , ε j j = 0,1, 2 χi ,k |k −1 = f ( χ i ,k −1 , uk −1 , wk −1 )

Ts 2 − Ts 2

zi ,k |k −1 = h ( χi ,k |k −1 , vk −1 )

2n

on-modulation

off-modulation

xˆk |k −1 = ∑ Wi m χ i ,k |k −1 i =0

2n

tmax = max ( ton ,i ) i

tmin = min ( ton ,i ) i

zˆi ,k |k −1 = ∑ Wi m zi ,k |k −1

( χi,k|k −1 , xˆk|k −1 , Qk −1 ) → Pk|k −1

i =0

tbias = Ts 2 − tmax ton,i = ton,i − tmin

(W

i

c

,Wi m , χi ,k |k −1 , xˆk |k −1 , zi ,k |k −1 , zˆi , k |k −1 ) → ( Pxz , Pzz )

ton,i = ton,i + tbias

K k −1 = Pxz Pzz−1

Ts 2

M thruster → M command Ts

xˆk = xˆ k |k −1 + K k −1 ( z k |k −1 − zˆk |k −1 )

Pk = Pk |k −1 − K k −1 Pzz K kT−1

k=k+1

Fig. 2 Block diagram of on/off-modulated thrust control

Fig. 3 Flow chart of unscented kalman filter algorithm

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Unscented Kalman Filter Algorithm In the course of satellite attitude determination filter, in order to solve the nonlinear problem of state equation and measure equation, the normal method is to use Extended Kalman Filter (EKF) for linear approximation of nonlinear function, and the higher-order terms of approximate expansion are neglected in the course of approximation. The EKF process results in the following problems: when the higher-order terms of Taylor expansion of nonlinear function cannot be neglected, the linearization results in major errors in the system, even makes the filter difficult to be stable in the iterative process. It is difficult to find out Jacobian matrix derivation of nonlinear function in many problems. In order to increase the accuracy of filter and to improve the performance of filter, this paper uses Unscented Kalman Filter (UKF) algorithm in the satellite attitude determination process [3,4]. The state equation and measure equation of UKF have the following standard forms (6) xk +1 = f ( xk , uk , wk ) zk = h ( xk , vk )

(7)

where xk is the n-dimensional state vector of the system, and the variance is set as Pk ; uk , is r-dimensional input vector; f is n-dimensional vector function; h is m-dimensional vector function; wk is p-dimensional stochastic process noise, the variance matrix is Q ; vk is q-dimensional random noise, the variance matrix is R . A more detailed derivation of reference [5]. The unscented kalman filter algorithm shown in Fig 3. Attitude determination subsystem analysis CSS + Scanning Horizon Sensor + TMA Satellite Attitude Estimation. 1)Attitude Estimation State Variable: The nine-dimensional attitude estimation state variable is used for micro-satellite T ˆ ˆ xˆ = φ θ ψˆ φˆ θˆ ψˆ ∫ φˆ ∫ θˆ ∫ψˆ  (8)   2) Direct Observation Equation: If the attitude is measured only by CSS, horizon sensor and magnetometer instead of gyro, the measurement output of CSS, horizon sensor and magnetometer is adopted directly as the observations. The filter output value should be compared with the observed value, so the most straightforward observation vector can be selected as the measured value of sun vector Sb , horizon sensor Eb and three-dimensional geomagnetic field vector Bb in the satellite body system, i.e. z =  SbT

EbT

T

BbT  =  Sbx

Sby

Sbz

Ebx

Eby

Ebz

Bbx

Bby

 Cob ( x ) So    The corresponding measure equation is z = h ( x ) + v = Cob ( x ) Eo   Cob ( x ) Bo 

Bbz 

T

(9) (10)

T

T T T where v = vS v E v B  is the measurement noise of CSS, horizon sensor and magnetometer. S o , Eo and Bo are the sun vector, earth radiation and geomagnetic field vector respectively calculated according to the orbital location look-up table of satellite.

3) Simulation Results and Analysis: The gyroless UKF designed in this section is simulated. As the satellite experiences attitude large-angle motion and attitude stabilization motion in the attitude capture process, the attitude changes frequently. Therefore, the attitude changes in the satellite attitude capture are selected as objects for attitude filter estimation, from the filter effect of CSS + scanning horizon sensor + three-axis magnetometer on gyroless UKF in this section.

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4) Simulated Conditions: The magnetometer measurement error is 500nT, the solar sensor measurement error is 10%, satellite attitude three-axis initial attitude is different from. UKF initial attitude: Satellite altitude 500 km, longitude 108 , latitude 35 , sampling time 4sec, on-modulator magnitude = 2, satellite attitude motion trajectory is shown in Fig 4. The CSS tasks decrease from four tasks to two CSS tasks at 200 sec. The UKF of direct observation equation is used. The simulation results show when the CSS + scanning horizon sensor + three-axis magnetometer work normally, the estimated large-angle attitude change has relatively small error, the maximum error is 10°. If the number of CSS tasks is reduced, the error is relatively large when the attitude changes, the instantaneous maximum error is 32°. 0 0

Time response of actual Eular angle[ φ θ ψ ) ]= [-22 36 45]deg

0

magnitude (deg)

0 -5 -10

0

200 400 600 800 Time (sec) Time response of estimate body rate dt/d [ φ θ ψ ]= [-4.1365 -8.9497 0 0

50

0

1000

-50

1200

0

200

400

600 Time (sec)

0

200 400 600 800 Time (sec) Time response of estimate Eular angle [φ θ ψ ]= [-21.3378 38.8325 0 0

100

800

1000

1200

52.4787]deg

0

200

400

600 Time (sec)

800

1000

1200

1000

1200

Time response of Error of Eular angle

50

40 magnitude (deg)

magnitude deg/sec

1000

0

Time response of body rate error

0

-50

0

50

-50

1200

0

0

-3.1542]deg/sec

0

-50

0 0

50

magnitude (deg)

magnitude deg/sec

magnitude (deg/sec)

Time response of actual body rate dt/d [ φ θ ψ ]= [5 -3 -6]deg/sec 5

0

200

400

600 Time (sec)

800

1000

20 0 -20 -40

1200

0

200

400

600 Time (sec)

800

Fig 4(a) Time response of micro-satellite measured Fig 4(b) Time response of micro-satellite measured and estimated angular rate CSS 4
2 at 200sec and estimated angular CSS 4
2 at 200sec

0 1000

1 0 200

400 600 800 Time (sec)

1000

1 0 200

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1000

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1200 u2 magnitude

u3 magnitude

400 600 800 Time (sec)

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0

u4 magnitude

200

1

u3 magnitude

u2 magnitude

0

u1 magnitude

1

Time response of estimate state Thruster command u 2

u4 magnitude

u1 magnitude

Time response of actual state Thruster command u 2

1 0

Fig 4(c) Time response of thruster as CSS 4
2 at 200sec

Acknowledgments This study was financially sponsored by the National Science Council under Project No. 101-2221-E-344-002, and the 2012 "Subsidies for Teachers (Instructors) of Military Academies in Academic Research" No. 1010005122.

References [1] P. M. Stoltz, S. Sivapiragasam, and T. Anthony: Advances in Astronautical Science, AAS 98-007(1998), p. 1-13. [2] J. R. Wertz: Spacecraft Attitude Determination and Control (Kluwer Academic Publishers 1978). [3] H. Shou and C. Lin: Storage Management Solutions, Issue 5 (2011), p.35-41. [4] H. Shou and C. Lin: Journal of Industrial Technology, Vol.28, No.4 (2001), p.173-180. [5] H. Shou and Y. Kuo: Appl. Math. Inf. Sci. Vol.7, No. 1S (2013), p. 267S-276S.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 758-762 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.758

A Fuzzy-Based Management for Power-Aware Wireless Sensor Network Shu-Ching Wang1, a, Shun-Sheng Wang2,b*, Ching-Wei Chen3,c and Kuo-Qin Yan4,d* 1

168, Jifong E. Rd., Wufong District, Taichung County 41349, Taiwan, ROC.

2

168, Jifong E. Rd., Wufong District, Taichung County 41349, Taiwan, ROC.

3

168, Jifong E. Rd., Wufong District, Taichung County 41349, Taiwan, ROC.

d

168, Jifong E. Rd., Wufong District, Taichung County 41349, Taiwan, ROC.

a

b*

c

d*

[email protected], [email protected], [email protected], [email protected] *: Corresponding author

Keywords: Wireless Sensor Network, Power-aware Management, Mobile Agent.

Abstract. In recent years, Wireless Sensor Network (WSN) is one important type of mobile network that consists of many sensor nodes (SNs). The power consumption rate and bandwidth of each SN becomes an important issue and needs to be addressed. For increasing the reliability of WSN, this paper proposed a power-aware mechanism to select a stable manager from SNs by fuzzy based inference systems based on the factors of speed, power and location. Further, our mechanism can trigger a mobile agent to distribute the managerial workload. Introduction Owing to the improvement of MEMS, the development of WSN is progressing rapidly to become a popular network [7]. However, the capability of SN is limited by the computation capability, communication capability, power resources, and capability of memory. Although the hardware technologies have been enhanced, the power constraint is still a challenge [7]. Thus, an efficient power -aware mechanism is necessary to avoid the power exhaustion of WSN. In general, the SN of a traditional fixed wireless network is built by specific intermediaries to communicate each other. However, the infrastructure is easy to be destroyed by external environment, such as natural disasters and wars. Therefore, the WSN is more flexible due to absence of a fixed infrastructure. A WSN consists of SNs that can flexibly and quickly obtain the latest location information for automated battlefield, disaster relief, and rescue situations. However, an efficient routing among a set of SNs is one of the most critical issues in WSN. Therefore, the traditional routing protocols [1] focusing on the aspect includes the shortest path and cluster methods. The concept of the shortest path method is using the least SNs to forward messages. However, it is difficult to establish co-coordination due to the SNs is usually working independently in WSN. In cluster method, the cluster head (manager) can be elected to manage and forward message for SNs within a specific range [4]. Only manager needs to keep the routing table and other SNs can save the power in WSN. Therefore, a fuzzy-based power-aware management is proposed in this paper to assign the manager in WSN. Unfortunately, the topology of WSN may be destroyed due to the manager exhausts its limited power and bandwidth when overloaded with packets. For prolong the lifetime of manager, the power-aware manager is invoked by introducing a fuzzy theory inference system [4]. A multi-Mobile Agent (multi-MA) is proposed in this protocol to assist the manager to manage the specific SNs when the workload is overloaded. Methodology There are two phases in the proposed mechanism, the Power-aware Manager Election (PME) phase and Power-aware multi-MA Assignation (PMAA) phase. The main job of the PME phase is

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electing the appropriate manager for WSN when a management overload exists. The power-aware multi-MA is elected by the PMAA assignation phase to divide the management workload. (1) The Power-aware Manager Election (PME) phase This phase is divided into three parts. First, the GPS receiver information [8] is used to select a manager for each cell. Subsequently, a new method is given in which the distance, average roaming speed, and power are considered. Finally, the Power-aware Assignation Inference System (PAIS) is induced to improve the PME phase to select an appropriate manager. In PME phase, there are two steps to elect the power-aware manager as follows. Step1: The cell is divided into several ranks and the SN is selected in center of cell according to the GPS information. Step2: The average roaming speed and power are computed in all SNs to elect the appropriate manager. The location of each SN is compared to determine which SN can become the manager. However, to reduce the network load, the intra-cell is divided into three filter levels, as shown in Fig. 1. First, the intra-cell is divided into six equal triangles based on the intra-cell center. Subsequently, the center in each triangle is connected to form a hexagon, which is 2/3 multiples of the intra-cell as level II. Level II is used to select the multi-MA. Fig. 1 indicates that the cell closest to center is level I. The level I area is set up according to the density of SN in intra-cell. In general, the manager is closer to center in intra-cell than Multi-MA, thus level I is smaller than level II. We assume the count_max as maximum number of SNs and s is multiple of count_max. The area of level I is 1/s times to level II when the number of SNs are s times to preset threshold of SN. Namely, the area of level I is 2/3s times to intra-cell. However, the diagonal line of the hexagon formed by level I cannot be less than (r-0.86603)/2. This is because the level I area may not exist when we have a small amount of SNs in the WSN (the 0.8663 is the distance between the center of a circle and edge of a hexagon). The limited condition is shown in Fig. 2. s=r-0.86603

r

s=r-0.86603

Fig. 1. The level of the divided filter

Fig. 2. The minimum area of level I

In general, the divided filter area varies with the density of the SNs. However, we do not know the amount of SNs in the management election phase, thus the area of level I is equal to level II initially. Subsequently, the manager is selected from level I in the PME phase. In this paper, the divided filter is used to select appropriate SN as cluster header, thus only the specific SNs need to participate in PME phase. The cluster head is elected by min{Iu, 1≤u≤n, u∈n, n is the amount of nodes}. Iu is the cost of the node u and shown in (1), where Mu is the average roaming speed; Tu is the misery power index; Du = |du-M| indicates the difference between du and M, M is the threshold of connectivity; c1, c2, c3 is the weight of each parameter. Iu=c1Mu+c2Tu+c3Du (1) However, Equation (1) is used to elect the manager closest to center. In short, the average roaming speed and power are considered, thus Iu represents the costs for the average roaming speed, power, and distance from center. However, the power is the most important factor, thus the power misery index computation is used to compute the power. According to (2), the lower cit represents higher power misery index on packet transmission/receipt, and f i (cit ) is high where i is the id of SN, t is time and cit is the power of SNi in time t.

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f i (cit ) = 1 / cit

(2) After PME phase, a temporary power-aware manager in intra-cell can be elected. However, equations (1) and (2) cannot fully represent the relationship among distance, roaming speed, and power misery index. Therefore, the Power-aware Assignation Inference System (PAIS) needs to be invoked into PME phase to elect more appropriate power-aware manager. PAIS is divided into two steps, setting up the fuzzy members and fuzzy rule design. Step 1: Setting up fuzzy members The fuzzy members include three parts, distance from center, roaming speed, and power misery index. To reduce the complexity, the distance is divided into far and near. The roaming speed is divided into slow, medium and fast. The power misery index is divided into low, medium and high. In general, a SN closer to center has a lower distance item value, thus the signal strength is consistent between the selected manager and SNs. Namely, we can gain lower cost Iu, however the high Iu represents the SN is far from center. Step 2: The fuzzy rule of manager After the Step 1, each SN transfers the information about the distance, roaming speed and power misery index to the temporary manager. Subsequently, the temporary manager selects an appropriate manager according to that information. However, we set up the distance, roaming speed, and power misery index weights as 0.7, 0.2, and 0.1 as proposed by Huang et al. [3], shown in Table 1. Therefore, we can resilient adjust the weight of the (1) to adapt to network situation. The fuzzy rules contain 18 items and the less sum of value has higher probability to be the manger. Table 1. The fuzzy rule of manager election

In WSN, the manager usually take care the SNs in intra-cell and handles routing and packet transmission between inter-cells. The main management tasks are divided into four parts: (1) Routing maintenance: The manager needs to maintain location, roaming speed, and bandwidth of all SNs in intra-cell by member table. (2) Packet relay: The manager takes careful the message exchange and connection between SNs in intra-cell including routing phase and packet relay. (3) Routing discovery: Set up the routing path and packet relay in inter-cell. (4) Select a successor: When manager leaves intra-cell or retires, it needs to re-compute the area of level I to reduce the filter area and find the appropriate successor. In general, a single manager needs to manage SNs, handle routing path construction, and date relay between inter-cells. Therefore, manager has two kinds of tables in its memory, member table and routing table. The member table notes location, level of location, level of identification, speed, and power of the SNs in intra-cell. Otherwise, the routing table has the information of routing path about source and destination. Therefore, the workload increases fast due to the simultaneous handling cost and bandwidth assignment. Further, the management workload of manager will reduce the performance and exhaust its power easily if the misery index rises. The multi-MA inference system is triggered to reduce the management workload in PMAA phase when the bandwidth and power misery index achieve the preset maximum threshold.

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(2) Power-aware multi-MA Assignation (PMAA) phase The main function of MA is designed for a non-stable network. The MA with the highest mobility can adjust itself immediately to achieve transparency among the platforms. Mieso et al. [6] introduced a MA application in a cluster environment. The selected MA acts as a gateway to take care of inter-cluster communications. The MA has multiple process capability to assign tasks to different kinds of SNs. The different kinds of SNs are also called multi-MA. The main task of multi-MA is to assist in managing the SNs in intra-cell and divide the management workload. The manager can assign the multi-MA via PMAA phase where the congestion and misery index rises. The manager must elect the appropriate multi-MA by computing the capability of all SNs. There are two kinds of MAs in PMAA phase, the Power-aware IntrA-MA (PIA-MA) and Power-aware IntEr-MA (PIE-MA). (a) The Power-aware Intra-MA (PIA-MA) in PMA election phase In general, the manager needs to detect where bandwidth is overloaded and select the appropriate multi-MA during the PMAA phase. If the overload is coming from the SNs in the intra-cell, the manager will use the PAIS to elect the PIA-MA, which is located in level II to divide the management in the PMAA phase. The manager needs only to take careful the routing construction and packet relay between the inter-cells. The PIA-MA is responsible for the other jobs such as identity management of SNs, routing construction, and packet relay in intra-cell. The member table of PIA-MA needs to record intra-cell SN and management information. However, the manager member table needs only to record the PIA-MA information. The main change is that the manager needs to release the bandwidth and relay the packets forwarded to the PIA-MA. The PIA-MA is replaced by the intra-cell manager. (b) The election of Power-aware IntEr-MA (PIE-MA) in PMAA phase According to mention above, the manager needs to elect a PIA-MA to divide jobs due to the overloading is coming from SNs in intra-cell. In contrast to PIA-MA, the manger needs to elect a Power-aware IntEr-MA (PIE-MA) when the overload comes from Inter-cells. Therefore, the PIE-MA must be elected in level I to find the appropriate SNs. The PIE-MA is divided into two kinds of multi-MAs according to their job characteristics. The first kind is transient PIE-MA, the main job is providing the service of transmission when manager is overloaded. The transient PIE-MA is different from PIA-MA, the transient PIE-MA has the character of volatility due to it can change its mode to a general MA after finishing its jobs. Namely, the transient PIE-MA can be temporal elected to divide the management load. Another kind of PIE-MA is the permanent PIE-MA. It is the same as the PIA-MA. The permanent PIE-MA needs to elect the new PIE-MA to replace it when original permanent PIE-MA roams away its intra-cell. In general, the manager can select many PIE-MAs to transfer the packets. However, the manager needs to handle the routing construction and packet relay in intra and inter-cell; hence, the power-aware multi-MA inference system (PMAIS) is provided. To avoid the Ping Pong Effect [2], the fuzzy theorem is used to replace with the preset fixed threshold as the evaluated index. The PMAIS uses fuzzy theorem to decide whether the manager needs to elect a multi-MA or not. The PMAIS includes there steps: set up the fuzzy member, construct the fuzzy rule to trigger the multi-MA and fuzzy engine, and de-fuzzy. Step 1: Set up the fuzzy member Two factors are used in fuzzy members to consider the status of manager, the throughput load and power misery index. To reduce the complexity, the throughput is divided into the low (Lt), medium (Mt), and high (Ht). However, the throughput load needs to be between the [0, tmax]. The power misery index is divided into low (Lp), medium (Mp), and high (Hp), with the values between [0, pmax]. The workload is divided into four states: low (Lw), medium (Mw), high (Hw), and very high (VHw). Similarly, the values need to be between the [wmin,wmax]. We set the membership function for the preset four states between [0,1] as shown in Fig. 3. Equations (3) to (6) are inferred from Fig. 3. Step 2: Constructing the fuzzy rule to trigger the multi-MA and fuzzy engine Equations (3) to (6) the if-then fuzzy rule can be used to represent the workload state. We infer nine rules and discuss these rules one by one in Table 2. After steps 1 and 2, the management workload can

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be generalized as shown in Table 3 that the vertical axis is the throughput load (t) and the horizontal axis is the power misery index (p). Step 3: De-fuzzy To obtain fast computation results, the CoA method [5] is used to convert the fuzzy set representing the overall conclusion obtained in Step 2 into a real number. Based on the conservative rule, the manager must trigger the multi-MA in PMAA phase.

Fig. 3. The state of workload of manager Table 4. Fuzzy rule of multi-MA

Table 5. The inference engine of manager

Conclusion This study used an inference engine to elect a power-aware manager and multi-MA by considering the bandwidth and power misery index. In the PME phase, an appropriate power-aware manger is elected to take care of intra-cell and inter-cell tasks. Our method uses multi-MAs to divide the manager workload in PMAA phase. Furthermore, the multi-MAs are divided into PIA-MA and PIE-MA. The PIA-MA is responsible to support the workload of manager in intra-cell and the PIE-MA is responsible to inter-cell. Therefore, the lifetime of manager can be prolonged in a WSN. Reference [1] K. Akkaya and M. Younis: A Survey on Routing Protocols for Wireless Sensor Networks. Elsevier Ad Hoc Network Journal, Vol. 3 (2005), pp. 325-349. [2] J. Gu, S.J. Bae, M.Y. Chung, K.Y. Cheon and A.S. Park: Mobility-based Handover Decision Mechanism to Relieve Ping-pong Effect in Cellular Networks. Proc. of the 2010 16th Asia-Pacific Conference on Communications (APCC) (2010), PP. 487-491. [3] C.C. Huang, R.H. Chang and M.H. Guo: Weight-based Clustering Multicast Routing Protocol for Mobile Ad Hoc Networks. Wireless Communications and Networking on IEEE, Vol. 2 (2003), pp. 1112-1117. [4] G. Indranil, D. Riordan and S. Srinivas: Cluster-head Election using Fuzzy Logic for Wireless Sensor Networks. Proceedings of the 3rd Annual Conference on Communication Networks and Services Research (2005), pp. 255-260. [5] R. Saneifard: A Method for Defuzzi_cation by Weighted Distance. International Journal of Industrial Mathematics, Vol. 1, No. 3 (2009), pp. 209-217. [6] L. Vasiu and Q.H. Mahmoud: Mobile Agents in Wireless Devices. Computer, Vol. 37 (2004), pp. 104-105. [7] J. Yick, B. Mukherjee and D. Ghosal: Wireless Sensor Network Survey. Computer Networks, Vol. 52, Issue 12 (2008), pp. 2292–233. [8] Glenn Baddeley-GPS-NMEA sentence information, http://home.mira.net/~gnb/gps/nmea.html, 2013.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 763-767 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.763

A Centre Clustering Mechanism of Wireless Sensor Network Kuo-Qin Yan1,a, Shu-Ching Wang2,b*, Chin-Shan Peng3,c and Shun-Sheng Wang4,d* 1

168, Jifong E. Rd., Wufong District, Taichung County 41349, Taiwan, ROC.

2

168, Jifong E. Rd., Wufong District, Taichung County 41349, Taiwan, ROC.

3

168, Jifong E. Rd., Wufong District, Taichung County 41349, Taiwan, ROC.

4

168, Jifong E. Rd., Wufong District, Taichung County 41349, Taiwan, ROC.

a

b*

c

d*

[email protected], [email protected], [email protected], [email protected] *: Corresponding author

Keywords: Wireless sensor network, Center-based structure, Hierarchical management, Manager selection.

Abstract. A Wireless Sensor Network (WSN) consists of spatially distributed autonomous devices which use sensor nodes (SNs) to monitor physical or environmental conditions cooperatively. However, the SN is limited by the energy resource, the memory, the computation, the communication capability, etc. Therefore, the hierarchical clustering topology has been proposed to prolong the lifetime of WSNs by decreasing the energy consumption of SNs. Unfortunately, the network topology is still unstable due to the workload of the cluster managers is overloading. However, in this study, a Centre Clustering Mechanism (CCM) underlying the center-based WSN is proposed to improve the stability of network topology, assists SN within the working area, and takes advantage of message exchange.

Introduction Owing to the improvement of MEMS, the development of WSN is progressing rapidly to become a popular network [6]. A WSN consists of spatially distributed autonomous devices which use SNs to monitor physical or environmental conditions cooperatively. In WSN, each SN may act similarly to router to assist other SNs forward their packets in the network [5]. In addition, when WSN is in the stage of forming the entire network topology, it also easily causes signal disturbance, collision, or broadcast storm [4]. Sometimes the SNs may be too few, which causes the deliver path for packets in WSN to be insufficient, which reduces the transmit bandwidth in network, or to cause the communication quality bad. This will cause the stability of WSN to reduce quickly, making the network idle or clogged up. In WSN, the cluster managers (CMs) share to forward packets of all SNs, it may be because of the massive workload that causes the CM to be paralyzed, and even affects transmission of packets in the overall network [1,2,5]. Therefore, the cluster characteristic of CMs in WSN is used in this study to build small clusters under this environment, and choose the CM in each cluster to form a hierarchal management structure, to maintain the stability of WSN. However, the goals of this study are (1) divide network into suitable scale that can be handled by a CM; (2) cluster network by centre clustering, expect that the CM's covering scope be good; and (3) the hierarchical manager may reduce the waste of bandwidth, and increase transmission efficiency. In short, this study will design a clustering and hierarchical manager election mechanism based on a WSN environment. Research Method It often contains many small networks in WSN, and it has many SNs in each small network [6]. Each SN possibly distributes or gathers at the different place, and needs to transmit information between each other. Therefore, how to cluster and elect CM effectively in this environment is an important point for the maintenance of stable network topology [6]. The goal in this study is to discuss

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how to cluster and build a hierarchal management mechanism in WSN. In this study, a Centre Clustering Mechanism (CCM) underlying the center-based WSN is proposed. The advantage of being based on centre of cluster is it can let the CM cover more SNs, so it can cover SNs in network by better scope. Moreover, if there are too many SNs in cluster that is over CM’s capability, it will divide the cluster to sub-clusters depends on CM’s position and elect new sub-CMs in sub-clusters. It will achieve the goal of hierarchal management, and will maintain the overall effective in network transmission. The clustering mechanism in this study contains follow four steps: Step (1): First, to calculate the centre location of the network. Step (2): Then, to find some SNs that are close to the centre of network, and elect suitable CM by computing capability of these nodes attributes. Step (3): When the message quantity transferred by CM in cluster is bigger than bandwidth utilization percentage (BU%) set up by the user, CCM will divide the cluster into four sub-clusters base on CM’s position, and compute the transmit loading of network in each sub-cluster. If the transmit loading in each sub-cluster over 25% of CM’s bandwidth, it will repeat the Step (1) to (3) in the sub-cluster. This guaranteed the bandwidth of CM in cluster can shoulder information exchange, and does not increase the CM’s quantity because of the fewer nodes in cluster. Step (4): To build the hierarchal structure for transmitting messages depends on the relationship between parent and child of CMs in clusters.

By these four steps, the better CM in network depend on centre of cluster is found, and the SNs in the network area may be divided into different clusters to share the load of messages transmission by more quantity of CM. In addition, the structure of messages transmission in network in this study that we proposed is separated into three steps respectively is: Step (1): If the message-sending SN and receiver SN are at the same cluster, then the message will transmit directly between two SNs to reduce the loading of CM. Step (2): If the message-sending SN and receiver SN are at different clusters, then the send SN will send a message to the CM in its cluster first. Moreover, the CM will forward the message to its upper CM by hierarchal structure. Finally, the message will be sent to receiver SN by CMs forwarding between clusters. Step (3): If the receiver SN’s location outside the whole transmission region of message-sending SN, the message will transmit to the CM at uppermost layer, then the message will be sent to the receiver SN by message exchange between CM located at each uppermost layer.

The Centre Clustering and Cluster Manager Electing Mechanism The basic idea of CCM is to elect SN in best capability as CM after each data exchanges and comparisons, and clusters will form gradually. Finally, each SN will be assigned into a unique cluster. There are three steps, (1) Clustering when WSN initialize, (2) Clustering after SN move in or out the cluster; and (3) Processing when CM fails. The construction of hierarchal management First, the centre of network is computed and CM is elected recursively in WSN. Then, to calculate the quantity of each SN depends on the CM’s capacity and loading. Finally, the mechanism will involve clustering and building the network structure in hierarchal management. When computing the network centre, we assume that there are total i nodes in j clusters. The position of each node Nji is (Xji, Yji), and the position of centre of cluster j (CXj, CYj) can be computed by formula (1): CX

j

= ∑ X ji / i

CY j = ∑ Y ji / i

(1)

After obtaining the position of centre of cluster j, then the CM based on centre of cluster can be chosen. Because of the characteristic of centre is the distance between centre and SNs around it is shortest. So coverage will get better when SNs are closer the centre, and the CM should be the SN that is closest to the centre. Therefore, the distance dji between each SN and centre is computed by formula (2), and a SN is elected as CM that has shortest distance to centre.

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min d

ji

=

(X

ji

− CX

ji

) 2 + (Y ji − CY ji ) 2

765

(2)

But if the CM is chosen only by the distance between SN and centre, then it has the possibility to choose the SN that in low power, degree of busy, or low bandwidth to affect the transmit efficiency. Therefore, the factors such as remaining power, degree of busy, and bandwidth of SNs are considered when CM is elected to avoid such situations. Therefore, the percentage of surplus power (e), degree of busy (b), communication capacity (c), and distance to centre (d) will be transformed into a capacity value (p) according to the formula (3), while the weight values w1, w2, w3, and w4 will be defined in accordance with the important of each item of factors for meeting the various needs. p = (e)*w1 + (1/b)*w2 + (c)*w3 +(1/d)*w4, Σwi=1

(3)

The clustering mechanism in this study will choose SNs depending on the user requirements first, then compute the capability of each SN by formula (3), and elect the SN in best capability as a CM. When the CM of cluster has been elected, the loading in transfer of CM needs to be considered in order to avoid the CM that we choose cannot take over works on messages forwarding. Therefore, in this study, we draw up when the bandwidth used in packet exchanges of CM over BU percentage of its total bandwidth, then CCM will segment the cluster to four sub-clusters based on the position of CM in cluster. CCM will reassign the CM’s ID to SNs in the cluster to achieve the goal of clustering. Then, the total bandwidth loading of SNs in sub-cluster reaches 25% of CM’s total bandwidth then CCM will be re-elected new CM in sub-cluster to manage the message transmission in sub-cluster. The advantage that clustering by bandwidth loading of CM is it can cluster and elect CM depending on the quantity of SNs in network. Because of the quantity of transmitted messages will be bigger in the cluster with more SNs, then the requirement quantity of clusters and managers get bigger. It can give all SNs the equal backbone for transmitting message in network. After the child cluster establishment, the CM in child cluster will know which the managers in its parent clusters are by exchanging messages. The hierarchal management structures that are built in this way are used to manage SNs and transfer data in whole network. When the sending SN and receiving SN of messages are both in the same cluster, then they will communicate directly to reduce loadings of CM. However, if the sending SN and receiving SN of messages are in different clusters, then the sending SN will send its data to its CM in cluster first, and the data will send to receive SN by forwarding between CMs in clusters. If the message sending SN and message receiving SN in different management scope, then the data will be sent to the CM in top-level and sent to the message receiving SN by forwarding between CHs in top-level clusters. Experimental Results The environment of the experiment is designated as an area of 1000*1000. Attributes of each SN contain the Node_ID, horizontal position (Pos_X), upright position (Pos_Y), motion angle (Direction), moving speed (Speed), transmission region (Range), relative electric power % (Energy), relatively degree of busy % (Busy), and relative bandwidth % (Bandwidth). Besides, NS2 is used to generate all parameters and 1000 nodes [7]. Table 1 shows the sampled data for the experiment that produced by NS2. Use Borland C++ Builder to develop all emulators in the experiment of this research. Some values such as the SNs quantity used for the experiment, clustering range, weighted range, etc. all that will be defined by the users, Fig. 1 illustrates the interface of the emulator. In the experimental design, the fourth weight values (w1~ w4) of CCM are w1 is 0.4, w2 is 0.2, w3 is 0.1, w4 is 0.3, and the BU of CM is 0.9. However, the experiments in this research are divided two parts as follows: Experimental design 1: There are different quantities of SNs of 20, 40, 60 and 80 in network, and simulates the CCM method 30 times repeatedly. Each time the required SN quantity is chosen from

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SNs table randomly to run the simulation, and record the forming cluster counts and counts of packets forwarded by CM. Experimental design 2: There are different quantities of SNs of 20, 40, 60 and 80 in network, clustering scope is 150, and simulates the CCM and Non-clustering methods 30 times repeatedly. Each time the required SN quantity is chosen from SNs table randomly to run the simulation, and record the counts of packets forwarded by CM. Table 1. Sample parameter of nodes in the experiment

Fig. 1. The user interface for simulation program

Results of experiment 1 There are different quantities of SNs of 20, 40, 60 and 80 in network, and simulates the CCM method 30 times repeatedly. Each time, the required SNs quantity is chosen randomly from SNs table to run the simulation, the number of clusters is recorded, and the number of forward packets by CM is counted. The average number of clusters formed is shown in Fig. 2, and the comparison with the average number of forward packets by CM is shown in Fig. 3.

Fig. 2. The average number of clusters formed in experiment 1

Fig. 3. Compare with the average number of forward packets by CM in experiment 1

The experiment results are shown in Fig. 2 and Fig. 3, because the CM will separate its cluster into sub-groups when the quantity of data transfers over CM’s capability in this study. Therefore, when the number of SNs increases, it will increase the number of CMs and clusters. In opposition to the CM’s quantity increase, because the management level increases, the quantity of packets transferred by CM has the obvious rise, and both numbers grow up close linearity. Results of experiment 2 There are different quantities of SNs of 20, 40, 60 and 80 in network, clustering scope is 150, and simulates the CCM and Non-clustering methods 30 times repeatedly. Each time, the number of required SNs quantity is chosen from SNs table randomly to run the simulation, and the number of forward packets by CM is recorded. From the result shown in Fig. 4, because of the clustering is not

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considered in traditional WSN, so the number of forward packets by SNs will grow up with the number of SNs. However, in CCM, the each SN is formed into a cluster and managed by a CM, and the transmitted packets are only forwarded by CM. Therefore, the number of average forward packets still gets fewer; even there are more SNs in network.

Fig. 4. Compare with the average number of forward packets by nodes in experiment 2

Conclusion This study discusses the clustering and manager election mechanism according to the centre of network, and solves possible problems by integrating methods of similar research. To propose a more comprehensive method that allows this mechanism to be simpler, more feasible, and more effective. Formerly many clustering and manager election methods did not consider the loading of CM in WSN [1,3,5]. Therefore, this study focuses on the discussion of clustering and manager election mechanism and tries to reduction the clustering size to a possible loading of manager. Moreover, the factors of the percentage of surplus power, degree of busy, communication capacity, and the distance to centre are used to elect the CM. By the experimental result, we discuss that no matter how many SNs in the network there are, the clustering method in this study also can maintain network stability. Beside this, our method in this study will get more stable in network topology and fewer transfer packets of CM. Therefore, the CM may have longer existence time. References: [1] N. Azizi, J. Karimpour and F. Seifi: HCTE: Hierarchical Clustering based Routing Algorithm with Applying the Two Cluster Heads in each Cluster for Energy Balancing in WSN. IJCSI International Journal of Computer Science (IJCSI), Vol. 9, Issue 1, No 2 (2012), pp. 57-61. [2] L. Guo, F. Chen, Z. Dai and Z. Liu: WSN Cluster Head Selection Algorithm Based on Neural Network. International Conference on Machine Vision and Human-Machine Interface (MVHI) (2010), pp. 258-260. [3] C.C. Huang, R.H. Chang and M.H. Guo: Weight-based Clustering Multicast Routing Protocol for Mobile Ad Hoc Networks. Wireless Communications and Networking on IEEE, Vol. 2 (2003), pp. 1112-1117. [4] H. Jeong, H. Jeong and Y. Yoo: Dynamic Probabilistic Flooding Algorithm based-on Neighbor Information in Wireless Sensor Networks. Proceedings of the 2012 International Conference on Information Networking (ICOIN) (2012), pp. 340-345. [5] C. Silva, R. Costa, A. Pires, D. Rosário and E. Cerqueira: A Cluster-based Approach to provide Energy-Efficient in WSN. IJCSNS International Journal of Computer Science and Network Security (IJCSNS) (2013), Vol. 13, No. 1, pp. 55-62. [6] J. Yick, B. Mukherjee and D. Ghosal: Wireless Sensor Network Survey. Computer Networks, Vol. 52, Issue 12 (2008), pp. 2292-233. [7] The network simulator - NS-2, http://www.isi.edu/ nsnam/ns/, April 2, 2013.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 768-772 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.768

Motion Control of a Robot Arm Kuo-Lan Su 1, a, Bo-Yi Li 2, b, Jr-Hung Guo 2, c, H. H. Kevin Chau 3, d 1

Department of Electrical Engineering, National Yunlin University of Science & Technology, Taiwan 2

Graduate school Engineering Science and technology, National Yunlin University of Science & Technology, Yunlin, Taiwan

3

Graduate School of Electrical Engineering, National Yunlin University of Science & Technology, Taiwan a

b

c

email: [email protected], [email protected], [email protected] Keywords: robot arm, PC-based controller, DC servomotors, NI motion controller card, PID controller.

Abstract. The article designs a seven joints robot arm using PC-based controller. The robot arm contains seven DC servomotors, seven driver devices and a NI motion control card and uses proximity sensors to locate the limit position, and programs motion trajectories to finish assigned tasks. We tune the parameters of the PID controller for each joint of the robot arm, and get the nice response to control the robot arm moving to the assigned position. The user interface is developed in the supervised computer using Visual Basic. The supervised computer (controller) computes the kinematic equations of the seven joints robot arm, and calculates the motion displacement of each joint using inverse kinematic equation. Users can program the motion paths on the user interface. The controller of the robot arm can implement precision point to point motion trajectories according to the programmed motion trajectories. In the experimental result, users can write words on the user interface. The robot arm catches the pin to write the assigned word on the plane. Introduction Robot arm search strategy is a very important research problem. Under many path planning solving method, how to find an effective and fast method to program the motion trajectory become an important problem. A robot arm is a mechanical device that is driven by some electronic motors, some pneumatic devices or some hydraulic actuators, and helps human to finish the assigned tasks in automation field. The purpose of the paper is to design and implement a seven-degree-of-freedom robot arm. We mainly use seven DC servomotors to assemble the robot arm. In the control aspect, a PC based controller and a DSP based 8 axis motion control card are used to control the robot arm. When the robot hardware is finished, the PID control parameters of each joint should be tuned. Then we compute the kinematic equations of the robot arm, and program the motion trajectories for each joint according to the assigned task. The paper programs some difficult motion mode, a ball or a stick, adjustment or execution to be selected made according to the user. There are some researches regarding the robot arm. Ahmad discussed the drive train of a robot arm. Due to the backlashes, the eccentric joints and the influences that the flexibility of driving axies would have on the accuracy and repeat accuracy of the arm positioning, Ahmad used linear positioning compensation and obtained good effects [1]. Lee conducted the kinematic analysis of a robot arm of the closed kinematic chains, utilizing the Homogeneous Transformation method to do the analysis of the parallel-link robot arm, which calculating the moving space [2]. Veitschegger developed the kinematic adjustment model of the PUMA560 six-axis robot arm. They used the model on compensating the positioning tolerance of the manipulator [3]. Zhang worked on the adjustment of a robot arm and proposed a new kinematic analysis method, which could avoid the tolerance caused by the singularity of kinematic analysis [4]. Meza proposed a semiglobal asymptotic stability analysis via Lyapunov theory for a new proportional-integral-derivative (PID) controller control scheme which is based on a fuzzy system for tunning the PID gains for robot, manipulators [5]. Nagesh used an adaptive observer to estimate the

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uncertainties in the state matrices of a two-degree-of-freedom robot arm model [6]. Zhai designed a dual-arm humanoid cooking robot arm is able to cook disher like a master chef in ordinary home kichens [7]. Robot arm The size of the seven-axis robot arm is 165cm, 118cm and 110cm respectively. The arm includes shoulder: two DOFs; elbow one DOF, wrist three DOFs and gripper one DOF. The prototype of the robot arm is shown in Fig. 1. The arm contains seven DC servomotors with gear train. The working region is 140cm, 90cm and 80cm in X axis, Y axis and Z axis respectively. We define the coordination system for each joint in Fig. 2.

Fig. 1 Seven-axis robot arm.

Fig. 2 The link relation between joints and links.

Fig. 3 Hardware configuration of the robot arm.

Fig. 4 User interface for writting function.

In order to achieve the purpose of accurate positioning, the control structure of the robot arm can be divided into kinematic path programming, position control, velovity control, current control, voltage control, etc. From the hardware design view, the controller transmits the motion command to the driver devices according to kinematic path of the robot arm, and produces the motion control code of the robot arm. Fig. 3 shows the hardware configuration of the seven-axis robot arm. Using the eight-axis motion control card control each joint of the robot arm. The parameters of each joint must be adjusted to achieve excellent control responsen. The eight-axis motion control card could provide the software package to automatically tune every axis’ PID parameters of each joint. The user interface of the robot arm presents writing function on the plane shown in Fig. 4. There are two parts. One is motion programming area; the other displays written words using image system. Users can program four joints of the robot arm in the motion programming area. The robot arm only uses four joints to catch the pin and writes the assigned english words on the writting area. The controller of the arm is arranged in the left side to be a PC-based system. First, users can write english words in the user interface of the controller. Then the controller converts the information of the written words to the motion commands of each joint, and controls the robot arm to catch the pin. Then the robot arm writes the assigned words on the writting area step by step.

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Kinematic Analysis Kinematic equation mainly discusses the coordinate transformation of the robot system. Kinematics can be divided into forward kinematics and inverse kinematics. As for the links of a robot arm, the Denavit-Hartenberg (D-H) coordinate transformation method is generally used. The transformation matrix of the coordinate could be abbreviated as D-H transformation matrix. Forward kinematics gives the rotation angle of each joint to calculate the position and the direction of a manipulator or an end effecter. First, we must know the D-H parameters of each joint of the robot arm before establishing the motion equations. The coordinate system of the robot arm is shown in Fig. 2. The D-H parameters of each joint are shown in Table 1. Table 1. The D-H parameters of each joint Joint 1 2 3 4 5 6 7

di d1 d2 d3 d4 d5 d6 d7

θi θ1 θ2 θ3 θ4 θ5 θ6 θ7

ai 0 0 0 0 0 0 0

αi 0° -90° 90° 0° -90° 90° -90

The transformation matrixes of two joints are shown as follows: cos θi  sin θi i −1 Ai =   0   0

- cos αi sin θi

sin α i sin θi

cos α i cos θ i

- sin α i cos θi

sin α i

cos α i

di

0

0

1

  

cos θ 2  sin θ 2 1 A2 =   0   0

0

- sin θ 2

0

sin θ3

0

cos θ 2

0

0

-1

0

0

0

0

- sin θ5

0

cos θ5

-1

0

0

0

cos θ5  sin θ5 4 A5 =   0   0

α icos θi  α i sin θi 

0 cos θ3   0 2 sin θ3 , A3 =   0 d2   1   0 0 cos θ6   0 5 sin θ6 , A6 =    d5 0   1  0 

cos θ1 - sin θ1  sin θ1 cos θ1 0 A1 =   0 0  0  0

,

1 - cos θ3 0

0

0

sin θ6

0

- cos θ6

1

0

0

0

0 0 1 0

0 cos θ4   0 3 sin θ 4 , A4 =   0 d3   1   0 0 cos θ7   0 6 sin θ7 , A7 =    d6 0   1   0

0  0 d1  1 

(1)

- sin θ4

0

cos θ4

0

0

1

0

0

0

- sin θ7

0

cos θ7

-1

0

0

0

0  0 d4  1  0  0 d7   1 

(2)

(3)

Where Cθ i = cos θ , Sθ i = sin θ , the total transformation between the base of the robot arm and the hand will be i

i

 nx n y 0 0 1 2 3 4 5 6 T7 = A1 A2 A3 A4 A5 A6 A7 =   nz  0

ox

ax

oy

ay

oz

az

0

0

px  p y  pz   1

  C5 [C4C3 (C2C1 − S1S2 ) − S4 (C1S2 + S1C2 ) ]   nx = C7 C6   + S3 S6 (S1S2 − C1C2 )   − S5 [S4C3 (C2C1 − S1S2 ) + C4 (C1S2 + S1C2 ) ]    S5 [S4 (C1 S2 + S1C2 ) - C3C4 (C1C2 - S1S2 ) ]  + S7   - C5 [ S4C3 (C2C1 - S1 S2 ) + C4 (C1S2 + S1C2 ) ] 

(4)

(5)

Applied Mechanics and Materials Vols. 479-480

  C5 [C4C3 (S2C1 + S1C2 ) + S4 (C1C2 - S1S2 ) ]   n y = C7 C6   − S3 S6 (S1C2 + C1S2 )   S5 [− S4C3 (C2 S1 + C1S2 ) + C4 (C1C2 − S1S2 ) ]    - S5 [S4 (C1C2 − S1S2 ) + C3C4 (S1C2 + C1S2 ) ]  + S7   C5 [- S4C3 (C2 S1 + C1S2 ) + C4 (C1C2 − S1S2 ) ] 

nz = C7 [C6 (S3 S4 S5 − S3C4C5 ) − C3 S6 ] + S7 (S3 S4 S5 + S3 S4C5 )  C5 [C4C3 (C2C1 − S1S2 ) − S4 (C1S2 + S1C2 ) ]  ox = − S 6   + S3C6 (S1 S2 - C1C2 ) − S5 [S4 C3 (C2C1 - S1 S 2 ) + C4 (C1 S 2 + S1C2 ) ]   C5 [C4C3 (S 2C1 + S1C2 ) + S4 (C1C2 − S1S2 ) ]  o y = − S6   − S3 S6 (S1C2 + C1 S 2 ) S5 [- S4 C3 (C2 S1 + C1 S2 ) + C4 (C1C2 − S1 S 2 ) ] 

771

(6)

(7) (8)

oz = S6 (S3C4C5 − S3 S 4 S5 ) − C3C6 (9)

  C5 [C4C3 (C2C1 − S1S2 ) − S4 (C1 S2 + S1C2 ) ]   ax = − S7 C6   + S3 S6 (S1S2 − C1C2 )   − S5 [S 4C3 (C2C1 − S1S2 ) + C4 (C1S 2 + S1C2 ) ]    S5 [S4 (C1 S2 + S1C2 ) − C3C4 (C1C2 − S1 S2 ) ]  + C7   - C5 [S4C3 (C2C1 − S1 S 2 ) + C4 (C1 S2 + S1C2 ) ] 

(10)

  C5 [C4C3 (S 2C1 + S1C2 ) + S4 (C1C2 − S1S 2 ) ]   a y = − S7 C6   − S3 S6 (S1C2 + C1S2 )   S5 [− S 4C3 (C2 S1 + C1S 2 ) + C4 (C1C2 − S1S 2 ) ]    - S5 [S4 (C1C2 − S1 S2 ) + C3C4 (S1C2 + C1S 2 ) ]  + C7   C5 [- S4C3 (C2 S1 + C1S 2 ) + C4 (C1C2 − S1 S2 ) ] 

(11)

az = C7 (S3C4 S5 + S3 S 4C5 ) − S7 [C6 (S3 S 4 S5 − S3C4C5 ) − C3 S6 ]

(12)

  C5 [C4C3 (C2C1 − S1S 2 ) − S4 (C1 S2 + S1C2 ) ]   p x = d 7 S 6   + S3C6 (C1C2 − S1S2 )   − S5 [S4C3 (C2C1 − S1S 2 ) + C4 (C1S 2 + S1C2 ) ]    S5 [S4 (C1 S 2 + S1C2 ) − C3C4 (C1C2 − S1 S2 ) ]  + d7   + d5 S3 (C1C2 − S1S 2 ) - C5 [S4C3 (C2C1 − S1 S 2 ) + C4 (C1 S 2 + S1C2 ) ]  + d 4 S3 (C1C2 − S1S2 ) − d3 (S1C2 + C1S 2 )   C5 [C4C3 (S 2C1 + S1C2 ) + S4 (C1C2 − S1 S 2 ) ]   p y = d 7 S 6   + S3C6 (S1C2 + C1S 2 )   S5 [− S 4C3 (C2 S1 + C1S2 ) + C4 (C1C2 − S1S 2 ) ]   - S5 [S4 (C1C2 − S1S 2 ) + C3C4 (S1C2 + C1 S 2 ) ]  + d6   + d 5 S3 (S1C2 + C1S2 ) C5 [- S4 C3 (C2 S1 + C1 S2 ) + C4 (C1C2 − S1 S 2 ) ]  + d 4 S3 (S1C2 + C1S 2 ) + d 3 (C1C2 − S1S 2 ) pz = d 7 [S6 (S3 S4 S5 − S3C4C5 ) + C3C6 ] + d 6 (S3C4 S5 + S3 S4C5 ) + d5C3 + d 4C3 + d 2 + d1

(13)

(14)

(15)

Experimental results In the writing function, the robot arm writes the assigned English words “Advisor” in the first column, and writes “Dr. Kuo-Lan Su” on the second column. First, the robot arm catches the pin to write the first column in the writing plate shown in Fig. 5(a) and (b). Then the robot arm has finished the assigned words in the first column, and moves to the location of the second column to write other words On the writing plate. We can see the writing process shown in Fig. 5(c)-(f), and the written words display in the writing area of the user interface on real-time.

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The user interface displays the green label to present the joint in the motion processing. The red label presents the joint to stop. We can see two joints are processing to write the assigned words shown in Fig. 5(e) and (f). Finally, the assigned English words are finished by the robot arm. Fig. 5(g) displays the writing English words on the user interface through the vision system, and sees four joints of the robot arm to stop. The experimental result of the written English words is shown in Fig. 5(h).

(a)

(e)

(b)

(c)

(f) (g) Fig. 5 Writing process for the robot arm.

(d)

(h)

Conclusion The paper had designed and implemented a seven-axis robot arm of the human robot, and verified the robot arm’s kinematic equations. In addition, the rotation angle of each joint is calculated from inverse kinematic to be utilized along with the DSP based motion control system. Finally, the PC based controller could control the robot arm to catch a pin moving to the writing area to write the assigned english words. The user interface can display the written English words on real-time through the vision system. Acknowledgment. This work was supported by National Science Council of Taiwan. (NSC 1012221- E-224-007). References [1] S. Ahmad: Analysis of robot drive train errors, their state effect, and their compensations, IEEE Journal of Robotics and Automation, Vol. 4, No. 2(1988), pp.117-128. [2] K.M. Lee and D.K. Shah: Kinematic analysis of a three-degree-of-freedom in-parallel actuated manipulator, IEEE Journal of Robotics and Automation, Vol. 4, No. 2(1988), pp.354-360. [3] W. Veitschegger and C.H. Wu: Robot calibration and compensation, IEEE Journal of Robotics and Automation, Vol. 4, No. 6(1988), pp.643-656. [4] H.A. Zhang: Complete and parametrically continuous kinematic model for robot manipulators, IEEE Transaction of Robotics and Automation, Vol. 8, No. 4(1992), pp.451-463. [5] J.L. Meza, R. Soto and M.A. Llama: Fuzzy seft-tuning PID semiglobal regulator for robot manipulators, IEEE Transaction on Industrial Electronics, Vol. 59, No. 6(2012), pp.2709-2717. [6] S.B. Nagesh, Z. Lendek, A.A. Khalate and R. Babuska: Adaptive fuzzy obserter and robot controller for a 2-DOF robot arm, IEEE World Congress on Computation Intelligence(2012). [7] J. Zhai, W. Yan, Z. Fu and Y. Zhao: Kinematic analysis of a dual-arm humanoid cooking robot, IEEE Inter. Conf. on Mechatronics and Automation(2012), pp.249-254.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 773-777 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.773

Enhance A* Searching Algorithm Applying in Multiple Robot System Kuo-Lan Su 1, a, Bo-Yi Li 2, b and Cheng-Yun Chung 2, c 1

Department of Electrical Engineering, National Yunlin University of Science & Technology, Taiwan 2

Graduate school Engineering Science and technology, National Yunlin University of Science & Technology, Yunlin, Taiwan a

b

c

email: [email protected], [email protected], [email protected] Keywords: mobile robots, Chinese chess game, evaluation algorithm, enhance A* searching algorithm, wireless RF interface

Abstract. The article programs the shortest motion paths of the multiple mobile robots to be applied in the Chinese chess game, and presents the movement scenario of the chess using mobile robots on the grid based chessboard platform. Users play the chess game using the mouse to obey the evaluation algorithm on the user interface. The user interface is developed in the supervised computer and programs the motion paths that are the shortest displacement using enhance A* searching algorithm. The article will reprogram the new motion paths to solves the collision problem of the programmed motion paths using enhance A* searching algorithm, too. The supervised computer controls mobile robots according to the programmed motion paths of the assigned chess moving on the platform via a wireless RF interface. In the experimental results, we use simulation method to search the motion paths of the assigned chesses on the user interface, and implement the simulation results on the chessboard platform using mobile robots. Mobile robots move on the platform according to the programmed motion paths from the start points to the target points and avoid the collision points. Introduction Chinese chess game [1] is similar to Western chess belong to two players, and is classified red side and black side. The game will be over for a winner using a chess to take the chess “king“ of the other side. In the recent, the Chinese chess game has gradually attracted by many researchers’ attention, and many evolutionary algorithms to be proposed. Darwen proposed the co-evolutionary algorithm to solve problems where an object measure to guide the search process is extremely difficult to device [2]. Zhou analysed the existing problems of computer Chinese chess game, the structure and performance of computer Chinese chess game platform and the latest progress in the field of computer Chinese chess game [3]. In the paper, we use the multi-robot system to present the movement scenario of the chess for Chinese chess game, and uses enhance A* searching algorithm to program the shortest path for mobile robots (chesses) moving to the target points. Players move the chess to the assigned location or takes the chess of the other side in the Chinese chess game. They may be two chesses (robots) moving on the platform simultaneously. The assigned two robots may collide on the programmed motion paths. We want to solve the collision problem to improve the shortest motion paths of the two robots. There are many algorithms to be proposed in Chinese chess game. Wang used adaptive genetic algorithm (AGA) to solve the problems of computer Chinese chess [4]. Su developed smart mobile robot using voice module, and programmed the motion trajectories for multiple mobile robots based Chinese chess game [5]. Kong used adaptive harmony search algorithm to solve optimization problems [6]. Fu used the position evaluation function to play an important role for building an intelligent chess computer game [7].

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Algorithm analysis A* searching algorithm solves the path planning problem of multiple nodes travel system. The formula of A* searching algorithm is following f (n ) = g (n ) + h(n )

(1) The core part of an intelligent searching algorithm is the proper heuristic function f (n ) . g (n ) is the exact cost at sample time n from start point to the next point. h(n ) is the minimum cost. In this study, n is reschedules as n′ to generate an approximate minimum cost schedule. The equation (1) can be rewritten as follows: f (n ) = g (n ) + h(n')

(2) The A* searching algorithm can only program local minimum motion path. We improve A* searching algorithm that is called enhance A* searching algorithm, and reprogram the searched motion path for mobile robots. In the Chinese chess game, the chesses of red side must face to the black side. In the same way, the chesses of black side must face to red side, too. We make an example to explain the motion programming process using enhance A* searching algorithm for mobile robots. Player moves the chess “red cannon” to take the chess “black horse”. First, the user interface programs the motion path using A* searching algorithm for the taken chess “black horse” shown in Fig. 1(a). The chess “black horse” moves to the point “A” that locates at the bottom side of the chess “red rook”, and faces to the red side. The programmed motion path of the taken chess “black horse” turns right three times, turns left five times and moves 14 grids. We can find out the six turning points to make the landmarks 1, 2, 3, 4, 5 and 6 shown in Fig. 1(b). Then the enhance A* searching algorithm select all cross points on the programmed motion path to make the landmark 2, A, B and 6 to be similar to a rectangle shown in Fig. 1(c). We can see the path to collision the chess “red advisor” from the point 2 to the point B. The user interface must reprogram the new motion path to avoid the chess “red advisor” shown in Fig. 1(d). The path contains four cross points to make the landmark 2, D, C and 4. We can see no chess in the programmed motion area, and select the new motion path shown in Fig. 1(e). There are four turning points to make the landmark 1, 2, 3 and 4. The user interface displays the shortest motion path in Fig. 1(f). The motion path of the chess “black horse” turns right two times, turns left four times and moves 14 grids.

(a)

(b)

(c)

(d) (e) (f) Fig. 1. The motion path of the taken chess “black horse”

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Then the user interface programs the motion path using A* searching algorithm for the taken chess “red cannon” shown in Fig. 2(a). The chess “red cannon” moves to the start location of the chess “black horse”, and faces to the black side. The programmed motion path turns right five times, turns left five times and moves 11 grids. We can find out the seven points to make the landmarks 1, 2, 3, 4, 5, 6 and 7. The total pulse numbers of the motion path f (n ) can be calculated as f (n ) = 11 × 355 + 10 × 92 = 4825

(3) Then the proposed algorithm select enable cross points from the programmed motion path to make the landmark 2 and 6 shown in Fig. 2(b). We can see the path to collision the chess “black pawn”. The user interface must reprogram the new enable motion path shown in Fig. 2(c). The path contains four cross points to make the landmark 2, A, B and 4. We can see the path to collision the chess “black pawn” from the point “2” to the point “B”. The user interface must reprogram the new enable motion path, too. The new enable motion path shown in Fig. 2(d). The path contains four cross points to make the landmark 6, C, D and 4. We see no chess in the motion area, and select the new motion path shown in Fig. 2(e). Next we improve the motion path at the cross points 1, 2 and 3 using the same method shown in Fig. 2(f). The user interface reprograms the new enable motion path shown in Fig. 2(g), too. The path contains four cross points to make the landmark 1, E, F and 3. We can see no chess in the programmed motion area, and select the new motion path from the point “1” to the point “3” through the point “E”. The user interface displays the shortest motion path in Fig. 2(h). The new motion path turns right three times, turns left three times and moves 11 grids. We calculate the total pulse numbers of the new motion. The displacement of the new motion path is shorter than the old motion path. f (n ) = 11 × 355 + 6 × 92 = 4457

(a)

(e)

(b)

(c)

(f) (g) Fig. 2. The motion path of the chess “red cannon”

(4)

(d)

(h)

Experimental results Users move the chess using the mouse to play Chinese chess game on the user interface, and present movement scenario of mobile robots using enhance A* searching algorithm. The

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experimental scenario is the chess “black horse” moving to the right side of the chess “black cannon”. The user interface programs the motion path using enhance A* searching algorithm. The programmed motion path is very easily, and has not collision or obstacle problem shown in Fig. 3(a) and (b). Then the supervised computer controls the mobile robot (black horse) moving to the assigned location. The mobile robot turns right one time, turns left one time and moves three grids on the platform shown in Fig. 3(c).

(a)

(b) (c) Fig. 3. The experimental result for “black horse”

The other experimental scenario moves the chess “red rook”to take the chess “black cannon” on the user interface. The user interface programs two motion paths using enhance A* searching algorithm for the assigned two robots. The first motion path is the chess “black cannon” moving to the bottom side of the red side. The taken chess “black cannon” locates at the right side of the chess “black horse” shown in Fig. 4(a). The motion path of the taken chess turns right three times, turns left one time, and moves 11 grids.

(a)

(b)

(d)

(c)

(e)

Fig. 4. The experimental result for “red rook” taking “black cannon” Then the user interface programs the motion path for the chess “red rook” that moves to the location of the taken chess “black cannon” shown in Fig. 4(b). The assigned motion path has the collision points with the pre-programmed motion path of the taken chess “black cannon”. The user interface displays the alarm signal to re-program the new motion path, and avoids the collision points. We can find out the new motion path of the chess “red rook” to be shown in Fig. 4(c). The old motion path of the chess “red rook” only moves three grids. The new motion path must turns right two times, turns right two times, and moves five grids to avoid the collision points.

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The user interface has been programmed the two motion paths for two chesses “red rook” and “black cannon”. Then the supervised computer orders command to the two mobile robots (red rook and black cannon) moving on the chessboard platform according to the programmed motion paths. Two mobile robots move on the platform simultaneously, and speak the movement status using Chinese language. The movement scenarios are shown in Fig. 4(d) and (e). We plot the motion trajectories of the two mobile robots, too. Finally, we can see the taken chess “black cannon” moving to the bottom side of the red side, and see the robot “red rook” moving to the origin location of the taken chess “black cannon”. Conclusion We have developed a Chinese chess game, and presented the movement scenario of the chess using multiple mobile robots. The user interface used thirty-two mobile robots to represent the chesses of the Chinese chess. We develop the user interface on the supervised computer. The user interface can programmed motion paths of the assigned chesses using enhance A* searching algorithm, and solved the collision problem of the programmed motion paths. The supervised computer controls mobile robots and receives the status of mobile robots on real-time via wireless RF interface. Users can move the chess using the mouse on the user interface, and moves the chess to obey the rules of Chinese chess game. Acknowledgment. This work was supported by the National Science Council of Taiwan, (NSC101-2622-E-224-008-CC3). References [1] S.J. Yen, J.C. Chen, T.N. Yang and S.C. Hsu, Computer Chinese Chess, ICGA Journal, Vol.27, No. 1(2004), pp.3-18. [2] P. Darwen and X. Yao, Coevolution in Iterated Prisoner’s Dilemma with Intermediate Levels of Cooperation: Application to Missile Defense, International Journal of Computational Intelligence Applications, Vol. 2, No. 1(2002), pp.83-107. [3] W. Zhou, J.C. Liu and Y.H. Zhao, The construction of Chinese chess computer game platform, The 6th International Conference on Computer Science & Eduation(2012), SuperStar Virgo, Singapore, pp.126-128. [4] J. Wang, Y.H. Luo, D.N. Qiu and X.H. Xu, Adaptive Genetic Algorithm’s Implement on Evaluation Function in Computer Chinese Chess, Proceeding of ISCIT(2005), pp.1206-1209. [5] K.L. Su, S.V. Shiau, J.H. Guo and C.W. Shiau, Mobile Robot Based Onlin Chinese Chess Game, The Fourth International Conference on Innovative Computing, Information and Control(2009), pp.63. [6] Z. Kong, L.Q. Gao, L.F. Wang and Y.F. Ge, Onan adaptive harmony search algorithm, International journal of Innovative Computing, Information and Control, Vol. 5, No. 9(2009), pp.2551-2560. [7] T. Fu and H. Yin, Designing a hybrid position evaluation function for Chinese-chess computer game, International Conference on Software Engineering and Service Science(2012), Beijing, China, pp.75-78. [8] K.L. Su, C.Y. Chung, Y.L. Liao and J.H. Guo, A* Searching Algorithm Based Path Planning of Mobile Robots, The Innovative Computing, Information and Control – Express Letters, Part B: Applications (ICIC-ELB),Vol. 2, No. 1(2011), pp.273-278.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 778-782 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.778

A Cyclostationarity-Based Spectrum Sensing Scheme for Dynamic Traffic Circumstances Youngseok Lee1,a, Seong Ro Lee2,b, Seungsoo Yoo3,c, Jaewoo Lee1,d, Jeongyoon Shim1,e, and Seokho Yoon1,f,† 1

College of Information and Communication Engineering, Sungkyunkwan University, Suwon, Korea

2

Department of Information and Electronics Engineering, Mokpo National University, Muan, Korea 3

Department of Electronics Engineering, Konkuk University, Seoul, Korea a

[email protected], [email protected], [email protected], {dlllp3743, ehobbangdk}@skku.edu, and [email protected] †

Corresponding author

Keywords: Cognitive radio (CR), spectrum sensing, dynamic traffic circumstances

Abstract. In this paper, we propose a cyclostationarity-based spectrum sensing scheme for dynamic traffic circumstances. First, we model the spectrum sensing problem in dynamic traffic circumstances as a binary hypothesis testing problem where primary users (PUs) might randomly depart or arrive during the sensing period. Then, we develop a generalized likelihood ratio (GLR) and derive a test statistic via the GLR, which is based on the cyclostationarity of the PU signals. Numerical results confirm that the proposed scheme offers a better spectrum sensing performance than the conventional scheme based on energy detection for dynamic traffic circumstances. Introduction Driven by the rapid growth of broadband wireless applications, the frequency spectrum is increasingly becoming scarce, and thus, it is required to use the spectrum resource more efficiently. The cognitive radio (CR) is a promising technology to exploit underutilized spectrum in an opportunistic manner and the spectrum sensing technique identifying spectrum opportunities is one of the most important techniques in CR [1,2]. Until now, various spectrum sensing techniques have been developed under static traffic circumstances where the spectrum band is assumed to be occupied by the primary user (PU) or to be vacant during the whole sensing period [3,4]. Practically, however, the PU signal could depart or arrive during the sensing period, especially when a long sensing period is used to achieve good sensing performance, or when spectrum sensing is performed for a high traffic network, and under such dynamic traffic circumstances, the performances of the conventional spectrum sensing techniques have been found to degrade severely [5]. Although a spectrum sensing technique [6] was proposed based on the energy detection approach for dynamic traffic circumstances, it performs poorly when the signal-to-noise ratio (SNR) is low. In this paper, a novel spectrum sensing scheme is proposed based on the cyclostationarity approach for dynamic traffic circumstances. We first formulate the spectrum sensing problem in dynamic traffic conditions as a binary hypothesis testing problem and develop the corresponding generalized likelihood ratio (GLR). Obtaining an estimate of spectral autocoherence function (SAF) of the PU signal and applying it to the GLR, we propose a test statistic for spectrum sensing in dynamic traffic circumstances. The proposed cyclostationarity-based scheme is expected to perform better than the conventional energy detection-based scheme of [6], since the cyclostationarity approach has an advantage over the energy detection approach in that its detection performance is generally better than that of the energy detection approach, and also, it can distinguish the PU signal from the interference unlike the energy detection approach.

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System Model We model the spectrum sensing problem in dynamic traffic circumstances where the PU randomly departs or arrives during the sensing period of CR user as a binary hypothesis testing problem: Given the received signal, a decision is to be made between the null hypothesis H0 and the alternative hypothesis H1 defined as  x[ n] + w[ n], for n = 1, 2,… , J 0 , H 0 : y[ n] =  for n = J 0 + 1, J 0 + 2,… , N  w[ n],

(1)

and for n = 1, 2,… , J1 ,  w[ n], H1 : y[ n] =   x[ n] + w[ n], for n = J1 + 1, J1 + 2,… , N ,

(2)

respectively, where y[n] and x[n] represent the nth sample of the baseband equivalent of the received and PU signals, respectively, w[n] represents the nth sample of an additive white Gaussian noise (AWGN) with mean zero and variance σ 2 , and N is the number of samples available during the sensing period. Under the hypothesis H0, the random departure of the PU occurs between the J0th and (J0+1)th samples, on the other hand, under the hypothesis H1, the random arrival of the PU occurs between the J1th and (J1+1)th samples. In the receiver of a CR user, a test statistic is calculated from the received samples { y[n]}nN=1 (e.g., a traditional energy detector calculates

∑

N n =1

2

y[n] as a test statistic), and then, compared with a

threshold that satisfies a given false alarm probability Pfa (i.e., Pr( H1 H 0 ) ). If the test statistic exceeds the threshold, the CR user chooses the hypothesis H1 deciding that the spectrum band is occupied by the PU; otherwise, the CR user chooses the hypothesis H0 and utilizes the spectrum band of the PU.

Proposed Scheme Applying the GLR test to the binary hypothesis model of Eq. 1 and Eq. 2 gives the following decision rule J1

N

H1

> y [n] − ∑ y [n] γ ', < n = J 0 +1 n =1

∑

2

2

(3)

H0

where γ ' is a predetermined threshold. To exploit the cyclostationarity of the received PU signal, in

Eq. 3, we replace y[n] with the SAF ρ αy ( f ) defined as [7] 1/2

ρ αy ( f ) = S αy ( f )  S y ( f + α / 2) S y ( f − α / 2)  ,

(4)

where α is a cyclic frequency, S y ( f ) is the PSD of y(t), and ∞

S αy ( f ) = ∫ Rαy (τ )e− j 2π f τ dτ −∞

(5)

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is the spectral correlation density (SCD) function defined as the Fourier transform of Rαy (τ ) , where

Rαy (τ ) is the cyclic autocorrelation function and expressed as 1 A/2 y ( t + τ / 2 ) y * ( t − τ / 2 ) e- j 2πα t dt , A→∞ A ∫− A /2

Rαy (τ ) = lim

(6)

where (i)* is the conjugation operation. From Eq. 4 and Eq. 5, we can see that the SAF is the normalized version of the SCD. Since ρ αy ( f ) is the SAF of a continuous signal y(t), we cannot replace the discrete value y2[n] of

(ρ

Eq. 3 with

α y

2

2

( f ) ) directly. Thus, we employ the discrete estimate ρˆ αy ( f ) of the squared magni-

tude of the SAF obtained as 2

ρˆ αy ( f ) =

∑

N

u[ n]v*[ n ] n =1

2

∑

N n =1

u[ n]

2

∑

N n =1

v[ n]

2

(7)

to replace y2[n] of Eq. 3, where u[ n ] = y[ n ]e jπ ( f −α / 2) n and v[ n] = y[ n]e jπ ( f +α / 2) n are the frequencyshifted versions of y[n]. Now, replacing y2[n] with Eq. 7 yields N

∑

J1

H1

ρˆ y ( f ) − ∑ ρˆ y ( f ) α

2

n = J 0 +1

α

2

n =1

> γ,
n

(5)

i =0

where n indicates the total number of nodes existed in the network. Root Node Rotation Mechanism. Before starting each data collection round, a new root node for the routing tree should be selected from the set of the sensor nodes. The selection process is executed in a distribution manner; each node uses an identical equation, as shown in (6), to determine the node with address Ar to be root node for the rth round of data collection. Ar = r mod n , r ∈ Z (6) Since the routing tree constructed for a set of arbitrary n nodes might not be a complete tree structure, the address space allocated for the nodes is not guaranteed to be a sequence of continuous numbers. In order to avoid selecting an address Ar that has not been assigned to an existing node (called empty address here); each node should maintain a list of address gaps that are collected from all of the sensor nodes and uses the following rule to skip the empty address Ar:  A + b a ≤ Ar < ai + bi and Ar + bi < ai +1 (7) Ar' =  r i i  Ar

otherwise

The interval [ai, bi] denotes the ith address gaps existed in the address space for the routing tree. Simulation Results To examine the performance of the design presented above, the simulation platform that was developed for a two-tiered routing topology of LSWSN [8] is modified to implement the distributed tree routing scheme and is used to conduct the simulation work. The settings for the simulation parameters used for the simulation are n=3000, R=500m (divided into four grids), BS located at (250, 600), 0.5 J of node initial energy, Eelec=50 nJ/bit, Eamp=100 PJ/bit/m2, 2000 bits of packet-length, and 5 nJ of data fusion energy. Table 1 lists the simulated results on average transmission delay, average number of node degree, and average network lifetime. The transmission delay is measured in the number of hops required to send a packet to the BS; the lifetime is defined as the number of data collection rounds that can be performed till the first node death occurs. Based on the simulation results from Table 1, we can find that both the network lifetime and delay time increase with the depth Lm of routing tree; whereas the node degree is decreased accordingly. When comparing with the optimal chain-based Intra-PEGASIS protocol [9], as shown in Fig. 3(a), the distributed tree scheme (Lm=7) has a longer lifetime than that of Intra-PEGASIS while Fig. 3(b) shows a shorter transmission delay of the distributed tree scheme than the Intra-PEGASIS. Table 1. Indicators of simulation performance Lm 1 2 3 4 5 6 7 8 9 10

Delay 3 6 8 10 12 14 15 18 20 22

Degree 750 27 9 5 4 3 3 3 2 2

Lifetime 491 1947 2352 2570 2786 2914 3071 3132 3306 3377

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(a)

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(b)

Figure 3. Performance comparison with Intra-PEGASIS; (a) Network lifetime; (b) Transmission delay. Conclusions This paper addresses the particular requirements of routing protocols for LSWSNs, and proposes a distributed tree-based routing protocol with regard to the considered requirements. According to the simulation results, the proposed distributed tree-based routing has been shown that the network lifetime and data transmission delay can be controlled well by the parameter of tree depth. Furthermore, the distributed tree-based routing is also shown to be superior to the optimal chain-based protocol in terms of network lifetime and transmission delay.

References [1] C. Li., H. Zhang, B. Hao and J. Li, “A survey on routing protocols for large-scale wireless sensor networks,” Sensors, 11(4), pp.3498-3526, 2011. [2] I. Akyildiz, W. Su, Y. Sankarasubramniam, and E. Cayirci, “A survey on sensor networks,” IEEE Communications Magazine, pp. 102–114, 2002. [3] K. C. Rahman, “A survey on sensor network,” Journal of Computer and Information Technology, pp.76-87, 2010. [4] S. Lindsey, C. Raghavendra, “PEGASIS: Power-efficient gathering in sensor information systems,” In Proceeding of IEEE Aerospace Conference; volume 3, pp. 1125-1130, 2002. [5] W. R. Heinzelman, A. Chandrakasan and H. Balakrishnan, “Energy-efficient communication protocol for wireless microsensor networks,” IEEE Proceedings of the Hawaii International Conference on System Sciences 2000, pp.1-10, 2000. [6] S. S. Satapathy, and N. Sarma, “TREEPSI: Tree based energy efficient protocol for sensor information,” International Conf. on Wireless and Optical Communications Networks, Bangalore, India, 2006. [7] ZigBee Alliance Document 053474r17; ZigBee Specification 2007. [8] Y. C. Lin, and J. H. Zhong, “Hilbert-chain topology for energy conservation in large-scale wireless sensor networks,” IEEE Proceedings of the International Conference on Ubiquitous Intelligence & Computing, pp. 252-232, Sept. 2012. [9] Y. L. Chen, J. S. Lin, “Energy efficiency analysis of a chain-based scheme via intra-grid for wireless sensor networks,”Computer Communications, Volume 35, pp.507-516, 2012.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 788-792 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.788

A N-hop Concentric Clustering Algorithm with Sub-clusters in a Wireless Sensor Network Young-Long Chen1, a, Yi-Nung Shih 2, b and Siao-Jhu Shih3, c 1, 2, 3

Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, No.129, Sec. 3, Sanmin Rd., Taichung 404, Taiwan, ROC a

[email protected], [email protected], [email protected]

Keywords: WSNs, energy efficiency, clustering algorithm

Abstract. In this paper, we aim to improve the energy efficiency via a clustering algorithm based on social insect colonies (CASIC), in order to extend the lifetime of wireless sensor networks (WSNs). We propose a CASIC with sub-clusters (CASIC-S) for reducing the energy consumption of sensor nodes within the concentric layer during transmission or reception. We also investigate the CASIC-S scheme with different numbers of nodes in our simulations. The simulation results show that our proposed scheme performs better in terms of first node death and the number of nodes alive. Introduction The sensor nodes consume energy when gathering or sending data. When the energy is depleted, the node will become a death node. The dead nodes affect performance, including the sensing area and the lifetime of the WSNs. In recent years, researchers have proposed clustering architectures in extensive studies. A clustering architecture is composed of the cluster head and the cluster members. In clustering schemes, the cluster members aggregate the data from the environment and transmit them to the cluster head. The cluster head collects the data from the cluster members and transmits them to a remote base station [1]. The authors proposed a geographic routing which finds the energy-efficient path, to achieve the high throughput with low delay in multimedia transmission [2, 3]. Low energy adaptive clustering hierarchy (LEACH) is a decentralized algorithm which is proposed by W. B. Heinzelman et al. [4]. In a LEACH scheme, each sensor node produces a random value in order to decide that will be a cluster head. Cluster heads collect sensing data from their cluster members and transmit them to the base station. To avoid data collision and wasted energy, LEACH scheme use time division multiple-access (TDMA) protocol to assign time slots for each cluster member. The cluster members are based on time slots to transmit sensing data to their cluster heads. C. T. Cheng et al. proposed a clustering algorithm based on social insect colonies (CASIC) which is a single cluster scheme [5]. In the CASIC scheme, the cluster is divided into several layers of concentric circles, and its cluster radius covers the entire field area. The cluster members in the outermost layer collect data and transmit them to the inner layers. The cluster head located at the center aggregates the data and transmits them to the base station. In this case, compared to direct transmission to the cluster head, this way can reduce more energy consumption. In this paper, we proposed a concentric clustering topology scheme: CASIC with sub-clusters (CASIC-S). In CASIC-S scheme, the selecting cluster head phase considers the remaining energy of the sensor nodes to pick the cluster head, in order to ensure that the cluster head's energy is sufficient for transmission or reception. In selecting the sub-cluster head phase, it considers the transmitting distance of sensor nodes to select a sub-cluster head which has the minimum transmitting distance between the sub-cluster head and destination node within the competition radius. Since the sub-cluster head has the minimum transmitting distance, it consumes the least amount of power to transmit data to the destination node. Therefore, as the outermost nodes transmit data to the inner layer, the energy consumption of the entire network can be reduced and the operational time of the WSNs can be extended.

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CASIC with Sub-clusters To improve the efficiency of CASIC, we propose a concentric clustering topology architecture which is called CASIC with sub-clusters (CASIC-S). The CASIC-S scheme is divided into five phases: the selecting cluster head phase, the neighbors searching phase, the selecting sub-cluster head phase, the scheduling creation phase and the data transmission phase. We use a sub-cluster within the layer to improve data transmission between nodes, and reduce the energy consumption of the nodes. The CASIC-S scheme's cluster head is located at the center of the concentric clustering. The sensing data are sent from the outer to the inner layers, and the cluster head sends the compressed data to the BS. The selecting cluster head phase. According to C. T. Cheng et al.’s scheme [5], each wireless sensor node will perform a random competition period in the selecting cluster head phase. Each wireless sensor node uses the competition period to compete with each other in order to select a single cluster head. The competition period of the wireless sensor node i is defined ti . After the concentric layers of the bound are calculated, the cluster head sent join-message to inform non-cluster head nodes. When the cluster head has been selected, the cluster head broadcasts within cluster radius Rc a join-message to invite non-cluster head nodes. The cluster radius Rc is assumed that can cover the entire sensing area. The join-message includes: cluster head identification (ID), the communication radius rc and number of layers l . In this case, the concentric layers of the bound, parameters of rc and l are the same way that is proposed by [5]. When the non-cluster head nodes receive the join-message, they stop competing, and transmit a message to join the cluster head. Once the cluster head receives all messages, then the cluster will finish and divide into the number of the concentric layers L. The neighbors searching phase. When the belonging layer of the sensor node is known by receiving the join-message, each sensor node will become a cluster member and enter the neighbors searching phase. The cluster members broadcast a searching message that includes the node ID, location layer and the distance between the cluster head and itself. They broadcast to their neighbor nodes within communication radius rc . For the broadcast nodes, the neighbor nodes are defined whose position is located at other layers and closer to the cluster head. If node has no any one neighbor within communication radius rc , then it will increase its rc until its neighbor is found. Once the neighbors receiving the searching message, they will return message to broadcast nodes so that broadcast nodes can use the received signal strength indication (RSSI) to estimate the distances between the neighbor nodes and itself, store information and calculate the neighbors’ statistics with it. According to the recorded information, a sensor node can find a nearest neighbor node which has a minimum transmitting distance with it that is located in one layer closer to the cluster head. The minimum transmitting distance Din is given as:

Din = min(di1 ,
, diK ).

(1)

where Din represents the minimum distance between the nearest neighbor node n and cluster member i ; di1 represents the transmitting distance between the cluster member i and its neighbor node 1 ; K is the number of neighbor nodes of cluster member i . The selecting sub-cluster head phase. In this phase, the sub-cluster heads within the concentric layer will be selected. Each cluster member compares within the competition radius with each other which are located at the same concentric layer. In this case, each competition radius of cluster member is assumed that is the same as the communication radius rc . The cluster members broadcast the competition message to each other. The broadcast radius is assumed that is the same as the communication radius. The competition message includes that the cluster member ID, the number of concentric layers and the minimum transmitting distance Din . When the cluster members have

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received the messages, they will use individual Din to compete with each other regarding whose location is in the competition radius and the same concentric layer. If Din of the cluster member i is the least distance away, then it will become a sub-cluster head and broadcast the message to inform cluster members whose locations are within the competition radius and the same concentric layer. When the message has been received by the cluster members, they will store this message and use RSSI to estimate the distance Td ij between cluster member i and the source of the broadcasting sub-cluster head j . The distance Td ij is used to decide whether or not cluster member i will join sub-cluster head j . If the Td ij of cluster member i is less than its Din , then it will broadcast a message to join the sub-cluster head j and become its sub-cluster member, in order to guarantee that the sub-cluster member consumes less energy to transmit data to its sub-cluster head than when it directly transmits data to its neighbor node; otherwise. When all cluster members have joined the sub-cluster, the sub-cluster will be established and all sensor nodes will enter the scheduling creation phase. The scheduling creation phase. The transport mechanisms can avoid energy dissipation such that the data collisions cause the sensing data to be resent, and the throughput is reduced. In the scheduling creation phase, the cluster head uses TDMA protocol to establish time slots and uses the carrier sense multiple access (CSMA) media access control (MAC) protocol to assign them to all cluster member nodes, including sub-cluster heads and their sub-cluster members. When the sensor nodes receive the time slot from their cluster head, the sensor nodes are ready to transmit and receive sensing data. The data transmission phase. In this phase, each cluster member within layer L collects the sensing data and transmits the data to the sub-cluster head which is chosen. The sub-cluster heads are responsible for collecting data from its members and transmitting data to the nearest neighbor that is found by step 2. The sub-cluster head aggregates data from its members and transmits them to the nearest neighbor node which is located in layer L − 1 or one layer closer to the cluster head. Each sub-cluster head within layer 2 transmits the data to the cluster head which is located in layer 1. Finally, the cluster head then aggregates the data from the sub-cluster heads and transmits them to the base station. When the cluster members transmit and receive the sensing data, all cluster members stop their activities until the cluster head allocates new time slots to transmit. Simulation results In this study, we analyze the performances of the LEACH, CASIC and our proposed CASIC-S scheme in terms of the first node death and the number of nodes alive. The sensor nodes are randomly distributed in sensing field of 50 × 50 (m2), and the base station is located at (25 m, -100 m). Each sensor node is assumed that can communicate with each other, the battery energy is initially given as 0.05 (J). For experiments, we set the number of nodes N at 50. Here we assume the packet size of sensing data is set at 4000 (bits). In the simulation details, we do not consider the energy consumption of the base station, because its energy is solar-powered and unlimited. The electronics energy is set at 50nJ/bit. Table 1 shows the simulation parameters. In our experiments, we use the same radio energy dissipation model to calculate the energy consumption [4]. Figure 1 shows that the first node death of the CASIC-S scheme appeared in round 75; the CASIC scheme and LEACH scheme node deaths appeared in rounds 68 and 35, respectively. As shown in Fig. 2, compare our proposed scheme with CASIC and LEACH schemes in terms of the number of nodes alive. The result shows that the number of nodes alive for our CASIC-S scheme is about 80% in round 88, the number of nodes alive for the CASIC scheme is about 80% in round 84, and the number of nodes alive for the LEACH scheme is about 80% in round 44. In terms of the number of nodes alive, our proposed scheme can extend the lifetime of WSNs because the sub-cluster members consume less energy to transmit data to the sub-cluster head than in directly transmitting data to its neighbor node. The overall performance of our proposed scheme is the best.

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Table 1 Simulation parameters parameters

value

The number of nodes

N=50

Sensing field

50 × 50 (m2)

The BS position

(25 m,-100 m)

The initial energy of the node

0.05 (J)

Electronic energy Amplifier energy of free space and multi-path Data packet

Eelec =50n (J/bit) εfs=100p (J/bit/m2) εmp=0.0013p (J/bit/m4) k=4000 (bits)

80 70 60

Rounds

50 40 30 20 10 0

LEACH

CASIC Schemes

CASIC-S

Fig. 1. First node death with different schemes for N=50, rc=10 and l=20. 50 LEACH CAISC CAISC-S

45

The number of nodes alive

40 35 30 25 20 15 10 5 0 0

20

40

60 80 Rounds

100

120

140

Fig. 2. The number of nodes alive with different schemes for N=50, rc=10 and l=20.

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Summary In this study, we proposed a concentric clustering topology scheme: CASIC with sub-clusters (CASIC-S) which has a single cluster head, sub-cluster heads and sub-cluster members. In CASIC-S scheme, it uses the sub-cluster to improve CASIC and enhance the efficiency of WSNs. The sub-cluster member consumes less energy to transmit data to its sub-cluster head than it would to directly transmit data to its neighbor node. The sub-cluster head has a minimum transmitting distance with its destination node, so it consumes the least amount of power to transmit data. We considered the remaining energy of the cluster head to ensure that the cluster head is not subject to rapid death, and its energy is sufficient for transmission or reception. Since the outermost nodes transmit data to the inner layer, the energy consumption of the entire network can be reduced and the lifetime of the WSNs can be extended. Furthermore, the performances of our proposed scheme offer improvement over the CASIC and LEACH schemes by 4% and 100%, respectively. Acknowledgements This work was supported in part by the National Science Council (NSC) of Republic of China under grant No. NSC102-2221-E-025-001. References [1] W. Dali., J. Yichao, S. Vural, K. Moessner, and R. Tafazolli: IEEE Trans. Wireless Commun. Vol. 10 (2011), p. 3973 [2] A. Kumar and S. Varma: IEEE Sensors J. Vol. 10 (2010), p. 1138 [3] H. Zhang and H. Shen: IEEE Trans. Parallel Distrib. Syst. Vol. 21 (2010), p. 881 [4] W.B. Heinzelman, A. Chandrakasan and H. Balakrishnan: IEEE Trans. Wireless Commun. Vol. 1 (2002), p. 660 [5] C.T. Cheng, C.K. Tse, and F.C.M. Lau: IEEE Sensors J. Vol.11 (2011), p. 711

CHAPTER 9: Methods and Algorithms for Processing and Analysis of Data

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Development of Causal Model of Four Parameters upon Statistical and Mathematical Analysis and Management Huei-Ming Shih1,2,a, Shieh-Liang Chen3,b, Chih-Hung Wang4,c 1

PhD student, Department of Business Administration, Asia University, Taichung, Taiwan Assistant Professor, Department of Kinesiology, Health, Leisure Studies, Chienkuo Technology University,No. 1, Chieh Shou N Rd.,Chang Hua 500, Taiwan,R.O.C. 3 Professor, Department of Business Administration, Asia University, Taichung, Taiwan 4 Assistant Professor, Department of Business Administration, Asia University, Taichung, Taiwan a [email protected], b [email protected], c [email protected] 2

Keywords: Serious leisure traits, leisure internal motivation, leisure benefits, sense of happiness, moderating variable

Abstract. This study aims to probe into causal relationship among “serious leisure traits”, “leisure internal motivation”, “leisure benefits” and “sense of happiness” and further examines the mediating roles of “leisure internal motivation” and “leisure benefits”. Research design is based on questionnaire survey. Bicyclists of 2009 Giant Cup, 2009 “Mountain Tour and Sea Appreciation, Challenge 100” cycling in Miaoli and 2009 Taichung 100K Cycling Race are treated as the subjects. The researcher conducts investigation on the fields by convenience sampling and acquires 500 valid samples. According to research findings, serious leisure traits positively influence leisure internal motivation, leisure benefits and sense of happiness. Leisure internal motivation positively influences leisure benefits and sense of happiness. Leisure benefits positively influence sense of happiness. Leisure internal motivation and leisure benefits play partial moderating roles between serious leisure traits and sense of happiness. Overall explained power of serious leisure traits, leisure internal motivation and leisure benefits on sense of happiness is 88%. Research findings aim to serve as reference for governmental departments in the promotion of bicycle activities, private bicycle groups’ or firms’ strategies of bicycle activities and market expansion and future academic studies. Introduction Leisure activities can be the necessary measures to be healthy, pursue high-quality lives and have sense of happiness (Godbey, 2003). Appropriate leisure exercises can release stress in lives and allow people to have positive feelings and avoid negative emotion (Iso-Ahola & Park, 1996; Siegenthaler, 1997; Chang, 2006; Chang, 2008). Leisure activities can balance life experience, complete life content and enhance life quality (Kao, 1995). According to past research, exercises can positively influence sense of happiness (Giii, Williams, Morgan, & Bath, 1997). Leisure benefits obtained by serious leisure trait participants are positive and significant (Russell, 1987). Chen, Ou, and Ou (2009) demonstrated that serious leisure traits positively influence sense of happiness. Leisure benefits play moderating role between sports involvement frequency and sense of happiness (Chen & Huang, 2007; Li & Hong, 2008). According to related studies, enduring involvement will positively influence leisure benefits and sense of happiness. Leisure benefits will positively influence sense of happiness. Leisure benefit is the moderating variable between enduring involvement and sense of happiness. Thus, this study aims to probe into relationship among serious leisure traits, internal leisure motivation, leisure benefits and sense of happiness, tries to construct causal model of leisure psychological behavior of serious leisure traits, leisure internal motivation, leisure benefits and sense of happiness and further explores the moderating roles of leisure internal motivation and leisure benefits in serious leisure traits, leisure internal motivation and sense of happiness. The empirical research finding on participants of cycling leisure activities serves as reference for governmental departments and firms in future promotion of cycling activities and academic research.

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Research Method Research Structure

Fig.1 Model of hypotheses Research subjects and sampling analysis. As to sampling, this study adopts convenience sampling in non-random sampling. On October 18, 2009, it adopted questionnaire pretest on participants of “2009 Giant Cup”. 350 questionnaires were distributed, with a total of 316 returns. After eliminating 11 invalid questionnaires, the researcher obtained 305 valid questionnaires. Return rate is 87.1%. In “2009 Mountain Tour and Sea Appreciation, Challenge 100 in Miaoli” cycling on October 31, 2009 and “2009 Taichung 100K Cycling Race” on November 15, 2009, formal questionnaires were conducted on the bicyclists. 600 questionnaires were distributed, with a total of 543 returns. After eliminating 43 invalid questionnaires, the researcher obtained 500 valid ones. Return rate is 83.3%. Research Tools. (1) Scale of serious leisure traits It is revised according to six serious leisure traits proposed by Stebbins (1992) and scale of serious leisure traits developed by Liang Ying-wen, Tsao (2007) and Chen et al.,(2009), with a total of 6 constructs and 23 items. Cronbach’s α of overall scale is 0.93. Reliability of six constructs are 0.66, 0.73, 0.78, 0.89, 0.79 and 0.91. (2) Scale of leisure internal motivation It is revised according to scale of leisure internal motivation constructed by Weissinger and Bandalos (1995), with a total of 4 constructs and 17 items. Cronbach’s α of overall scale is 0.82. Reliability of four constructs are 0.43, 0.58, 0.30 and 0.83. (3) Scale of leisure benefits It is revised according to scale of leisure benefits constructed by Kao (1995), with a total of 3 constructs and 11 items. Cronbach’s α of overall scale is 0.91. Reliability of three constructs are 0.90, 0.88 and 0.67. (4) Scale of sense of happiness It is revised according to scale of sense of happiness constructed by Andrew and Withy (1976), with a total of 3 constructs and 13 items. Cronbach’s α of overall scale is .83. Reliability of three constructs are 0.81, 0.93, 0.97 and 0.83. In this study, after Confirmatory Factor Analysis, fit measures of the scales are acceptable. Discriminant validity means to measure two different constructs. If correlation between two constructs is low after correlation analysis, it means there is discriminant validity between two constructs (Anderson & Gerbing, 1988; Churchill, 1979). As to test of discriminant validity, the judgment in this study is that square roots of AVE of constructs are higher than numbers of correlation coefficients of constructs and they should be at least 75% of comparison numbers (Hair, Black, Babin, Anderson, & Tatham, 2006). Thus, square roots of AVE of constructs are 0.59~ 0.88, which are higher than correlation coefficients between the constructs. The analytical result shows that the constructs match the criteria of judgment. Thus, the scales have discriminant validity.

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Results Overall fit measurement of hypothesis model. Model of this study is acceptable. The researcher thus examines hypotheses and causal relationship among variables. Overall fit measures are shown in Table 2: Table 2 Overall fit measures of hypothesis model Relative Fit Measure

Parsimonious Normed Fit

Absolute Fit Measure

Evaluation

Measure indicators Hypothesis model

χ²

df

348.45

96

χ²/ df

3.63

Acceptance value

0 , surface element is visible. cos α is defined as

n⋅s cos α =

. (13) n⋅s To judge shelter on the surface element, we need to analyze whether there is point of intersection exits of rays from probe points to the center of surface element and other surface elements. Suppose the rays from probe points to the center of surface element are expressed as 
P ( t ) = P0 + t ⋅ f . (14)
Where P0 represents as the start point of the rays in Eq.14. f is expressed as the ray of the direction

vector. Besides f = − s and t ∈ [0, ∞] . The plane on which the space shelter of the surface element exists can be expressed as follow
n ⋅ ( P − Pm ) = 0. (15)

Suppose d = − n ⋅ Pm , then n ⋅ Pm + d = 0 . Where Pm is an arbitrarily point on the plane in Eq.15.
Symbol n is the unit normal vector of the surface element. Substitute the ray equation into Eq.15 and we can obtain an equation as follow
− n ⋅ P0 − d t= (16)

. n⋅ f If t = 0 , we can confirm that there is point of intersection rays from probe points to the center of surface element and other surface elements.

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The simulation of target optical properties in near space In the simulation, the longitude and latitude of the target in near space is set as ( E116.6°，N 39.9°) , and the distance from the ground is set as 40km. Four observation ways of outerspace(OS)-based, space-based, nearspace(NS)-based and ground-based are set in the simulation. Moreover, three appropriate locations are determined for each detection method. The simulation time is set in 2012.05.04 . calculate the solar zenith angle, azimuth angle and corresponding simulation parameters such as time of the target can be calculated by using the longitude and latitude ( E116.6°，N 39.9° ) . The simulation results are shown in Fig.3.

(a)SNR of the visible spectrum (ground-based)

(b)SNR of near-infrared spectrum (ground-based)

(c) SNR of the visible spectrum (space-based)

(d) SNR of near-infrared spectrum (space-based)

(e) SNR of the visible spectrum (NS-based)

(f) SNR of near-infrared spectrum (NS-based)

(g) SNR of the visible spectrum (OS-based)

(h) SNR of near-infrared spectrum (OS-based)

Figure 3 The simulation results of an aerostat optical properties in the sky somewhere Conclusion

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Three conclusions can be drawn from the result. Firstly, once the detection time and height have b een fixed, signal-to-noise ratio is almost on the decline if the detection angle increases; when the val ue of SNR is fixed, the spectral visual area of visible light moves backward; Secondly, once the dete ction position and target position have been fixed, the signal-to-noise ratio is almost on the rise if the sun zenith angle of the target increases; when the value of SNR is fixed, the spectral visual area of v isible light moves backward; Finally, Under the condition of we set in this simulation, the performan ce of space-based platform is the best. More detection windows can be used and the signal-to-noise r atio is highest.

Conclusion We have presented an improved target optical properties modeling method based on the reverse Monte Carlo light tracking. The invalid light can be eliminated adaptively meanwhile the environment illumination characteristic, different light transmission characteristics and atmospheric characteristics in near space are considered in detail. The target optical properties required can be obtained efficiently and accurately by using the proposed modeling method. The results of the numerical simulations can be used to analysis the best observation position and time for the low-speed target in near space. Besides, this research provides a theoretical basis and data support for the further demonstration of low-speed target detection and recognition system.

References [1] Wang H, Zhang W. Infrared characteristics of on-orbit targets based on space-based optical observation. Opt Commun (2013); 290: 69-75. [2] Zhu D, Shen W, Cai G. Numerical simulation and experimental study of factors influencing the optical characteristics of a spatial target. Appl. Therm. Eng. (2013); 50: 749-762. [3] Zhang W, Wang H, Wang Z. Modeling method for visible scattering properties of space target. Acta Photonica Sinica (2008); 37: 2462-67. [4] Anthony C. Initial feasibility assessment of a high altitude long endurance airship. NASA CR (2003); 212724. [5] Hurtado J, Barbat A. Monte Carlo techniques in computational stochastic mechanics. Arch Comput Meth Eng (1998); 5: 3-29. [6] Schueller G, Calvi A, Pellissetti M, Paradlwarter H. Uncertainty analysis of a large-scale satellite finite element model. J Spacecraft Rockets (2009); 46: 191-202. [7] Guimaraes M, Costa B, Pires A, Souza A. Phase diagram of the 3D quantum anisotropic XY model-A quantum Monte Carlo calculation. J Magn Magn Mater (2013); 332: 103-108. [8] Nagy, N, Simon, P. Monte Carlo simulation and analytic approximation of epidemic processes on large networks. Cent Eur J Mathe (2013); 11: 800-15. [9] McAuley, G, Barnes, S, Slater, J. Monte Carlo simulation of single-plane magnetically focused narrow proton beams. Hhys Med Biol (2011); 49: 542-6. [10] Drovandi C, McGree, J, Pettitt, A. Sequential Monte Carlo for Bayesian sequentially designed experiments for discrete data. Comp Stati Data Anal (2013); 57: 320-35. [11] Lin Y, Wang F, Zheng, X. Monte Carlo simulation of the Ising model on FPGA. J Comp Phys (2013); 237: 224-34. [12] Subramanian H, Pradhan P, Kim Y. Modeling low-coherence enhanced backscattering using Monte Carlo simulation. Appl Opt (2006); 45: 6292-300. [13] Machado K, Sanchez D, Brunatto S. Reverse Monte Carlo simulations of an amorphous Se-0 S-90(0) (10) alloy produced by mechanical alloying combining XRD and EXAFS data. J Non-Cryst Solids (2010); 356: 2865-68. [14] Zotov N, Schlenz H, Beck, J. Structural study of amorphous Te2X (X = Br, I): X-ray diffraction, neutron diffraction and reverse Monte Carlo simulations. J Non-Cryst Solids (2005); 351: 37-9.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 849-854 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.849

Application of Maple on the Integral Problems Chii-Huei Yu Department of Management and Information, Nan Jeon University of Science and Technology, Tainan City, Taiwan Email: [email protected] Keywords: integrals, hyperbolic functions, geometric series, integration term by term theorem, Maple.

Abstract. This paper takes the mathematical software Maple as the auxiliary tool to study four types of integral problems related to hyperbolic functions. We can obtain the infinite series forms of these four types of integrals by using geometric series and integration term by term theorem. The research methods adopted in this study involved finding solutions through manual calculations and verifying these solutions by using Maple. This type of research method not only allows the discovery of calculation errors, but also helps modify the original directions of thinking from manual and Maple calculations. For this reason, Maple provides insights and guidance regarding problem-solving methods. Introduction The computer algebra system (CAS) has been widely employed in mathematical and scientific studies. The rapid computations and the visually appealing graphical interface of the program render creative research possible. Maple possesses significance among mathematical calculation systems and can be considered a leading tool in the CAS field. The superiority of Maple lies in its simple instructions and ease of use, which enable beginners to learn the operating techniques in a short period. In addition, through the numerical and symbolic computations performed by Maple, the logic of thinking can be converted into a series of instructions. The computation results of Maple can be used to modify previous thinking directions, thereby forming direct and constructive feedback that can aid in improving understanding of problems and cultivating research interests. Inquiring through an online support system provided by Maple or browsing the Maple website (www.maplesoft.com) can facilitate further understanding of Maple and might provide unexpected insights. For the instructions and operations of Maple, we can refer to [1-7]. In calculus and engineering mathematics course, we learnt many methods to solve the integral problems, including change of variables method, integration by parts method, partial fractions method, trigonometric substitution method, and so on. This paper studied the following four types of integrals related to hyperbolic functions, which are not easy to obtain their answers by using the methods mentioned above.

∫e

ax

tanh( bx + c ) dx

(1)

∫e

ax

coth(bx + c )dx

(2)

∫e

ax

sech (bx + c )dx

(3)

∫e

ax

csch (bx + c )dx

(4)

, where a, b, c are real numbers. We can determine the infinite series forms of these four types of integrals by using geometric series and integration term by term theorem ; these are the main results of this study (i.e., Theorems 1 , 2, 3 and 4). On the other hand, we provide four definite integrals to do calculation practically. The research methods adopted in this study involved finding solutions through manual calculations and verifying these solutions by using Maple. This type of research method not only allows the discovery of calculation errors, but also helps modify the original

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directions of thinking from manual and Maple calculations. Therefore, Maple provides insights and guidance regarding problem-solving methods. As for the study of integral problems can refer to [8-14]. Main results Firstly, we introduce two important theorems used in this study. Geometric series. ∞

If u < 1 , then

1 1 k = ∑ u , and = 1 − u k =0 1+ u

∞

∑ ( − 1) k u k . k =0

Integration term by term theorem ([15]). Suppose that {g n }n∞= 0 is a sequence of Lebesgue integrable functions defined on inteval I . If ∞

∑ ∫I

∞

gn

is convergent, then

n=0

∫I ∑ g n n=0

∞

=

∑ ∫I g n

.

n=0

Next, we derive the first integral result which is related to hyperbolic tangent function. Theorem 1. Assume a, b, c are real numbers, and a, b ≠ 0 . (i) If bx + c > 0 and

a is not a positive integer, then the integral 2b

ax ∫ e tanh(bx + c)dx =

(ii) If bx + c < 0 and −

∞ 1 ax ( −1) k − 2 k ( bx + c ) e + 2 e ax ⋅ ∑ e +C a k = 1 a − 2 kb

a is not a positive integer, then 2b

ax ∫ e tanh( bx + c ) dx = −

Proof. (i) If bx + c > 0 and

∫e

ax

= ∫e

ax

= ∫ e ax

(5)

∞ ( −1) k 1 ax e − 2 e ax ⋅ ∑ e 2 k ( bx + c ) + C a a + kb 2 k =1

a is not a positive integer, we obtain 2b

tanh( bx + c ) dx

e bx + c − e − ( bx + c ) e bx + c + e − ( bx + c ) 1 − e − 2 ( bx + c ) 1 + e − 2 ( bx + c )

dx

dx

2   = ∫ e ax  − 1 +  dx − 2 ( bx + c ) 1+ e   ∞   = ∫ e ax  1 + 2 ∑ ( − 1) k e − 2 k ( bx + c )  dx   k =1  

(by geometric series )

=

∞ 1 ax e + 2 ⋅ ∑ ( − 1) k e − 2 kc ∫ e ( a − 2 kb ) x dx a k =1

=

∞ ( − 1) k 1 ax e + 2 e ax ⋅ ∑ e − 2 k ( bx + c ) + C . a a − 2 kb k =1

(by integration term by tern theorem)

(6)

Applied Mechanics and Materials Vols. 479-480

(ii) If bx + c < 0 and −

∫e

ax

851

a is not a positive integer, by (i) of this theorem, we obtain 2b

tanh( bx + c ) dx = − ∫ e ax tanh[ − ( bx + c )] dx =−

∞ ( − 1) k 1 ax e − 2 e ax ⋅ ∑ e 2 k ( bx + c ) + C a k =1 a + 2 kb

€

The same proof as Theorem 1, we have the following integral result related to hyperbolic cotangent functions. Theorem 2. Let the assumptions be the same as Theorem 1. a is not a positive integer, then 2b

(i)If bx + c > 0 and

∫e

ax

coth( bx + c ) dx

(ii)If bx + c < 0 and −

=

∞ 1 ax 1 e + 2 e ax ⋅ ∑ e − 2 ( bx + c ) k + C a k =1 a − 2 kb

(7)

a is not a positive integer, then 2b

ax ∫ e coth( bx + c ) dx = −

∞ 1 ax 1 e − 2 e ax ⋅ ∑ e 2 ( bx + c ) k + C a a + 2 kb k =1

(8)

Secondly, we determine the integral related to hyperbolic secant function. Theorem 3. Suppose a , b, c are real numbers and b ≠ 0 . a is not a positive odd integer, then b

(i)If bx + c > 0 and

( −1) k +1 e − ( 2 k −1)( bx + c ) + C ( 2 1 ) a − k − b k =1 ∞

ax ax ∫ e sech (bx + c )dx = 2 ⋅ e ∑

(ii)If bx + c < 0 and −

(9)

a is not a positive odd integer, then b ( −1) k +1 e ( 2 k −1)( bx + c ) + C k =1 a + ( 2 k − 1)b ∞

ax ∫ e sech (bx + c)dx = 2 ⋅ e ax ∑

a is not a positive odd integer, then b

Proof. (i) If bx + c > 0 and

∫e

ax

= ∫ e ax

= ∫ e ax

sech ( bx + c ) dx 2 e bx + c + e − ( bx + c )

2 e − ( bx + c ) 1 + e − 2 ( bx + c )

= ∫ 2 e ax

dx

dx

∞

∑ ( − 1) k +1 e − ( 2 k −1)( bx + c ) dx

(by geometric series )

k =1 ∞

= 2⋅

∑ ( − 1) k +1 e − ( 2 k −1) c ∫ e[ a − ( 2 k −1)b ] x dx k =1

= 2 ⋅ e ax

( −1) k +1 ∑ a − ( 2 k − 1)b e − ( 2 k −1)( bx + c ) + C . k =1 ∞

(by integration term by tern theorem)

(10)

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Applied Science and Precision Engineering Innovation

(ii)If bx + c < 0 and −

∫e

ax

a is not a positive odd integer, by (i) of this theorem, we obtain b

ax sech (bx + c )dx = ∫ e sech [ −(bx + c )]dx

= 2 ⋅ e ax

( −1) k + 1 ∑ a + ( 2k − 1)b e ( 2k −1)( bx + c ) + C k =1 ∞

€

Also, using the same proof as Theorem 3, we obtain the following integral result related to hyperbolic cosecant function. Theorem 4. If the assumptions are the same as Theorem 3. a is not a positive odd integer, then b

(i)If bx + c > 0 and

∞

1 e − ( 2 k −1)( bx + c ) + C a − k − b ( 2 1 ) k =1

ax ∫ e sech (bx + c)dx = 2 ⋅ e ax ∑

(11)

a (ii)If bx + c < 0 and − is not a positive odd integer, then b

ax ax ∫ e sech (bx + c )dx = −2 ⋅ e

∞

1

∑ a + ( 2k − 1)b e ( 2 k −1)( bx + c ) + C

(12)

k =1

Examples In the following, we propose four definite integrals and use our main theorems to evaluate their infinite series forms. Simultaneously, we employ Maple to calculate the approximations of these definite integrals and their infinite series forms for verifying our answers. Example 1. By Theorem 1, we obtain the infinite series form of the following definite integral related to hyperbolic tangent function ∞ ( −1) k 1 12 3 4x 4 = ( e − e ) + 2 ⋅ e tanh( 6 x + 5 ) dx (13) ∑ 4 − 12k ( e12 − 46k − e 4 − 22 k ) ∫1 4 k =1 Next, we use Maple to calculate this definite integral and its infinite series form. >evalf(int(exp(4*x)*tanh(6*x+5),x=1..3),14); 40675.048317238 >evalf((exp(12)-exp(4))/4+2*sum((-1)^k/(4-12*k)*(exp(12-46*k)-exp(4-22*k)),k=1..infinity),14); 40675.048317238 Example 2. Using Theorem 2, we can determine the infinite series form of the following definite integral related to hyperbolic cotangent function ∞ 1 3 6 1 −1 − 3 x = ( e − e ) − 2 ⋅ ( e 3−14 k − e 6 − 20 k ) e coth( 3 x − 4 ) dx (14) ∑ ∫− 2 3 k =1 − 3 + 6 k Also, we use Maple to verify our answer. >evalf(int(exp(-3*x)*coth(3*x-4),x=-2..-1),14);

>evalf((exp(3)-exp(6))/3-2*sum(1/(-3+6*k)*(exp(3-14*k)-exp(6-20*k)),k=1..infinity),14); Example 3. By Theorem 3, we obtain the infinite series form of the following definite integral related to hyperbolic secant function 5 4 5x e 12

∫

( −1) k +1 41 4 − 8 k (e − e7 9 − 8 k k =1 ∞

sech ( 4 x − 1) dx = 2 ⋅ ∑

2 − 2k

)

(15)

Applied Mechanics and Materials Vols. 479-480

853

We also employ Maple to verify our answer. >evalf(int(exp(5*x)*sech(4*x-1),x=1/2..5/4),14); 9.8497745605814 >evalf(2*sum((-1)^(k+1)/(9-8*k)*(exp(41/4-8*k)-exp(7/2-2*k)),k=1..infinity),14); 9.8497745605818 Example 4. From Theorem 4, we can determine the following definite integral related to hyperbolic cosecant function 2 −4 x e 1

∫

∞

1 ( e − 7 − 2 k − e −1− 6 k ) k =1 − 6 + 4 k

csch ( 2 x − 5 ) dx = −2 ⋅ ∑

(16)

Using Maple to calculate the definite integral and its infinite series form as follows: >evalf(int(exp(-4*x)*csch(2*x-5),x=1..2),14); >evalf(-2*sum(1/(-6+4*k)*(exp(-7-2*k)-exp(-1-6*k)),k=1..infinity),14);

Conclusion As mentioned, the geometric series and the integration term by term theorem play significant roles in the theoretical inferences of this study. In fact, the applications of these two theorems are extensive, and can be used to easily solve many difficult problems; we endeavor to conduct further studies on related applications. On the other hand, Maple also plays a vital assistive role in problem-solving. In the future, we will extend the research topic to other calculus and engineering mathematics problems and solve these problems by using Maple. These results will be used as teaching materials for Maple on education and research to enhance the connotations of calculus and engineering mathematics.

References [1] [2] [3] [4]

M.L. Abell and J.P. Braselton: Maple by Example, 3rd ed., Elsevier Academic Press (2005). J.S. Robertson: Engineering Mathematics with Maple, McGraw-Hill (1996). F. Garvan: The Maple Book, Chapman & Hall/CRC (2001). D. Richards: Advanced Mathematical Methods with Maple, Cambridge University Press (2002). [5] C. Tocci and S.G. Adams: Applied Maple for Engineers and Scientists, Artech House (1996). [6] C.T.J. Dodson and E.A. Gonzalez: Experiments in Mathematics Using Maple, Springer-Verlag (1995). [7] R.J. Stroeker and J.F. Kaashoek: Discovering Mathematics with Maple : An Interactive Exploration for Mathematicians, Engineers and Econometricians, Birkhauser Verlag (1999). [8] C.-H. Yu: Application of Maple:Taking Two Special Integral Problems as Examples, The 8th International Conference on Knowledge Community, Chinese Culture University, Taiwan (2012), pp.803-811. [9] C.-H. Yu: Application of Maple on Some Integral Problems, International Conference on Safety & Security Management and Engineering Technology 2012, WuFeng University, Taiwan (2012), pp. 290-294. [10] C.-H. Yu: Application of Maple on the Integral Problem of Some Type of Rational Functions, Annual Meeting and Academic Conference for Association of IE, 2012, Da-Yeh University, Taiwan (2012), D357-D362. [11] C.-H. Yu: Application of Maple on Some Type of Integral Problem, Ubiquitous-Home Conference 2012, Kun Shan University, Taiwan (2012), pp.206-210.

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Applied Science and Precision Engineering Innovation

[12] C.-H. Yu: Application of Maple on Evaluating the Closed Forms of Two Types of Integrals, The 17th Mobile Computing Workshop, Chang Gung University, Taiwan (2012), ID16. [13] K.N. Boyadzhiev and V. H. Moll:The Integrals in Gradshteyn and Ryzhik. Part 21: Hyperbolic Functions, Scientia, Series A: Mathematical Sciences, Vol. 22 (2011), pp.109-127. [14] J.H. Barnett: Enter, Stage Center: the Early Drama of the Hyperbolic Functions, Mathematics Magazine, Vol. 77, No. 1 (2004), pp.15-30. [15] T.M. Apostol: Mathematical Analysis, 2nd ed., Addison-Wesley (1975), p269.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 855-860 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.855

Application of Maple on Solving the Differential Problem of Rational Functions Chii-Huei Yu Department of Management and Information, Nan Jeon University of Science and Technology, Tainan City, Taiwan Email: [email protected] Keywords: rational functions, binomial theorem, Maple.

Abstract. This paper uses the mathematical software Maple as the auxiliary tool to study the differential problem of four types of rational functions. We can obtain the closed forms of any order derivatives of these rational functions by using binomial theorem. On the other hand, we propose four examples to do calculation practically. The research methods adopted in this study involved finding solutions through manual calculations and verifying these solutions by using Maple. This type of research method not only allows the discovery of calculation errors, but also helps modify the original directions of thinking from manual and Maple calculations. For this reason, Maple provides insights and guidance regarding problem-solving methods. Introduction The computer algebra system (CAS) has been widely employed in mathematical and scientific studies. The rapid computations and the visually appealing graphical interface of the program render creative research possible. Maple possesses significance among mathematical calculation systems and can be considered a leading tool in the CAS field. The superiority of Maple lies in its simple instructions and ease of use, which enable beginners to learn the operating techniques in a short period. In addition, through the numerical and symbolic computations performed by Maple, the logic of thinking can be converted into a series of instructions. The computation results of Maple can be used to modify previous thinking directions, thereby forming direct and constructive feedback that can aid in improving understanding of problems and cultivating research interests. Inquiring through an online support system provided by Maple or browsing the Maple website (www.maplesoft.com) can facilitate further understanding of Maple and might provide unexpected insights. For the instructions and operations of Maple, we can refer to [1-5]. In calculus courses, determining the n -th order derivative value f (n) (c) of a function f ( x ) at x = c , in general, needs two procedures: firstly finding the n -th order derivative f ( n ) ( x ) of f ( x ) ,

and secondly taking x = c into f (n) ( x) . These two procedures will make us face with increasingly complex calculations when calculating higher-order derivative values of a function (i.e. n is large). Therefore, to obtain the answers by manual calculations is not an easy thing. Aimed at this difficult problem, this paper studies the differential problem of the following four types of rational functions

f1 ( x ) =

f2 ( x) =

g1 ( x ) =

m / 2   m  ∑  2 p  a 2 p ( bx + c ) m − 2 p  p=0 

[( bx + c ) 2 − a 2 ]m

m / 2   m  ∑  2 p  ( − 1) p a 2 p ( bx + c ) m − 2 p  p =0 

[( bx + c ) 2 + a 2 ]m

( m +1) / 2   m  ∑  2 p − 1 a 2 p −1 ( bx + c ) m − 2 p +1   p =1

[( bx + c ) 2 − a 2 ]m

(1)

(2)

(3)

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Applied Science and Precision Engineering Innovation

g 2 ( x) =

(m +1) / 2  m  ∑  2 p − 1(−1) p +1 a 2 p −1(bx + c)m − 2 p +1  p =1 

(4)

[(bx + c) 2 + a 2 ]m

, where a, b, c are real numbers and m is a positive integer. We can determine the closed forms of any order derivatives of these four types of rational functions by using binomial theorem ; these are the main results of this study (i.e., Theorems 1-4), and hence greatly reduce the difficulty of evaluating their higher order derivative values. As for the study of rational functions can refer to [6-8]. On the other hand, we provide four examples of rational functions to do calculation practically. The research methods adopted in this study involved finding solutions through manual calculations and verifying these solutions by using Maple. This type of research method not only allows the discovery of calculation errors, but also helps modify the original directions of thinking from manual and Maple calculations. Therefore, Maple provides insights and guidance regarding problem-solving methods. Main results Firstly, we introduce some notations used in this paper. Notations. (i) Assume r is a real number and n is a positive integer. Define [ r ]n = r ( r + 1) ⋅ ⋅ ⋅ ( r + n − 1) , and [r ]0 = 1 . (ii)Suppose s is any real number, the largest integer less than or equal to s is denoted by s  . (iii) the imaginary number i = − 1 . Next, we introduce an important theorem used in this paper. Binomial theorem ([9]). If u, v are real numbers, m is any positive integer, then ( u + v ) m =  m  k m −k  u v  k = 0 m

m

m!

, where   = .  k  k ! ( m − k )! In the following, we derive four major results in this paper. Firstly, we determine any order derivatives of the function (1). Theorem 1. Assume a, b, c are any real numbers, m, n are any positive integers. Suppose the

∑  k

domain of the function

m / 2   m  ∑   a 2 p ( bx + c ) m − 2 p p=0  2 p 

f1 ( x ) =

[( bx + c ) 2 − a 2 ] m

is {x ∈ R bx + c ≠ ±a} . Then the n -th

order derivative of f1 ( x ) , ( −1) n b n [m ]n ⋅

f1( n ) ( x ) = m

( m + n ) / 2   m + n  ∑  2 p a 2 p (bx + c) m + n − 2 p   p =0

[( bx + c ) 2 − a 2 ]m + n

(5)

m

∑  k  a k [1 + ( − 1) k ]( bx + c ) m − k

1 k =0  ⋅ 2

Proof. Because f1 ( x ) =

m

=

 [( bx + c ) 2 − a 2 ]m

m

m

m

∑  k a k ( bx + c ) m − k + ∑  k ( − a ) k (bx + c ) m − k

1 k =0   ⋅ 2

k =0   [( bx + c ) 2 − a 2 ]m

=

1 [( bx + c ) + a ]m + [( bx + c ) − a ]m ⋅ 2 [( bx + c ) 2 − a 2 ]m

=

1 2

 1 1 ⋅ + m  [( bx + c ) − a ] [( bx + c ) + a ] m

, the n -th order derivative of f1 ( x ) ,

(by binomial theorem)   

(6)

Applied Mechanics and Materials Vols. 479-480

f1( n ) ( x ) = =

1 dn ⋅ 2 dx n

 1 1 +  m  [( bx + c ) − a ] [( bx + c ) + a ]m

857

  

  1 1 1 ⋅ ( −1)n bn [m]n  +  2  [(bx + c) − a ]m + n [(bx + c) + a ]m + n  ( −1) n b n [m ]n ⋅

=

( m + n ) / 2  m + n  ∑  2 p a 2 p (bx + c)m + n − 2 p   p=0

[(bx + c ) 2 − a 2 ]m + n

■

In Theorem 1, taking ia instead of a , we immediately obtain any order derivatives of the function (2). Theorem 2. If the assumptions are the same as Theorem 1, and a 2 + b 2 + c 2 ≠ 0 . Suppose the domain of the function

f2 ( x) =

m / 2   m  ∑  2 p  ( − 1) p a 2 p ( bx + c ) m − 2 p  p =0 

derivative of f 2 ( x ) , f 2( n ) ( x ) =

is ( −∞, ∞ ) . Then the n -th order

[( bx + c ) 2 + a 2 ]m (m + n ) / 2  m + n  ( −1) p a 2 p (bx + c) m + n − 2 p ( −1) n bn [m]n ⋅ ∑  2 p   p =0

[(bx + c) 2 + a 2 ]m + n

(7)

Next, we find any order derivatives of the function (3). Theorem 3. The assumptions are the same as Theorem 1, and a 2 + b2 + c 2 ≠ 0 . Suppose the domain of the function

g1 ( x ) =

( m +1) / 2   m  ∑  2 p − 1  a 2 p −1 ( bx + c ) m − 2 p +1   p =1

[( bx + c ) 2 − a 2 ]m

is {x ∈ R bx + c ≠ ±a}. Then the n -th

order derivative of g1 ( x ) , ( −1) n b n [m ]n ⋅

g1( n ) ( x ) =

( m + n +1) / 2   m + n  ∑  2 p − 1a 2 p −1 (bx + c) m + n − 2 p +1   p =1

[(bx + c ) 2 − a 2 ]m + n

(8)

Proof. The same proof as Theorem1, we have  1 1 ⋅ − m  [( bx + c ) − a ] [( bx + c ) + a ] m Thus, the n -th order derivative of g1 ( x ) ,

g1 ( x ) =

1 2

( −1) n bn [m]n ⋅

g1( n ) ( x ) =

  

(m + n +1) / 2  m + n  ∑  2 p − 1a 2 p −1(bx + c)m + n −2 p +1   p =1

[(bx + c) 2 − a 2 ]m + n

(9)

■

In Theorem 3, taking ia instead of a , and using the same proof as Theorem 3, we can determine any order derivatives of the function (4). Theorem 4. If the assumptions are the same as Theorem 1, and a 2 + b 2 + c 2 ≠ 0 . Suppose the domain of the function g 2 ( x ) =

( m +1) / 2   m  ∑  2 p − 1( −1) p +1 a 2 p −1 (bx + c ) m − 2 p +1  p =1 

[( bx + c ) 2 + a 2 ]m

is ( −∞, ∞ ) . Then the n -th

order derivative of g 2 ( x ) , (−1) n bn [m]n ⋅

g 2(n ) ( x ) =

(m + n +1) / 2  m + n  ∑  2 p − 1(−1) p +1 a 2 p −1(bx + c)m + n − 2 p +1   p =1

[(bx + c) 2 + a 2 ]m + n

(10)

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Examples In the following, we propose four examples of rational functions and use our theorems to determine the closed forms of their any order derivatives and calculate some of their higher order derivative values practically. At the same time, we employ Maple to verify our answers. Example 1. Suppose the domain of the function f1 ( x ) =

(3 x − 2 ) 5 + 160 (3 x − 2 ) 3 + 1280 ( 3 x − 2 ) [( 3 x − 2 ) 2 − 4 2 ]5

(11)

is {x ∈ R 3x − 2 ≠ ±4}. By Theorem 1, the closed form of the any n -th order derivative of f1 ( x ) , ( −1) n 3n [5]n ⋅

f1( n ) ( x ) =

(5+ n ) / 2   5 + n  ∑  2 p 42 p (3x − 2)5+ n − 2 p  p =0 

[(3 x − 2) 2 − 4 2 ]5+ n

(12)

Thus, the 6 -th order derivative value of f1 ( x ) at x = 3 , 3 6 [ 5 ]6 ⋅

f1(6) (3) =

 11  2 p 11 − 2 p   4 ⋅ 7 p =0  2 p  5

∑

33 11

(13)

We use Maple to calculate f1( 6) (3) and its closed form as follows: >f1:=x->((3*x-2)^5+160*(3*x-2)^3+1280*(3*x-2))/((3*x-2)^2-4^2)^5; >evalf((D@@6)(f1)(3),20); 311.11130427671096889 >evalf(3^6/33^11*product(5+j,j=0..5)*sum(11!/((2*p)!*(11-2*p)!)*4^(2*p)*7^(11-2*p),p=0..5),20); 311.11130427671096889

Example 2.

If the domain of the function f2 ( x) =

( 4 x + 5) 4 − 54 ( 4 x + 5) 2 + 81 [( 4 x + 5) 2 + 32 ]4

(14)

is ( −∞, ∞) . Using Theorem 2, we obtain the closed form of any n -th order derivative of f 2 ( x ) , ( −1) n 4 n [4]n ⋅

f 2(n ) ( x) =

( 4 + n ) / 2  4 + n  ∑  2 p ( −1) p 32 p (4 x + 5)4 + n − 2 p  p =0 

[(4 x + 5) 2 + 32 ]4 + n

(15)

Therefore, the 8 -th order derivative value of f 2 ( x ) at x = −2 , 4 8 [ 4 ]8 ⋅

f 2 (8 ) ( −2 ) =

 12    ( − 1 ) p 3 2 p ⋅ ( − 3 ) 12 − 2 p 2 p   p=0 6

∑

18 12

(16)

In the following, we employ Maple to calculate f 2 (8) ( −2) and its closed form to verify our answer. >f2:=x->((4*x+5)^4-54*(4*x+5)^2+81)/((4*x+5)^2+3^2)^4; >evalf((D@@8)(f2)(-2),20); >evalf(4^8/18^12*product(4+j,j=0..7)*sum(12!/((2*p)!*(12-2*p)!)*(-1)^p*3^(2*p)*(-3)^(12-2*p),p=0..6),20);

Example 3. Suppose the domain of the function g1 ( x ) =

24 ( 7 x − 5) 5 + 1280 ( 7 x − 5) 3 + 6144 ( 7 x − 5) [( 7 x − 5) 2 − 4 2 ]6

(17)

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is {x ∈ R 7 x − 5 ≠ ±4}. By Theorem 3, we obtain the closed form of any n -th order derivative of ( −1) n 7 n [6]n ⋅

g1( x) ,

g1( n ) ( x ) =

( 7 + n ) / 2   6 + n  ∑  2 p − 142 p −1 (7 x − 5) 7 + n − 2 p  p =1 

[( 7 x − 5) 2 − 4 2 ]6 + n

(18)

Hence, the 7 -th order derivative value of g1 ( x ) at x = 1 , g1(7 ) (1) =

7 7 [6 ]7 ⋅

7

 13  2   4 p = 1 2 p − 1 

∑

In the following, we use Maple to calculate

12 13 g1( 7 ) (1)

p −1

⋅ 2 14

−2p

(19) and its closed form.

>g1:=x->(24*(7*x-5)^5+1280*(7*x-5)^3+6144*(7*x-5))/((7*x-5)^2-4^2)^6; >evalf((D@@7)(g1)(1),20); >evalf(7^7/12^13*product(6+j,j=0..6)*sum(13!/((2*p-1)!*(14-2*p)!)*4^(2*p-1)*2^(14-2*p),p=1..7),20);

Example 4.

Let the domain of the function 1 g2 ( x) = ⋅ [24( 2 x + 1) 7 − 1512( 2 x + 1)5 + 13608 ( 2 x + 1) 3 − 17496 ( 2 x + 1)] (20) 2 2 8 [( 2 x + 1) + 3 ] be ( −∞, ∞ ) . Using Theorem 4, we obtain the closed form of any n -th order derivative of ( −1) n 2 n [8]n ⋅

g2 ( x) ,

g 2( n ) ( x ) =

( 9 + n ) / 2  8 + n  ∑  2 p − 1( −1) p +1 32 p −1 (2 x + 1) 9 + n − 2 p  p =1 

[( 2 x + 1) 2 + 32 ]8 + n

(21)

Therefore, the 9 -th order derivative value of g 2 ( x ) at x = 1 / 2 , − 2 9 [8]9 ⋅

g 2 ( 9 ) (1 / 2 ) =

9

 17 

∑  2 p − 1( − 1) p +1 32 p −1 ⋅ 218 − 2 p

p =1



1317

(22)

In the following, we use Maple to calculate g 2 ( 9 ) (1 / 2) and its closed form to verify our answer. >g2:=x->(24*(2*x+1)^7-1512*(2*x+1)^5+13608*(2*x+1)^3-17496*(2*x+1))/((2*x+1)^2+3^2)^8; >evalf((D@@9)(g2)(1/2),20); 607.92295995283605921 >evalf(-2^9/13^17*product(8+j,j=0..8)*sum(17!/((2*p-1)!*(18-2*p)!)*(-1)^(p+1)*3^(2*p-1)*2^(18-2*p),p=1..9),20);

607.92295995283605921

Conclusion As mentioned, the binomial theorem plays a significant role in the theoretical inferences of this study. In fact, the application of this theorem is extensive, and can be used to easily solve many difficult problems; we endeavor to conduct further studies on related applications. On the other hand, Maple also plays a vital assistive role in problem-solving. In the future, we will extend the research topic to other calculus and engineering mathematics problems and solve these problems by using Maple. These results will be used as teaching materials for Maple on education and research to enhance the connotations of calculus and engineering mathematics. References [1] F. Garvan: The Maple Book, Chapman & Hall/CRC (2001). [2] D. Richards: Advanced Mathematical Methods with Maple, Cambridge University Press (2002). [3] R.J. Stroeker and J.F. Kaashoek: Discovering Mathematics with Maple : An Interactive Exploration for Mathematicians, Engineers and Econometricians, Birkhauser Verlag (1999). [4] J.S. Robertson: Engineering Mathematics with Maple, McGraw-Hill (1996). [5] M.L. Abell and J.P. Braselton: Maple by Example, 3rd ed., Elsevier Academic Press (2005).

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[6] C.-H. Yu: The Differential Problem of Two Types of Rational Functions, Journal of Mei Ho University, Vol. 32, No. 1 (2013), in press. [7] C.-H. Yu: Application of Maple:Taking the Differential Problem of Rational Functions as an Example, 2012 Optoelectronics Communication Engineering Workshop, National Kaohsiung University of Applied Sciences, Taiwan (2012), pp. 271-274. [8] C.-H. Yu: Application of Maple:Taking the Evaluation of Higher Order Derivative Values of Some Type of Rational Functions as an Example, 2012 Digital Life Technology Seminar, National Yunlin University of Science and Technology (2012), pp.150-153. [9] R.A. Brualdi: Introductory Combinatorics, North-Holland (1977), p54.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 861-864 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.861

An Artificial Evolutionary Approach for Solving the Nonlinear Constrained Optimization Problems Y.-C. Hsieh1,a and P.-S. You2,b 1

Department of Industrial Management, National Formosa University, Huwei, Yunlin 632, Taiwan 2

Graduate Institute of Marketing and Logistics/Transportation, National ChiaYi University, Chia-Yi 600, Taiwan a

[email protected], [email protected]

Keywords: Nonlinear, Optimization, Immune algorithm.

Abstract. In this paper, an artificial evolutionary based two-phase approach is proposed for solving the nonlinear constrained optimization problems. In the first phase, an immune based algorithm is applied to solve the nonlinear constrained optimization problem approximately. In the second phase, we present a procedure to improve the solutions obtained by the first phase. Numerical results of two benchmark problems are reported and compared. As shown, the solutions by the new proposed approach are all superior to those best solutions by typical approaches in the literature. Introduction Nowadays, there are many real problems can be formulated as the nonlinear constrained optimization problems, such as engineering design, management, economic policy, traffic problem and so on. The general mathematical formulation of the nonlinear constrained optimization problem is: (P1)

Min f(n1, n2,…, nN; r1, r2,…, rN) (1) (2) St gj(n1, n2,…, nN; r1, r2,…, rN)≥bj, j=1,2,…,M li≤ri≤ui, ai≤ni≤bi, ri are real variables, ni are integers or discrete variables, i=1,2,…,N.

Problem (P1) is a very general optimization problem subject to general constraints with real variables, integer variables, and discrete variables. Clearly, Problem (P1) is a nonlinear mixed-integer programming problems and they are more difficult than the so-called component redundancy allocation problems. Since the simplest component redundancy allocation problem is NP-hard [1], Problem (P1) is also NP-hard [2]. Typical global optimization methods, such as dynamic programming [3], branch-and-bound approach [3], and implicit enumeration [4], can be used to solve Problem (P1). However, they are very time-consuming especially when the problem size is larger. During 1980s and 1990s, several heuristic methods have been developed for solving Problem (P1), for example, [5-7]. In our previous work [8], we have successfully applied a two-phase approach for solving the reliability redundancy problem. As known, the reliability redundancy problem contains only real variables within in (0,1) (for component reliabilities) and integer variables (for the number of redundancy of components). In this paper, we attempt to apply the two-phase approach for a general nonlinear constrained optimization problem with non-negative real variables. Numerical results of two benchmark problems will be reported and compared to show the performance of the proposed approach. Immune Based Two-Phase Approach. Phase-I： ：Immune Based Algorithm. Procedure of Immune Based Algorithm The main steps of proposed immune based algorithm are as follows. Step 1. Generate an initial population of strings (antibodies) randomly.

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Step 2. Evaluate each individual in current population and calculate the corresponding fitness value for each individual. Step 3. Select the best v individuals with highest fitness values. Step 4. Clone the best v individuals (antibodies) selected in Step 3. Note that the clone size for each select individual is an increasing function of the affinity with the antigen. Step 5. The set of the clones in Step 4 will suffer the genetic operation process, i.e., crossover and mutation [9]. Step 6. Calculate the new fitness values of these new individuals (antibodies) from Step 5. Select those individuals who are superior to the individuals in the memory set, and then the superior individuals replace the inferior individuals in the memory set. While the memory set is updated, the individuals will be eliminated while their structures are too similar. Step 7. Check the stopping criterion, if not stop then go to Step 2. Otherwise go to next step. Step 8. Stop. Report the optimal or near optimal solution(s) from the memory set. Note that, in Step 2 and Step 6, if gj(n1, n2,…, nN; r1, r2,…, rN) ε

(3)

is a triangular function and

Pl (τ ) =

1 4 k −1 ∑ hl hm ΛTs (τ + (l − m)Ts ) 4k m =0

(4)

is the lth partial sub-correlation function.

Proposed Correlation Function We generate an unambiguous correlation function with a high and sharp main-peak via two stages. The first and second stages are described in Fig. 1 and 2, respectively, for BOCsin (kn, n). In the first stage, we combine P0 (τ ) and P4 k −1 (τ ) as follows: R0 (τ ) = P0 (τ ) ⊕ P4 k −1 (τ )
P0 (τ ) + P4 k −1 (τ ) − P0 (τ ) − P4 k −1 (τ )

(5)

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Fig. 1. The first stage of the proposed scheme for BOCsin (kn, n).

Fig. 2. The second stage of the proposed scheme for BOCsin (kn, n).

to

generate an unambiguous correlation function R0 (τ ) with no side-peak, where

a ⊕ b
a + b − a − b and we use the fact that | x | + | y | − | x − y |= 0 when xy ≤ 0. From Fig. 1, we

can observe that the main-peak width of R0 (τ ) is determined by the location of a zero-crossing point nearest to τ = 0 in P0 (τ ) and P4 k −1 (τ ). Thus, to generate an unambiguous correlation function with a low and narrow main-peak, R0 (τ ), P1 (τ ) − P4 k −2 (τ ), and P4 k −2 (τ ) − P1 (τ ) are first combined as follows:

T1 (τ ) = ( P1 (τ ) − P4 k − 2 (τ ))  T2 (τ ) = ( P4 k − 2 (τ ) − P1 (τ ))

R0 (τ )
P1 (τ ) − P4 k − 2 (τ ) + R0 (τ ) − P1 (τ ) − P4 k − 2 (τ ) , R0 (τ )

(6)

thus constructing correlation functions T1 (τ ) and T2 (τ ) whose zero-crossing points nearest to τ = 0 are the same, i.e., 0.34Ts for BOCsin (kn, n), where a

b
a + b − a . Then, we combine T1 (τ ) and

T2 (τ ) as follows: R1 (τ ) = T1 (τ ) ⊕ T2 (τ )

(7)

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yielding an unambiguous correlation function R1 (τ ) with a low and narrow main-peak; however,

R1 (τ ) does not contain the sufficient signal energy required for reliable tracking since it is produced using only four partial sub-correlations out of 4k partial sub-correlations.

Fig. 3. Tracking error standard deviation of the proposed and conventional functions (a) as a function of k when CNR = 30dB-Hz and (b) as a function of CNR when k = 2. Thus, in the second stage we construct multiple unambiguous correlation functions through the combinations of {Pl (τ ) ⊕ R1 (τ )}l4=k1− 2 , and then, increase the height of a low and narrow main-peak as follows: 4k −2

Rproposed (τ ) = R1 (τ ) +

∑ P (τ ) ⊕ R (τ ) l

1

(8)

l =1

yielding an unambiguous correlation function Rproposed (τ ) with a high and sharp main-peak, which is shown in Fig. 2. It should be noted that the proposed two-stage method is also applicable to BOCcos (kn, n), although the proposed method is described for BOCsin (kn, n) only. Specifically, the normalized height of the main-peak of the proposed correlation function is two regardless of the value of k . The main-peak widths are 0.68Ts and 0.5Ts for BOCsin (kn, n) and BOCcos (kn, n), respectively. It is straightforward to show that the absolute slopes of the main-peak of the proposed correlation function for BOCsin (kn, n) and BOCcos (kn, n) are 23.52k and 32k , respectively. As the main-peak width of the proposed correlation function is narrower than those of the conventional correlation functions, the available code tracking range of the proposed correlation function is smaller than those of the conventional correlation functions; however, the absolute slope of the main-peak of the proposed correlation function is much larger than those of the conventional correlation functions. Thus, we can anticipate that the proposed correlation function will offer a performance improvement over the conventional correlation functions. Finally, in the tracking process, the discriminator output 2 2 D (τ ) = Rproposed (τ + ∆2 ) − Rproposed (τ − ∆2 )

(9)

is applied to the loop filter to drive the numerically controlled oscillator, which advances or delays the clock of the local signal generator until τ becomes zero, where ∆ is the early-late spacing.

Numerical Results Tracking performances of several unambiguous correlation functions are compared in terms of the tracking error standard deviation (TESD), which is defined as σ 2 BLTI / G , where σ is the standard deviation of D(0), BL is the bandwidth of the loop filter, TI is the integration time, and G = ( d D (τ ) / d τ ) τ =0 is the discriminator gain [8]. We assume the following parameters: Galileo

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E1-B PRN code with period T = 4 ms, TI = T , ∆ = Ts / 4, BL = 1Hz, κ = 0.3 for the scheme of [5] (the tunable parameter κ set to 0.3 which guarantees the best TESD performance), and Tc−1 = 1.023MHz. Fig. 3 shows the TESD of the proposed and conventional correlation functions as a function of k when the carrier-to-noise ratio (CNR) is 30dB-Hz, and as a function of the CNR when k = 2 : Here, the CNR is defined as S / N 0 with the noise power spectral density N0 . We would like to note that [5] is dedicated to only sine phased BOC signals, and it is shown for only BOCsin(kn,n) in Fig. 3. From the figure, it is clearly observed that the proposed correlation function provides a better TESD than the conventional correlation functions. Although the TESD of the conventional correlation functions becomes smaller as the value of k increases, the proposed correlation function always provides the best performance due to its sharp main-peak. Fig. 3(b) confirms that the proposed correlation function also provides a significant performance improvement over the conventional correlation functions in the CNR range 20 ~ 40 dB-Hz of practical interest.

Conclusion In this paper, we have proposed an unambiguous BOC correlation function with a high and sharp main-peak for BOC signal tracking. Specifically, we have constructed a correlation function with a low and narrow main-peak via first stage, and then, generated an unambiguous correlation function with a high and sharp main-peak via the combinations of the correlation function with the partial correlation functions in the second stage. Finally, we have confirmed that the proposed correlation function offers a performance improvement over the conventional correlation functions in terms of the TESD.

Acknowledgment This research was supported by the National Research Foundation (NRF) of Korea under Grant 2012R1A2A2A01045887 with funding from the Ministry of Science, ICT & Future Planning (MSIP), Korea, by the Information Technology Research Center (ITRC) program of the National IT Industry Promotion Agency under Grant NIPA-2013-H0301-13-1005 with funding from the MSIP, Korea, and by National GNSS Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.

References [1] J. W. Betz: J. Inst. Navig., Vol. 48 (2001), pp. 227-246 [2] J. A. Avila-Rodriguez: Ph.D. dissertation, Dept. Aer. Engineer., University of Munich, Munich, Germany (2008) [3] A. Burian, E. S. Lohan, and M. K. Renfors: EURASIP J. Wireless Commun. Network, 2007 (2007), pp. 1-20 [4] O. Julien, C. Macabiau, M. E. Cannon, and G. Lachapelle: IEEE Trans. Aer., Electron. Syst., Vol. 43 (2007) pp. 150-162 [5] Z. Yao, X. Cui, Z. Feng, and J. Yang: IEEE Trans. Aer., Electron. Syst., Vol. 46 (2010) pp. 1782-1796 [6] Y.Lee, D. Chong, I. Song, S. Y. Kim, G.-I. Jee, and S. Yoon: IEEE Commun. Lett., Vol. 16 (2012) pp. 569-572 [7] F. D. Nunes, M. G. Sousa, and M. N. Leitao: IEEE Trans. Aer., Electron. Syst., Vol. 43 (2007) pp. 951-964 [8] A. J. Van Dierendonck, P. Fenton, and T. Ford: J. Inst. Navig., Vol. 39 (1992) pp. 265-283

Applied Mechanics and Materials Vols. 479-480 (2014) pp 870-877 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.870

Image Contrast Enhancement by Hybrid 3SAIHT and CLAHE Algorithm Cheng-Yi Yu1,a, Hsueh-Yi Lin1,b, Cheng-Jian Lin1,c 1

Department of Computer Science and Information Engineering, National Chin-Yi University of Technology,

No.57, Sec. 2, Zhongshan Rd., Taiping Dist., Taichung 41170, Taiwan R.O.C. a

[email protected], [email protected], [email protected]

Keywords: Image Contrast Enhancement, Image Fusion, 3SAIHT, CLAHE

Abstract. Human visual perception is insensitive to certain shades of gray but can distinguish among 20 to 30 shades of gray under a given adaptation level. In this paper, we propose an image fusion pipeline that generates a high vision quality image by fusing the Three-Scale Adaptive Inverse Hyperbolic Tangent (3SAIHT) and the Contrast-Limited Adaptive Histogram Equalization (CLAHE) algorithms to increase detail and edge information. Fusion results are clearer and better with regard to display quality and contrast enhancement. Introduction When viewing pictures of outdoor scenes, we can tell when part of the image is over-exposed or under-exposed because the dynamic range of human vision is much higher than the range of most image sensors [1][2]. The three-scale parameter adjustment is a natural extension of the adaptive inverse hyperbolic tangent algorithm. The human vision system (HVS) heavily depends on brightness and contrast in the comprehension and perception of scenes [3]. However the local contrast enhancement can't be done simply by using the 3SAIHT algorithm; therefore, a CLAHE technique should also be deployed to resolve this problem. The former provides for a good contrast enhancement with regard to local performance but can over enhance with excessive contrast resulting in a serious chromatic aberration.

In this paper, we propose an image fusion pipeline that generates a high vision quality image by fusing two algorithms. This pipeline chooses two appropriate algorithms from the image contrast enhancement and applies 3SAIHT and CLAHE algorithms to deal with detail problem and chromatic aberration. It then blends them by performing simple quality control measures. Contrast Enhancement for Image Contrast enhancement is a common operation with regard to image processing. Used to improve poor quality images, it is also useful in improving detail in photographs which are over or under-exposed. With this in mind, the goal of this assignment is to develop a contrast enhancement algorithm. Histogram Equalization (HE) Algorithm. A simple method with which to enhance the contrast of a grayscale image involves histogram equalization. The histogram of a digital image represents its tonal distribution. Histogram equalization effectively spreads out the most frequent intensity values,

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resulting in a better distribution on the histogram. This allows for areas of lower local contrast to gain a higher contrast without affecting the global contrast. Duan and Qiu extended this idea to include color images, but the equalized images are not visually pleasing in many cases [4].The traditional histogram equalization (HE) method typically results in extreme over-enhancement, which causes the image to appear unnatural in the processed image. CLAHE Algorithm. Adaptive histogram equalization (AHE) is a computer image processing technique used to improve contrast in images. It differs from ordinary histogram equalization such that the adaptive method computes several histograms, each corresponding to a distinct section of the image, and uses them to redistribute the lightness values of the image. Therefore, it is suitable for improving the local contrast of an image and bringing out more detail [5]. The CLAHE is an image contrast enhancement algorithm which overcomes limitations in standard HE. The two primary features include AHE, which divides the images into regions and performs local HE, and the contrast limited AHE (CLAHE), which reduces noise by partially reducing the local HE. Bilinear interpolation is used to avoid visibility of regional boundaries [6]; hence, contrast enhancement can be limited by limiting the slope of the cumulative distribution function (CDF). The slope of CDF at a bin location is determined by the height of the histogram for that bin. Therefore, if we limit the height of the histogram to a certain level we can limit both the slope of the CDF and the amount of contrast enhancement [7]. The major problem with CLAHE methods is that they often over enhance the image by creating so called contrast objects that were not visible in the original image. The enhanced image often does not look natural and is visually disturbing [8]. AIHT Algorithm. The principal characteristic of AIHT is an adaptive adjustment of the inverse hyperbolic tangent (IHT) function determined by each pixel’s radiance. With regard to the AIHT algorithm in contexts involving very small and very large luminance values, its logarithmic function enhances the contrast in both dark and bright areas of an image. The enhanced pixel xij by AIHT is defined as follows:   1 + xijbias ( x )    − 1 × gain( x ) Enhance(xij ) =  log   1 − xijbias ( x )      

(1)

where xij is the image gray level of the i t h row and j t h column. The bias is a power of xij to speed up the changing. The bias function is a power function defined over the unit interval which remaps x according to the bias transfer function. The bias function is used to bend the density function either upwards or downwards over the [0,1] interval. The bias power function is defined as:  mean ( x )  bias ( x ) =    0 .5 

0 .25

 1 m n  ∑ ∑ x ij  m × n i =1 j =1 = 0 .5  

     

0.25

(2)

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The gain function is a weighting function which is used to determine the steepness of the AIHT curve. A steeper slope narrows a smaller range of input values to the display range. The gain function is defined as:  1 m n 0 .5 gain ( x ) = 0.1 × (variance ( x ) ) = 0.1 ×  ∑ ∑ xij − µ  m × n i =1 j =1

(

m

where

µ=

)

0 .5

(3)



n

1 ∑∑ xij m × n i =1 j =1

The AIHT algorithm can determine the contrast levels of an original image as well as the parameter space for different contrast types such that, not only the original histogram shape features are preserved, but also that the contrast can be enhanced effectively[1][2]. Three-scale Parameter Adjustment of AIHT Algorithm. Figure 1 shows a block diagram of the 3SAIHT algorithm. The input data is converted from its original format to a floating point representation of RGB values. Our proposed 3SAIHT algorithm is a further extension from the 2SAIHT algorithm but differs in that pixels can be ranged from High band, to Medium band and to Low band and it can process its own parameters. The 3SAIHT function relates to the average of all pixel radiances and is non-equally divided into low and high band. For sub-band (low and high band), average pixel radiances obtain low and high band averages. Moreover, it is based on low and high band averages in relation to the benchmark and is non-equally divided into high, medium and low bands of the input image [3].

Fig. 1. A flowchart of the 3SAIHT algorithm

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Figure 2 shows a block diagram of the 3SAIHT algorithm to generate three-scale bias(x) and gain(x) parameters. There are two important goals for this three-scale band design scheme. One is to avoid noise visibility, especially in smooth regions, and the other is to prevent intensity saturation for possible minimum and maximum intensity values (e.g., 0 and 255 for 1 byte per channel source format). This three-scale algorithm for processing input image x is described as: 3 3   1 + xkbiask ( xk )    − 1 × gaink ( xk ) Enhance_ 3SAIHT(x ) = ∑ AIHTbias( k ), gain( k ) ( xk ) = ∑  log biask ( xk )    k =1 k =1   1 − xk  

(5)

where k is the number of sub-bands used, xk is sub-band image of the input image.

Fig. 2. A flowchart of 3SAIHT parameters Image Contract Enhancement by Fusing 3SAIHT and CLAHE Algorithms This section presents the basic ideas and principles of contrast enhancement using 3SAIHT and CLAHE fusion. Data fusion is performed through a mathematical technique using overlapping information, i.e., information from both processes. We used one of the data fusion techniques for generating combined 3SAIHT and CLAHE enhancement data [9]-[13]. We propose an image fusion pipeline that can generate a new image by fusing two different algorithms. We apply multiple processes by combining 3SAIHT with CLAHE algorithms and incorporate data fusion with regard to image contrast enhancement. The algorithm from a conjugate of 3SAIHT and CLAHE image contrast enhancement is based on the 3SAIHT⊕CLAHE algorithm. The CLAHE has good contrast enhancement performance, but excessive contrast enhance can result in producing serious chromatic aberrations. We apply the 3SAIHT and CLAHE advantage to present a joint multiple process algorithm to achieve better contrast enhancement effect. Figure 3 shows a block diagram of the processing procedures of 3SAIHT and CLAHE with regard to data fusion. The enhanced result will be multiplied by α and β of the weight parameters, respectively; then, an integrated output of both was multiplied by the result. The enhanced output image IFusion integrates the outputs of both 3SAIHT and CLAHE by α and β of weight parameter, respectively. The data fusion approach is described by Equation (6): I Fusion (i , j ) = αI 3SAIHT (i , j ) ∗ βI CLAHE (i , j ) M −1 N −1

= αβ ∑∑ I 3SAIHT (m, n)I CLAHE (i-m , j-n) m =0 n=0 M −1 N −1

= (α − α 2 ) ∑∑ I 3SAIHT (m, n)I CLAHE (i-m , j-n) m =0 n=0

(6)

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For i=0,1,2,…M-1 and j=0,1,2,…N-1, the α and β is less the weight of 3SAIHT and CLAHE, respectively. The α and β have to satisfy α+β=1, and 0 ≤ α ≤ 1 and 0 ≤ β ≤ 1 .

Fig. 3. The processing procedures for combining 3SAIHT with CLAHE by data fusion We start with the simple case of contrast enhancement for grayscale images. Then, we apply a similar method to color images. Implementation and Experimental Results A different illuminated environment can significantly affect the contrast ratio, producing various types of histogram distributions. Various types of histogram distributions images, i.e. dark images, bright images, back-lighted images and low-contrast images- were tested under this proposed method. Experiment results demonstrate the effectiveness of using this method. Figure 4 shows a comparison of the results of the 3SAIHT⊕CLAHE method at different weight ( α and β ) parameters; We can choose a set of best weight parameters with α = 0.5 , β = 0.5 . Figure 5 demonstrates the fusion property of the proposed method. In summary, the proposed algorithm outperforms conventional (HE and CLAHE) and 3SAIHT algorithms with regard to the contrast and detail of an image.

Conclusions In this paper, we propose an image fusion pipeline to generate a high quality image. We propose algorithms with regard to long exposure where images contain details of darker areas and the short exposure contain details of brighter areas such that a fusion image can preserve all details in the scene. However, chromatic aberration problems may occur if the weight β ratio is too high. Here, using the same weight parameters value with α=0.5 and β=0.5 provides a solution. Experimental results demonstrate that the 3SAIHT⊕CLAHE method is capable of improving upon the 3SAIHT algorithm which lacks local contrast enhancement capability and corrects for CLAHE where excessive contrast enhancement can produce a serious chromatic aberration problem.

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Original

CLAHE

3SAIHT*0.1 CLAHE*0.9

⊕

3SAIHT*0.2 CLAHE*0.8

3SAIHT*0.3 CLAHE*0.7

⊕

3SAIHT*0.4 CLAHE*0.6

⊕

3SAIHT*0.5 CLAHE*0.5

⊕

3SAIHT*0.6 CLAHE*0.4

⊕

3SAIHT*0.8 CLAHE*0.2

⊕

3SAIHT*0.9 CLAHE*0.1

⊕

3SAIHT

3SAIHT*0.7 CLAHE*0.3

⊕

⊕

⊕

Fig.4. The compared results of the 3SAIHT CLAHE method at different weight ( α and β ) parameters

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Original

CLAHE

3SAIHT

3SAIHT *0.5

⊕CLAHE*0.5

Fig. 5. The 3SAIHT⊕CLAHE method produced by fixed parameter values α = 0.5 and β = 0.5 Reference [1]

C. Y. Yu, Y. C.Ouyang, C. M. Wang and C. I. Chang, “Adaptive Inverse Hyperbolic Tangent Algorithm for Dynamic Contrast Adjustment in Displaying Scenes,” EURASIP Journal on Advances in Signal Processing, vol. 2010, Article ID 485151, 20 pages, 2010.

[2]

Cheng-Yi Yu, Yen-ChiehOuyang, Chuin-Mu Wang, Chein-I Chang, Zei-Wei Yu ,“Contrast Adjustment in Displaying Scenes Using Inverse Hyperbolic Function”, 2009 The 22th IPPR Conference on Computer Vision, Graphics, and Image Processing, Aug. 23–25, 2009, Nantou, Taiwan, pp.1020–1027.

[3]

Cheng-Yi Yu, Yen-ChiehOuyang, Hsueh-Yi Lin, Tzu-Wei Yu,“Three-scale Image Contrast Enhancement Based on Adaptive Inverse Hyperbolic Tangent Algorithm”, The18th National Conference on Fuzzy Theory and Its Application,Dec. 3-4, 2010, Hualien, Taiwan, pp.463–469.

[4]

Duan and G. Qiu, “Novel histogram processing for color image enhancement”, ICIG 2004, 3rd International Conference on Image and Graphics, Hong Kong, December, pp.18–22, 2004.

[5]

Adaptive

histogram

equalization,

http://en.wikipedia.org/wiki/Adaptive_histogram_equalization. [6]

KarelZuiderveld, "Contrast Limited Adaptive Histogram Equalization," in Chapter VIII.5, Graphics Gems IV, Cambridge, MA, Academic Press, pp.474-485, 1994.

[7]

E. D. Pisano, S. Zong, B. M. Hemminger, M. DeLuca, R. E. Johnston, K. Muller, M. P. Braeuning, S. M. Pizer, “Contrast limited adaptive histogram equalization image processing to improve the detection of simulated spiculations in dense mammograms,” J Digit Imaging, Vol. 11, pp. 193-200.

[8]

J. A. Stark, “Adaptive image contrast enhancement using generalizations of histogram equalization,” IEEE Transactions on Image Processing, vol. 9, no. 5, pp. 889–896, 2000.

[9]

L. Wald, “Some terms of reference in data fusion,” IEEE Transactions onGeoscience and Remote Sensing, vol. 37, pp. 1190–1193, May 1999.

[10] J. L. Genderen and C. Pohl, “Image fusion: Issues, techniques and applications,” Strasbourg, France,pp. 18–26, September 1994.

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[11] J. J.Clark and A. L. Yuille, “Data fusion for sensory information processing systems,” Kluwer AcademicPublishers, 1990. [12] J.Santamaria and M.T. Gomez, “Visble-IR image fusion based on gaberwavelets decomposition,” SENER, Spain, EuropeanOptical Society Digest, 1993, Vol.3 [13] Z. Yin, A. A. Malcolm, “Thermal and visual image processing and fusion,”Machine Vision & Sensors Group, Automation Technology Division, pp. 1-6, 2000.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 878-882 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.878

A Low Complexity Integer Frequency Offset Estimation Scheme Based on Coherence Phase Bandwidth for OFDM Systems Youngseok Lee1,a, Seong Ro Lee2,b, Seungsoo Yoo3,c, Jeongyoon Shim1,d, Jaewoo Lee1,e,and Seokho Yoon1,f,† 1

College of Information and Communication Engineering, Sungkyunkwan University, Suwon, Korea

2

Department of Information and Electronics Engineering, Mokpo National University, Mokpo, Korea 3

Department of Electronics Engineering, Konkuk University, Seoul, Korea a

[email protected], [email protected], [email protected], {dhobbangdk, elllp3743}@skku.edu, and [email protected] †

Corresponding author

Keywords: OFDM, integer frequency offset, threshold, coherence phase bandwidth (CPB).

Abstract. In this paper, we propose a low complexity integer frequency offset estimation scheme based on coherence phase bandwidth for orthogonal frequency division multiplexing (OFDM) systems. The proposed scheme overcomes the effect of the timing offset via correlating the local and received OFDM training symbols in a coherence phase bandwidth block unit. Moreover, by utilizing a threshold to determine an interger frequency offset etimate, the proposed scheme need not calculate correlation values for all possible interger frequency offset candidates. From numerical results, it is demonstrated that the proposed scheme can estimate the integer freqeuncy offset with a reduced complexity while minataining the same level of the estimation performance. Introduction In orthogonal frequency division multiplexing (OFDM) techniques, the data is transmitted on the multiple orthogonal subcarriers. Due to its high spectral efficiency and immunity to multipath fading, OFDM has attracted much attention in the field of wireless communications [1]. For example, OFDM has been adopted as the transmission method of many standards in wireless communications, including European digital video broadcasting (DVB), IEEE 802.16, and Long Term Evolution (LTE). However, the OFDM system is very sensitive to the frequency offset caused by Doppler shift or the mismatch of the oscillators. The frequency offset is generally interpreted as a sum of an integer and a fractional parts: The former is a multiple of a subcarrier spacing, which shifts subcarrier indices of demodulated complex data, and the latter is a fractional part with an absolute value smaller than a half of the subcarrier spacing, which results in the intercarrier interference. To alleviate the problem, several schemes have been proposed for fractional frequency offset [2,3] and integer frequency offset [4,5]. In [2], the fractional frequency offset is estimated by using the cyclic prefix of an OFDM symbol. The scheme of [3] utilizes a training symbol with identical halves improving the frequency offset estimation performance. On the other hand, for integer frequency offset estimation, an estimation scheme was proposed in [4] using the crosscorrelation between the received and locally generated training symbols. However, the scheme of [4] is very sensitive to the timing offset, thus, in [5], an estimation scheme robust to the timing offset was proposed considering the coherence phase bandwidth (CPB) in its estimation process. However, the scheme of [5] still has the problem that the complexity in implementation rapidly increases, as the number of subcarrier increases. In this paper, we focus on the integer frequency offset estimation using a training symbol. In this paper, a novel frequency offset estimation scheme with reduced complexity is proposed using the CPB and threshold. Specifically, the proposed scheme correlates the local and received OFDM training symbols in a CPB block unit to overcome the effect of the timing offset. Moreover, the proposed scheme employs a threshold to determine a frequency offset estimate reducing the

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complexity in calculating correlation values. The proposed scheme is robust to a timing offset and has a lower computational complexity than the scheme of [5]. Signal Model An OFDM training symbol is generated by inverse fast Fourier transform (IFFT) as N −1

zn = (1/ N )∑Z k e j 2π nk / N ,

(1)

k =0

where Z k is a training symbol in the kth subcarrier and N is the size of IFFT. In the presence of frequency and timing offsets, the received OFDM symbol rn can be expressed as

rn = zn − n0 e j 2π f0 ( n − n0 )/ N + wn ,

(2)

where f 0 and n0 represent the normalized frequency and timing offsets normalized by the subcarrier spacing and sampling interval, respectively, and wn is the complex additive white Gaussian noise (AWGN) sample with mean zero and variance σ w2 . A frequency offset f 0 can be divided into an integer and a fractional parts as f 0 = ε + ∆f f ,

(3)

where ε is the integer part of f 0 and f f ∈ [ −0.5, 0.5) is the fractional part of f 0 . Since our focus in this paper is on the estimation of ε , we assume that the fractional part f f is known and perfectly compensated. The received OFDM symbol is demodulated after the FFT operation. The kth FFT output Rk can be expressed for k = 0,1, 2,
, N − 1 as Rk = Z k −ε e − j 2π n0 ( k −ε )/ N + Wk ,

(4)

where Wk is the FFT output of wn .

Conventional Scheme In the conventional scheme of [5], the correlation functions are calculated individually within each CPB block, and then, summated. Here, CPB is defined as [5] Bc = 12n0t N ,

(5)

where n0t is a maximum tolerable timing offset value of the system. To estimate the integer frequency offset, the scheme of [5] calculates the correlation between the known training symbol {Z k }kN=0−1 and the cyclically shifted version of the received training symbol in frequency domain, and then, obtains the integer frequency offset estimate as

 K −1 εˆ[5] = arg max  ∑ d  m =0

Bc −1

∑Z k =0

* k + mBc

R( k + mB

c +d )N

 , 

(6)

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Fig. 1. The correlation values from the scheme of [5] versus the integration range for several values of timing offset (when d = ε , N = 1024, and Bc = 256 ). where d is an integer frequency offset candidate in {0,1,
, N − 1}, (⋅) N is the modulo- N operator, and K = N / Bc . As shown in Fig. 1, the correlation values of the scheme of [5] increase monotonically as the integration range increases when n0 < Bc overcoming the effect of the timing offset. However, the scheme of [5] has high computational complexity since the correlation values are calculated for all possible values of d .

Proposed Scheme To reduce the computational complexity, we employ a threshold in the estimation process. Specifically, we first obtain the CPB as in Eq. 5, and then, calculate a threshold η based on the calculated CPB value. Increasing the value of d by one (sample interval), we compare the correlation value

∑

K −1 m =0

c | ∑ k =0 Z k*+ mB R( k + mB B −1

c

c +d )N

| with the threshold η and determine the value of d as the

integer frequency offset estimate εˆ when the correlation value is larger than the threshold. In this paper, we calculate the threshold η as follows. Considering one CPB block in Eq. 6, a correlation value C (d ) can be expressed as Bc −1

C (d ) =

∑Z

* k

(7)

R( k + d ) . N

k =0

Assuming d = ε and ignoring AWGN components in Eq. 7, the correlation value C can be expressed as C ( d ) |d = ε = Z k

2

Bc −1

∑e

− j 2π n0 k / N

.

(8)

k =0

The value C in Eq. 8 is minimum when n0 = n0t for n0 ≤ n0t . Therefore, the minimum correlation value Cmin can be expressed as 2

Cmin = Z k 1 − j cot (π n0t / N ) . We also express the minimum value of full correlation in a similar manner as

(9)

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Fig. 2. Block diagram of the proposed integer frequency offset estimation scheme. 2

full Cmin = 2n0t Z k 1 − j cot (π n0t / N ) .

(10)

full In this paper, we use a threshold η as a half of Cmin

2

η = n0t Z k 1 − j cot (π n0t / N ) .

(11)

When the correlation value exceeds η , the corresponding d is determined to be the correct estimate of ε . Otherwise, the received signal is cyclically shifted by d = d + 1 and the procedure above is repeated. The operation of the proposed scheme is described in Fig. 2. When the number of subcarriers is sufficiently large, the proposed scheme will generally have about a half computational complexity compared with the scheme of [5]. It also should be noted that the proposed scheme does not require additional memory for correlation values unlike schemes of [4] and [5].

Numerical Results In this section, we first compare the complexity of the proposed and conventional schemes as shown in Table 1. We can see from Table 1 that the proposed scheme has approximately a half computational complexity compared with the conventional scheme of [5] for N
1. To compare the estimation performance of the schemes, we consider two channel models: AWGN and multipath channel models. The signal-to-noise ratio (SNR) of the AWGN channel model is 5 dB. The multipath channel model has four paths with 5, 10, and 15 sample delays from the first path, respectively, each path has 4, 8, and 12 dB attenuation in the amplitude, and the SNR is 10 dB. Tables 2 and 3 compare the correct estimation probabilities of the proposed and conventional schemes, defined as the probability that the estimate equals to ε , over AWGN and multipath channels, respectively. The frequency offset used in this simulation is an integer value in [0, 500], N = 1024, and Bc = N / 32. As we can see from tables, the scheme of [5] is shown to have the same correct estimation probability as that of the proposed scheme, however, the complexity of the scheme of [5] is almost twice the proposed scheme as shown in Table 1. Table 1. Complexity comparison for the schemes. Scheme [5] Proposed

Number of complex multiplication

Number of comparison operation

Size of memory for correlation value

N2 N ( N + 1) / 2

N −1 ( N + 1) / 2

N

-

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Table 2. Correct estimation probabilities in the AWGN channel model. Timing offset (samples)

[5]

Proposed scheme

0

1

1

1

1

1

2

1

1

5

1

1

Table 3. Correct estimation probabilities in the multipath channel model. Timing offset (samples)

[5]

Proposed scheme

0

1

1

1

1

1

2

1

1

5

1

1

Conclusion In this paper, we have proposed an integer frequency offset estimation scheme with a reduced complexity by employing a threshold and CPB. When a correlation value exceeds the threshold, the corresponding integer frequency offset candidate has been determined to be the integer frequency offset estimate. Otherwise, the received signal has been cyclically shifted and the estimation process has been repeated. From numerical results, we have shown that the proposed scheme has much a reduced complexity than the conventional scheme while maintaining the same level of correct estimation probability performance.

Acknowledgment This research was supported by the National Research Foundation (NRF) of Korea under Grant 2012R1A2A2A01045887 with funding from the Ministry of Science, ICT & Future Planning (MSIP), Korea, by the Information Technology Research Center (ITRC) program of the National IT Industry Promotion Agency under Grant NIPA-2013-H0301-13-1005 with funding from the MSIP, Korea, and by National GNSS Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.

References [1] K. Fazel and S. Kaiser: Multi-carrier and spread spectrum systems (John Wiley and Sons, England (2003)) [2] J. J. van de Beek, M. Sandell, and P. O. Borjesson: IEEE Trans. Signal Process., Vol. 45 (1997), pp. 1800-1805 [3] T. M. Schmidl and D. C. Cox: IEEE Trans. Comm., Vol. 45 (1997), pp. 1613-1621 [4] H. Nogami and T. Nagashima: Proceedings of IEEE PIRMC, Vol. 3 (1995), pp. 1010-1015 [5] K. Bang, N. Cho, H. Jun, K. Kim, H. Park, and D. Hong: IEEE Trans. Comm., Vol. 49 (2001), pp.1320-1324

Applied Mechanics and Materials Vols. 479-480 (2014) pp 883-888 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.883

Face Recognition by Geometrical Feature-Point Bilateral Matching Yea-Shuan Huang and Guo-Da Peng CSIE, Chung-Hua University, Hsinchu 707, Taiwan a

[email protected], [email protected]

Keywords: Face Recognition; Feature Point Detection; Block Matching.

Abstract. This paper presents a novel feature-point bilateral recognition method for recognizing human faces. At first, from either an input face image or a reference face image, a set of distinct feature points is extracted by using a general salient point detection algorithm. Then, based on the detected feature points, a bilateral recognition is performed. Bilateral recognition means there are two ways of recognition, forward recognition and backward recognition. Finally, the forward score and the backward score are summed up into a bilateral score which is used to obtain recognition result. In order to perform recognition in real-time, we also use a GDA algorithm to select the possible candidates, and then use the proposed bilateral recognition operation to make the final recognition decision. Experiments on two famous face databases show that the proposed algorithm get excellence recognition result and is complementary to traditional global-feature-based face recognition methods. Introduction In human face recognition, there were already lots of researches and methods propsoed in recent years, and they were mostly focusing on how to enhance the correctness rate of the recognition technology under the influence of different variations such as face orientation, illumination, expression and image resolution. In the commonly seen dimension reduction methods, PCA[1], LDA[2], Locality Preserving Projection (LPP)[3] and Orthogonal Local Preserving Projection (OLPP)[4], etc. Both PCA and LDA are used extensively in various pattern recognition applications. LPP constructs a nearest-neighbor graph for each data point, and it remains the manifold structure information among data; OLPP constructs its feature space bases with orthogonal characteristic so that it keeps the manifold structure of the raw data more completely. There are also other dimension reduction methods belonging to the nonlinear types, for example, method based on Kernel approach[5][6], Locally Linear Embedding (LLE)[7], and Generalized Discriminant Analysis (GDA)[8]. GDA is a nonlinear discriminant analysis using Kernel function, and it maps the raw data vector into high dimension feature space, and in this high dimension feature space, the data distribution is formed to be linearly divisible, meanwhile, it uses LDA conversion to find out the projection vectors having the largest ratio of between-class variation and within-class variation. In the traditional dimension reduction method (for example, PCA, LDA and GDA), the entire structure of a human face is considered, and through linear statistical analysis, the dimension of the raw data is reduced to perform classificaiton and recognition. Although these methods can generate the recognition results quickly, yet they can only identify human face that has distinguished difference on the entire feature. However, for twins or look-alike persons, correct recognition will be very difficult to be obtained, because, the entire structures of these faces are very similar. Through detailed observation, it is clear that if partial feature on face can be found out, for example, mole, texture and scar, etc., then even if it is as similar as twins, correct recognition can still be made. Therefore, this paper starts from the viewpoint of partial texture to find out the feature points with distinct texture on faces, then based on these feature points, face recognition is performed. Structure of Face Recognition Fig. 1 shows the overall structure of the proposed face recognition approach. After image is captured, both face detection and eye detection algorithms [14] are used to find out the locations of face and pupils, then through the use of the coordinates of both pupils, operations such as orientation normalization, size normalization, and lighting compensation [15] are then performed on the

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Applied Science and Precision Engineering Innovation

extracted face image in the pre-processing module. Then a GDA algorithm is used to perform to make a fast sorting on all users in the enrolled database, and the users who have similar global face structure as the input face image are selected for further recognition. Then, through a proposed feature point bilateral recognition (FPBR) module, the final recognition result is obtained. Since both image preprocessing and GDA FPBR is the essential contribution of this paper, it is described in detail in the next section.

Fig. 1: Flow chart of the proposed face recognition algorithm Bilateral Recognition Fig. 2 shows the main architecture of FPBR. In this method, feature point detection is performed resepctively to the input face image and a database image, then it enters a bilateral recognition module to generate the final recognition result. Fig. 2 is the process flow of the bilateral recognition, in this design, the feature points of the input image and a database image are operated through the recognition module to get a forward recognition score; similarly, the feature points of the database image and the input image are operated through the recognition module to get a backward recognition score. Finally, both forward and backward recognition scores are associated to get a bilateral recognition score.

Fig. 2 The architectural diagram of bilateral recognition module Since a bilateral recognition score is performed with the bilateral recognition calculation using the input image and a database image, and these two images will be used respectively to detect feature points and to find out their optimal matched feature points, hence, for representation convenience, the image used for feature point detection is called the reference image (RI), and the image used to find out the optimal matched feature point is called the matching image (MI) in the following discussion. Fig. 4 is the flow chart of the recognition module in Fig. 3. Take the forward recognition as example, RI is the input image, and MI is a database image; similarly, for backward recognition, RI is a database image, and MI is the input image. Through the use of a block matching algorithm, each feature point of RI can be found its corresponding matched feature point in MI and its matched strength, next, a geometric model comparison is performed between the reference image feature point

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set and the found matched feature point set to generate a model differential score. Finally, the model differential score and the average feature point matched strength are associated to get a unilateral (either forward or backward) recognition score. To sum up the forward and the backward recognition scores, a bilateral recognition score can be obtained.

Fig. 3 Flow chart of the proposed bilateral recognition

Fig. 4 Process flow chart of recognition module. Feature Point Detection and Block Matching. This paper uses both SURF and LBP operators to perform feature point detection. After the completion of feature point detection, the system will enter the bilateral recognition module to make pattern comparison and recognition. During the recognition, each feature-point block B of the reference image will perform a block matching operation to the matching image in a defined search scope, then a block of the matching image most similar to B will for sure can be found out, meanwhile, the center of this most similar block is called the corresponding matched feature point in the matching image. Suppose there are K feature points in the reference image, represents the importance of the i-th feature point and represents the matching strength of the i-th feature point, then the average matching strength (AMD) is ∑

∑

(1)

Geometrical Model. Beside AMD, we use a geometrical model and calculate the geometrical differential amount between the reference feature point set and the corresponding matched feature point set. A geometrical model represents the geometrical relationship between the reference feature points or the matched feature points, and such relationship contains attributes such as the distance between two points and the angle among three points. The geometrical model built up by the reference image feature point is called the reference geometrical model RG, and the geometrical model set up by the matched feature point is called the matched geometrical model MG. In this paper, a global-based geometry model (GBGM) is designed. Fig. 5 shows one GBGM of five feature points, wherein represents the t-th reference or matched feature point.

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Fig. 5 An example of global-based geometrical model GBGM uses all triads of feature points to form a geometrical structure, which is as shown in is used as a base point, from the rest four feature points, we can select arbitrarily two Fig.5, when ‖) and ‖ ‖ and included points (suppose they are and ), then two segment lengths (‖ and ) will form a sub-model set. Since 4 angle ( , , ) formed by these three points (i.e. , feature points have kinds of selection formed by two feature point sets, accordingly there are sub-model sets generated. Suppose one sub-model set uses as the base feature point, and the ‖, ‖ ‖, , , ), other two points are and , then this sub-model set can be represented as (‖ and , , , (2)

, ,

Suppose

∙ ‖‖

‖

,

and

(3)

‖

are the weight values of

,

and

, ,

respectively, then

,

(4)

,

(5)

, ,

‖

,

‖

,

‖

‖

(6)

Therefore, among K feature points, a global-model set G possessing ′ sub-model sets can be generated, and represents the t-th sub-model set, that is, ,

,

,

1, … , ′

(7)

where 1 and 2 represents the segment lengths at both sides of the t-th sub-model set, represents the included angle of the t-th sub-model set. In GBGM, the computation of differential ( ) between RG and MG is as follows: ,

,

,

And the weight value set of ∑

is

′ ∑

where

1

2

and

′

1

,

2



,

,

,

(8)

. Then the differential

1

is (9)

1

2

2

2

2

.

Score Integration and Recognition. Through the integration of the average matching strength AMD of feature points and the differential GD of geometrical model, we can obtain one way recognition score S as . Suppose 1 is the forward recognition score and 2 is the backward recognition score, by adding the two scores together, we can then obtain a bilateral recognition score . Suppose the number of candidates selected from the first stage is M, the FS, that is number of trained images of each candidate is , , and , are respectively the bilateral recognition score and the GDA recognition score of the test image on the j-th trained image

Applied Mechanics and Materials Vols. 479-480

of the i-th candidate, and i-th candidate, then

887

represents the integrated recognition score of the test image on the ,

,…,

/

,

(10)

Then the candidate ∗ having the largest integrated recognition score is determined to be the final recognition result, that is ∗ . 1,⋯, Experiment Results Related experiments have been performed with the proposed FPBR technology. In the experiments, PCA and GDA are used to be accompanied with the bilateral recognition (FPBR) module as proposed by this paper for comparison, and two commonly seen public databases, namely, Feret[12] and Banca [13] face databases, are used for learning and testing. GDA⨁FPBR represents that GDA is used not only to select candidates, but also to associate its score with the bilateral recognition score to generate the final recognition score; and GDA+FPBR represents GDA is used only to generate the candidates, and FPBR is used solely to generate the final recognition score. FERET Face Database. The famous FERET face database consists of 993 subjects. Each subject has several images taken at different angles and at different time. Here, for each subject, two images with significant distinct expressions are used, then one image is selected randomly as the training sample, and another image is used as test sample. Table 1 is the recognition result. Table 1 Recognition results of the FERET database Algorithm PCA+FPBR PCA⨁FPBR GDA+FPBR GDA⨁FPBR

First Stage 68.47% 81.26%

Second Stage 73.51% 74.11% 85.78% 86.60%

From the experimental result, it can be seen that the recognition rate of PCA is 68.47%, and the recognition rate of GDA is 81.26%, which clearly shows that GDA performs much better than PCA. With GBGM, the recognition rates of PCA⨁FPBR and GDA⨁FPBR are enhanced respectively to 74.11% and 86.6%, hence, it is clear that the bilateral feature-point recognition can practically improve the efficiency of the traditional dimension reduction methods. Banca Human Face Database. The Banca face database includes images of 52 persons, among them, 26 are male and 26 are female. In this experiment, the four sets of face images taken at the first scene (Controlled) are used as the experimental samples, and two of them are taken as training images, one set is used for validating parameters and another set is used for testing. For each person, there are 20 training images, 10 validation images and 10 test images. The main objective of this experiment is examine how much of the recognition accuracy influence will be brought on FPBR when different number of training samples are used. Table 2 shows the experimental results. When observing the result, we can obtain two conclusions: (1) more training images in general correspond to better recognition accuracy; and (2) the proposed FPBR has pretty good generalization ability, that is, the recognition rate will not be greatly reduced due to decreasing training samples. Table 2 Recognition results of the Banca database num 2 6 14 20

PCA

PCA⨁FPBR

GDA

GDA⨁FPBR

81.92% 83.65% 85.38% 89.42%

85.19% 87.50% 91.15% 93.65%

93.26% 95.38% 95.19% 98.26%

97.50% 98.07% 98.26% 99.03%

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From the above experiments with two famous face databases, it is clear that the proposed recognition method shows significant efficiency enhancement as compared to those of traditional methods such as PCA and GDA; for the FERET database, under the subject number is as high as 993, it includes images of different levels of expression change, and the recognition rate is still as high as 86.6%. For the Banca database, with different numbers of training samples, stable recognition result still can be acquired, that is, the recognition accuracy will not be seriously degraded when just a few training samples are used. For the Cas-Peal database with strong illumination change, it fully reveals that the proposed algorithm has considerable tolerance on illumination change. Therefore, the proposed FPBR approach accompanied with traditional statistical dimension reduction algorithm can indeed enhance the correctness rate of face recognition effectively. Conclusion This paper proposes a feature-point bilateral recognition algorithm which uses a block matching operation accompanied with geometrical model to calculate the geometrical distribution variation among feature points. For a designed Global-Based Geometrical Model, it describes in detail the distribution relation among feature points, and the accuracy for calculating geometrical model difference has been enhanced. From the experiment results, it is clear that the proposed face recognition method has improved the insufficiency of traditional dimension reduction algorithms, and the recognition accuracy is also effectively enhanced. Meanwhile, only very few training samples are required to achieve stable recognition result, and even when images are taken with different illuminations, it has astonishingly good recognition accuracy. Reference [1] M. Turk and A. Pentland, 1991, “Eigenfaces for recognition,” Journal of Cognitive Neuroscience, Vol. 3, No. 1, pp. 71-86. [2] V. Belhumeur et al., 1997, “Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection,” IEEE Transactions on Pattern Analysis and Machine Intelligence,vol.19,no.7, pp.711-720. [3] Xiaofei He et al., 2005, “Face recognition using Laplacianfaces,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 3, pp. 328-340. [4] Deng Cai et al., 2006, “Orthogonal Laplacianfaces for face recognition,” IEEE Transactions on Image Processing, vol. 15, no. 11, pp. 3608-3614, 2006. [5] J. Shawe-Taylor and N. Cristianini, 2004, “Kernel Methods for Pattern Analysis,” Cambridge University Press. [6] W. Liu et al., 2010, “Kernel Adaptive Filtering: A Comprehensive Introduction,” Wiley . [7] Hong Chang and Dit-Yan Yeung, 2005, “Robust Locally Linear Embedding,” Technical Report HKUST-CS05-12. [8] G. Baudat and F. Anouar, 2000, “Generalized discriminant analysis using a kernel approach,” Neural Comput., vol. 12, pp. 2385–2404. [9] Y.S. Huang, et al., 2006, “Face Detection with High Precision Based on Radial-Symmetry Transform and Eye-Pair Checking,” IEEE International Conference on Video and Signal based Surveillance, pp. 62. [10] Y.S. Hung, et al., 2011, “An Effective Illumiation Compensation Method for Face recognition,” 17th International Conference on Multimedia Modeling, pp. 525~535. [11] Z.H. Ou, 2011, “Visual Localization for Mobile Robots Based on Composite Map, Department of Computer Science and Information Engineering,” Chung Hua University. [12] P.J. Phillips et al., 1988, “The FERET Database and Evaluation Procedure for Face-Recognition Algorithms,” Image and Vision Computing, vol. 16, no. 5, pp. 295-306. [13] S. Bengio et al., 2002, “Experimental protocol on the BANCA database,” IDIAP-RR 05. [14] Wen Gao Senio et al., 2008, “The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations,” IEEE Transactions on systems, man, and cybernetics-part A : systems and humans, Vol. 38, No. 1.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 889-893 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.889

Robust Observer-Based Output Feedback Control for Time-Varying Systems Chieh-Chuan Feng Department of Electrical Engineering, I-Shou University, Kaohsiung City, Taiwan, R.O.C. [email protected] Keywords: Time-varying system, learning scheme, output-feedback.

Abstract. In this paper, we study an observer-based robust learning output feedback control for a class of time-varying system. where the observer is used to estimate the system states and a learning scheme is also proposed to learn the time-varying parameters. A regulator control problem is pursued with known time-varying bounds. It is shown that to estimate the system states asymptotically only part of the time-varying function need to be learned, not necessarily all the time-varying parameters. The designed output feedback closed-loop control system guarantees a robust norm bound performance measure and uniformly asymptotic stability based on quadratic stability.

Introduction A natural motivation for considering time-varying perturbations in the control system is that for many engineering problems the possible variations with time should be taking into account no matter how small they are. There are many literatures tackling the problems under robust and adaptive control framework for linear time-varying (LTV) systems. The robust control, in the last decade, has been widely studied for its robustness and its capacity for disturbance attenuation in both linear and nonlinear systems, see [2] and reference therein. In conventional robust control, the plant models are not necessarily known exactly, allowing small perturbations. On the other hand, the adaptive control is known to be effective and robust for uncertain systems[3], [4]. However, the assumptions that commonly made for adaptive control framework are: the system dynamics must be exactly linearized parameterized and can only deals with constant parameters or slowly time varying parameters. To cope with the restrictions based-on adaptive control, [5] suggest that a combination of adaptive and robust control may produce better results. These control schemes have already designed to treat linear and nonlinear uncertain systems. In this paper, we address the problem of designing an observer-based robust output feedback control for a class of time-varying systems perturbed by time-varying parametric uncertainties and external disturbances. The time-invariant control technique combined with adaptive learning scheme is to construct a robust-control-based stabilization controller such that a robust L2 -gain bound performance measure is achieved. The performance measure has twofold: 1) this control is in the sense that a prescribed L2 -gain from external disturbance to the controlled variable can be guaranteed for the closed-loop system regardless time-varying parameters. 2) the closed-loop system achieves uniformly asymptotically stability. A learning scheme that follows the adaptive control concepts is designed such that the time-varying parameters are detected. The paper is organized as follows: Section 2 introduces and formulates the plant and observer that will be used throughout the paper. The assumptions are also made. A robust L2 -gain bound performance measure to be followed and and control problems to be solved are defined. In section 3, we provide the main results and learning schemes to the control problem. Section 4 gives illustrative applications for a regulator control is designed under one control framework and then followed by the conclusion.

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System Formulation Consider time-varying systems ¯x + B ¯1 u + B ¯2 w, x¯˙ = F (t)A¯ y¯ = C¯ x¯, ys = ϕ(t)¯ y, ¯ x, z¯ = D¯

(1)

where x¯ ∈ Rn is the state of the system, u ∈ Rm is the control input, w ∈ Rl is the disturbance to be attenuated, F (t) ∈ Rn×n and ϕ(t) ∈ Rp×p are both time-varying matrices and the latter takes the form ϕ(t) = diag(ϕ1 (t), · · · , ϕp (t)). The normal outputs are suppose to be y¯ ∈ Rp and y¯ = C¯ x¯. But in the real situation, the real output may be contaminated by various reasons such as time-varying ¯ sensor faults, which is denoted by ys = ϕ(t)¯ y in (1). The controlled variable z ∈ Rq . The matrices A, ¯1 , B ¯2 , C, ¯ and D ¯ are constant matrix of appropriate dimensions. B In this paper we study an observer based output feedback control as follows, ˆ yo − ys ), ¯xo + B ¯1 u + B ¯2 w + L(ϕ(t)¯ x¯˙ o = A¯

(2)

ˆ is a learning scheme to estimate the timewhere y¯o = C¯ x¯o , x¯o is the observed state of x¯. The ϕ(t) varying function ϕ(t) and will be setup in the sequel. Now as the paper proceeds, the time argument of ϕ(t) and F (t) will be omitted without confusing the contents. Define the errors ϕ˜ = ϕˆ − ϕ and x˜ = x¯o − x¯, then the equation (2) becomes ˜yo + ϕC¯ x˜). ¯xo + B ¯1 u + B ¯2 w + L(ϕ¯ x¯˙ o = A¯

(3)

Now the error dynamics between plant states and observer is ˜yo . ¯ x + (I − F )A¯ ¯x + Lϕ¯ x˜˙ = (A¯ + LϕC)˜

(4)

For robust control, the following assumption is made for all time-varying uncertainties: We assume that the matrices ( ) F (t) ϕ(t) ∈ Ω, where the Ω is a ploytope that can be described by a set of its vertices, i.e., in the form {( ) ( )} Co F1 ϕ1 , · · · , Fn ϕn ,

(5)

where the matrices (5) are given. Definition and control problem: Let a constant γ > 0 be given. The time-varying systems (1) and (2) are said to be quadratically stabilizable with a robust L2 -gain bound γ if there exists a fixed feedback control law u = K x¯o with observer gain L such that for any admissible time-varying matrices, F and ϕ, the controlled output z¯ satisfies 1. The system is uniformly asymptotically stable. 2. Subject to the assumption of zero initial conditions, the controlled output z¯ satisfies ∥¯ z ∥2 ≤ γ, ∥w∥2 for every w(·) ∈ L2 [0, ∞) and initial conditions being equal to zero. Here, we will also use the notion of quadratic stability with an L2 -gain measure which was introduced in [2]. This concept is a generalization of that of quadratic stabilization to handle L2 -gain measure constraint to time-varying parameters attenuation. To this end, the characterizations of robust performance based on quadratic stability will be given in terms of matrix inequalities, where if LMIs can be found then the computations by finite dimensional convex programming are efficient.

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RESULT-LINEAR MATRIX INEQUALITY CHARACTERIZATION In this section the main results and a learning scheme are presented to solve a regulator control problem that guarantees quadratically stability with a robust L2 -gain bound γ. Main Theorem Theorem 1 Consider the system described by (1) and (2) with admissible time varying matrices stated in the Assumption. If there exist matrices P1 > 0, P2 > 0, K, and L and positive scalars γ, β1 , and β2 such that ( ( ) ) ¯2 (P1 B ¯2 )T P1 B ¯2 R−1 (P1 B ¯1 K ¯2 )T P1 B ¯1 K Π1 + γ −2 P1 B Π1 + P1 B < 0, < 0, ⋆ Π2 ⋆ Π2

(6)

γ −2 I − R−1 < 0,

(7)

1 ˜ ϕ˜˙ = − β12 P3 y¯oT y¯o ϕ, 2

(8)

and a learning scheme of ϕ˜ defined as

then the closed-loop system with u = K x¯o is said to be quadratic stable with a robust L2 -gain bound γ. The choice of matrix P3 > 0 is arbitrary and determines the decaying rate of (8). The matrices, Π1 and Π2 , defined in (6) are ¯1 K)T P1 + P1 (F A¯ + B ¯1 K) + β 2 A(I ¯ − F )T (I − F )A¯ Ω1 = (F A¯ + B 2

(9)

¯ T P2 + P2 (A¯ + LϕC) ¯ + β 2 P2 LLT P2 + β 2 P2 P2 Π2 = (A¯ + LϕC) 1 2

(10)

¯TD ¯ Π1 = Ω1 + D

(11)

Proof: Due to limitation of space, the proof is omitted. Remark: Applying congruence transformation and Schur complement, the matrix inequality (6) can be equivalently written as     ¯ 1 W QD ¯ T QA¯T (I − F )T ¯ 1 W QD ¯ T QA¯T (I − F )T Σ1 B Σ2 B ∗    Π2 0 0 Π2 0 0   < 0,  ∗  < 0, (12) ∗  ∗  ∗ −I 0 ∗ −I 0 −2 −2 ∗ ∗ ∗ −β2 I ∗ ∗ ∗ −β2 I where

¯2 B ¯2T , ¯ +B ¯1 W + γ −2 B ¯1T + F AQ ¯ T + WTB Σ1 = Q(F A) ¯ T + WTB ¯ T + F AQ ¯ +B ¯1 W + B ¯2 R−1 B ¯T , Σ2 = Q(F A) 1 2

and W = KQ with the control law K = W Q−1 . Remark: To include the computation of observer gain L, the (12) can be decomposed by applying the same technique as the above remark and thus we have 

¯1 W Σ1 B ∗ Σ3  ∗ ∗  ∗ ∗  ∗ ∗ ∗ ∗

¯T QD 0 −I ∗ ∗ ∗

QA¯T (I − F )T 0 0 −β2−2 I ∗ ∗

 0 0 Y P2   0 0   < 0, 0 0   −β1−2 I 0  0 −β2−2 I

(13)

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

¯1 W Σ2 B ∗ Σ3  ∗ ∗  ∗ ∗  ∗ ∗ ∗ ∗

¯T QD 0 −I ∗ ∗ ∗

QA¯T (I − F )T 0 0 −β2−2 I ∗ ∗

 0 0 Y P2   0 0   < 0, 0 0   −β1−2 I 0  0 −β2−2 I

(14)

¯ T + Y ϕC¯ and observer gain is L = P2−1 Y . where Σ3 = A¯T P2 + P2 A¯ + (Y ϕC) Remark: Thus, to find the control and observer gains, a convex feasibility problem is established Q > 0, P2 > 0, W, Y, R, γ

(15)

subject to (13), (14), (7), where the control gain K = W Q−1 and the observer gain L = P2−1 Y . Remark: It needs to be emphasized that the expression in the learning scheme (8) should clear from the context. Now, the y¯o = diag (¯ yo,1 · · · , y¯o,p ) and ϕ˜ is a column vector. Learning Schemes From Theorem 1 the closed-loop system described by (1) and (4) is quadratically stabilizable with a robust L2 -gain bound γ. Although (4) is used in the formulation of stability of the closed-loop system, we in fact need the observer (2). Therefore, to observe the state x¯ from (2) ˆ instead of ϕ. ˜ Thus a learning scheme of ϕˆ correctly, we need the estimate information of ϕ that is ϕ, must be established. Based-on the learning scheme in (8), we ensure the stability of the entire system. To retain such result, the following model are built ˙ ϕˆi = −ai ϕˆi + ri ,

(16)

where the parameter ai is an assigned parameter that determines the convergence rate of the learning scheme and ri is defined to be { ai y , if y¯o,i ̸= 0 y¯o,i s,i ri = (17) 0, if y¯o,i = 0 ri will drive the model (16) to the true value of ϕi as close as possible. This is intuitively understandable, since the observer design assures that y¯o,i → y¯i and thus ˙ ϕˆ = −ai ϕ˜i , where the asymptotic property is guaranteed by (8). ILLUSTRATIVE APPLICATIONS Consider the mass-damper-spring system and assume k1 and c1 are linear spring and damping. k2 (t), c2 (t), and c3 (t) are time-varying spring and viscous damping. The system is described by the following equation of motion 0 = −k2 (t)y + c3 (t)y˙ m¨ y = −k1 y − (c1 + c2 (t))y˙ + u,

(18)

where time-varying functions are c2 (t) = c2 (sin ω2 t), k2 (t) = km1 e−αt (cos ω1 t), and c3 (t) = 1 − c1 −αt e (cos(ω1 t)), and the constants are k1 = k and c1 = c2 = c. m Define x1 = y and x2 = y, ˙ the state space representation of (18) is ¯x + B ¯1 u x¯˙ = F (t)A¯ ys = y¯ = C¯ x¯,

(19)

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where

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( ( ) ) 1 e−αt cos ω1 t x1 x¯ = , F (t) = , x2 − cm2 sin ω2 t 1 ) ( ) ( ( ) 0 1 0 ¯ ¯ , B1 = 1 , and C¯ = 1 0 . A= c1 k1 −m −m m

Here, we consider ϕ = I and the observer is ¯xo + B ¯1 u + L(¯ x¯˙ o = A¯ yo − ys ).

(20)

Consider the parameters m = 1, c = 1, k = 1, α = 1, ω1 = 1, and ω2 = 10 (rad/sec). Thus the set of vertices of polytope Ω associated with time-varying matrix F (t) is {( ) ( ) ( ) ( )} 1 1 1 1 1 −1 1 −1 Co , , , . 1 1 −1 1 1 1 −1 1

(21)

Using the Matlab as simulation tool, we obtain the gain K and L from (15) as follows, ( ) ( ) −3.2039 K = −15.4880 −15.1873 , L = . −0.3763 ¯1 K) are placed in the left-half plane, which It can be easily shown that all eigenvalues of (F A¯ + B indicates that closed-loop poles have negative real part and, thus, the system is asymptotically stable. ¯ are located at −2.1020 ± j0.4025. Thus, it is concluded that The eigenvalues of observer (A¯ + LC) both states asymptotically approach to the origin. CONCLUSION In this paper we have devised an observer-based output feedback control to cope with time-varying system. Both regulator and tracking control can be placed under one framework. The notion of quadratic stability with a robust L2 -gain bound γ is used to guarantee the stability of the closed-loop system. The contribution of the paper shows that only part of the time-varying function needs to be learnt, not necessarily all the time-varying parameters. The example of mass-damper-spring system subject to sensor fault system is to demonstrate the effectiveness of the design. References [1] S. Sastry and M. Bodson, Adaptive Control - Stability, Convergence, and Robustness, New Jersey: Prentice Hall, Chap. 2, 1989. [2] S. Boyd, L. El Ghaoui, E. Feron and V. Balakrishnan, Linear Matrix Inequalities in Systems and Control Theory, vol. 15 of Studies in Appl. Math. SIAM, Philadelphia, June 1994. [3] K. Narendra and A. M. Annaswamy, Stable Adaptive Systems, New Jersey: Prentice Hall, Chap. 8, 1989. [4] M. Krstic, I. Kanellakopoulos, and P.V. Kokotovic, Nonlinear and Adaptive Control Design, New York: Wiely, 1995. [5] P.A. Ioannou and J. Sun, Robust Adaptive Control, New Jersey: Prentice Hall, 1996. [6] C.-C. Feng, "Fault-tolerant control and adaptive estimation schemes for sensors with bounded faults", IEEE Conference on Control Applications, Singapore, Oct., 2007.

CHAPTER 10: Computer and Information Technologies

Applied Mechanics and Materials Vols. 479-480 (2014) pp 897-900 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.897

Volumetric Model Body Outline Computation for an Object Tracking in a Video Stream Jihun Park1,a Hongik University, Dept. Computer Engineering, 94 Wowsanro, Mapo, Seoul, Korea a [email protected] Keywords: moving camera calibration, object tracking, quaternion, maximum likelihood estimation.

Abstract. This paper presents a new outline contour generation method to track a rigid body in single video stream taken using a varying focal length and moving camera. We assume feature points and background eliminated images are provided, and we get different views of a tracked object when the object is stationary. Using different views of a tracked object, we volume-reconstruct a 3D model body after 3D scene analysis. For computing camera parameters and target object movement for a scene with a moving target object, we use fixed feature background points, and convert as a parameter optimization problem solving. Performance index for parameter optimization is minimizing feature point errors as well as outline contour difference between reconstructed 3D model and background eliminated tracked object. The proposed method is tested using an input image set. Introduction

Initial Guessing

A

3D Stationary Scene Analysis

3D Model in Voxel

Stationary Scene Images with Feature Points & Background Elimination

Camera Parameters

This paper presents a new computation method for a rigid body movement in single video stream using a 3D volume reconstruction using 3D scene analysis method. The method presented by this paper can handle an object tracking in a video stream using varying focal length as well as fixed focal length portable cameras. For Zhang's calibration method[1], man-made grid pattern images are commonly used for camera calibration. But we can sometimes find right angle shapes or grid patterns with known side ratios in a real life scene. These patterns give clues for world coordinate points of target objects in a scene. The proposed camera calibration and 3D scene analysis is useful for camera external parameter computation for the following adjacent scene which includes previously computed known points. We have extended our approach by calibrating using only a single image in a single video stream which is not easy to calibrate by Zhang's method. But our presented calibration method is possible using four nonplanar points.

Perturb Variables

Tracked Body Moving Images

B

Tracked Object Movement Computation using Tracked Object Feature Points Tracked Object Outline Contour N Optimum? Y DONE

Fig. 1: Overview of camera calibration and 3D scene analysis Numerous approaches in rigid objects tracking are proposed. The objects are represented as points, geometric shapes [3], or outline contour [4]. Their recognition can be classified as probability based, template based, model based, or appearance based. Our tracking approach is 3D reconstructed model generated outline silhouette contour.

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Overview of Our Object Tracking System Figure 1 shows an overview of our single stream video object tracking. We have developed an object movement computation system using stationary 3D scene analysis, phase A in figure 1. At the 3D scene analysis phase, we compute camera parameters as well as 3D target object geometry. The more input images guarantees the better 3D model object reconstruction quality. In phase A, the tracked object is not moving, and we can get different views for the tracked object. In phase A, we can get 3D background scene geometry information as well as tracked object feature points. In some cases computing tracked object feature points is not possible due to lack of texture feature. But we can handle this situation by computing contour outline of the tracked 3D model body. Parameter optimization variables for 3D scene analysis phase are camera parameters for the view used to take different scene for 3D target object stationary scene. Camera parameter computation is done using parameter optimization or called nonlinear programming. The single frame camera parameter and object movement computation is done using parameter optimization as well. Camera parameters for a single frame and tracked object movement are variables for this case. The performance index is how precise camera parameters are how close fit the moved 3D reconstructed model body compared to background eliminated input image. We used computed 3D scene information for an object tracking. The input for an object tracking is single image as well as feature point correspondence relation and tracked object outline contour. Projected 3D model outline contour is computed using a local window based hull generation, which is explained later in more detail. The close fitness index is average shortest distance from a contour boundary pixel in a background eliminated input image to a computed outline contour line. A camera scans a stationary target object to get two or more images of different views of the target object for 3D stationary scene analysis. Feature point information on the background stationary scene is accumulated throughout a video sequence while the target object coordinate points are computed only once at 3D scene analysis process for the stationary scene, and they are used to track a moving target object through the entire video sequence. We need pixel position information on the tracked object as well as on the fixed environmental object. Projected Model Points Outline Computation In order to track a textureless target, we use object outline shape to evaluate tracking accuracy. From 3D scene analysis phase, we volume-reconstruct a 3D model for the tracked target. In volume reconstruction, we can compute voxel center points of the 3D model. The voxel center points of the 3D model is projected on the input image after movement to chase the target. The model body movement is determined by perturbation inside the parameter optimization process. An outline contour representing a 2D bounding hull for projected 3D model voxel center points shows a silhouette for the projected model body. For computing tracking accuracy, we need to compute outline contour for model body projected points. Outline contour is generated using a piecewise straight line. Performance Index for Single Frame Video Tracking Performance index consists of two sections. One is for camera calibration accuracy. For calibration computation, inputs are feature points and correspondence relation on fixed environmental objects. Camera related performance index is minimizing projection errors. The other part of the performance index is in terms of object tracking. If there are no feature points on the tracked body, the only way is using object silhouette. The volume reconstructed 3D model body outline contour is computed as a set of straight lines. 3D reconstructed voxel points are projected to find a set of straight lines making an outline silhouette contour of a projected 3D model body. The background eliminated input frame is used for generating outline pixels. The silhouette fitness is checked by comparing background eliminated input image tracked blob outline pixels with 3D reconstructed and projected straight outline sets. The shortest distance from a pixel to a segment of straight line is computed. For every outline pixels, we compute shortest distances. The pixel number weighted average of shortest distance is added at a performance index value.

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Algorithm for Camera Calibration Modified Zhang's Algorithm for Additional Frame 3D Scene Analysis. 3D scene analysis and camera parameter computation is done at phase A of figure 1. In this phase, we include points on both tracked body as well as fixed environmental objects in 3D scene analysis. Our actual maximum likelihood estimation uses extra 3D point(s) that do not exist on the 2D plane used for initial guessing computation. The tracked object is stationary for a while. But after 3D scene analysis, these stationary objects will move eventually. Object Movement and Camera Parameter Computation Because only n-th single image is used in object movement computation, phase (B) computes nth image's camera position and orientation and tracked object(s) movement using equation (1). Inputs for phase (B) are computed 3D background scene analysis points and feature points on tracked object(s) before movement, and these points are computed in phase (B) or feature points correspondence relations are provided. But for an image with moved object, we still need to find camera external parameters. The total number of correspondence relation known or 3D coordinate computed points are (v + p) in phase (A). p consists of stationary background feature points as well as feature points on tracked moving body(s). Let us denote p1 as background environmental stationary feature points, and p2 as feature points on tracked body(s). p points are unknown 3D feature points but can be found in many input images, and p = p1 +p2 . We have minimized projection errors of fixed environmental points and outline contour shape errors as well as points on tracked rigid body(s) after translation and rotation. A is the camera intrinsic matrix, R is the camera rotation matrix, t is the camera translation vector, and m ˆ i (A, Ri , ti , Mj ) is the projection of 3D point Mj in image i. w1 is a weighting factor for Zhang's calibration which uses 3D known points, and w2 denotes a weighting factor for including rigid object movement, w3 denotes sum of shortest distance between computed body projected outline hull and background eliminated input image outline pixel, divided by number of contour pixels. p2 denotes the number of points on tracked objects computed in phase (A), b denotes the number of moving objects in an object moving scene, and a denotes an index for moving objects, i denotes an index for feature points on tracked body(s), Oai denotes i-th feature point on a-th tracked object computed using stationary 3D scene images. That is to say, Oai is a point before movement. T ra is a transformation for a-th target rigid body to model target movement using seven variables for quaternion based orientation and translation, n is the image index for the single added image with moving target object(s). We employ four variables for n-th camera orientation, three variables for n-th camera position, and one variable for n-th camera focal scale factor, seven variables for a single tracked body movement, total (8 + 7b) variables for phase (C) computation. (v + p1 ) 3D stationary scene feature points as well as p2 feature points on moving object(s) are projected on n-th image. We run maximum likelihood estimation[2] to compute camera parameters and object movement for a single input image minimizing 3D feature point's projection errors and outline contour matching errors on the single input image. We could reduce the number of variables by using quaternion. Our phase (B) computation can be done using a single modified maximum likelihood estimation function of equation (1). 1 w1 Σv+p ˆ n (A, Rn , tn , Ml )∥2 l=1 ∥mnl − m 2 ∥mni − m ˆ n (A, Rn , tn , T ra Oai )∥2 + w3 +w2 Σba=1 Σpi=1

(1)

Experimental Results Figure 2(a) shows one of input images. We have provided background eliminated images as well as feature point correspondences. In figure 2(b), we have generated a resulting texture-colored 3D volume reconstructions of a woman from silhouettes in order to demonstrate our camera calibration

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(a)

(b)

(c)

Fig. 2: (a) An input image, (b) corresponding three dimensional volume reconstruction of a stationary woman after 3D scene analysis, and (c) woman moved input image with 3D volumetric and its corresponding outline contour superimposed. and 3D scene analysis computation works correct. Figure 2(c) is an actual input image used to compute a human body movement. On the input image, we have generated a 3D voxel based model body, and superimposed on the input image. The superimposing is based on our optimization result. In order to demonstrate our computation works well, we have computed camera position and orientation used for taking the n-th scene with moved human body. In figure 2(a,c), world coordinate origin is set on the tile wall while X direction is toward ground, Y direction is human back, and Z direction is out from the tile wall. Actual object movement measurement is not easy. Size of the wall tiles in the input images is 207mm X 108mm. All codes were written in C programming language without using any other libraries except GRG2 [2], and we used IXY810 and IXUS210 portable digital cameras for images. Conclusion Because we use previous 3D scene analysis result, our single image based camera parameter computation as well as object(s) movement computation is very accurate. We just extract object movement information using previously computed 3D stationary scene analysis. The experimental results show our algorithms work nice for computing object movement in a single video stream as well as for accurate camera calibration. Because the suggested maximum likelihood estimation includes non-planar points as well as object outline contour, the calibration and object movement computation is more accurate. Acknowledgements This work was supported by 2012 Hongik University Research Fund. References [1] Z. Zhang, "A Flexible New Technique for Camera Calibration," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no 11, pp. 1330-1334 (2000) [2] L. S. Lasdon and A. D. Warren and A. Jain, and M. Ratner, "Design and testing of a generalized reduced gradient code for nonlinear programming," ACM Trans. Math. Software, vol. 4, no. 1, pp. 34-50 (1978) [3] J. Park, S. Park and J. K. Aggarwal, "Accurate object contour tracking based on boundary edge selection," Pattern Recognition, vol. 40, no 3, pp. 931-943, May 2003. [4] M. Roh and T. Kim and J. Park and S. Lee, "Human Motion Tracking by Combining View-Based and Model-Based Methods for Monocular Video Sequences," Lecture Notes in Computer Science, vol. 2669, pp. 650-659, March 2007.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 901-905 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.901

Efficient Scheduling for Real-time Pinwheel Tasks on DVS Processors Da-Ren Chen1, aand You-Shyang Chen2,b 1

Dept. of Information Management, National Taichung University of Science and Technology,129 Sec. 3, Sanmin Rd. Taichung 40401, Taiwan, R.O.C.

2

Dept. of Information Management, Hwa Hsia Institute of Technology, No.111, Gongzhuan Rd., Zhonghe Dist., New Taipei City 235, Taiwan, R.O.C. a

b

[email protected], [email protected]

Keywords: hard real-time systems, power-aware scheduling, dynamic voltage scaling, pinwheel tasks.

Abstract. In this paper, we focus on the pinwheel task model for a variable voltage processor with d discrete voltage/speed levels. We propose an intra-task DVS algorithm which constructs a minimum energy schedule for k tasks in O(d+ k log k) time. Previous approaches solve this problem by generating a canonical schedule beforehand and adjusting the tasks’ speed in O(dn log n) or O(n3) time. However, the length of a canonical schedule depends on the hyperperiod of those task periods and is of exponential length in general. In our approach, the tasks with arbitrary periods are first transformed into harmonic periods and then profile their key features. Afterward, an optimal discrete voltage schedule can be computed directly from those features. 1.

Introduction In the last decade, energy-aware computing has become widespread not only for portable and mobile devices powered by batteries, but also for large systems in which the cost of energy consumption and cooling is substantial. With dynamic voltage scaling (DVS) techniques [1, 7, 8, 9, 10, 13], processors are capable of performing at a range of voltages and frequencies. Since energy consumption is at least a quadratic functions of the supply voltage (hence CPU speed)[1, 11, 12, 13], the total energy consumption could be minimized by sharing slack time while satisfying the time constraints of the tasks. There are many studies that have addressed the problem of task scheduling and min-energy DVS scheduling. Yao et al. [12] proposed a theoretical DVS model and an O(n3) algorithm for computing min-energy DVS schedule in a continuous variable voltages CPU. Ishihara et al. [5] proposed an optimal voltage allocation technique using discrete variable voltage processor. However, the optimality of the technique is confined to a single task. Kwon et al. [4] proposed an optimal discrete approach, which is based on the continuous version in [12] and therefore requires O(n3) time. Recent result proposed by Li et al. [9] gives an O(dn log n) time algorithm which constructs a minimum energy schedule without first computing the optimal continuous schedule. In the min-energy DVS scheduling algorithms mentioned above, those techniques have to generate in advance certain schedules as the intermediate processing of their algorithms. For example, the algorithm Bipartition in [9] has to generate an s-schedule and a reversed s-schedule in advance. Moreover, algorithm Alloc-vt in [8] has to generate a min-energy continuous schedule from [12] prior to perform their algorithm. Since the lengths of such schedules depend on the LCM of task periods, their algorithms could not be completed in polynomial time. Additionally, in the periodic tasks systems, the preprocessing overhead produced by these approaches may become much severe when tasks join and leave the systems frequently. In a network system, jitter is the variation in the time between packet arriving, caused by network congestion, timing drift, or route changes [10]. In a periodic task schedule, a task’s jitters are often caused by the interference of other tasks. A jitterless schedule means that the inter-arrival times of successive instances (jobs) of a task are identical. In many real-time applications, tasks must be executed in a distance-constrained manner, rather than just periodically. C. -W. Hsueh et al. propose Sr[4] algorithm to transform the period lengths of pinwheel task into harmonic which is shorter than or equal to the original periods.

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This paper discusses the theoretical power-aware real-time scheduling. We consider a discrete DVS scheduling problem for periodic task systems given worst-case execution times (WCET). We proposed an algorithm that finds a min-energy intra-task schedule in O(d+k log k) time. In section 2, we give the model and the notational conventions. Section 3 presents the properties of jitterless schedule and the algorithm that generates pinwheel schedule. The DVS algorithms are proposed in Section 4. In Section 5, we present the performance analyses of the proposed algorithms and compare the utilization of transformed task sets with those of their original task sets. Section 6 concludes this paper. 2.

Task Model Pinwheel task systems are first motivated by the performance requirements of satellite-based communications [4]. A pinwheel task Ti is defined by two positive integers, an execution requirement and a window length, with explanation that the task Ti needs to be allocated to the shared resource for at least a out of every b consecutive time units[2, 6, 7, 10]. In the distance-constrained task systems (DCTS)[4], the temporal distance between any two consecutive executions of each job in the pinwheel schedules should always be less than a certain value. In DCTS, pinwheel tasks transform the distance-constraints into two times of other shorter periods [4], which is not longer than its original distance-constraints by using algorithm Sr [4]. The advantage of the period transformation is that the produced schedules have regular start, preemption and finish times, and therefore provide good predictability. We focus on synchronous, preemptive and periodic task systems. In the task set τ={T1, …, Tk} of k periodic real-time tasks, every task Ti consists of an infinite sequence of jobs ji,1, ji,2, …. A task Ti with a WCET requirement ei and a period pi has weight wi=ei/pi, where 0sd the clock speeds corresponding to d given discrete voltage levels. The highest speed s1 is always fast enough to guarantee a feasible schedule for given tasks. Moreover, ei and eig denote the duration of the execution at speed s1 and sg, respectively. Time overhead to vary the supply voltage and clock frequency is negligible. Let Uτg = ∑i=1 wig denote the total weight of tasks in τ at k

speed sg where wig = eig / pi . For simplicity, Uτ denotes the total weight of τ at highest speed. The power P, or energy consumed per unit time, is a convex function of the processor speed. The energy t consumed by processor during the time interval [t1, t2] is E(t1, t2)= ∫ P ( s (t ))dt . We refer to this 2

t1

problem as discrete DVS scheduling (abbreviated to intraDVS). The first goal is to find, for any given task set τ, a feasible intraDVS schedule that minimizes E. On the contrary, in the inter-task version, every job has only one speed during its execution. 3. Jitterless Schedule In this section, we introduce the concept of h-schedule produced by Sr and propose its important properties. In Figure 1(a), a system have five tasks with periods {9.2, 10.6, 21.2, 22.6, 23.4}, and their execution times are {1.0, 1.1, 9.98, 0.94, 1,87}, respectively. After applying Sr, the new task periods {5.3, 10.6, 21.2, 21.2, 21.2} are illustrated in Figure 1(b). Because the periods are harmonics, the schedule for each task has no jitter, and its relative starting and ending times are fixed.

Applied Mechanics and Materials Vols. 479-480

CriticalSpeed(τ) Input: task set τ Output: critical speed sc g=d, Uτg =0 While Uτg 1 do { Uτg = Uτ × ( s1 / si ) ; g=g-1;} return sg.

FIG.1. (a)Periodic and (b) jitterless schedule

FIG. 2. Pseudo-code of Algorithm 1.

FeautreRetrieving(τ) Input: task set τ and speed level sc Output: a set of pairs (bi, fi) where 0 Lmax ) Lmax ← L(i ) forwarder ← i end if end for

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Simulation Performance To evaluate the performance of our proposed information dissemination schemes, we have developed the simulators[8,9] to measure the efficiencies of propagation speed and success rate of information dissemination. In our simulation, we refer the MOBIL (minimizing overall breaking induced by lane-changes) and IDM (intelligent-driver model) to model the driving behaviors. The road geometry in our designed simulation covers a 2000m * 2000m square area. Three types of road segments: one-way lane, bidirectional lane and four-lane roads constructs the grid road network. There are 6 roads and nine intersections. The corresponding simulation parameters are depicted in Fig. 2. Parameter Value Simulation Time 1000s Simulation Repetitions 100 Simulation Area 2000m x 2000m Communicating Range (R) 250m Number of Lane 1, 2, 4 Mean of Vehicle Velocity 40 km/h Vehicle Density 30 vehicles/km per lane Nmax 10 SlotTime 20 µs Packet Size 1000 bytes Fig. 2 Parameter setting It compares the efficiency of information dissemination between our proposed EBBP and Black-Burst (BB) protocol. Fig. 3 shows that the higher rate of packet generation rate may cause the decrease of message propagation speed. But our proposed scheme can efficiently reduce the computing power of iteration produce deciding the best next forwarder. Thus, it performs better than original BB.

Fig. 3 Simulation result

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Conclusions In this paper, we focus on the multi-hop broadcast protocols to propose two enhanced information dissemination schemes for efficiently broadcasting the disseminated message based on the black-burst time and with the factor of vehicle velocity. The simulation results show that our proposed schemes can disseminate the message faster and further indeed. In the future work, other factors, such as driving behaviors and road conditions, can be taken into account for precisely modeling the VANET in the real world. Acknowledgments: This work was partially supported by National Science Council of Taiwan (R.O.C.) under Grants NSC 99-2219-E-415-001, 100-2219-E-415-002 and 101-2219-E-415-002. References [1] L. Le, A. Festag, R. Baldessari and W. Zhang, “Vehicular Wireless Short-Range Communication for Improving Intersection Safety,” IEEE Communications Magazine, Vol. 47, No. 11, pp. 104-110, Nov. (2009). [2] P. Krishnamurthy, “Information Dissemination and Information Assurance in Vehicular Networks: A Survey,” Proceedings of the Third Annual iConference, Los Angeles, USA, February (2008). [3] Y.-C., S.-Y. Ni, Y.-S. Chen and J.-P. Sheu, “The Broadcast Storm Problem in a Mobile Ad Hoc Network,” Wireless Networks, Vol. 8, No. 2/3, pp. 153–167, Mar.–May (2002). [4] S. Panichpapiboon and W. Pattara-atikom, “Connectivity Requirements for Self-Organizing Traffic Information Systems,” IEEE Transactions on Vehicular Technology, Vol. 57, No. 6, pp. 3333-3340, Nov. (2008). [5] J. Zhao, Y. Zhang and G. Cao, “Data Pouring and Buffering on the Road: A New Data Dissemination Paradigm for Vehicular Ad Hoc Networks,” IEEE Transactions on Vehicular Technology, Vol. 56, No. 6, pp. 3266-3277, Nov. (2007). [6] G. Korkmaz, E. Ekici and F. Özgüner, IEEE T. VEH. TECHNOL., 56, 3159 (2007). [7] L. Briesemeister and G. Hommel, Role-Based Multicast in Highly Mobile but Sparsely Connected Ad Hoc Networks, Proceedings of the First Annual Workshop on Mobile Ad Hoc Networking and Computing, Boston, pp. 423-428, USA (2000). [8] J. M. Hsu and W. T. Wang, “The Improvement of Backoff-Time Based Information Dissemination Protocols for Vehicular Networks,” Proceedings of The 6th Intelligent Living Technology Conference, Taichung, June (2011). [9] W. T. Wang, A Study of Information Dissemination Based on Back-off Time and Inter-Vehicle Distance in Vehicular Ad Hoc Networks, National Chiayi University (2011).

Applied Mechanics and Materials Vols. 479-480 (2014) pp 978-982 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.978

Threshold-based Privacy-Preserving Key Management Scheme for Vehicle-to-Grid Networks Huei-Ru Tseng Information and Communications Research Labs Industrial Technology Research Institute No. 195, Sec. 4, Chung Hsing Rd., Chutung, Hsinchu, Taiwan, 31040 [email protected] Keywords: Vehicle-to-Grid, Electric vehicles, Secret sharing, Aggregator.

Abstract. The concept of vehicle-to-grid (V2G) is that electric vehicles (EVs) communicate with the smart grid to sell demand response services by delivering electricity into the grid. Due to the scale of the network, the speed of the vehicles, their geographic positions, and the very sporadic connectivity between them, V2G communications have the crucial requirements of fast session key establishment. In this paper, we propose a threshold-based privacy-preserving key management scheme for V2G networks, which utilizes the threshold-based secret sharing and symmetric key technique to protect the identities of the EV owners and to establish the shared session key between the aggregator and the vehicle. The proposed scheme can achieve the property of identity privacy, confidentiality of the communications, and known-key security. Introduction Vehicle-to-grid (V2G) networks are crucial components of the smart grid for the capability of providing better ancillary services. The concept of V2G is that electric vehicles (EVs) communicate with the smart grid to sell demand response services by delivering electricity into the grid. By letting EVs discharge during peak hours and charge during off-peak hours, V2G networks could bring numerous social and technical benefits to the smart grid. The scenario of V2G is shown in Fig. 1. Currently, many projects and researches for V2G networks have been conducted [1-9]. In addition, in Europe and the USA, the standards for V2G technology have been conducted by International Organization for Standardization (ISO), European Telecommunications Standards Institute (ETSI), and Society of Automotive Engineers (SAE). Due to the scale of the network, the speed of the vehicles, their geographic positions, and the very sporadic connectivity between them, V2G communications have the crucial requirements of fast session key establishment. In 2011, Wu and Zhou [10] proposed a fault-tolerant and scalable key management for smart grid, which combines symmetric key technique and elliptic curve public key technique. However, their protocol is vulnerable to the man-in-the-middle attack [11]. Therefore, Xia and Wang [11] proposed a secure key distribution for smart grid, which uses a third-party setting for key distribution letting the server work as a lightweight directory access protocol server without losing security. In this paper, we propose a threshold-based privacy-preserving key management scheme for V2G networks, which makes use of threshold-based secret sharing [12] and symmetric key technique to protect the identities of the EV owners and to establish the shared session key between the aggregator and the vehicle. The proposed scheme can achieve the property of identity privacy, confidentiality of the communications, and known-key security. The rest of the paper is organized as follows. In Section 2, we will show the design of the proposed scheme in detail, which is followed by security analysis in Section 3. Finally, Section 4 makes a conclusion.

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Fig. 1: The scenario of V2G communications. Table 1: Notations Sym. SGCC AG RSU EVi IDi P IDi x ki fk (·) SKij Enc(·) Dec(·) H1 (·) H2 (·) ∥

Definition A smart grid control centre An aggregator A road-side unit The i-th electric vehicle A real-identity of the entity (EVi /AG) A pseudo-identity of the EVi A master key of the SGCC A secret key of EVi /AG A pseudorandom function (PRF) generator f with security parameter k, produces k-bit output The session key computed by EVi and the AG with an identity IDj A secure symmetric encryption algorithm [13] A secure symmetric decryption algorithm [13] A one-way hash function A one-way hash function Message concatenation operation

The Proposed Scheme In this section, a threshold-based privacy-preserving key management scheme for V2G networks is presented. In the proposed scheme, there are four parties, including a smart grid control centre (SGCC), road-side units (RSUs), an aggregator (AG), and individual EVs. EVs are equipped with a bidirectional grid power interface and wireless connectivity. The aggregator is a middleman between a control centre and EVs. Based on the real-time condition, the control centre will send the electricity requirement to the aggregator. Then the aggregator will broadcast the messages to call the EVs within its communication range. If EVs want to take action according to the electricity requirement, the EVs will first communicate with the RSU to obtain a passage, and then utilize the passage to respond and generate the session key with the aggregator. The notations are listed in Table 1. The scheme is divided into two phases: initialization and session key generation. Initialization The SGCC sets up the system parameters as follows: 1. SGCC chooses two two large primes p and q satisfying p = 2q+1, pseudorandom function fk (·), one-way hash functions H1 and H2 , and a secure symmetric encryption algorithm Enc(·) [13]. 2. The SGCC then chooses a random number x ∈ Zq∗ as its master key and chooses µ ∈ Zq∗ for generating the pseudo-identity and secret keys.

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1.

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EVi Send {P IDi , IDj } to the RSU

→

Receive {C1 , t1 } Check the freshness of t1 If so, decrypt C1 and obtain fkj (P IDi , t1 ) Choose r Send {r, t1 , P IDi } to the AG

←

→

5.

Receive {s, C2 } Check whether the following equation holds C2 = H2 (fkj (P IDi , t1 ), r, s) If so, compute SKij = H2 (fkj (P IDi , t1 ), r, s, P IDi , IDj ) Compute C3 = H2 (fkj (P IDi , t1 ), SKij ) Send {C3 } to the AG

2.

4.

←

→

6.

RSU Receive {P IDi , IDj } Communicate with (m − 1) RSUs to obtain m's Di Utilize Lagrange interpolation to reconstruct µ Compute C1 = Encki (fkj (P IDi , t1 )) Send {C1 , t1 } to EVi

AG Receive {r, t1 , P IDi } Compute fkj (P IDi , t1 ) Choose s Compute SKij = H2 (fkj (P IDi , t1 ), r, s, P IDi , IDj ) Compute C2 = H2 (fkj (P IDi , t1 ), r, s) Send {s, C2 } to EVi

Receive {C3 } Check whether the following equation holds C3 = H2 (fkj (P IDi , t1 ), SKij ) If so, AG accepts the session key generation

Fig. 2: The session key generation phase of the proposed scheme.

For EVi with an identity IDi participating the V2G network, SGCC generates its pseudo-identity P IDi = Encx (IDi ), where x is the master key of the SGCC, and computes its secret key ki = H1 (P IDiµ mod p), and sends the pseudo-identity and secret key back to EVi through an existing secure channel. For the aggregator with an identity IDj , SGCC generates the its secret key kj = H1 (IDjµ mod p), and sends back to the aggregator through an existing secure channel. Assume there are n RSUs in the system. SGCC utilizes the threshold-based secret sharing technique [12] to divide the secret value µ into n pieces, and defines the secret value is easily reconstructable form any subset of m of these pieces. SGCC chooses a random (m − 1) degree polynomial q(y) = a0 + a1 y + · · · + am−1 y m−1 in which a0 = µ, and evaluates as follow. D1 = q(1), D2 = q(2), · · · , Dn = q(n)

(1)

For the RSU with an identity IDk , SGCC sends Dk to the RSU through an existing secure channel. Session Key Generation Based on the real-time condition, the control centre will send the electricity requirement to the aggregator. Then the aggregator will broadcast the messages to call the EVs within its communication range. The EVs will respond and generate the session key with the aggregator if EVs want to take action according to the electricity requirement. Assume the EV with a pseudo-identity P IDi responds and generates the session key with the aggregator with an identity IDj . A high-level depiction of the session key generation phase is illustrated in Fig. 2. The details are presented as follows. 1. EVi sends {P IDi , IDj } to the RSU. 2. Upon receiving the above message, the RSU communicates with (m−1) RSUs and then obtains m's Di . The RSU utilizes Lagrange interpolation to reconstruct µ, and then computes C1 as follows. C1 = Encki (fkj (P IDi , t1 )) (2) where t1 is the timestamp. Then the RSU sends {C1 , t1 } back to EVi .

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3. After receiving the message, EVi checks whether t1 is fresh. If so, EVi decrypts C1 by using its secret key ki and obtains fkj (P IDi , t1 ). After that, EVi chooses a random number r, and sends {r, t1 , P IDi } to the AG. 4. The AG first computes fkj (P IDi , t1 ), and computes the session key SKij and C2 as follows. SKij = H2 (fkj (P IDi , t1 ), r, s, P IDi , IDj )

(3)

where s is a random number. C2 = H2 (fkj (P IDi , t1 ), r, s)

(4)

Then AG sends {s, C2 } back to EVi . 5. EVi first checks whether the following equation holds. C2 = H2 (fkj (P IDi , t1 ), r, s)

(5)

If so, EVi computes the session key SKij and C3 as follows. SKij = H2 (fkj (P IDi , t1 ), r, s, P IDi , IDj )

(6)

C3 = H2 (fkj (P IDi , t1 ), SKij )

(7)

Then EVi sends {C3 } back to the AG. 6. After receiving C3 , the AG checks whether the following equation holds. C3 = H2 (fkj (P IDi , t1 ), SKij )

(8)

If so, the AG accepts the session key generation.

Security Analysis of The Proposed Scheme We now analyze the security properties of our scheme. We will show that our scheme can provide identity privacy, confidentiality of the communications, and known-key security. Theorem 1. The proposed scheme can ensure the identity privacy of EVs. Proof. In the proposed scheme, we propose to use pseudo-identities to preserve the identity privacy of EVs. Since the vehicle EVi uses the pseudo-identity P IDi during its communication with the RSU and AG, the RSU and AG cannot deduce the EVi 's real identity. As a result, the real-identity IDi is protected. Hence, the privacy preservation can be satisfied in the proposed scheme.  Theorem 2. The proposed scheme can achieve confidentiality of the communications. Proof. In the proposed scheme, EVi and the aggregators generate the session key to ensure the confidentiality of the communications. Only valid EVi and aggregators have the corresponding secret keys to compute the session key. The session key shared between EVi and the AG is defined as SKij (equation (3), equation(6)). Therefore, the proposed scheme can achieve confidentiality of the communications.  Theorem 3. The proposed scheme can provide known-key security. Proof. In the proposed scheme, even if a session key SKij is revealed to an adversary A, he still cannot derive other session keys since the random nonce and the timestamp embedded in session keys are different for each session. Hence, the proposed scheme can achieve known-key security. 

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Summary In this paper, we propose a threshold-based privacy-preserving key management scheme for V2G networks, and make use of threshold-based secret sharing and symmetric key technique to protect the identities of the EV owners and to establish the shared session key between the aggregator and the vehicle. The proposed scheme can achieve the property of identity privacy, confidentiality of the communications, and known-key security. References [1] Smartgrid city. [Online]. Available: http:// smartgridcity.xcelenergy.com/ [2] Center for carbon-free power integration. [Online]. Available: http:// www.carbonfree.udel.edu/ [3] Z. Yang, S. Yu, W. Lou, and C. Liu, IEEE Transactions on Smart Grid, 2, 4 (2011). [4] H. R. Tseng, A secure and privacy-preserving communication protocol for V2G networks, IEEE Wireless Communications and Networking Conference (WCNC), Paris, France, IEEE Press (2012), pp. 2706-2711. [5] H. R. Tseng, A robust aggregated message authentication protocol for vehicle-to-grid networks, The 19th World Congress on Intelligent Transport Systems, Vienna, Austria (2012). [6] H. R. Tseng and T. H. Chueh, Applied Mathematics and Information Sciences, In Press (2013). [7] T. H. Chueh and H. R. Tseng, Applied Mechanics and Materials, 145 (2012), pp. 364-368. [8] H. R. Tseng, Applied Mechanics and Materials, 284-287 (2013), pp. 3380-3384. [9] H. R. Tseng, Privacy-preserving key management scheme for vehicle-to-grid networks, The 20th World Congress on Intelligent Transport Systems, Tokyo, Japan (2013). [10] D. Wu and C. Zhou, IEEE Transactions on Smart Grid, 2, 2 (2011), pp. 375-381. [11] J. Xia and Y. Wang, IEEE Transactions on Smart Grid, 3, 3 (2012), pp. 1437-1443. [12] A. Shamir, Communications of the ACM, 22, 11 (1979), pp. 612-613. [13] D. R. Stinson, Cryptography: Theory and practice, Chapman & Hall/CRC, Boca Raton, FL, 2006.

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Robust exponential stability for uncertain discrete-time switched systems with interval time-varying delay via a switching signal Jenq-Der Chena*,Chang-Hua Lienb, Ker-Wei Yub, Chin-Tan Leea, Ruey-Shin Chenc, Chyi-Da Yangd a*

Department of Electronic Engineering, National Quemoy University, Kinmen, Taiwan , R.O.C. Department of Marine Engineering, National Kaohsiung Marine University, Kaohsiung, Taiwan , R.O.C. c Department of Computer Engineering, National Quemoy University, Kinmen, Taiwan, R.O.C. d Department of Microelectronics Engineering, National Kaohsiung Marine University, Kaohsiung, Taiwan, R.O.C. * Corresponding author: [email protected]. Tel: 886-82-313557. Fax: 886-82-313537. b

Keywords: Switching signal design, robust exponential stability, discrete-time switched system, interval time-varying delay.

Abstract-In this paper, the switching signal design to robust exponential stability for discrete-time switched systems with interval time-varying delay is considered. LMI-based conditions are proposed to guarantee the global exponential stability for such system with parametric perturbations by using a switching signal. The appropriate Lyapunov functionals are used to reduce the conservativeness of systems. Finally, a numerical example is illustrated to show the main results. 1. Introduction A switched system is composed of a family of subsystems and a switching signal that specifies which subsystem is activated to the system trajectories at each instant of time [1]. Some real examples for switched systems are automated highway systems, automotive engine control system, chemical process, constrained robotics, power systems and power electronics, robot manufacture, and stepper motors [2-14]. Switching among linear systems may produce many complicate system behaviors, such as multiple limit cycles and chaos [1]. It is also well known that the existence of delay in a system may cause instability or bad performance in closed control systems [15-18]. Time-delay phenomena are usually appeared in many practical systems, such as AIDS epidemic, chemical engineering systems, hydraulic systems, inferred grinding model, neural network, nuclear reactor, population dynamic model, and rolling mill. Hence stability analysis and stabilization for discrete switched systems with time delay have been researched in recent years [2-4, 7, 9-10, 12-14]. It is interesting to note that the stable property for each subsystem cannot imply that the overall system is also stable under arbitrary switching signal [4, 6, 8-9]. Another interesting fact is that the stability of a switched system can be achieved by choosing the switching signal even when each subsystem is unstable [5, 7-8]. In [7], a switching signal design technique is proposed to guarantee the asymptotic stability of discrete switched systems with interval time-varying delay. In [14], the switching signal is identified to guarantee the stability of discrete switched time-delay system. Additional nonnegative inequality terms had been used to improve the conservativeness for the obtained results in our past results [4-5, 18]. Hence the global exponential stability problems for uncertain switched discrete systems with interval time-varying delay under some certain switching signal will be considered in this paper. Some numerical examples are provided to demonstrate the use of obtained results. From the simulation results, our proposed approach provides some less conservative results.The notations are used throughout this paper. For a matrix A, we denote the transpose by AT , spectral norm by A , symmetric positive (negative) definite by A > 0 ( A < 0 ), maximal eigenvalue by λmax ( A) , minimal eigenvalue by λmin ( A) , n × m dimension by A(n×m ) . A ≤ B means that matrix B − A is symmetric positive semi-definite. 0 and I denote the zero matrix and identity matrix with compatible dimensions. diag {
} stands for a block-diagonal matrix. For a

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x , we denote the Euclidean norm by xk s = max x(k + θ ) . θ = − r , − r +1,
, 0

vector

M

x

. Define

N = {1, 2,
, N } ,

N >1 ,

M

2. Problem Statement and Preliminaries Consider the following uncertain discrete switched system with interval time-varying delay of the form x(k + 1) = (Aσ ( k ) + ∆Aσ ( k ) (k ))x(k ) + (Ad σ ( k ) + ∆Adσ ( k ) (k ))x(k − r (k )) , x(θ ) = φ (θ ) , θ = −rM , − rM + 1,
, 0 , (1) where x(k ) ∈ ℜ n is the state vector, xk is the state at time k defined by xk (θ ) := x(k + θ ), ∀θ ∈ {− rM , − rM + 1,
, 0} , switching signal law σ (k , x(k )) is a piecewise constant function depending on the state in each time. The switching signal σ (k , x(k )) takes its value in the finite set N and will be designed. φ (k ) ∈ ℜ n is a vector-valued initial state function. The time-varying delay r (k ) is a function from {0, 1, 2, 3,
} to {0, 1, 2, 3,
} , and satisfies the following condition: 0 < rm ≤ r (k ) ≤ rM ,

(2)

where rm and rM are two given positive integers. Moreover, the σ (k ) = i implied that the i − th subsystem ( Ai + ∆Ai (k ), Ad i + ∆Ad i (k )) is activated, where Ai , Ad i ∈ ℜ n×n , i = 1,2,
, N , are some given constant matrices. ∆Ai (k ) , ∆Ad i (k ) , i = 1,2,
, N , are some perturbed matrices and satisfy the following conditions [∆Ai (k ) ∆Ad i (k )] = M i Fi (k )[N1i N 2i ] , (3) where M i and N ji , j = 1,2 i = 1,2,
, N , are some given constant matrices of system with appropriate dimensions, and Fi (k ) , i = 1, 2,
, N , are unknown matrices representing the parameter perturbations which satisfy Fi T (k )Fi (k ) ≤ I .

(4)

In order to derive our main results, the Lemmas are introduced as follows:

Lemma 2.1: [4] Let U, V, W and M be real matrices of appropriate dimensions with M satisfying M = M T , then M + UVW + W T V T U T < 0 for all V TV ≤ I , if and only if there exists a scalar ε > 0 such that M + ε −1 ⋅ UU T + ε ⋅ W T W = M + ε −1 ⋅ UU T + ε −1 ⋅ (εW ) (εW ) < 0 . T

W

W 

12 T T Lemma 2.2: [19] For a given matrix W =  11T  with W11 = W11 , W22 = W22 , then the following W W 22   12 conditions are equivalent: (1) W < 0, (2) W22 < 0, W11 − W12W22−1W12T < 0.

Define the some sets Ω i (α , P, U , Ai ) = {x ∈ ℜ n : x T (α −2 ⋅ AiT PAi − P + U ) x ≤ 0} , i = 1, 2,
, N ,

(5)

where 0 < α < 1 , P > 0 , and Q > 0 , then we obtain Ω1 = Ω1 , Ω2 = Ω1 − Ω1

i −1

N −1

,
, Ωi = Ω i − ∪ Ω j ,
, Ω N = Ω N − ∪ Ω j . j =1 j =1

From the above sets definition, then the switching law is designed as follows: σ = i , if x ∈ Ωi , i ∈ N , where Ωi is defined in (6).

(6)

(7)

Applied Mechanics and Materials Vols. 479-480

985

The key lemma can be easily proved by the similar way in [7]. Lemma 2.3: For any constant matrix M ∈ ℜ nxn , M = M T > 0 , integers γ 2 ≥ γ 1 , vector function ω : {γ 1 , γ 1 + 1,
, γ 2 } → ℜ n such that the sums in the following are well defined, then T

γ γ  γ  − (γ 2 − γ 1 + 1) ∑ ω T (θ )Mω (θ ) ≤ −  ∑ ω (θ ) R1  ∑ ω (θ ) . θ =γ θ =γ  θ =γ  2

2

1

2

1

(8)

1

3. Main results Theorem 3.1: System (1) is globally exponentially stable with convergence rate 0 < α ≤ 1 for any time-varying delay r (k ) satisfying (2), if there exist some n × n matrices P > 0 , S > 0 , T > 0 , Q > 0 , U > 0 , Ri > 0 , i = 1, 2, 3, 4 , and the positive numbers ε q , q = 1,2,
, N , such that the following LMI conditions are feasible: Ξ11j q  Ξ jq =  ∗  ∗ 

Ξ 22 q ∗

N

− P + U

i =1



∑αi ⋅ 

Ξ13 q   Ξ 23q  < 0 , j = 1,2 , q = 1,2,
, N , Ξ 33 q 

Ξ12 q

∗

(9)

AiT P   < 0, − α 2 ⋅ P

(10)

where Ξ111q = diag{−α−2 ⋅ AqT PAq −U + S +(rMm +1) ⋅Q+T −α2r ⋅ S −α2r ⋅ Q −α2r ⋅T}−α2r ⋅W1T R1W1 −α2r ⋅ (W2T R2W2 +W3T R3W3 +2⋅W4T R4W4 +W5T R4W5 ) m

M

M

m

M

Ξ112 q = diag{−α−2 ⋅ AqT PAq −U + S +(rMm +1) ⋅Q+T −α2r ⋅ S −α2r ⋅ Q −α2r ⋅T}−α2r ⋅W1T R1W1 −α2r ⋅ (W2T R2W2 +W3T R3W3 +W4T R4W4 + 2⋅W5T R4W5 ) m

M

M

m

M

 AqT P rm ⋅ ( Aq − I )T R1 rˆMm ⋅ ( Aq − I )T R2 rM ⋅ ( Aq − I )T R3 rMm ⋅ (Aq − I )T R4    0 0 0 0 0  Ξ12q =  T AdqP rm ⋅ AdqT R1 rˆMm ⋅ AdqT R2 rM ⋅ AdqT R3 rMm ⋅ AdqT R4    0 0 0 0  0 

Ξ13 q

0 ε q ⋅ N1Tq    0 0  = 0 ε q ⋅ N 2Tq    0  0

,

Ξ 23q

 PM q  r ⋅RM  m 1 q = rˆMm ⋅ R2 M q   rM ⋅ R3 M q rMm ⋅ R4 M q 

0 0 0  0 0

,

1 (rMm + 1) ⋅ (rM + rm ) , W1 = [I − I 0 0](n×4 n ) , 2 W4 = [0 0 I − I ](n×4n) , W5 = [0 I − I 0](n×4 n ) . rˆMm =

, Ξ 22 q = −diag {α 2 ⋅ P R1 R2 R3 R4 } ,

Ξ 33q = −diag {ε q ⋅ I

W2 = [I

0 −I

εq ⋅ I}

0](n×4 n ) ,

,

rMm = rM − rm

,

W3 = [I 0 0 − I ](n×4n) ,

Proof: The Lyapunov-Krasovskii functionals candidate is given by k −1

k −1

k −1

θ = k − rM

θ =k −r ( k )

− rm

V (xk ) = α −2 k ⋅ x T (k )Px(k ) + ∑α −2θ ⋅ x T (θ )Sx(θ ) + ∑α −2θ ⋅ x T (θ )Tx(θ ) + ∑α −2θ ⋅ x T (θ )Qx(θ ) + ∑ θ = k − rm

0

∑

+ rm ⋅

l = − rm +1

 0 ∑ α − 2θη T (θ )R1η (θ ) + rM ⋅  ∑ θ = k −1+ l l = − r ( k ) +1

0

+ rM ⋅

k −1

k −1

∑ θ ∑α

l = − rM +1

− 2θ

∑ α − 2θ ⋅η T (θ )R2η (θ ) + ∑

θ = k −1+ l

− rm −1

k −1

l = − rM

θ = k +l

⋅η T (θ )R3η (θ ) + rMm ⋅ ∑ ∑ α

= k −1+l

− rm

k −1

l = − rM +1 θ = k + l

 

k −1

∑ α − 2θ ⋅ (θ − k − l + 1) ⋅η T (θ )R2η (θ )

l = − rM +1 θ = k + l

− 2θ

k −1

∑α −2θ ⋅ xT (θ )Qx(θ ) ,

⋅η T (θ )R4η (θ ) ,

(11)

where P > 0 , S > 0 , Q > 0 , T > 0 , Ri > 0 , i = 1,2,3,4 , and η (θ ) = x(θ + 1) − x(θ ) . Taking the difference of Lyapunov functionals, along the solutions of system (1) has the form ∆V (xk ) = α −2 k ⋅ [α −2 ⋅ x T (k + 1)Px(k + 1) − x T (k )Px(k )] + α −2 k ⋅ [x T (k )Sx(k ) − α 2 r ⋅ x T (k − rm )Sx(k − rm )] , + α −2 k ⋅ [x T (k )Sx(k ) − α 2 r ⋅ x T (k − rm )Sx(k − rm )] + α −2 k ⋅ [x T (k )Tx (k ) − α 2 r ⋅ x T (k − rM )Tx (k − rM )] , m

m

M

986

Applied Science and Precision Engineering Innovation

k

k −1

θ = k − r ( k +1) +1

θ =k −r ( k )

+ α −2 k ⋅ [x T (k )Tx (k ) − α 2 r ⋅ x T (k − rM )Tx(k − rM )] +

∑ α −2θ ⋅ x T (θ )Qx(θ ) − ∑ α −2θ ⋅ x T (θ )Qx(θ ) ,

M

k − rm

k −1

+ α − 2 k ⋅ (rM − rm ) ⋅ x T (k )Qx(k ) − ∑ α − 2θ ⋅ x T (θ )Qx(θ ) + α −2 k ⋅ rm2 ⋅η T (k )R1η (k ) − rm ⋅ ∑ α − 2θ ⋅η T (θ )R1η (θ ) , θ = k − rM +1 0

+ rM ⋅

k

∑

∑α

− 2θ

⋅η (θ )R2η (θ ) − rM ⋅ ∑

l = − r ( k +1) +1 θ = k + l − rm

θ = k − rm k −1

0

T

∑α

− 2θ

− rm

k

⋅η (θ )R2η (θ ) + rM ⋅ ∑ T

l = − r ( k ) +1 θ = k −1+ l

∑ α − 2θ ⋅ (θ − k − l ) ⋅η T (θ )R2η (θ )

l = − rM +1 θ = k + l +1

k −1

k −1

∑ α −2θ ⋅ (θ − k − l + 1) ⋅η T (θ )R2η (θ ) + α − 2 k ⋅ rM2 ⋅η T (k )R3η (k ) − rM ⋅ ∑ α − 2θη T (θ )R3η (θ ) ,

− rM ⋅ ∑

l = − rM +1 θ = k + l

θ = k − rM k − rm −1

+ α − 2 k ⋅ (rM − rm ) 2 ⋅η T (k )R4η (k ) − (rM − rm ) ⋅ ∑ α −2θ ⋅η T (θ )R4η (θ ) ,

(12)

θ = k − rM

Assume the special case σ (k , x(k )) = q , then we can obtain the following result from (12) ∆V (x k ) ≤ α −2 k ⋅ {α −2 ⋅ x T (k + 1)Px(k + 1) + x T (k )[− P + S + (rMm + 1) ⋅ Q + T ]x(k ) − α 2 r ⋅ x T (k − rm )Sx(k − rm ) m

[

]

2 2 − α 2 r ⋅ x T (k − rM )Tx (k − rM ) − α 2 r ⋅ x T (k − r (k ))Qx(k − r (k )) + η T (k ) rm2 ⋅ R1 + rˆMm ⋅ R2 + rM2 ⋅ R3 + rMm ⋅ R4 η ( k ) M

M

− α 2 r ⋅ W1T R1W1 − α 2 r ⋅ (W2T R2W2 + W3T R3W3 + W4T R4W4 + W5T R4W5 + λ (k ) ⋅ W4T R4W4 + (1 − λ (k )) ⋅ W5T R4W5 ) m

M

[

]

= α −2 k ⋅ x T (k )(α −2 ⋅ AqT PAq − P + U )x(k ) + β T (k ) ⋅ (λ (k ) ⋅ Ξ1q + (1 − λ (k )) ⋅ Ξ 2 q )β (k ) ,

where β T (k ) = [xT (k ) xT (k − rm ) x T (k − r (k )) xT (k − rM )] , λ (k ) = T

Ξiq = Ξ11i q

(

 A −I  AqT P   AqT P   q     0 0 − 1 0 +  T  (α 2 ⋅ P )  T  +   AT  Adq P   Adq P  dq       0  0   0 

r (k ) − rm , rMm

)  T

(13)

(

 A −I  q  (r 2 ⋅ R + rˆ 2 ⋅ R + r 2 ⋅ R + r 2 ⋅ R ) 0  m 1 Mm 2 M 3 Mm 4  A T dq     0

)  T

T

 , i = 1,2 ,   

(14)

with Ξ11i q , W j , i = 1,2 , j = 1,2,3,4,5 , q = 1,2,
, N , are defined in (9). Since 0 ≤ λ (k ) ≤ 1 , the λ (k ) ⋅ Ξ1q + (1 − λ (k )) ⋅ Ξ 2 q is a convex combination of Ξ1q and Ξ 2 q . λ (k ) ⋅ Ξ1q + (1 − λ (k )) ⋅ Ξ 2 q < 0 will imply Ξ1q < 0 and Ξ 2 q < 0 .

Hence,

Define Ξ11i q Ξˆ iq =   *

Ξ12 q  T T T  + Λ q Fq (k )Γq + Γq Fq (k )Λ q , Ξ 22 q 

(15)

where ΛTq = [0 0 0 0 M qT P M qT R1 M qT R2 M qT R3 M qT R4 ] , ΓqT = [N1q 0 N 2 q 0 0 0 0 0 0] , and Ξ11i q , Ξ12 q , Ξ 22 q are defined in (9). By the condition (10) with Lemma 2.3 and the switching signal in (7), we can obtain the following result x T (k )(α −2 ⋅ AqT PAq − P + U ) x(k ) < 0 , ∀x(k ) ∈ Ωq .

(16)

By Lemmas 2.1-2.3 with above conditions, the conditions Ξ iq < 0 , i = 1,2 , in (9) will imply Ξˆ iq < 0 , i = 1,2 , in (15), the conditions Ξˆ iq < 0 , i = 1,2 , in (15) will also imply Ξiq < 0 in (14).

Therefore, the conditions Ξiq < 0 , i = 1,2 , in (14) are equivalent to λ (k ) ⋅ Ξ1q + (1 − λ (k )) ⋅ Ξ 2 q < 0 in (13). From the condition (16) and the matrix λ (k ) ⋅ Ξ1q + (1 − λ (k )) ⋅ Ξ 2 q < 0 in (13) with (9), we have ∆V (xk ) = V (xk +1 ) − V (xk ) ≤ 0 , k = 0, 1, 2, 3,
, V (xk +1 ) ≤ V (xk ) , k = 0, 1, 2, 3,
. This implies 2 2 V (xk ) ≤ V (x0 ) , k = 0, 1, 2, 3,
, α −2 k ⋅ λmin ( P ) ⋅ x( k ) ≤ V (xk ) ≤ V (x0 ) ≤ δ 1 ⋅ x0 s ,

Applied Mechanics and Materials Vols. 479-480

987

where δ 1 = λmax ( P) + rm ⋅ λmax ( S ) + rM ⋅ λmax (T ) + (rM2 − rM rm + rm ) ⋅ λmax (Q) + rm2 ⋅ λmax ( R1 ) 1   +  rM2 + (rM + rm + 1) ⋅ (rM − rm ) ⋅ (rM − 1) ⋅ λmax ( R2 ) + rM2 ⋅ λmax ( R3 ) + (rM − rm ) ⋅ rM ⋅ λmax ( R4 ) . 2  

By some simple derivations, we have x(k ) ≤ δ 1 λmin (P ) ⋅ α k ⋅ x0 s , k = 0, 1, 2, 3,
. Therefore, we conclude that the system (1) is exponentially stable with convergence rate 0 < α ≤ 1 . This completes this proof.

4. Illustrative Examples Example 4.1: Consider the system (1) with no uncertainties and the following parameters: (Example 3.1 of [7]) 1.02   0.54 − 0.01 − 0.06 N = 2 , A1 =   , Ad 1 =  , 0.04  − 0.17 − 0.31  0.01

0.18  − 0.01 − 0.06  0.11 A2 =   , Ad 2 =  . 0.04   0.01 − 0.03 − 0.04

(17)

In order to show the obtained results, the allowable delay upper bound and switching sets that guarantees the global exponential stability for system (1) with (17) is provided in Table 1.

Table 1. Comparison of the maximum of rM with fixed α and rm for Example 4.1 α = 1 , rm = 1 , rM = 5 globally asymptotically stable (choose α1 =α 2 = 0.5 )

[7]

{

Ω1 = [x1

}

x2 ] ∈ ℜ 2 : −12.0213 x12 − 38.8254 x1 x2 − 31.6356 x 2 < 0 , Ω2 = ℜ 2 − Ω1 T

α = 1 , rm = 1 , rM = 186 globally asymptotically stable ( α1 = 0.1 and α 2 = 0.9 )

Our results

{

Ω1 = [x1

}

x2 ] ∈ ℜ 2 : 13.3904 x12 + 37.6318 x1 x2 + 13.5976 x 2 < 0 , Ω 2 = ℜ 2 − Ω1 T

α = 0.8 , rm = 1 , rM = 6 globally exponentially stable ( α1 = 0.1 and α 2 = 0.9 )

{

Ω1 = [x1

}

x 2 ] ∈ ℜ 2 : 0.4499 x12 + 1.5783 x1 x 2 + 1.1756 x 2 < 0 , Ω 2 = ℜ 2 − Ω1 T

It is seen that the maximum of rM and the minimum number of variables are obtained from Table 1. By a new switching law approach, less conservative results are reached in our paper.

5. Conclusions In this paper, the global exponential stability for uncertain discrete-time switched systems with interval time-varying delay has been considered. Owing to defining new switching signal and Lyapunov functional are used and no any free-weighting matrices are adopted. The computational burden of the derived stability condition is greatly reduced. In addition, the novel stability criteria in this paper are also less conservative than the existing paper [ 7]. Acknowledgements The research reported here was supported by the National Science Council of Taiwan, R.O.C. under grant no. NSC under grant no. NSC 101-2221-E-507-002 and NSC 100-2221-E-507-001. References [1] Sun, Z., and Ge, S. S., 2005, Switched Linear Systems Control and Design. Springer-Verlag, London. [2] Han, Y., and Tang, H., 2007, “Robust H ∞ control for a class of discrete switched systems with uncertainties and delays”, Proc. 26th Chinese Control Conf., Hunan, China, pp. 681-684. [3]

Ibrir, S., 2008, “Stability and robust stabilization of discrete-time switched systems with time-delays: LMI approach”, Appl. Math. Comput., vol. 206, pp. 570-578.

988

[4]

Applied Science and Precision Engineering Innovation

Lien, C. H., Yu, K. W., Chung,Y. J., Chang, H. C., Chung, L. Y., and Chen, J. D., 2011, “Exponential stability and robust H ∞ control for uncertain discrete switched systems with interval time-varying delay”, IMA J. Math. Control Inform., vol. 7, pp. 433-444.

[5]

Lien, C. H., Yu, K. W., Chung, Y. J., Chang, H. C., Chung, L. Y., and Chen, J. D., 2011, “Switching signal design for global exponential stability of uncertain switched nonlinear systems with time-varying delay”, Nonlinear Analysis: Hybrid Systems, vol. 5, pp. 10-19.

[6]

Liu, J., Liu,X., and Xie, W. C., 2008, “Delay-dependent robust control for uncertain switched systems with time-delay”, Nonlinear Analysis: Hybrid Systems, vol. 2, pp. 81-95.

[7]

Phat, V. N., and Ratchagit, K., 2011, “Stability and stabilization of switched linear discrete-time systems with interval time-varying delay”, Nonlinear Analysis: Hybrid Systems, vol. 5, pp. 605-612.

[8]

Sun, X. M., Wang, W., Liu, G. P., and Zhao, J., 2008, “Stability analysis for linear switched systems with time-varying delay”, IEEE Trans. Syst. Man, Cybernetics, Part B, vol. 38, pp.

528–533. [9] Zhang, L., Shi, P., and Basin, M., 2008, “Robust Stability and Stabilisation of Uncertain Switched Linear Discrete Time-Delay Systems”, IET Control Theory Appl., vol. 2, pp. 606-614. [10] Sun, Y. G., Wang, L., and Xie, G., 2007, “Delay-dependent robust stability and H ∞ control for uncertain discrete-time switched systems with mode-dependent time delays”, Appl. Math. Comput., vol. 187, pp. 1228-1237. [11]

Xie, D., Xu, N., and Chen, X., 2008, “Stabilisability and observer-based switched control

design for switched linear systems”, IET Control Theory Appl., vol. 2, pp. 192-199. [12]

Zhai, G., Liu, D., Lmae, J., and Kobayashi, T., 2006, “Lie algebraic stability analysis for

switched systems with continuous-time and discrete-time subsystems”, IEEE Trans. Circuits Syst., vol. 53, pp. 152–156. [13]

Zhang, L., Shi, P., and Basin, M., 2008, “Robust stability and stabilisation of uncertain

switched linear discrete time-delay systems”, IET Control Theory Appl., vol. 2, pp. 606-614. [14] Zhang, W. A., and Yu, L., 2009, “Stability analysis for discrete-time switched time-delay systems”, Automatica, vol. 45, pp. 2265-2271. [15] Gau, R. S., Lien, C. H., and Hsieh. J. G., 2011, “Novel stability conditions for interval delayed neural networks with multiple time-varying delays”, Int. J. Innovative Comput. Inform. Control, vol. 7, pp. 433-444. [16]

Li, T., Guo, L., and Sun, C., 2007, “Robust stability for neural networks with time-varying delays and linear fractional uncertainties”, Neurocomputing, vol. 71, pp. 421-427.

[17]

Gu, K., Kharitonov, V. L., and Chen, J., 2003, Stability of Time-Delay Systems, Birkhauser, Boston, Massachusetts.

[18]

Yu, K. W., 2010, “Further results on new stability analysis for uncertain neutral systems with

time-varying delay”, Int. J. Innovative Comput. Inform. Control, vol. 6, pp. 1133-1140. [19] Boyd, S., Ghaoui, L., Feron, E., and Balakrishnan, V., 1994, Linear matrix inequalities in system and control theory. SIAM, Philadelphia, PA.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 989-995 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.989

The Hybrid Differential Evolution with Dynamic Scaling Mutation and Wrapper Local Search for Optimization Problems *

Chun-Liang Lu1,a, Shih-Yuan Chiu2,b , Chih-Hsu Hsu3,c and Shi-Jim Yen4,d

1,3

Department of Applied Information and Multimedia, Ching Kuo Institute of Management and Health, Keelung County, Taiwan, ROC.

2,4

Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien County, Taiwan, R.O.C. a

email: [email protected] (*Corresponding author) b

email: [email protected] c

email: [email protected]

d

email: [email protected]

Keywords: Differential Evolution, Dynamic Scaling Mutation, Wrapper Local Search, Particle Segment Operation-Machine Assignment, Flexible Job-Shop Scheduling Problem.

Abstract. In this paper, an improved hybrid Differential Evolution (DE) is proposed to enhance optimization performance by cooperating Dynamic Scaling Mutation (DSM) and Wrapper Local Search (WLS) schemes. When evolution speed is standstill, DSM can improve searching ability to achieve better balance between exploitation and exploration in the search space. Furthermore, WLS can disturb individuals to fine tune the searching range around and then properly find better solutions in the evolution progress. The effective particle encoding representation named Particle Segment Operation-Machine Assignment (PSOMA) that we previously published is also applied to always produce feasible candidate solutions for hybrid DE model to solve the Flexible Job-Shop Scheduling Problem (FJSP). To test the performance of the proposed hybrid method, the experiments contain five frequently used CEC 2005 numerical functions and three representative FJSP benchmarks for single-objective and multi-objective optimization verifications, respectively. Compare the proposed method with the other related published algorithms, the simulation results indicate that our proposed method exhibits better performance for solving most the test functions for single-objective problems. In addition, the wide range of Pareto-optimal solutions and the more Gantt chart diversities can be obtained for the multi-objective FJSP in practical decision-making considerations. 1. Introduction Optimization algorithms have become a useful technique in all-major engineering applications. Many practical engineering design or decision making problems involve single-objective or multi-objective optimization. In single-objective optimization, the goal is to find the best design solution corresponding to the minimum or maximum value of the objective function [1]. On the contrary, the multi-objective optimization gives rise to a set of Pareto-optimal solutions [2] because of the interaction among different conflicting objectives. In 1995, the concept of original differential evolution (DE) was proposed by Storn and Price [3], is a vector-based evolutionary algorithm with very competitive optimization technique in various application fields. In 2006, Brest et al. presented a self-adaptive method for DE [4] with extended parameters Fi and Cri for the individual in population. The combination of two mutation approaches “DE/rand/1” and “DE/current-to-best/1” called SaDE [5] has been developed by Qin et al. in 2009. Later, Zhang et al. implemented a new mutation strategy “DE/current-to-pbest” with optional external archive named JADE [6] to track the previous history status with adaptive parameters in generations. In 2012, Islam et al. proposed the MDE_pBX [7], which adds a variation to the classical “DE/current-to-best/1” mutation scheme by perturbing the current target vector with the best solution in a group of randomly selected individuals.

990

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The Flexible Job-Shop scheduling problem (FJSP) [8] is quite difficult to achieve an optimal solution owing to the high computational complexity and well-known a NP-hard problem. Xia and Wu [9] proposed a method which hybridized PSO and simulated annealing (SA). It involved a variable inertia weight w and adopted a weighted concept to transform triple objectives into single objective problems. Ho et al. [10] later proposed a method to estimate bounds of different types of schematic may exist corresponding to the Pareto-optimal fitness value, but Ho's method did not deal with the diversity under the same Pareto-optimal solutions. In this paper, an improved hybrid DE algorithm with DSM and WLS schemes is proposed to solve for global numerical single-objective test functions and multi-objective FJSP optimizations. The remainder of this paper is organized as follows. Section 2 describes the related works and FJSP problem definition. In Section 3, the proposed hybrid DE algorithm is presented. Experimental results are shown in Section 4. Finally, conclusions are made in Section 5. 2. Related Works 2.1 Typical MDE_pBX Algorithm Differential evolution (DE) is one of the most powerful stochastic real-parameter optimization algorithms in the mainstream. Islam et al. propose a new mutation strategy, a fitness induced parent selection scheme for the binomial crossover of DE and a simple but effective scheme of adapting most important control parameters called MDE_pBX [7]. The new mutation operator named “DE/current-to-gr_best/1” scheme is as follows.





Vi ,G = X i ,G + Fi ( X gr _ best ,G − X i ,G + X r i ,G − X r i ,G ) (1) 1 2
X gr _ best ,G is the best solution from 15% of individuals selected randomly in the current generation. Then, normal binomial crossover is performed between the donor vector and the randomly selected p-best vector to generate the trial vector at the same index. Parameter p is linearly reduced by generations in the following formula. Np G −1 p = ceil ( × (1 − )) (2) Gmax 2 G is the current generation number, Gmax is the maximum number of generation set up, and ceil ( y ) is the ”ceiling” function returning the lowest integer greater than its argument y. Finally, the parameter adaptation schemes in MDE_pBX is independently generated as follows. Fi = Cauchy ( Fm , 0.1) (3) Eq. 3 is a random number sampled from a Cauchy distribution with location parameter Fm and scale parameter 0.1. Location parameter Fm of the Cauchy distribution is initialized to be 0.5 and updated at the end of each generation. The crossover probability adaptation is similar with scale factor adaptation except the Gaussian distribution instead of Cauchy one. 2.2 FJSP Problem Definition The FJSP [9] which concerned with finishing assigned jobs on minimal critical machine workload, total workload, and completion times, is described as follows: The problem is to organize the execution of n jobs J i (i = 1, 2,..., n) on m machines M k (k = 1, 2,..., m) , where each job J i needs o i operations on the order of restraint and each working procedure of job can be processed by multiple processes of M machines. A suitable job assignment must consider a set of solutions and three criteria ( F1 , F2 , F3 ) must be evaluated simultaneously as follows: The total workload of all machines indicated as F1 = ∑ pi , j , k , where pi , j , k is the processing time of j-th operation of i-th job in k-th machine. The workload of the critical machine denoted as F2 = max{W1 , W2 ,...,Wm } , where Wk

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denotes the workload of k-th machine M k . F3 = max{CT1 , CT2 ,..., CTn } is shown the completion time of the critical job, where CTi denotes the completion time of i-th job.

3. The Proposed Hybrid DE Algorithm 3.1 Particle Segment Operation-Machine Assignment (PSOMA) Representation The effective particle encoding representation scheme that we previously proposed and detailed in [11], each dimension contains three components: integer part (machine selection), decimal part (priority order) and real-value number (operation number). The structure of proposed particle representation of each dimension is shown in Fig. 1. When updating the velocity and position of the particles, we divide the particle into two swarms (integer and decimal) during the iteration. Hence, the particle representation is flexible enough to encode the FJSP to satisfy the precedence constraints for operations in each job by using the structure of the classical DE algorithm with real value number.

Fig. 1 Each dimension of particle structure. The main difference between Single-Objective Problem (SOP) and Multi-Objective Problems (MOP) is that MOP contains more than one objective that needs to be accomplished simultaneously. In [12], the authors presented an external repository (or archive) to keep the historical record of the non-dominated solutions found along the search process. The basic concept of external repository scheme is also adopted in our proposed hybrid DE algorithm for solving the multi-objective FJSP.

3.2 Dynamic Scaling Mutation Search (DSM) Approach The original DE mutation scheme is “DE/rand/1” in [3]. Islam et al. [7] proposed the MDE_pBX of new mutation approach. Although the effect of the method performs better results than many other algorithms, this diversity of solution searching scheme is getting premature convergence at local optima within a smaller number of generations. Taking into consideration of these facts and to overcome the limitations of this feature, the extension of modified mutation searching strategy in [13], which we called DSM approach, can be expressed as





Vi ,G = X i ,G + Fi ( X gr _ better ,G − X i ,G + X r i ,G − X r i ,G ) (4) 1

2

i (5) w = wmax − now ( wmax − wmin ) imax

In Eq. 4, X i ,G is known as the target vector, Vi ,G is known as the donor vector, the scaling factor Fi is a





positive control parameter for scaling the difference vectors. The X r ,G and X r ,G are two distinct i 1

i 2




vectors picked up randomly from the current population, and none of them is equal to X gr _ better ,G or the


target vector. The X gr _ better ,G is dynamically chosen from top w% individuals of each population. The linearly decreasing inertia weight is set as Eq. 5, where inow is the current iteration, imax is the pre-defined maximum iteration, and the lower and upper bounds of w described as wmin ≤ w ≤ wmax . The new proposed mutation operator of DSM scheme is a variant of the MDE_pBX in [7]. It dynamically uses the best of a group (whose size is w% of the linearly decreasing population size) of randomly selected solutions, from current generation to perturb the parent vector, and unlike in the
[13] that the X better ,G always picks the best vector from the entire population fixed-ratio to perturb the target vector. DSM can drive the population to the better direction instead of convergence to the best individual in the iteration and help DE not to fall into local optimum quickly in smaller generation.

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3.3 Wrapper Local Search (WLS) Scheme According to related works, it can be found that classical DE can perform well performance on widely search for exploring unsearched solution space but weakly on searching depth. In 2010 [14] we published the efficient wrapper-based hybrid model for solving the biomedical problem and is capable of producing high prediction accuracy and fewer number of features selection simultaneously. In this study, the wrapper-based selection framework is properly adopted to enhance the local search performance for DE, named Wrapper Local Search (WLS) scheme, is involved to adjust the scale of moving vector via trying to increase or decrease current moving vector by the Cauchy distribution. The proposed WLS utilized these random wrapper-based selected dimensions to identify a suitable balance tradeoff of DE search and Local Search. It can save much time than one by one the single dimension search [13], and will fine tune the searching direction for finding the global best solution. The completed flowchart of the proposed hybrid algorithm is given in Fig. 2. After initializing, the proposed DSM is involved; next, crossover process, scale factor (Fi) and crossover probability (Cr) adaptation are referring to MDE_pBX [7]. After DE selection, fitness evaluation (for SOP or MOP) and WLS scheme, all individuals are performing the next iteration until the stop criteria is reached. Table 1. Experimental results of CEC 2005 test functions

Fig. 2. Flowchart of the Proposed Hybrid DE Algorithm

4. Experimental Results 4.1 The CEC 2005 Test Functions For the single-objective optimization test, the CEC 2005 benchmarks [15] were randomly adopted 5 functions (from Basic multimodal, Expanded multimodal, Hybrid Composition) for testing the proposed method and comparing it to related works. In the experiments, five test functions with 50 dimensions are conducted for comparing the proposed method with five related works jDE, SaDE, JADE, DEGL and MDE_pBX reported in [7]. The initial population size is set as 100. The fitness evaluation (FEs) is 500,000. The mean values and standard deviation of are calculated. Table 1 presents the mean and standard deviation, 25 runs of the six algorithms on the 5 test functions with 50 dimensions. The best results among the six approaches are shown in bold. From the

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results, the proposed hybrid method performs better results such as F1, F2, F3 and F4 functions and proposed method in F5 archive the same results which real optimum solutions are found.

4.2 The FJSP Representative Benchmarks For the multi-objective optimization verification, three representative benchmarks which are problem 8×8, 10×10, 15×10 have been conducted, and to compare with other related works, such as the PSO-SA [9] and the MOEA-GLS [10]. For each problem, the obtained results are reported in table contains three objectives: F1 (total workload), F2 (critical machine workload), F3 (makespan), are mentioned in Section 2. The solutions found from three methods are shown in Table 2 to Table 4. For example, two new non-dominated solutions (77, 12, 14) and (77, 11, 16) can be obtained by the MOPSO-SDE compared with the PSO-SA, and more diversity Gantt chart solutions can be obtained by the MOPSO-SDE compared with the MOEA-GLS. From the simulation results of Gantt chart diversity, the proposed hybrid MOPSO-SDE approach performs significantly better than the other two PSO-SA and MOEA-GLS methods in solving all benchmarks. Afterward, the Gantt chart of the solution (75, 12, 15) for problem 8×8 is exhibited related solution diversity in Fig. 3 to Fig. 4 as giving an illustration. Table 2. Comparison of results on problem 8×8.

Fig. 3. Gantt chart solution with diversity 1. Table 3. Comparison of results on problem 10×10.

Fig. 4. Gantt chart solution with diversity 2. Table 4. Comparison of results on problem 15×10.

5. Conclusion In this paper, an improved Differential Evolution hybridized Dynamic Scaling Mutation and Wrapper Local Search schemes is proposed to improve both single-objective and multi-objective

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optimization performances. DSM can enhance searching ability to balance between exploitation and exploration in the search space. Meanwhile, WLS can disturb individuals to help individuals avoid trap into local minimum in evolution progress. Compare the proposed method with the published algorithms, the simulation results show the proposed method exhibits better performance for solving most the test functions for single-objective problems. In addition, the wide range of Pareto-optimal solutions and the more Gantt chart diversities can be obtained for multi-objective problems.

Acknowledgment This work was partially supported by the National Science Council, Taiwan, under Grant NSC 101-2218-E-254-001.

References [1] K. Deb, Optimization for Engineering Design: Algorithm and Examples, New Delhi: Prentice-Hall, (1995) [2] K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, John Wiley, (2001) [3] R. Storn and K. Price, “Differential evolution-A simple efficient heuristic for global optimization over continuous spaces,” Journal of Global Optimization, Vol. 11, pp. 341–359, (1997) [4] J. Brest, S. Greiner, B. Bokovic, M. Mernik, “Selfadapting control parameters in differential evolution: A comparative study on numerical benchmark problems,” IEEE Trans. on Evolutionary Computation, Vol. 10, no. 6, pp. 646–657, (2006) [5] A. K. Qin, V. L. Huang, and P. N. Suganthan, “Differential evolution algorithm with strategy adaptation for global numerical optimization, ”IEEE Trans. on Evolutionary Computation, Vol. 13, no. 2, pp. 398–417, (2009) [6] J. Zhang and A. C. Sanderson, “JADE: Adaptive differential evolution with optional external archive,” IEEE Trans. on Evolutionary Computation, Vol. 13, no. 5, pp. 945–958, (2009) [7] S.M. Islam, S. Das, S. Ghosh, S. Roy, P.N. Suganthan, “An Adaptive Differential Evolution Algorithm with Novel Mutation and Crossover Strategies for Global Numerical Optimization,” IEEE Trans. on System, Man, Cybernetics- Part B, Vol. 42, no. 2, pp. 482–500, (2012) [8] D. L. Luo, S. X. Wu, M.Q. Li, and Z. Yang, Ant colony optimization with local search applied to the flexible job shop scheduling problems. ICCCAS conference in Communications, Circuits and Systems, 1015-1020, (2008) [9] W. Xia and Z. Wu, An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems. Computers and Industrial Engineering. Vol. 48, 409-425, (2005) [10] N. B. Ho and J. C. Tay, Solving multiple-objective flexible job shop problems by evolution and local search. IEEE Trans. on Systems, Man, and Cybernetics, Part C. Vol. 38, No. 5, pp. 674-685, (2008) [11] Hsiang-Chun Cheng, Chun-Liang Lu and Shih-Yuan Chiu, “ Hybrid Multi-Objective PSO with Solution Diversity Extraction for Job-shop Scheduling Management ,” International Conference on Data Mining and Intelligent Information Technology Applications (ICMIA2012), Taipei, Taiwan., pp. 705–710, (2012) [12] C. A. Coello and M. S. Lechuga, “MOPSO: A proposal for multiple objective particle swarm optimization,” In Proc. Congress Evolutionary Computation (CEC’2002), vol. 1, Honolulu, pp. 1051–1056, (2002)

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[13] Sheng-Ta Hsieh, Shih-Yuan Chiu and Shi-Jim Yen, "Real Random Mutation Strategy for Differential Evolution,” The 2012 Conference on Technologies and Applications of Artificial Intelligence TAAI 2012, Tainan, Taiwan, (2012) [14] Min-Hui Lin, Chun-Liang Leu, “A Hybrid PSO-SVM Approach for Haplotype Tagging SNP Selection Problem,” International Journal of Computer Science and Information Security, Vol. 8, No. 6, pp. 60-65, (2010) [15] Data information in http://www3.ntu.edu.sg/home/epnsugan/

Applied Mechanics and Materials Vols. 479-480 (2014) pp 996-1000 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.996

Implementation and Experiments of TDOA Monitoring Techniques for Broadcasting Interferences Yao-Tang Chang1, a, Yi-Chang Lin 2,b 1

Department of Information Technology, Kao Yuan University, Taiwan

2

Graduate School of Operation and Management, Kao Yuan University, Taiwan a

[email protected], [email protected]

Keywords: Time Difference of Arrival (TDOA), Angle of Arrival, (AOA), Radio Interference

Abstract. Since the rapid developing of economy in Taiwan in recently years, a large numbers of constructions have made the changes on theterrain surrounding of the radio monitoring stations rapidly. Hence, the accuracy performance of the radio monitoring station configured by signal angle of arrival (AOA) location technology has been seriously degraded. In this paper, the simulated result of 20km ~ 30km coverage area is evaluated. Furthermore, the implementation and experiments supported by the radio frequency interference have been governed by authority of national communication commissions (NCC) in Taiwan. The results show that the locating accuracy at circle error probability (CEP) 50% is less than 950 m distance under multi-path effect in metropolitan area. Hence, the solution of integrated the AOA/TDOA technologies can be applied and the interference transmitter characterized with low transmitted power, burst and weak signal and metropolitan interference is easy identified, analyzed (located) and prevented. Introduction In order to execute telecommunication act in Taiwan, the radio frequency monitoring system is applied to protect and maintain a great radio frequency environment for easy communication at anywhere, anytime and any-devices. Since the rapid developing of economy in Taiwan recently years, a large number of constructions have made the rapid changes on the terrain surrounding of the radio monitoring stations. Furthermore, more complex-communications technology and equipment has been invented. Hence, the monitoring station that configured originally and based on signal angle of arrival (angle of arrival, AOA) location technology is unable to meet the changing of geography and radio-frequency environment [1]. That is, the accuracy performance of the radio monitoring station has been seriously degraded. The special interference case increased rapidly in advanced communicational technologies such as low transmitted power, burst and weak signal and metropolitan interference [2-3]. As new monitoring and direction finder technologies are invented to prevent the radio interference, the TDOA-based location system is proposed to integrate the previous AOA-based location system [4]. Here the implementation and experiments supported by the radio frequency interference governed authority of national communication commissions (NCC) in Taiwan. Hence the interference transmitter for low transmitted power, burst and weak signal and metropolitan interference is easy identified, analyzed (located) and prevented. The Proposed Integrated AOA/TDOA-based Monitoring System As shown in Fig. 1, the major advantage of integrated AOA/TDOA monitoring system is to extend the coverage area and improve the location performance of previous AOA-based monitoring system installed in Taiwan. For location accuracy of TDOA consideration, the surround of three monition station is characterized with better location-performance. On the contrary, AOA monitoring system is suitable for the inside as well as outside of monitoring system.

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Fig. 1. Integrated AOA/TDOA monitoring system for extending the coverage area and improve location accuracy.

Combine with simply and efficiency advantage, the AOA/TDOA monitoring system is proposed and shown in Fig.2. The AOA-based system can calculate the straight line of bearing and TDOA-based achieve the hyperbola curve. Hence, the proposed efficiency configuration of integrated AOA/TDAO monitoring system is achieved to prevent broadcasting interferences occurred in metropolitan area.

Fig. 2. The proposed efficiency configuration of integrated AOA/TDAO monitoring system to prevent broadcasting interferences occurred in metropolitan area.

The Design of TDOA-based Monitoring System In order to implement TDOA monitoring system, the design configuration consists of hardware selection, the cross-correlation algorithm and application user interface and estimation of accuracy location. The installation of system architecture and the location requirements is shown in Fig. 3. Under the cost consideration, the proposed integrated AOA/TDOA receiver configuration is proposed and shown in Fig.4. The AOA-based technology needs a pair of modular of local oscillator, down converter and digitizer. The only one modular is need for TDOA-based technology.

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Fig. 3. The installation of proposed system architecture and the location requirements

Fig. 4. The proposed receiver configuration of integrated AOA/TDOA location system

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Implementation and Experiments of AOA/TDOA-based Monitoring System The required number of TDOA-based in metropolitan area of Tainan is simulated and evaluated. The results show that the number of 3 to 5 TDOA-based location stations are needed to install for 20km ~ 30km coverage area in metropolitan of Tainan. Hence, the proper position TDOA-based monitoring station is selected and shown in triangle of Fig. Moreover, as shown the broadcasting station of 88.3 MHz, 91.5 MHz, 89.1 MHz and 91.9 MHz are specified to verify the location performance by moving from the center to outside of TDOA coverage area. As shown in Fig. 5, the proposed experiment configuration is easy to verify the TDOA limitation of location performance in multi-path effect of metropolitan area. In this study, a central station of AOA/TDOA #1 is installed in Kaohsiung Science Park. The TDOA #2 and TDOA #3 (Tainan metropolitan area) is act as remote monitoring station. This monitoring station is selected under considering the impact of the barrier of the aforementioned buildings, ground reflection and the reflected wave. Also, the up-load transmission rate of 3G mobile network design is needed. The related position (longitude and latitude) of TDOA monitoring and transmitted station is shown in Table I. The practical simulation on open air scenarios (outdoor environment) is demonstrated. Here, three TDOA-based radio monitoring station is installed and located in Luzhu (TDOA #1), Tainan Gaote (TDOA #2) and Jinkang (TDOA #3), respectively. By monitoring the frequency modulation (FM) for broadcasting station of 88.3, 91.5, 89.1 and 91.9 MHz lactated on metropolitan, rural and urban area, respectively. By applying the proposed TDOA and AOA/TDOA-based location system to integrate the previous AOA-based location system installed in current national communication commission (NCC), the anti-interference solution is analyzed and then the interference transmitter for flight, low transmitted power, burst and weak signal and metropolitan interference is investigated and verified to easy identify, analyze (locate) and prevent the special interference. Hence, the possible architecture, equipment specification of proposed TDOA location system is proposed to solve the special interference and improve the monitoring network of NCC. For an example of measured FM 88.3 MHz, the location result is shown in Fig. 6.

Fig. 5. The proposed experiment configuration for investigating the TDOA limitation of location performance in multi-path effect of metropolitan area.

Fig. 6. The location result of an example of FM 88.3 MHz in experiment

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The experiment results are summarized in Table II. The various location error depend on the various broadcasting station of 88.3, 91.5, 89.1 and 91.9 MHz. The result show the least locating accuracy for 91.9 MHz at circle error probability (CEP) 50% is less than 950 m distance under multi-path effect. Hence, the average and deviation error of distance is proved to apply in metropolitan interference. Table I. The proposed monitoring and transmitted position of proposed experiment

Table II. The summarized result of experiment for measured location

Summary By applying F(50, 50) transmission channel model of applied in Federal Communications Commission (FCC) and following specifications/requirement of TDOA-based receiver, the required number of TDOA-based in metropolitan area of Taiwan is simulated and evaluated. Since the number of 3 to 5 TDOA-based location stations are needed to install for 20km ~ 30km coverage area in metropolitan of Tainan, The results show that the locating accuracy at circle error probability (CEP) 50% is less than 950 m distance under multi-path effect in metropolitan area. Acknowledgement This study was supported under grant No. NSC 102-2221-E-244-001 from the National Science Council and the special-interference project of National Communications Commission (NCC) in Taiwan. References [1] ITU- Spectrum Monitoring Handbook, 2011. [2] Y. C. Liang, A.R. Leyman and B. H. Song, “Multipath time delay estimation using higher order statistics” Higher-Order Statistics, Proceedings of the IEEE Signal Processing, 1997. [3] Nikias, C.L, R. Pan, “Time delay estimation in unknown Gaussian spatially estimation for large BT signals”, IEEE Transactions on Signal Processing, Vol.39, No.4, Apr.1991. [4] Li Cong, Weihua, “Hybrid TDOA/AOA Mobile User Location for Wideband CDMA Cellular Systems”， IEEE Transactions on Wireless Communications, VOL. 1, NO. 3, July, 2002

Applied Mechanics and Materials Vols. 479-480 (2014) pp 1001-1005 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.1001

Development of an Equipment Failure Identification Expert System with Multiple Reasoning Approaches Yeong-Ho Ho1,a, Huei-Sen Wang2,b, Hei-Chia Wang3,c 1

Department of Leisure and Information Management, Taiwan Shoufu University 2

Department of Materials Science and Engineering, I-Shou University

3

Institute of Information Management, National Cheng Kung University

a

[email protected], [email protected], [email protected]

Keywords: Equipment Failure Analysis Expert System, RBR, CBR, Knowledge acquisition, inference

Abstract. The goal of the reasoning system in this study is to identify the most similar failure type or failure cases. As a user inputs all possible requirements (attributes), the inference engine of the system carries out its similarity assessment (inference approaches) and ranks rules or cases from the data base. Various inference approaches are chosen to find out the optimal method for the RBR and CBR system. The CBR system offers two types of inference methods which are hierarchical factors, flat factors without weight. For RBR system, there three types of inference methods are chosen, one is complete matched and the others are partial matched approaches which use the inference capability of CBR. The performance of developed system is then evaluated by using the real cases from China Steel Corporation (CSC). For the RBR system, performance is directly check the inferred order of the document ranking list. For the CBR system, the effectiveness of each inference method is evaluated by using “Recall”, “Precision”, and “F-Measure” approaches. From the test results, many recommendations are proposed. 1. Introduction To work on the failure analysis, a Corrosion-Testing Center at the China Steel Corporation (CSC), the largest steel corporation in Taiwan, was established in 1977. From their over 28 years of experience, so much valuable knowledge has been accumulated by their domain specialists and kept in their mind. However, when the specialist moves to a different department within the company or even to a different company, or retired, this may leads to the lost of their expertise. In additions, for a new employee, it needs to takes year of training followed by years practical experience to become an expert. Hence, CSC considers using the modern information technology to develop an expert system (ES) to deal with the above problems. To help corrosion engineers effectively diagnose the causes of the failure mechanism and provide a reliable remedy, this work is carried out to develop an Equipment Failure Analysis Expert System (EFAES) with an innovative reasoning approach: integrating the rule-based reasoning (RBR)[1-3] and the case-based reasoning (CBR)[4,5] methods. This system present in EFAES is an

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example of the third approach which keeps the RBR and the CBR as two “equal” reasoning modules [6] For the RBR system, 46 failure mechanisms (See Table1) are covered where rules are dominantly generated from the domain experts. For the CBR system, a total 586 failure cases are collected from the various paper resources or industrial partner. As a target problem is given, the RBR system applies the rules to get an approximate answer. Simultaneously, the CBR system draws analogies from cases to cover exceptions to the rules. This reminder of this paper is organized from the viewpoint of knowledge engineer (materials scientists with essential AI knowledge) and described as two sections. The first section describes the system design and system development procedures. At the second section, the developed expert system is then evaluated through a variety of cases. From the test results various recommendations are therefore proposed. Table 1. Total 46 failure mechanisms and their cases used in this system. High Temperature Failure C. No. 1.High-temperature creep 5 2.High-temperature fatigue 2 3.Temper embrittlement 1 4.Secondary embrittlement 1 5.High-temperature 5 oxidizing 6.Carburization 2 7.Nitridizing 2 8.Metal dusting 4 9.High-temperature 5 sulphurizing 10.Melting salt corrosion 1 11.Blow-ash corrosion 1 12.Sigma-phase 2 embrittlement 13.475oC embrittlement 1 Total 32 Mechanical Failure C. No. 1.Fatigue 4 2.Erosion 72

% 0.85% 0.34% 0.17% 0.17%

3.Cavitation corrosion 4.Brittle failure Total Chemical Failure 1.Uniform corrosion

2 1 79 C. No. 58

0.34% 0.17% 13.48% % 9.90%

15.Microbiologically induced corrosion 16.Coating failure 17.Ammonia corrosion 18.Stray current corrosion 19.Sulphur corrosion

21 19 10 7 8

3.58% 3.24% 1.71% 1.19% 1.37%

7

1.19%

0.85% 2.Galvanic corrosion

44

7.51% 20.Alkalinity corrosion

0.34% 3.Crevice corrosion 0.34% 4.Pitting 0.68% 5.Intergranular corrosion

12 17 16

2.05% 21.Filiform corrosion 2.90% Total 2.73% Mixed Failure

0.85% 6.Selective leaching

18

3.07% 1.Stress corrosion cracking

53

9.04%

0.17% 7.Knife-line corrosion 0.17% 8.Weld decay

1 10

0.17% 2.Corrosion fatigue 1.71% 3.Hydrogen cracking

9 3

1.54% 0.51%

0.34% 9.Deposition corrosion

24

4.10% 4.Hydrogen attack

10

1.71%

0.17% 5.46% % 0.68% 12.29%

9 6 36 32 32

1.54% 1.02% 6.14% 5.46% 5.46%

1 4 4 1 85

0.17% 0.68% 0.68% 0.17% 14.51%

10.Corrosion under insulation 11.Dew point corrosion 12.Halide attack 13.Atmospheric corrosion 14.Oxygen corrosion

5.Sulphide Stress corrosion cracking 6.Liquid metal embrittlement 7.Alkalinity stress corrosion 8.Hydrogen embrittlement Total

3 0.51% 390 66.55% C. No. %

2. System Development 2.1 System Architecture The expert system developed in this study basically consists of six major components. To develop an expert system, it is also necessary to understand the major roles of individuals who interact with the system. As show in Figure 1, since the expert may has less skill to encode their knowledge into the system and system engineer has far less domain knowledge, the knowledge engineer plays a role to act as a go-between to help a system to be built up. However, communication problems may occur and impede the process of transferring expertise into a program, thus the knowledge engineer, expert and system engineer must work together to develop an expert system with acceptable performance.

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System Engineer

User

Knowledge Engineer

Expert

Rule Knowledge

Case Knowledge

Knowledge Acquisition Interface for rules

Knowledge Acquisition Interface for Cases

1003

Factors and Attributes Editors

To knowledge acquisition interface

Case Base

Print out

Rule Base

Acceptable

RBR Inference Engine

Display: 1. Failure modes 2. Similar failure cases 3. Provide the possible causes and remedy

CBR Inference Engine

Explanation Facility

To user interface

User inputs the several groups of attributes for failure analysis

Figure 1 System architecture and participants in this study.

2.2. Knowledge Collection and Analysis In this study, knowledge for the RBR systems is basically obtained from the five experts of CSC corrosion-testing center. Knowledge engineer uses an acquisition table approach to induct the knowledge manually from experts because the domain experts feel more comfortable in providing information with such indirect interview approach. In this approach, knowledge engineer designs a self-administered matrix table which consists of 46 failure mechanisms in columns and, 7 first level failure factors in rows. Through the discussion, the CSC experts select the most agreed-on opinion or solution from the 265 attributes to fill out the table. The information elicited from the experts is then turned into the form of if-then rules. An example, as shown in Table 2, the selected attributes correspond to the failure mechanism of deposition corrosion. The elicited rule is then input into the knowledge base through the knowledge acquisition interface shown in Figure 2. Table 2 List of factors and some examples of attribute value used for failure identification. 1st level factors Materials

Environmental Description

2nd level factors Ferrous Un-ferrous System Part Contact Substance Operation Condition

Attribute values e.g. Carbon steel, Alloy steel, Cast iron e.g. Aluminum alloy, Magnesium alloy e.g. Steam system, Heating system e.g. Gear, Pipe, Bolt e.g. Water, Soil, Solvent e.g. Fluid flow, Vibration

Working Temperature Tool Life pH Value

Quantitative Express

Surface Observation Micro Analysis Micro- Observation EDS analysis XRD analysis Manufacturing Joint process Surface processing Machining process Heat Treatment Stress Analysis Mechanical Strength properties Analysis Hardness Ductility Toughness

e.g. Grooving, Crack, Rupture e.g. Intergranular cracking, Beach mark e.g. Fe, Zn, Si e.g. Oxide, Sulfide, Chloride e.g. Weld e.g. Burnish, Electroplate, Coating e.g. Forging, Percing, Squeeze e.g. Temper, Anneal, Quench e.g. Thermal stress, Repeated stress Quantitative Express

Totals 11 10 23 38 16

61 30 27 16 1 11 7 10 4

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Figure2 RBR knowledge acquisition interface, here demonstrated how a rule is to be established from this

For the CBR system, the knowledge is mainly acquired with document processing approach from various resources such as CSC technical reports, handbook (e.g. corrosion atlas), journal or failure cases from the other companies. Total 586 failure cases are gathered and analyzed by three knowledge engineers. Each case is coded and composed of three major parts, which are  general information (See Figure 3a); such as case number and failure type etc.. Based on the data, the system then creates a case number automatically shown on the top of attribute indexing page (next parts).  indexed failure attributes for each case (See Figure 3b). Attribute categories used in the CBR system is the same as the RBR system,  cause, remedy, and photos for surface observation and micro-analysis for each failure case, (See Figure 3c) . a

Selected information create a Case No.

b

c

Figure 3 Knowledge representation for the CBR in this study which includes three major parts: (a). general information (b) indexed attributes (c) cause, remedy and photos.

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3. Conclusions In this study, an EFAES is presented to help corrosion engineers effectively diagnose the causes of failure mechanism and provide a reliable remedy. This paper is shown how an EFAES is designed and developed. As the expert system is completed, the system performance is then evaluated by a variety of approaches. Based on the above work, the conclusions can be drawn as follows: 1. The present study has advantageously integrated both the RBR and the CBR approaches to develop an EFAES system. This system keeps the RBR and the CBR as two “equal” reasoning modules. 2.

3.

This system is evaluated by a variety of method, such as directly checking the inferred order of the document ranking list to evaluate the RBR system, and using “Recall”, “Precision”, and “F-Measure” approaches to evaluate the CBR system. From the test results, many recommendations are proposed. The developed system is expandable and adjustable, which allows more rules or cases to be added into the system or modified. Therefore, it can be expected that the system will become a very useful diagnostic tool for corrosion engineer as more expertise is supplement in this system.

Acknowledgement The authors are grateful to China Steel Corporation for financially supporting this research under grant RJ93603. Reference: [1]. T. W. Liao, Z. H. Zhan, C. R. Mount, Engineering Failure Analysis,.6(1999), 387-406. [2]. T. W. Liao, Z. H. Zhan, C. R. Mount, Engineering Failure Analysis, 6 (1999), 407-421. [3]. T. W. Liao, Z. M. Zhang, C. R. Mount, 13 (2000), 199-213. [4]. T. W. Liao, Engineering Applications of Artificial Intelligence, 17 (2004), 123-134. [5]. A. R. Golding and P. S. Rosenbloom, Artifical Intelligence, 87 (1996), 215-254. [6]. Steel Handbook，Material Research Society Taiwan (Taiwan，Hsinchu, 1998) p. 603.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 1006-1009 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.1006

Classification of Chinese Popular Songs Using a Fusion Scheme of GMM Model Estimate and Formant Feature Analysis Ing-Jr Ding, *Chih-Ta Yen and Che-Wei Chang Department of Electrical Engineering, National Formosa University, No.64, Wunhua Rd., Huwei Township, Yunlin County 632, Taiwan, R.O.C. *Email: [email protected] Keywords: song classification, Gaussian mixture model, formant feature, GMM-Formant.

Abstract. In this paper, a fusion scheme that combines Gaussian mixture model (GMM) calculations and formant feature analysis, called GMM-Formant, is proposed for classification of Chinese popular songs. Generally, automatic classification of popular music could be performed by two main categories of techniques, model-based and feature-based approaches. In model-based classification techniques, GMM is widely used for its simplicity. In feature-based music recognition, the formant parameter is an important acoustic feature for evaluation. The proposed GMM-Formant method takes use of linear interpolation for combining GMM likelihood estimates and formant evaluation results appropriately. GMM-Formant will effectively adjust the likelihood score, which is derived from GMM calculations, by referring to certain degree of formant feature evaluation outcomes. By considering both model-based and feature-based techniques for song classification, GMM-Formant provides a more reliable recognition classification result and therefore will maintain a satisfactory performance in recognition accuracy. Experimental results obtained from a musical data set of numerous Chinese popular songs show the superiority of the proposed GMM-Formant. Introduction. Popular song classification has been seen in lots of studies in the recent years. Popular song classification applications could be viewed as a branch in the field of speech/audio processing. Research pertaining to speech/audio information processing encompasses myriad branches including encoding/decoding, identification/verification and analysis/synthesis [1]. Popular song classification belongs to the category of identification/verification. Studies on popular song classification applications focuses on two main classification techniques, feature-based and model-based categories of methods. Feature-based approaches performed on song classification are to mainly carry out the work of automatic audio segmentation (AAS). Generally, the structure of a popular music is composed of verse, chorus and non-repetitive (such as intro, bridge and outro) segments. AAS application is to identify verse, chorus and non-repetitive segments. In [2], a method of segmenting musical audio into structural sections based on a hierarchical labelling of spectral features is presented. Such the approach is typically a feature-based classification mechanism with constrained clustering. In the work of [3], Lukashevich proposes an approach of applied normalization, which will enable the comparison of the automatic evaluation results, obtained for songs with a different amount of states. In addition, Peiszer develops a two-phase algorithm for boundary and structure detection where the complete annotation of all song parts both with sequential-unaware approaches and an approach that takes temporal information into account is paid much attention [4]. The category of model-based techniques for song classification operation is to establish a statistical model and then the trained model is used to classify the input test song and decide the tendency characteristics of the song. Gaussian mixture model (GMM) [5] has been a popular classification model in the field of popular music\song classification for its excellent recognition accuracy. In fact, GMM is frequently used in the field of speaker recognition [6, 7]. The GMM classifier is typical classification scheme of pattern recognition applications. In speaker recognition

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applications, the GMM is more effective in speaker identification. The architecture of a typical identification system is associated with established GMM classification models, where the input test acoustic samples are segmented into the frame sequence, and from which acoustic features are extracted to estimate the likelihood degree of GMM classification models via the classifier operation. When collecting the likelihood degree estimates at a predefined time period, the classification operation is completed and the decision of the classification tendency of this input test acoustic sample can then be made. Although the above-mentioned feature-based and model-based classification techniques could perform well in a general classification application, the classification accuracy of the system will be doubtful when encountering an adverse environment where the input test acoustic sample is substandard. Few studies focus on the fusion mechanism of feature-based and model-based classification techniques. In this paper, to increase the classification accuracy of a popular song classification application, a fusion scheme that combines GMM model-based calculations and formant feature-based analysis, called GMM-Formant, is developed. The proposed GMM-Formant method takes use of linear interpolation for combining GMM likelihood estimates and formant evaluation results appropriately, which will be introduced in the following sections. Popular Music Classification Techniques. Two main classification techniques, model-based and feature-based determination mechanisms, for popular music recognition are adopted for their effectiveness and efficiency on recognition classification performances. This section will describe the popular Gaussian mixture model model-based classification method and the widely-used formant evaluation feature-based classification method. The framework of a popular song classification system that uses the model-based technique is associated with established audio models, frequently-seen GMM for example, where the input popular music from the database is segmented into the frame sequence, and from which audio features are extracted to evaluate the characteristic and the classification tendency of this music via classification operations cooperated with GMM audio model calculations. Mathematically, a GMM is a weighted sum of M Gaussians, denoted as [5]

λ = {wi , µi , Σi }, i = 1, 2, ..., M ,

M

∑w

i

= 1,

(1)

i =1

where wi is the weight, µ i is the mean and Σ i is the covariance. In this study, four parameter sets,

λ1 , λ 2 , λ3 and λ4 (four GMM models, that is), for representing the music characteristics of four different categories are determined, respectively. In the classification operation of testing phase, the estimated likelihood score that an audio frame xi , belongs to a GMM of class Z ∈ {λ1 , λ 2 , λ3 , λ 4 } is then M 1  1  L ( xi | Z ) = ∑ w j ⋅ ⋅ exp− ( xi − µ j ) T (Σ j ) −1 ( xi − µ j ) . (2) 1/ 2 D/2 2   j =1 (2π ) ⋅ Σ j Formant is regional frequency of the sound energy and can calculate the low frequency region that the person’s ear could hear. Formant puts extremely little emphasis on a high and rough frequency region. Formant spectrum was produced by calculating the input musical data. Formant spectrum contains lots of peak values in every spectrum. For example, there are totally N formant in the spectrum, generally denoting as F1, F2, F3, …, FN,, each of which represents a different frequency and energy. In formant feature analysis, an all-pole mode for defining the characteristics of a song before calculating the envelopment is necessary, which is shown as follows. G . (3) H (z) = p z −k 1 − ∑ ak k =1

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In Eq. (3), the parameter G is a constant and usually set as 1, the parameter p denotes the linear predictive order and ak means the linear prediction coefficients. For simplicity on practical evaluation of input acoustic signals, the above formant feature analysis is transformed into the following operation formula, fs (4) frequency ( x ) = ⋅ index , framesize where frequency(x) is the frequency of the x-th peak value, f s denotes the sampling rate, framesize means the length of a frame and the parameter index is the index value of a peak value.

The Proposed GMM-Formant Approach. As mentioned in the previous section, the operation procedure of GMM classifier performs a fast recognition classification calculation using the simple likelihood calculation as shown in Eq. (2) to obtain the likelihood score between the input acoustic song data and the song classification model. When given proper song data with standard property, classification operation by using the GMM classifier is effective. However, given substandard song data for recognition classification, the accuracy of the estimated likelihood score using Eq. (2) is dubious. Poor estimation of the likelihood score in turn leads to incorrect recognition results on song classification. The problem of improper testing data for classification operation can be alleviated by additionally referring to certain degree of evaluation information of feature-based classification operation. Given substandard test song data for classification, it is necessary to be more “conservative” in using the derived likelihood score for classification decisions. In other words, the effect of the improper data should be restricted so that the final decision does not reference too much from the model-based classification calculation outcome derived by GMM classifier estimate. Therefore, this study proposes the GMM-Formant approach which combines both model-based and feature-based classification operations as follow, Adjusted Likelihood Score = α ⋅ GMM + (1 − α ) ⋅ Formant , 0 ≤ α ≤ 1, (5) where GMM is the likelihood score calculated by GMM classifier operation, i.e., Eq. (2) in the previous section and Formant is the evaluated information derived from formant feature analysis as described in the previous section. The likelihood score for song classification decisions is not determined by only the GMM likelihood estimate. Instead, this proposed approach as shown in Eq. (5) calculates a weighted sum of the GMM model-based estimate and the formant feature-based evaluation. The form of linear interpolation in Eq. (5) is used to tune the likelihood score derived from Eq. (2), and with the proper adjustment of formant evaluated information, the final adjusted likelihood score for recognition classification decision on input test songs will be more reliable and believable. Conclusions. This paper proposes a GMM-Formant scheme for popular song classification applications. The proposed GMM-Formant takes use of the popular linear interpolation technique to perform a proper fusion between model-based and feature-based classification processing. In developed GMM-Formant, Gaussian mixture model is adopted for model-based classification, and formant feature analysis is utilized to carry out feature-based classification. The problem of improper test song data for GMM classification recognition can be effectively alleviated in the presented GMM-Formant by additionally referring to certain degree of formant feature evaluation information. Experimental results demonstrated that developed GMM-Formant achieved competitive and acceptable performances on recognition accuracy.

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References [1] C. Wutiwiwatchai, S. Furui, Thai speech processing technology: A review, Speech Communication 49 (2007) 8–27. [2] M. Levy, M. Sandler, Structural segmentation of musical audio by constrained clustering, IEEE Transactions on Audio, Speech, Language Processing 16 (2008) 318–326. [3] H. Lukashevich, Towards quantitative measures of evaluating song segmentation, Proceedings of International Conference on Music Information Retrieval, 2008, pp. 375–380. [4] E. Peiszer, T. Lidy, A. Rauber, Automatic audio segmentation: Segment boundary and structure detection in popular music, Proceedings of International Workshop on Learning the Semantics of Audio Signals, 2008. [5] D.A. Reynolds, R.C. Rose, Robust text-independent speaker identification using Gaussian mixture speaker models, IEEE Transactions on Speech and Audio Processing 3 (1995) 72–83. [6] C. H. You, K. A. Lee, H. Li, An SVM kernel with GMM-supervector based on the Bhattacharyya distance for speaker recognition, IEEE Signal Processing Letters 16(1) (2009) 49–52. [7] P. Kenny, G. Boulianne, P. Ouellet, P. Dumouchel, Speaker and session variability in GMM-based speaker verification, IEEE Transactions on Audio, Speech, and Language Processing 15(4) (2007) 1448–1460.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 1010-1013 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.1010

Low Phase Noise and Low Power Voltage-Controlled-Oscillator Using Current-Reuse Techniques for Wireless Communication Circuits Tsung-Han Han 1 a, Meng-Ting Hsu 1 b, Cheng-Chuan Chung 1 c Microwave Communication and Radio Frequency Integrated Circuit Lab. Department and Institute of Electronic Engineering, National Yunlin University of Science and Technology 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R.O.C. a

[email protected],

b

c

[email protected], [email protected]

Keywords: Voltage Controlled Oscillator,Tuning Range,Phase Noise,Low Power,Current-Reused.

Abstract. In this paper, we present low phase noise and low power of the voltage-controlled oscillators (VCOs) for 5 GHz applications. This chip is implemented by Taiwan Semiconductor Manufacturing Company (TSMC) standard 0.18 µm CMOS process. The designed circuit topology is included a current-reused configuration. It is adopted memory-reduced tail transistor technique. At the supply voltage 1.5V, the measured output phase noise is -116.071 dBc/Hz at 1MHz offset frequency from the carrier frequency 5.2 GHz. The core power consumption is 3.7 mW, and tuning range of frequency is about 1.3 GHz from 4.8 to 6.1 GHz. The chip area is 826.19 × 647.83 um2. Introduction In recent years, due to the rapid development of wireless communications and single-chip system integration, integration of multi-band and a variety of standards in a mobile device in the practice has been more and more attention. A stable voltage-controlled oscillator makes communication system showing excellent performance in modern RF communication systems. Voltage-controlled oscillator is often used as a local oscillator source system signals up-and down-conversion frequency synthetic function. In order to reduce component count, size, cost, and improve system integration, a multi-band VCO will be a better choice. Circuit Topology Fig.1 shows the proposed VCO based on the current reused topology with memory circuits as tail current. The function of capacitor Cout1/Cout2 is the filter to enhance the phase noise.

Fig.1. The circuit structure. A. The current re-use (Current-Reused). General Current-Reused VCO circuit of an NMOS and PMOS transistors produce a negative-resistance to compensate the loss of the tank. Fig.2 (a) as shows the output voltage at the ends of LC tank, and sustain a stable oscillation frequency. However, this architecture of the VCO can not be an ideal balance of voltage swing. When the output voltage

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for the positive half cycle was shown in Fig.2 (b), MN1 and MP1 transistors are ON, you can get a large current flows through MN1 and MP2 transistors. At this point Cx = C/2 + Cpx, Cy = C/2 + Cpy. (Cpx Cpy, the parasitic capacitance of the X and Y, respectively). But when the output voltage of the negative half cycle was shown in Fig.2 (c), MP1 and MN1 are OFF. Owing to the voltage limit mode, the resulting voltage swing will be smaller.

(a)

(b)

(c)

Fig.2. (a) Current Reused the VCO oscillation mode (b) Equivalent circuit when output is positive half of the weeks(c) Circuit when the output is negative half of the week. B. Memory-reduced tail transistor. When the square wave transistors in strong inversion region and accumulated addition cyclic movements, this way can reduce 1/f noise. Switching bias current source can be applied in many circuits to reduce the value of low-frequency noise to the noise of the high-frequency conversion. MOS transistors with flicker noise will cause a lot of phase noise. So, there must have the tail transistor memory to replace the tail current source which was shown in Fig.3. In this structure, output sine wave switching mode of the tail transistor can release the e-capture in the transistor channel, to reduce flicker noise. Gradually switching transistor state does not produce sharp waves in the phase noise measurement on the way. Furthermore, not only to reduce low frequency noise to the frequency conversion but also reduce power consumption. No bias supply is another advantage.

Fig.3. The memory reduction tail transistor architecture. Results and Discussion Fig.4 shows the chip photograph of proposed VCO. Fig.5 shows the output spectrum at oscillation frequency of 5.2 GHz with output power 15.5240 dBm. Fig.6 shows the phase noise at the offset 1 MHz with the value of -116.071 dBc/Hz. The measurement of the tuning frequency range is from 4.79 GHz to 6.10 GHz. Table I shows the reference of the measured values and compares with other literature. Our work shows the excellent performance and low power consumption.

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Fig.4. Chip photograph.

Fig.5. Oscillation in the output spectrum when the 5.2GHz.

Fig.6. The phase noise at 1MHz offset. Table I Performance Comparison with other reported papers Reference Process technology (µm) Oscillation frequency (GHz) Tuning range (%) Phase noise @1MHz (dBc/Hz) core power (mW) FOM (dBc/Hz)

2011 [1] 0.18

2007 [4] 0.18

2005 [5] 0.18

2008 [6] 0.18

2007 [7] 0.18

2010 [8] 0.18

This work 0.18

5.07

5

5.5

5.31

5.25

5.4

5.2

9

9

19.6

7.9

11

2.6

24.3

-117.5

-110

-115

-120.1

-107

-112.7

-116.07

6.2 -183.7

2.59 -180

5.8 -182

8 -185

1.5 -175

0.9 -188

3.71 -184

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Summary This paper presents the architecture with the tail transistor current reused circuit to improve the traditional VCO circuit. The measurement results are the phase noise is -116.071 dBc/Hz at 1 MHZ offset under 5.2GHz oscillation frequency, the tuning frequency is from 4.79 GHz to 6.10GHz with 24.3% tuning range and the core power consumption is 3.7 mW. Acknowledgments The authors would like to thank the Taiwan Semiconductor Manufacture Company (TSMC) and National Chip Implementation Center (CIC) for the wafer fabrications and IC measurement. This project was supported by National Science Counsel (NSC), Taiwan. NSC 100-2221-the E-224-072. References [1] Po-Hung Chen, "IEEE802.11a low phase noise voltage-controlled oscillator design", National Yunlin University of Science and Technology of Electronic Engineering, Master's thesis, the Republic of China a hundred years. [2] Li Wei, sickle, the use of capacitance grounding of 8GHz Low Phase Noise Voltage Controlled Oscillator Design, National Yunlin University of Science and Technology Institute of Electronic and Information Engineering, Master's thesis, ninety-six year June [3] Xiao-Hui Chen, "Broadband switching switched-capacitor model modulation voltage control oscillator research and analysis", Master Thesis of National Yunlin University of Science and Technology Department of Electronic Engineering, ROC January ninety-seven. [4] Y. H. Chuang, S. L. Jang, S. H. Lee, R. H. Yen, and J. J.Jhao, "5-GHz low power current-reused balanced CMOS differential armstrong VCOs," IEEE Microw. WirelessCompon. Lett., vol. 17, no. 2, pp. 139-141, Feb. 2007. [5] J.-H. Chang and C.-K. Kim, "A symmetrical 6-GHz fully integrated cascade coupling CMOSLC quadrature VCO," IEEE Microw. Wireless Compon. Lett., vol. 15, no. 10, pp. 670-672, Oct.2005. [6] S.-L. Jang, S.-S. Huang, C.-F. Lee, and M.-H. Juang, "CMOS Quadrature VCO implemented with two first-harmonic injection-locked oscillators," IEEE Microw. Wireless Compon. Lett., vol. 18,no. 10, pp.695-697, Oct. 2008. [7] Y. C. Tsai, Y. S. Shen, and C. F. Jou, "A low-power quadrature VCOusing current-reused technique and back-gate coupling," Progress In Electromagnetics Research Symposium pp. 192-195, (2007). [8] I-Shing Shen, Han-Tzung Ke, and Christina F. Jou,” A Ultra Low Power 5.4-GHz Current-Reused VCO with Internal LC Series Resonance in O.18-11m CMOS Technology,” Proceedings of Asia-Pacific Microwave Conference 2010,WE3G-26 pp.457-460 (2010)

Applied Mechanics and Materials Vols. 479-480 (2014) pp 1014-1017 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.1014

Design of 3.1-10.6GHz CMOS LNA Based on input matching technique of common-gate topology Yi-Cheng Chang 1 a, Meng-Ting Hsu 1 b, Yu-Chang Hsieh1 c Microwave Communication and Radio Frequency Integrated Circuit Lab. Department and Institute of Electronic Engineering, National Yunlin University of Science and Technology 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R.O.C.

1

a

[email protected], b [email protected] , c [email protected]

Keywords: Low-noise Amplifier, Ultra-Wide-Band, low power

Abstract. In this study, three stage ultra-wide-band CMOS low-noise amplifier (LNA) is presented. The UWB LNA is design in 0.18µm TSMC CMOS technique. The LNA input and output return loss are both less than -10dB, and achieved 10dB of average power gain, the minimum noise figure is 6.55dB, IIP3 is about -9.5dBm. It consumes 11mW from a 1.0-V supply voltage. Introduction Wireless communication systems at high frequencies represent a huge market that drives the semiconductor technology toward low cost solutions. CMOS technology is an attractive solution due to the low cost, high level integration and high performance in terms of cutoff frequency. For high frequency design, more advanced technology will certainly provide better performance. The problem with CMOS technology for RF applications is the low transconductance. Typically, high gain and low noise implementation of CMOS low noise amplifiers (LNA) involves high power dissipation which is not desirable option with potable wireless system. A wideband amplifier is essential component in many communication systems. Recently, the Federal Communications Commission (FCC) in US approved the use of ultra-wideband (UWB) technology for commercial applications from 3.1GHz to 10.6 GHz. The UWB transmission system has two major proposed solutions, DS-UWB and MB-OFDM. The band of 5-6GHz is not considered in current UWB system which caused by 802.11a WLAN. UWB performs excellently for short-range high-speed uses, such as automotive collision-detection systems, through-wall imaging systems, and high-speed indoor networking, and plays a more and more important role in wireless local area network (WLAN) applications. Low power consumption is one of the most important design concerns in the applications of this technology. Circuit structure and analysis The proposed wideband low noise amplifier is shown in Fig.1. By a common gate amplifier to achieve wideband input matching, and matched to 50Ω. The second stage use high frequency gain topology. The cascode amplifier provide high gain increased isolation degree and stability and eliminate the Miller effect common source amplifier. The high frequency gain stage is sufficient to provide a gain in the higher frequency band. The circuit also uses a series-peaking technology, that can be enabled high-frequency gain to extend and enhance the high-frequency gain. The final output stage is to obtain impedance matching while adopted the source follower as the output stage to drive 50Ω impedance.

Applied Mechanics and Materials Vols. 479-480

V

Vdd3 dd3

Vdd1 dd1

dd1

1015

R3 R1

L3

L2

L4

M3 C2

M4

RF

M2

L6

OUT

R4

RF

1 sC1

M1

Vg 1 L5

IN

V g2

C1

1 sC 2

M5

V g3

L1

Fig.1. Schematic of the proposed UWB LNA.

1 sCds1

1 sCgs1

1 sCgd1

1 sCgd 2(1 − k )

1 sCgs 2

Fig.2. Simple high frequency model.

Input matching network. The input matching circuit design should avoid the use of the resistive element as a bias load resistor itself will generate a lot of noise, making the overall circuit noise rise. So this design uses inductor as a bias load has been reduced noise. Transistors, inductors and capacitors have their own internal resistance, so the use of its internal parasitic resistance as a 50Ω impedance matching by the ADS simulation software to simulate the appropriate transistors, inductors and capacitors for components size, making the input matching can obtain the operation range of 3.1-10.6GHz. It can be seen from Fig.2 , consider the parasitic resistance and capacitance of the inductor and transistor at high frequencies. That can be obtained by the small-signal model when Zin is equal to equation (1), ZD is equal to equation (2) and ZD1 displays equation (3). The input matching network can be completed to match 50Ω with these equations.

Zin =

1 1 + sL5 +{[ // sL1 // ZD ]} sC1 sCgs1 1 ) + Z D1 sC ds 1 1 + g m 1 ro 1

(1)

( ro 1 // ZD =

(2)

1 1 1 ZD1 ={{[( // // R4 ) + ] sCgs2 sCgd2 (1− K) sC2 //(sL2 + R1)}+ sL6}//

1 sCg d1

(3)

The second stage uses high-frequency gain stage. The cascode type amplifier not only provides gain but also supports sufficient stability to eliminate the high frequency Miller effect. The third stage is the buffer stage, which supply enough impedance for 50Ω matching.

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Measure Result

Fig.3. Measurement results of input return loss (S11)

Fig.5. Measurement results of gain (S21)

Fig.4. Measurement results of output return loss (S22)

Fig.6. Measurement results of noise figure (NF)

The measurement results of LNA input return loss (S11) and output return loss (S22) are shown in Fig.3 and Fig.4. The input return loss (S11) and output return loss (S22) are less than -10dB, respectively. The Fig.5 shows the measurement results of the gain (S21) with average gain of 10dB. The Fig.6 shows the measurement results of noise figure (NF) with average noise figure of 6.7dB. Table I summarizes the measurement results and comparisons with those of referred papers. Table I Performance Comparison with other reported papers Reference Technology [5] [6] [7] [8] [9]** This work

0.18-µm CMOS 0.18-µm CMOS 0.18-µm CMOS 0.18-µm CMOS 0.18-µm CMOS 0.18-µm CMOS

Frequency (GHz)

S11 (dB)

S22 (dB)

S12 (dB)

S21 (dB)

Nfmin PDC IIP3 Chip size (mW) (mW) (dBm) (mm2)

3.1-10.6

< -9.7

N/A

N/A

9.2

4.1

23.5

7.25

0.78

0.72

3.1-10.6

< -9

N/A

-40

16

3.1

11.9

-7

1.2

2.21

FOM

3.1-10.6

D − b + k v when v < − D df  d

(8)

where D denotes the yielding displacement and bd the characteristic strength. When Eq.(7) is substituted into Eq.(4), the governing equation of the i -th floor at instant i becomes u Ni 2 ( ) f N cd ( N ) i C K i 2 u

N + u
N + = −[(
x
gi −
x
Ni −1 ) − (
x
gI +
x
NI −1 )] − N u
Ni − N u Ni (9) mN mN mN mN where u Ni = [( x Ni − x Ni −1 ) − ( x NI − x NI −1 )] (10) i Substituting Eq.(8) into Eq.(9), and denoting the right-hand side of Eq.(9) as u

Ng , the governing

equation can be rewritten as u

Ni + u

Ni + u

Ni +

cd ( N ) mN cd ( N ) mN cd ( N )

u
Ni + u
Ni + u
Ni −

k de( N ) mN 2bd ( N ) mN 2bd ( N )

i u Ni = u

Ng

+

k df ( N ) mN

i u Ni = u

Ng

− D ≤ u Ni / 2 ≤ D

(11)

u Ni / 2 > D

(12)

k df ( N )

i u Ni = u

Ng u Ni / 2 < − D (13) mN mN mN Eq.(11)~(13) are used to identify the parameters of the N -th floor of energy-dissipated building.

+

Physical-Identification Identification of the system parameters can be conducted once the dynamic responses of the structure subjected to the input excitation are available. Based on an output-error concept [6], the system parameters are optimized by minimizing the discrepancy between the recorded and predicted responses of the system. Using the first set of data for u Ni / 2 ≤ D and Eq.(11), we define the partial measure-of-fit as 2  i c d ( N ) i k de ( N ) i i  e N 1 = ∑ u

N + u
N + u N − u

Ng  mN mN j =1   The values of c d ( N ) and k de ( N ) are obtained by simultaneously solving

(14)

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Applied Science and Precision Engineering Innovation

∂e N 1 =0, ∂ (c d ( N ) / m N )

∂eN 1 =0 ∂ (k de( N ) / mN )

(15)

Similarly, application of the second data set for u Ni / 2 > D and Eq.(12) produces another partial measure-of-fit as 2  i c d ( N ) i 2bd ( N ) k df ( N ) i i  e N 2 = ∑ u

N + u
N + + u N − u

Ng  (16) mN mN mN j =1   extremization of Eq.(17) with respect to the unknowns yields

∂e N 2 ∂e N 2 ∂e N 2 =0, = 0, =0 ∂ (c d ( N ) / m N ) ∂ (2bd ( N ) / m N ) ∂ (k df ( N ) / mN )

(17)

from which the values of cd ( N ) , bd ( N ) and k df (N ) are obtained. Finally, application of the third data set for − u bi / 2 < − D and Eq.(13), the third partial measure-of-fit is defined as 2

c d ( N ) i 2bd ( N ) k df ( N ) i  i  e N 3 = ∑ u

Ni + u
N − + u N − u

Ng (18)  mN mN mN j =1   Minimization of e N 3 with respect to c d ( N ) / m N , 2bd ( N ) / m N and k df ( N ) / m N respectively, i.e. solving the system equations of ∂e N 3 ∂e N 3 ∂e N 3 =0, = 0, =0 ∂ (c d ( N ) / m N ) ∂ (2bd ( N ) / m N ) ∂ (k df ( N ) / m N )

(19)

However, to ensure satisfaction of a prescribed criterion, say, the global measure-of-fit defined as eN = eN1 + eN 2 + eN 3 (20) The set of c d ( N ) , bd ( N ) , k de ( N ) , k df ( N ) , C N and K N that gives the minimum global measure-of-fit is regarded as the solution. Moreover, parameters identified from different set of data are somewhat different. In such a circumstance, the average value of all is adopted. Similarly, physical parameters of Floors N − 1 to 1 could be obtained using Eq.(5) and (6) and the aforementioned procedures.

Numerical Example As an effort to verify the proposed methodology for system identification of buildings, a numerical example is considered using a 3-story energy-dissipated building with SDBs. The system parameters considered in this study include: (1) m1 = m2 = m3 = 116.64 × 10 3 kg ; K 1 = K 2 = K 3 = 168.06 MN / m and C1 = C 2 = C 3 = 321.0kN .s / m for the primary structure; (2) bd (1) = bd ( 2 ) = bd (3) = 74.556kN .s / m k de (1) = k de ( 2) = k de (3) = 44.145MN / m

;

k df (1) = k df ( 2) = k df (3) = 6.867 MN / m

and

cd (1) = cd ( 2) = cd (3) = 156.0kN ⋅ s / m for the SDBs. Dynamic responses of the energy-dissipated building under the N-S component of the 1940 El Centro earthquake are calculated using Newmark’s linear acceleration method with a time-step of 0.02sec. The acceleration responses contaminated with an artificial white noise signal of 5% noise-to-signal ratio are considered in the system identification analysis to simulate the measured data in a more realistic manner. Fig. 1 presents the nonlinear restoring force of SDBs with a yielding displacement of 0.199 cm and a ductility ratio of 2.49. The force-displacement relationship of the story shear at the third floor (i.e. primary structure) is almost linear, as illustrated in Fig. 2. In the first cycle of the identification process, the initial value of C 3 is arbitrarily set to be zero. The global measure-of-fit with respect to K 3 is presented in Fig. 3 from which the least squares estimate of K 3 is shown to be 170.0 MN / m . The minimization process is then proceeded further to

Applied Mechanics and Materials Vols. 479-480

1153

find C 3 and other system parameters by keeping K 3 at this value. The optimal estimate of C 3 reads 280kN .s / m , as illustrated in Fig. 4. Meanwhile, the parameteric values of SDBs are identified as c d (3) = 198kN .s / m , bd (3) = 75.274kN , k de ( 3) = 42.170 MN / m and k df (3) = 5.064 MN / m . 1000

Symmetric ductile brace 3

200

Restoring force (kN)

Restoring force (kN)

250 150 100 50 0 -50 -100 -150 -200 -250

Floor 3 500

0

-500

-1000

-0.010

-0.005

0.000

0.005

0.010

-0.006

-0.004

Displacement (m)

Fig.1 Nonlinear restoring force of symmetric ductile brace 3

0.000

0.002

0.004

0.006

Fig.2 Restoring force and displacement of floor3 0.80

35

0.75

C3=0 (kN.s/m)

30

K3=170.0(MN/m)

0.70

25

e3(m2 /sec4)

e3 (m2 /sec4)

-0.002

Displacement (m)

20 15 10

0.65 0.60 0.55 0.50 0.45

5

0.40

0

0.35

0

50

100

150

200

250

0

300

100

200

300

400

500

600

C3(kN.s/m)

K3(MN/m)

Fig.4 Global measure-of-fit in the first cycle setting K 3 = 170 MN / m

Fig.3 Global measure-of-fit in the first cycle setting C 3 = 0kN .s / m

0.90 0.85 0.80 0.75 0.70 0.65 0.60 0.55 0.50 0.45 0.40 0.35

250

Restoring force (kN)

e 3 (m2 /sec4)

The second iterative cycle is next proceeded by considering the initial value of C 3 as 280kN .s / m derived from the previous cycle. Minimizing the global measure-of-fit, we have K 3 = 167.0 MN / m , as shown in Fig. 5. Table 1 summarizes the system parameters of the 3-rd SDBs and 3-rd floor identified respectively in three iterative cycles. Numerical results in this example suggest that three iterative cycles of identification are enough for sufficient accuracy. In addition, the skeleton curve estimated from the identified parameters of SDBs using the Masing criterion is illustrated in Fig. 6. Comparisons of the 3-rd floor acceleration and displacement are shown respectively in Figs. 7 and 8. Good agreement between the identified and measured responses has been observed, indicating adequacy of the proposed identification scheme for partially inelastic dynamic system. C3=280(kN.s/m)

200

Symmetric Ductile brace 3

150 100 50 0 -50 -100 -150 -200 -250

160

165

170

175

180

K3 (MN/m)

Fig.5 Global measure-of-fit in the second cycle setting C 3 = 280kN .s / m

-0.010

-0.005

0.000

0.005

0.010

Displacement (m)

Fig.6 Identified skeleton curve of symmetric ductile braces

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Applied Science and Precision Engineering Innovation

Number of cycle 1 2 3 True Value

Table 1 Identified parameters of the 3-rd SDBs and floor3 c d ( 3) bd ( 3 ) k df ( 3) k de ( 3) C3 kN .s / m kN .s / m kN MN / m MN / m 198.0 75.274 5.064 42.170 280.0 194.0 75.274 8.065 45.170 284.0 194.0 75.274 7.965 45.070 284.0 156.0 74.556 6.867 44.145 321.0 0.04

10

Displacement (m)

Floor 3

2

Acceleration(m/sec )

15

K3 MN / m 170.00 167.00 167.10 168.06

5 0 -5 Measured

-10

Identified

Floor 3

0.03 0.02 0.01 0.00 -0.01 -0.02

Measured

-0.03

Idintified

-15

-0.04

0

5

10

15

0

Time ( sec )

Fig.7 Comparison between identified and measured accelerations of floor 3

5

10

15

Time ( sec )

Fig.8 Comparison between identified and measured displacements of floor 3

Conclusion This paper develops a procedure for identification of the structural parameters of energy-dissipated buildings equipped with symmetric ductile braces. The behavior of the SDBs is characterized with a bilinear skeleton curve by which the multi-valued restoring force of displacement is transformed into a single-valued function to minimize the computational effort in the identification analysis. Feasibility of the proposed scheme has been demonstrated via a numerical example of an energy-dissipated multistory structure subjected to earthquake ground excitations. Features of the proposed procedure include: (a) Physical parameters of a partially inelastic MDOF system can be extracted directly. This method can be extended for system identification of building structures implemented with energy-dissipative seismic dampers if they can be represented with some form of skeleton curves. (b) All parameters of primary structure and energy-dissipated device, such as the stiffness, damping coefficients, characteristic strength et al., can be individually identified. (c) The system parameters are identified with reasonable accuracy in three iterations even in the presence of 5% noise contamination. Robustness of the algorithm makes it favorable for practical applications.

References [1] T.T. Soong and G.F. Dargush, John Wiley and Sons Inc., New York, (1997). [2] Y.P. Wang and C.S. Chang Chien: Ear. Eng. and Str. Dyn., Vol.38 (2009), p.1009. [3] C.S. Chang Chien: Ph. D. thesis, National Chiao Tung University, Hsinchu,Taiwan, (2008). [4] P.C. Jenning: J. of Eng. Mech., ASCE, Vol.91 (1965), p. 41. [5] M.C. Huang, Y.P. Wang, J.R. Chang and Y.H. Chen: J. of Str. Eng., ASCE, Vol.135 (2009), p. 1107. [6] M.T.A. Chaudhary, M. Abe, Y. Fujino and J. Yoshida: J. of Str. Eng., Vol.126 (2000), p.1187.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 1155-1159 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.1155

Modal Identification Of Structures From Seismic Response Data Via Amplitude-Dependent Time Series Model Wei Chih Su1, a, Chiung Shiann Huang2, Ching-Yu Liu2 1

National Center for High-Performance Computing, Hsinchu 30050, Taiwan 2

National Chiao Tung University, Hsinchu 30050, Taiwan a

[email protected]

Keywords: amplitude-dependent ARX, instantaneous modal parameters, moving least-squares.

Abstract. The present work develops a novel procedure of establishing an amplitude-dependent time series model for a nonlinear system and estimating the instantaneous modal parameters of the system from the dynamical responses. The undetermined coefficient in an amplitude-dependent autoregressive with exogenous input (amplitude-dependent ARX) model are assumed as functions of amplitude and are expanded by shape functions constructing by moving least-squares with polynomial basis functions. The amplitude of dynamical responses could be obtained by Hilbert transform. The instantaneous modal parameters of the system are directly estimated from the coefficient in the amplitude-dependent ARX model. Finally, the proposed approach is applied to process measured data for a frame specimen subjected to a series of base excitations in shaking table tests. The specimen was damaged during testing. The identified modal parameters are consistent with observed physical phenomena. Introduction In most identification methods for real system the model structure has been assumed beforehand such as linear system, time-varying system and nonlinear system. The linear system identification ARX (AutoRegressive with eXogenous inputs), ARMAX (AutoRegressive and Moving Average with eXogenous inputs) and OE (Output Error) models have been extensively studied [1-4]. However, many practical examples of nonlinear dynamic behavior have been reported in the engineering literature. In mechanical and civil engineering, a system with active control devices[5-9] modifying stiffness or damping is a time-varying system. A structure under damage normally exhibits nonlinear dynamic behaviors and time-dependent stiffness and damping [10,11]. Variations in system stiffness and damping over time result in time-varying modal parameters of the system. Consequently, determining modal parameters of a time-varying system or nonlinear system is generally very useful when assessing structural damage in real applications. The linear parameter estimation technique has been employed [4] for these nonlinear identifications. There are, however, few practical identification methods for nonlinear systems from input-output data. Several theoretical studies have been done for the identification of the nonlinear system represented by a linear in parametric model with nonlinear functions [12,13,14]. The amplitude-dependent autoregressive with exogenous input (ADARX) model is often utilized to establish an input–output relationship of a nonlinear system from its dynamic responses and input forces [15]. To identify the dynamic characteristics of nonlinear structures from the ambient vibration, free vibration, and earthquake response data, this study develops a unified procedure by extending, with some modification, the amplitude-dependent ARX model by Hilbert transform to obtain the function of amplitude. Furthermore, to demonstrate the feasibility of the proposed procedure, the procedure is applied to process measured data for a frame specimen subjected a series of base excitations in shake table test. The specimen showed strong nonlinear dynamic behaviors because the damage occurred during testing.

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Methodology The nonlinear structural system encountered in civil and mechanical engineering can be described by the following equations of motion, Mx + Cx + Kx = f , (1) where M, C and K are mass, damping and stiffness matrices, respectively, and C and K are functions of amplitude of responses, while x and f are displacement and force vectors, respectively. A building may behave nonlinearly when subjected to a large earthquake, and its C and K are functions of amplitude of responses. Consequently, the instantaneous modal parameters of the building change with amplitude of responses in each time step. One can easily judge whether a building is damaged or not in an event from the instantaneous natural frequencies obtained from dynamic responses of the building under the event. The equations of motion in a discrete form are equivalent to I

J

i =1

j =0

y ( t ) = ∑ Φ i ( A ) y ( t − i ) + ∑ Θ j ( A ) f ( t − j ) + a n (t ) ,

(2)

where y(t-i) and f(t-i) are the vectors of measured responses and input forces at time t-i ∆t , respectively; 1/ ∆t is the sampling rate of the measurement, Φi ( A) and Θ j ( A) are matrices of the coefficient functions to be determined in the model, and an (t ) is a vector representing the residual error accommodating the effects of measurement noise, modeling errors and unmeasured disturbances. Equation (2) is known as amplitude-dependent ARX model. The measured displacement responses are used for y(t-i) to ensure that instantaneous modal parameters can be directly identified from Φi ( A) without a systematic error[16]. Following the method proposed by Huang et al. [16], each coefficient function in Φi ( A) and Θ j ( A) is linearly expanded by the so called shapes functions constructed by a set of basis functions, which are polynomials herein, through a moving least-squares approach [17]. Let φkli ( A) and θ kli ( A) denote (k, l) element of Φi ( A) and Θ j ( A) , respectively, and they are expressed as

φkli ( A) = φ ( A)φkli and θ kli ( A) = φ( A)ϑkli

(3) l

where φ( A) = pT ( A)T Ω−1 ( A)Q( A) is a vector of shape functions, Ω( A) = ∑ W (t , tl )p( Al )pT ( Al ) , l =1

Q( A) = [q1 , q 2 ,… , q l ] , ql = W (t , tl )p( Al ) , pT = (1, A, A2 ,…, AN ) ,W is a weight function; A is the amplitude of dynamic responses that would obtained by Hilbert transform ; l is the number of nodal points used for each coefficient function, φkli and ϑkli are two unknown vectors of coefficients for φkli ( A) and θ kli ( A) , respectively. Many weight functions can be used in the above formulation [18]. In this work, the exponential weight function is applied:

 −((tm −t p ) 0.3d )2 | tm − t p | / d ≤ 1 e W tm , t p =  0 | tm − t p | / d > 1  where d is the support of the weight function. A least-squares approach is applied to determine φkli and ϑkli by minimizing

(

)

(4)

N

E = ∑ (a n (tn ))T a n (tn ) .

(5)

n =1

where N is the number of data points to be used in establishing the amplitude-dependent ARX model. Then, one can obtain the following equation through typical and lengthy mathematical manipulation

~ where C = [Φ1 Φ2

~ ~ C = (V T V ) −1V T Y ,

ΦI

Θ0

Θ1

~ ΘJ ] , Y = [y (t1 ) y (t2 )

(6)

y (t N )] ,

Applied Mechanics and Materials Vols. 479-480

 Γ1,t1   Γ1,t T V = 2  Γ1,tN

φi T  11i T φ Φi =  21   i T  φn1

Γ2,t1

Γ I ,t1

Π0,t1

Π1,t1

Γ2,t2

Γ I ,t2

Π0,t2

Π1,t2

Γ2,tN

Γ I ,t N

Π0,tN

Π1,tN

Π J ,t1   Π J ,t2    Π J ,tN  ,

( ) (φ ) ( ) (φ )

(φ )  (φ ) 

( ) (ϑ ) ( ) (ϑ )

(ϑ )  (ϑ ) 

( ) (φ )

( )

( ) (ϑ )

(ϑ )

ϑ j  11j  ϑ21  Θj =   j T φnni   ϑn1 ,

i T 12 i T 22

i T 1n i T 2n

i T n2

Γi ,t = y ( t − i ) ⊗ φ(t )

T

1157

T

T

T

j T 12 j T 22

j T n1

j T 1n ' j T 2 n'

j nn '

 T 

,

T

Π = f ( t − j ) ⊗ φ(t ) and ⊗ denotes the Kronecker product. After , j ,t , determining φkli and substituting them into Eq. (3), one obtains Φi (t ) . Then, like determining modal parameters from an ARX model, one can obtain the instantaneous modal parameters of the nonlinear system from Φi ( A) [19]. Application

Shaking table tests are vital to understanding the dynamic behavior, especially nonlinear behaviors, of structural systems under earthquakes. The National Center for Research on Earthquake Engineering in Taiwan conducted a series of test on reinforced concrete (RC) frames of two columns interconnected by a strong beam to investigate the dynamic behaviors of low-ductility RC columns and to understand their collapse mechanism. Figure 1 shows the dimensions of the typical frame and the test setup. In total, 21 tons of lead ballast were added to the beam to simulate axial loads on first-story columns in a typical four-story building in Taiwan. Accelerometers and linear displacement transducers were installed at appropriate locations to measure acceleration and displacement responses of a specimen. Load cells were installed between the specimen and shaking table to measure base shear forces.

Figure 1. A sketch of experiment setup. The specimen was subjected to a series of base excitation inputs; that is, it was first shaken under white noise input with small amplitude to estimate its modal parameters. The test is denoted as “before-damage” test because the specimen was not damaged. Then, the specimen was subjected to an earthquake input recoded during the 1999 Chi-Chi earthquake in Taiwan. Strong nonlinear behaviors observed during this test, and columns near beam connection were damaged. The test is denoted as “during-earthquake” test. Finally, the specimen was shaken again with a low-level white

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Applied Science and Precision Engineering Innovation

noise input, which is denoted as “after-damage” test. Figure 2 shows the acceleration input and displacement response histories during the earthquake test.

Figure 2. The input acceleration and response histories from during earthquake test. As expected, small variations of instantaneous natural frequencies with time were observed for the cases with white noise input as no further damage occurred under such small input excitation forces. The identified instantaneous natural frequencies in the “before-damage” test are larger than those obtained from the “after-damage” test; the trend is opposite from the identified instantaneous modal damping ratio. The instantaneous natural frequencies from the “during-earthquake” test are close to those identified from the “before-damage” test when t 0.5 , then item I i is a precondition item of item I j , denoted as I i → I j , and I i → I j otherwise. Eample 1. Let the joint probabilities of items I i and I j as Table 1, then we can obtain: γ ij = 1 −

0.02 1 = < 0.5 ⇒ Ii → I j , 0.06 × 0.5 3

γ ji = 1 −

0.46 1 = < 0.5 ⇒ I j → I i 0.5 × 0.94 47

(2)

Table 1. Joint and marginal probabilities of item I i and I j p ( I i = x, I i = y ) x=0 x =1 p( I j = y)

y=0 0.04 0.46 0.50

y =1 0.02 0.48 0.50

p( I i = x) 0.06 0.94 1

Liu’s Improved Nonparametric IRT Theory Based on both nonparametric regression models of Nadaraya (1964) [3] and Watson (1964) [4], Ramsay (1991) proposed his kernel smoothing nonparametric item response theory [5] without the local independence assumption, which can be used for analyzing the item relational structure of each subject. For more sensitive and efficient to estimate the abilities of examinees, Liu (2000, 2013) proposed his new improved kernel smoothing item response theory [6,7] as follows. Definition 2. Liu’s new improved nonparametric IRT [7] Four steps of Liu’s algorithm are described briefly as follows: (i) Estimate the rank of the weighted total score of each examinee [6] n

Ts( L ) = ∑ xis ln i =1

1 + Ri , s = 1,2,...,N 1 − Ri

(3)

where xis = 1 if examinee s answer item I i right, and xis = 0 otherwise, Ri is the correlation of xis and the total score of examinee s. Let T( s ) ∈ {T1 , T2 ,..., TN } , s = 1, 2,..., N , such that

0 ≤ T(1) ≤ T( 2 ) ≤ ... ≤ T( N )

(4)

If Ts = T( rs ) , then rs is the estimated rank of Ts . (ii) Enumerate the quantile of the rank [5] We can obtain the quantiles qs ~ N ( 0,1) , s = 1, 2,..., N from Eq. 5.

r 1 t2 exp( − )dt = s (5) ∫−∞ 2π 2 N +1 (iii). Find kernel function weighted probability of examinee for each item [5] By using the nonparametric regression method of Nadaray and Watson [3, 4], for item i , we can obtain the Gaussian kernel function weighted probability of the examinee with ability θ as follows: qs

Applied Mechanics and Materials Vols. 479-480

N

∑ P
i ( θ ) =

− (q s − θ )2 x 2 . 4 2 N − 0 .4 − (qs − θ )2 exp 2 . 4 2 N − 0 .4

exp

s =1 N

∑ s =1

1195

is

(6)

(iv) Iteratively estimate the ability of individual examinee and its probability for each item Based on Rasch model, Liu (2013) proposed his iteration estimating functions [ 7] as follows:

θs( k+1) = bi = ln

P
i( k) (θs( k) )  1 n  b + ln ∑ i 1− P
(k) (θ( k) ) , s =1,2,..., N, k = 0,1,2,... n i=1  i s 

(7)

1 − Pi 0 , i = 1, 2,..., n , θ s( ) = q s , s = 1, 2,..., N Pi

(8)

Where Pi is the proportion of the subjects correctly answer item I i , − (θ t( k ) − θ s( k ) ) 2 xis 2.42 N −0.4 k k P
i ( ) (θ s( ) ) = t =1N , i = 1, 2,..., n , s = 1, 2,..., N , k = 0,1, 2,... k k − (θ t( ) − θ s( ) ) 2 exp ∑ 2.42 N −0.4 t =1 N

∑ exp

(9)

−(θˆs −θ )2 xis 2.42N−0.4 s=1 ˆ and Pi (θ ) = , i =1,2,..., n N −(θˆs −θ )2 exp ∑ 2.42N−0.4 s=1 N

2

If

1 N  ( k +1) ( k )  θs −θs  < 0.001 then θˆs = θ s( k ) ∑  N s=1

∑exp

(10)

Item Relational Structure theory Based on Liu’s Improved Nonparametric IRT Theory Abovementioned IRS theory can only be used for constructing grouped item relational structures. In this paper, a novel individual examinee item relational structure theory based on Liu’s improved nonparametric IRT theory is proposed as follows. Definition 3. Item relational structure based on Liu’s improved nonparametric IRT Let I1 , I 2 ,..., I n denote n items with binary scores variable, each subject takes n-item test, for each examinee with ability θ , let P ( I i = 0, I j = 1| θ ) be the joint probabilities of item I i wrong and I j correct, P ( I i = 0 | θ ) and P ( I j = 1| θ ) be the marginal probabilities of I i wrong and I j correct, respectively, the ordering relation coefficient of items I i and I j foe examinee θ , γ ij|θ , is defined as below: N

γ ij|θ = 1 −

P ( Ii = 0, I j = 1| θ ) P ( Ii = 0 | θ ) P ( I j = 1| θ )

−(θˆs −θ )2

N

−0.4

= 1−

−(θˆs − θ )2

∑exp 2.42N ∑exp 2.42N (1− x ) x s =1 N

∑exp s =1

−0.4

is

js

s =1

N −(θˆs −θ )2 −(θˆs − θ )2 1 − exp x x js ( ) is ∑ 2.42N −0.4 2.42N −0.4 s =1

(11)

Where θˆs , s = 1, 2,..., N are defined as before. If γ ij|θ > 0.5 , then for examinee θ , item I i is a precondition item of item I j , denoted as I i → I j , and I i → I j otherwise.

Results of a Real Data Set For illustrating the performances of this new method, a calculus test with 15 items was administrated to 50 college students of Asia University in Taiwan. For convenience, only the item relational structures of 5 items of three students with low, moderate, and high abilities are displayed and these 5 items are shown in table 2. Fig. 1 is the all students’ item relational structure generated by rij with

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Applied Science and Precision Engineering Innovation

threshold 0.5. Fig. 2, 3 and 4 are item relational structures generated by rij|θ with threshold 0.5 for three students with low, moderate, and high abilities, respectively. Fig. 2, 3 and 4 show that the item ordering relations of different individual student decrease as the ability increase and those of high ability student do not exist. The new methods can provide more information than before. It can be used to detect the item relational structure for not only the all students but also each individual student. Table 2. Five items of calculas Items

d 2 1. e =? dx

d 2 2. x =? dx

3.

d x e =? dx

4.

d x2 + e2 = ? dx

(

)

5.

d x2 + ex = ? dx

(

)

Summary The well-known Takeya’s IRS theory can only be used to detect the item relational structure of a group of subjects. Parametric IRT theory with item independence assumption can not be used to detect the item relational structure. Liu’s improved nonparametric IRT theory, without above limitation, can be used to detect the item relational structure of each individual subject. In this paper, based on Liu’s improved nonparametric IRT theory, an improved IRS theory is proposed. This new method can be used to detect the item relational structures for not only a group of subjects but also any individual subject. It can provide more information for planning remedial instruction, developing instruction materials, or educational researches than before.

References [1] P.W. Airasian and W.M. Bart: Journal of Education Technology Vol. 5 (1973), pp. 56-60. [2] M. Takeya: Japan Journal of Educational Technology Vol. 5 (1980), pp. 93-103. [3] E. A. Nadaraya: Theory of probability and its applications Vol. 10 (1964), pp. 186-190. [4] G. S. Watson: Sankhya, series A Vol. 26 (1964), pp. 359-372. [5] J. O. Ramsay: Psychometrika Vol. 56 (1991), pp. 611-630. [6] H.C. Liu: Journal of Educational Measurement and Statistics Vol. 8 (2000), pp. 1-22. [7] H.C. Liu: in Proceeding of 2013 Conference of Innovation Technology in Electron, Signal and Communication, National Kaohsiung University of Applied Sciences, May. 31. 2013, pp. 11-12.

Applied Mechanics and Materials Vols. 479-480 (2014) pp 1197-1201 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.1197

AN EXTENSIVE EVALUATION DESIGN APPROACH TO QUALITY FUNCTION DEPLOYMENT Chang-Tzuoh Wu1,a, Nien-Te Liu2,b 1

Department of Industrial Design, Kaohsiung Normal University, Kaohsiung 824, Taiwan 2

Department of Product Design, Shu-Te University, Kaohsiung 824, Taiwan E-mail: [email protected]; [email protected]

Keywords: QFD, Innovative Design, Extension method

Abstract. This research focuses on “matter-element theory and extension method”, with help of this method; HOQ of QFD can be built more comprehensively and efficiently. Quality function deployment was designed to improve quality in product development. The major procedure of QFD is to identify the customers’ needs for the product and then convert into appropriate technical measures to fulfill the needs. According to their characteristics to identify the relevant engineering parameters, the prior engineering parameters will be selected as the key requirements to redesign. This study proposes an innovative design and problem-solving process, based on quality function deployment method with the assistances of extension of matter-element. With the help of extension method, customer requirements (CRs) can be translated into product design attributes more widely and engineering characteristics (ECs) can provide effect assistance for the designer to conceive new products comprehensively and deeply. The proposed design evaluation procedure was developed by integrating weighting coefficients of QFD and optimal criteria of extension method. The innovative design case, wheelchair for the elderly, successfully demonstrates the proposed design approach. Introduction Quality Function Deployment (QFD) is an important quality control theory proposed by the Japanese quality control masters Yoji Akao and Shigeru Mizuno. It was Akao who first realized the value of this approach in 1969 and wanted to utilize its power during the product design stage so that the product design characteristics could be converted into precise quality control points in the manufacturing quality control chart (Hill, 1994). Akao wrote a paper on this new approach in 1972 entitled “New product development and quality assurance deployment system” in the journal of “Standardization and Quality Control”. A Japanese book on QFD edited by Mizuno and Akao, Deployment of the Quality Function, was published in 1978, showing the fast development and wide applications of QFD in Japan. Then, Professor Akao Yoji further to organize and gradually developed into a “customer-oriented” manufacturing and development of the concept. In recent years, the correlative researches of application of QFD have been developed rapidly and widely. As for the methodology, Eco-QFD, QFD integrated with Kano Model and QFD integrated with FMEA have been proposed and applied well. Most of the associated researches provide valuable and valid methods to enhance the effect of QFD. Though these studies applied successfully the proposed methods to solve design problems, they focused on local perspective view only. This article will concentrate on the creativity way of thinking “matter-element theory and extension method”, with the help of this method to assist to translate customer requirements (CRs) into engineering characteristics (ECs) more deeply and widely. Matter-element and extension method, a powerful tool to systematically analyze concrete or intangible products, has been developed by W. Cai in 1983. Extension theory is a course to study the extensibility, extent rules, performing procedure of matter and try to employ to resolve contradictive problems. The extension method was derived from the extension theory that involves the matter-element theory and extension mathematics. The major research subject of extension theory is incompatible problem in the real world. The expression makes qualitative and quantitative analysis mixed, describes the real world further and visually, provides another way of resolving contradictions. Its applications and research have been

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already extended to each field, including business, management, engineering, economics, sociology, strategy, etc. ( Cai, 1994; Cai et al., 1997; Wang & Zhao, 1998; Wang, 2001). Yang (1996) studied on the extensible expression method of concept design knowledge and attempt to formalize the procedure of problem solving by set up the matter-element model to develop unique logic operation method and technology. The rhombus thinking model has also been constructed for the expansion and convergence of conceptual design process. In order to avoid the possible restriction on creative problem solving procedure, extension of matter-element based on concept model has been introduced in this paper to improve the efficiency and extent of concept evolutions. We make use of extensibility of matter-element to exchange the descriptions of design problems and solutions into creative fields. Extensible QFD The major procedure of QFD is to identify the customers’ needs for the product and then convert into appropriate technical measures to fulfill the needs based on the company’s competitive priorities. The priorities of product characteristics can be obtained by translating important technical measures into product characteristics. According to their characteristics to identify the relevant engineering parameters, the prior engineering parameters will be selected as the key requirements to redesign. Throughout the procedure, the creativity activities which matter-element theory and extension method can be imported or expanded mainly in two parts, 1. The course of translating customers’ needs into product design attributes (technical measures). 2. The course of identifying corresponding product defect or the parameters which needed to be improved The use of extensibility of matter-element and extension method for the translation of product design attributes and engineering properties can provide effect assistance for the designer to conceive new products comprehensively and deeply. Matter-element Analysis and Extension Method The extensibility of matter-element is the basis of dealing with incompatible problem. It includes divergence, expansibility, conjugate inside the matters and relativity of matter-element. Divergence is to study the possible routes of outward extension, it includes the same matter of matter-element, the same characteristics of matter-element, the measure of matter-element, the same matter and characteristics of matter-element, the same characteristics and measure of matter-element, the same matter and measure of matter-element. Extensibility studies plausibility, integration and separability of matter-element. As shown in Fig.1, rhombus thinking model constructed by matter-element symbols expresses the divergence and convergence in simple way. R1=(N1,c1,v1) R2=(N2,c2,v2) R=(N,c,v) ……

R’1=(N’1,c’1,v’1) …… R’m=(N’m,c’m,v’m)

Rm=(Nm,cm,vm) Fig.1 Rhombus thinking model The detail description of matter-element and extension method will not present. The structure of matter can be described more completely and the nature of variation of the development of matters can also be revealed more deeply while we explore the matter from the point of view of systemic, substance, dynamic and opposition. Therefore, we proposed corresponding four pairs of opposing concepts such as real/imaginary, soft/hard, potential/significant and positive/negative to describe the composition of matters called conjugate of matters. From the eight points of views to study the matter, is the conjugate properties of matter. Conjugated-pair method is the method which applied the conjugate properties and matter-element transformation to solve the design problems.

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While solving design problems based on QFD, diversity and creativity, the advantages of “extenics” method will be imported by implementing the extensibility of matter-element, event-element and relationship-element. Thus, the solution will not be limited to standard solutions but be inspired. Procedure for Improve Product Design Attributes. Throughout the procedure of QFD, the extensibility of matter-element and extension method can be introduced into the course of improving product design attributes (technical measures) based on product defects found from customers’ voice. The following are the steps of creative activities which matter-element theory and extension method be imported or expanded. STEP1: express the existing products N into an n-dimensional matter-element STEP2: Obtain the products’ functional defects or the shortcomings lead to customer dissatisfaction by the customer voice (complain). STEP 3: Transformation on the defects sub-matter-elements Ri (i=1,2,…,m). Treat the replacement, addition/deletion, expansion/ contraction transformation to the iso-matter-element but the addition/deletion, expansion/contraction transformation to the distinct matter-element. That is, either separately or integrated transform sub-matter-elements for each shortcoming Ri (i=1,2,…,m) TiRi=Ri* (i=1,2,…,m) (1) After performing the matter element transformation, a new n-dimensional matter-element R* which contained the revised sub-matter-elements will be occurred. The revised sub-matter-elements obtained by transforming the matter-element with shortcomings to a better one. Corresponding to the elements of R, a sequence of new products will occur. Engineering Design Parameters Transfer Procedure. Throughout the procedure of QFD, the extensibility of matter-element and extension method can be used to assist to translate product functional requirements into engineering design parameters. The following are the steps of creative activities which matter-element theory and extension method be imported or expanded. STEP 1：Determine the set of functional characteristics of product requirements and corresponding values of the functional characteristic elements.

{c

function

} = {c } and {(c f

f

, v f )}

(2) STEP 2：Derive and confirm the “hypostatic characteristics” from “functional characteristics” and then the corresponding “certain characteristics” will also be derived and confirmed based on the implication series. STEP 3：Solve design problems by using conjugate properties and transformation of the elements of “certain characteristics”. According to the requirements of potential function of product, we modify the concepts of design through transformation processes and thus the new product N possesses the required potential function. Besides, considering the negative value of functional part of product N, negative part of N ng(c)N, and the concept can be modified by transform operation to reduce negative effects. STEP 4：Repeat the above process to achieve a number of programs of product N to develop and expand the concepts of product. Use basic transformations on the matter-element and the transform operation to achieve a variety of new product ideas. Following is the operation, Design Evaluation. Rhombus thinking model, as shown in Fig.1, is a creative thinking way which divergency first and convergency later. The convergent part of Rhombus thinking model is the procedure of evaluation. By using the extensive properties of matter-element, many concept design solutions can be obtained. These possible solutions should be checked or evaluated to be screened out optimal solutions. Wnag and Zhao (1998) indicated that “Authenticity message discriminant method”, “Fuzzy convergency” are feasible extensive decision-making method. In this paper, an evaluation method has been developed based on HOQ of QFD. In HOQ, ECs are a list of relevant design characteristics. The absolute importance of ECs can be computed by integrating both the final importance of CRs and the relationship matrix. The corresponding weighting coefficients can be determined based on the weighting values of absolute importance of ECs.

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Design Case In this research, design case “wheelchair”, the auxiliary instrument for the elderly is adapt to explain and verify feasibility of the proposed innovative procedure. The proposed approach, QFD integrated with extension method, has been used to investigate the users’ needs and relative functional requirements. Determine the customers’ requirements. Two parts in this stage of research, first, obtained the needs of wheelchair by interviewing the elderly and translate to product design attributes, and then in the second part, the questionnaire checked for the elderly to pick the important requirements. In this study, survey candidates are the elderly in nursing home, and in order to avoid some problems are ignored, the nurse aides with long experience are included in addition. Gathering respondents’ views, users’ requirements are 1.Operation to be effort, 2. Comfortable, 3. Easy to keep clean, 4.Flexibility to adjust, 5. Sturdy and durable, 6.Convenience to get in (off) wheelchair, 7. Additional functions. Integrated QFD with Extenics. Usually, ECs are determined by divergent thinking of “focus group interview”. The extension and completeness can be ensured by using “rhombus thinking model” to assist the establishment of HOQ. First, we build the transformation model by extending tree: We can translate product functional requirements into product design attributes as shown in table 1. Table 1. Product design attributes Level 1 Level 2 Level 3 Form Specifications Weight Size Driving mechanism Basic Mechanism function Expanded mechanism Materials Safety Maintenance Structural strength Flexible adjustment Comfort Body dimensions ergonomic Operation type Handling Brake system Improve Product Design Attributes. Take the design attribute, driving mechanism, for example. The corresponding engineering parameters are “object stability”, “durability of moving parts”, “ease of use” and “harmful side effects”. By decomposition transformation, the major matter- element can be decomposed into subordinate matter-elements. Corresponding to the engineering parameter for “ease of use”, we separate wheel from the operating mechanism. Then, by replacement transformation, belt or gear systems will use to replace the traditional operation system. Transformation of Engineering Design Parameters. While we solve design problems by using conjugate property, positive/negative, “harmful side effects” is the engineering parameter what we concerned. Considering the negative value of functional part of product N, negative part of N ng(c)N, the concept can be modified by transform operation to reduce negative effects. For example, we try to transform “harmful side effects” to “beneficial side effects”. For the elderly, “poor blood circulation” seems to be the “harmful side effect” while long time in a wheelchair. Thus, a wave–like motion for pedal has been designed to avoid “poor blood circulation”. A linkage mechanism has been used to connect the wheel and pedal so that the wave–like motion for pedal will be occurred while moving the wheelchair. Design Evaluation. For this design case, the priorities and weighting percentages of ECs are determined as 1.Ergonomics dimensions (20.1%) 2.Material of seat (18.3%) 3.Flexible adjustment

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(14.6%) 4.Brake system (9.6%) 5.Operation type (9.1%) 6.Driving mechanism (8.8%). The others have been eliminated. Therefore, the priorities and corresponding weighting coefficients are also determined. The corresponding weighting coefficients vector is α= .201 .183 . 146 . 096 . 091 . 088 Conclusions This study proposes an innovative design and problem-solving process, based on quality function deployment method with the assistances of extension of matter-element. In this research, we focus on the creativity way of thinking “matter-element theory and extension method”, with the help of this method to assist to translate customer requirements (CRs) into product design attributes and engineering characteristics (ECs) can provide effect assistance for the designer to conceive new products comprehensively and deeply. The concrete result includes, 1. Assess possibility and advantage to combine quality function deployment and the extension of matter-elements. 2. Proposed the procedures for improving product design attributes and engineering design parameters transformation. 3. Proposed the procedures for evaluation of extension of matter-elements. The priorities and evaluation indices can be determined based on HOQ of QFD. An innovative design case, wheelchair for the elderly, successfully demonstrates that the proposed design process is feasible and efficient. Acknowledgments This work is supported by the National Science Council, Taiwan, NSC 95-2221-E-017-006 References [1]

B. Yan and W. Liu, “Indications of extension of matter-element based on concept model,” Journal of Dalian Maritime University, 29, Suppl. Aug., (2003). [2] C. Y. Yang and B. He, “Application of Extension Method In New Product Concept,” System Engineering Theory and Practice, 19(3), (1999), p.120 [3] C. Y. Yang, “Event-element and Its Application,” System Engineering Theory and Practice, 18(2), (1998), p.80 [4] L. K. Chan, M. L. Wu, “A systematic approach to quality function deployment with a full illustrative example,” The international journal of management science, Omega 33, (2005), p.119 [5] W. L. Wang and Y. W. Zhao, “Explore the Extensive Decision-Making of Mechanical Intelligent CAD”, System Engineering Theory and Practice, 18(2), (1998), p.114 [6] W. Cai: Matter-Element Model and Its Application, Science and Technology Literature Press, Beijing, (1994). [7] W. Cai, C. Y. Yang and W. C. Lin: Extensive Engineering Method, Science Press, Beijing, (1997). [8] Y. Akao, “New product development and quality assurance deployment system,” (in Japanese). Standardisation and Quality Control 25 (4), (1972), p.243 [9] Y. Akao: Quality Function Deployment: Integrating Customer Requirements into Product Design. Cambridge, MA: Productivity Press. (1990) [10] Y. W. Zhao, “The new Method of Concept Design Based on Multistage Rhombus Thinking Model,” Chinese Mechanical Engineering, June, (2000), p.684.

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A Framework of Fit Status of Organizational Innovation: Based on the Typology of Organizational Lag Jing Li1, a, Chun-sheng Shi1,b 1

School of Economics and Management, Harbin Institute of Technology, China a

[email protected], [email protected]

Keywords: organizational lag, innovation fit, organizational innovation, administrative innovation, technical innovation

Abstract： ：This paper discusses the fit between different types of organizational innovation (OI) : administrative innovation (AI) and technical innovation (TI). As different type of innovation requires different organizational skills, resource allocation and environment conditions, there always exists organizational lag, which changes inversely with organization performance (OP). Based on the dimensions of OI from different theories, this paper selected the rate and the speed of innovation to describe organizational lag and proposed “organizational lag vector” to represent the fit status of innovation. Organizational lag vector has two characteristics: absolute value and direction. After comparing the referential organizations with different OP, the absolute value could be divided into three categories, then combined with four directions of organization lag vector, this paper described 12 types of the fit status of OI as well as implicated organization actions. Introduction Innovation is becoming a core competence in various industries in modern society. Since the concept of innovation has ever been proposed, there are plenty of definitions of innovation in existing literature from different perspectives. In general, innovation is conceived to be an outcome - what innovation produces as well as a process - how innovation operates[1] . There are different dimensions of organizational innovation (OI), such as the types, the stages and other characteristics. Scholars have pointed that organizational performance (OP) is the results of the compatibility of different types of innovation, stages of innovation or some other innovation characteristics (such as the rate and the speed)[2]. The concept of fit is rooted in the natural selection theory, which leads to the survive of the best-performing organizations[3]. Fit in the fields of organization theory is associated with high performance[4]. Emphasis on either dimension of OI might generate organizational lag which may reduce OP. Though the amounts of scholars and studies on innovation are constantly growing[5], there is still a lack of an overall framework to explore the fit of organizational innovation. The development in this area could help achieve a much better and more adequate understanding of this complex phenomenon. Dimensions of OI There are several strains of the dimensions of organizational innovation: dual-core theory, ambidextrous theory, radicalness of innovation theory and so on. The dimensions of OI from different perspectives are shown in Fig. 1.

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dual-core theory: types of innovation[6]

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administrative innovation

organizational structure and administrative process

technical innovation

products, services and production process technologies

product innovation

new products or services

process innovation

new elements introduced into an organization’s production or service operations

radical innovation

fundamental or disruptive changes, departures clearly from existing practices

[7]

types of innovation

radical model: Radicalness of innovation[8]

incremental innovation initiation stage ambidextrous model: stages of innovation [9]

characteristics of innovation adoption [1,10]

dual-core theory: types of innovation[6]

changes departures less from existing practices problem perception, information gathering, attitude formation and evaluation, resource allocation

implementation stage

modifications of activities in innovation and organization, the initial and continued use of innovation lead to a routine in organization

rate of innovation

t h e number of innovations adopted from all available innovations within a certain period, reflects the extent of innovativeness

speed of innovation

timing of innovation

breadth of innovation

equipment, systems, products and services

depth of innovation

importance, degree of influence and effects on long-term profitability

policies,

processes,

Fig. 1. The dimensions of OI from different perspectives The Measure of Fit - Organizational Lag Organizational Lag Vector. Organizational lag is defined as “discrepancy in the rate at which new technical and administrative ideas are implemented in an organization”[12]. Damanpour pointed the degree of organizational lag is negatively correlated with OP and used organizational lag as the empirical measure of “fit” - the absolute difference between the relative measures of AI and TI in a given period[6]. However, organizational lag not only has its own value but also directions as its important characteristics. Put simply, even two organizations A and B have the equivalent values of organizational lag, there might be two cases: organization A with higher level of AI and lower lever of TI compared to organization B, while the other case is conversely. To distinguish organization lag efficiently, we choose the rate and the speed of innovation as two dimensions to measure the fit between AI and TI. To differentiate such cases above more specifically, we defined the organizational lag (the empirical measure of “fit”) as a vector with two dimensions: rate lag and speed lag and two characteristics as well: absolute value and direction as shown in Fig. 2.

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rate broad

AI

lag TI

speed

narrow low

fast

Fig. 2. Organization lag vector The Absolute Value of Organizational Lag. We use r to represent the absolute value of the innovation lag vector. If the coordinates of AI and TI are ( xra , ysa ) and ( xrt , yst ) respectively, then r can be calculated by Eq. 1:

r = f ( x, y ) = f [( xra , ysa ), ( xrt , yst ) = ( xra − xrt ) 2 + ( ysa − yst ) 2 .

(1)

xra and xrt represent the rate of AI and TI, while ysa and yst represent the speed of AI and TI respectively. For the evaluated organizations in a certain industry, we might list all the innovations in a given period and find out the amount of innovations each organization adopted; the speed of innovation could be calculated by the sum of the difference of each innovation adopted by the evaluated organization compared to the first adopted innovation in the research sample[7]. After we get the value of the rate and speed of both AI and TI, the lag value could be calculated by Eq.1. The Direction of Organizational Lag. The form of fit could be understood as profile deviation “allows researchers to specify an ideal profile and to demonstrate that adherence to such a profile has systematic implications for effectiveness”[13], which means the fit depends on the variables similarity of evaluated organizations to the high performers in an organizational field[14]. Fig. 3 shows the innovation fit forms adapted by the organizational structure-organization performance fit form proposed by Drazin and Ven de Ven[15]. In order to classify the degree of organizational lag, firstly we choose the organizations which rank top 10% of organizational performance within the organizations pool as the reference and make their r value as the standard of high fit. Then organizations rank between top 10% to 60 are regarded as medium fit, the last 40% is low fit.

B: medium fit, r1 r2

low fit, the rate of TI is much higher while the speed is much lower than AI, which has a negative effect on OP

0 < r ≤ r1

high fit between AI and TI, which promotes high OP

r1 < r ≤ r2

medium fit, the rate and the speed of TI are both lower than AI, but still in a proper extent to keep OP

r > r2

low fit, the rate and the speed of TI are both much lower than AI, which has a negative effect on OP

0 < r ≤ r1

high fit between AI and TI, which promotes high OP

r1 < r ≤ r2

medium fit, the rate of TI is lower while the speed is higher than AI, but both in a proper extent to keep OP

r > r2

low fit, the rate of TI is much lower while the speed is much higher than AI, which has a negative effect on OP

Implicated Organizational Actions Based on the typology of innovation fit, the organizations could make targeted strategies and employ management practice accordingly. For those organizations with high fit, they can maintain the present status and keep AI and TI activities coordinated well. For the organizations labeled “medium fit” and “low fit”, firstly they should distinguish their innovation status: the degree and the direction of the organizational lag. Generally speaking, those “medium fit” organizations could enhance both AI and TI activities and adjust the rate and speed of innovation, trying not to widen the existing gap. The organizations with “low fit” especially need to focus on one type of organizational innovation to reduce the gap and finally to improve their OP.

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Acknowledgement The research work was supported by National Natural Science Foundation of China under Grant No. 71272176 and Doctoral Foundation Program of the Ministry of Education of China under Grant No. 20112302110062. References [1] F. Damanpour; S. Gopalakrishnan. Theories of Organizational Structure and Innovation Adoption: the Role of Environmental Change. Journal of Engineering and Technology Management.Vol. 15 (1998), p.1-24 [2] E. Brynjolfsson; L. M. Hitt. Computing Productivity: Firm-level Evidence. The Review of Economics and Statistics. Vol. 85, No.4(2003), p.793-808, [3] R. Drazin; A. H. Van de Ven. Alternative Forms of Fit in Contingency Theory. Administrative Science Quarterly.Vol. 30, No. 4 (1985), p.514-539 [4] L.Donaldson. Strategy and Structural Adjustment to Regain Ft and Performance: In Defense of Contingency Theory. Journal of Management Studies. Vol.24, No.1 (1987), p.1–24 [5] M.M. Crossan; M. Apaydin. A Multi-Dimensional Framework of Organizational Innovation: A Systematic Review of the Literature. Journal of Management Studies. Vol. 47, No.6(2010), p.1154-1190 [6] F. Damanpour; W.M. Even. Organizational Innovation and Performance: the Problem of Organizational lag. Administrative Science Quarterly. Vol. 29(1984), p.392-409 [7] F. Damanpour; S. Gopalakrishnan. The Dynamics of the Adoption of Product and Process Innovations in Organizations. Journal of Management Studies. Vol. 38, No. 1 (2001), p.45-65 [8] R.D. Dewar; J.E. Dutton. The Adoption of Radical and Incremental Innovations: An Empirical Analysis. Management Science. Vol. 32 (1986), p.1422-1433 [9] R.B Ducan. The Ambidextrous Organization: Designing Dual Structures for Innovation. The Management of Organization. Vol. 1 (1976), p.167-188 [10] F. Damanpour; S. Gopalakrishnan.The Dynamics of the Adoption of Product and Process Innovations in Organizations. Journal of Management Studies. Vol. 38, No.1 (2011), p.45-65 [11] Li-Min Chuang; Chun-Chu Liu; Wen-Chia Tsai; Chien-Min Huang. Towards an Analytical Framework of Organizational Innovation in the Service Industry. African Journal of Business Management.Vol. 4, No.5 (2010), p.790-799 [12] W. M. Evan. Organizational Lag. Human organizations.Vol. 25 (1966), p.51-53 [13] N.Venkatraman. The Concept of Fit in Strategy Research: toward Verbal and Statistical Correspondence. Academy of Management Review. Vol. 14, No.3 (1989), p.423-444 [14] H. W. Volberda; N. van der Weerdt; E. Verwaal; M. Stienstra; A. J. Verdu. Contingency Fit, Institutional fit, and Firm Performance: a Metafit Approach to Organization-Environment Relationships. Organization Science.Vol. 23, No. 4 (2012), p.1040-1054 [15] R. Drazin; A. H. Van de Ven. Alternative Forms of Fit in Contingency Theory. Administrative Science Quarterly. Vol. 30, No.4 (1985), p.514-539

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Research on Human Resource Strategy under Customer Demand Using System Dynamics for the Thin Film Sputtering Target Material Industry Tian-Syung Lan1, a, *, Chun-Hsiung Lan2, b, Pin-Chang Chen1, c and Kai-Chi Chuang1, d 1

Department of Information Management, Yu Da University, Miaoli County 361, Taiwan

2

Department of Business Administration, Hsing Wu Institute of Technology, New Taipei City 244, Taiwan a

[email protected], [email protected], [email protected], [email protected]

Keywords: human resource, back-propagation network, system dynamics, target industry

Abstract This study integrates the forecast capacity and superiority of dynamic simulation of back-propagation network (BPN) and system dynamics, thereby enabling the target industries to formulate coping strategies and to make adjustment in both production capabilities and manpower. The main purpose of this study is to assess and confirm what the most effective policy is for production and human resources. The forecasting result of this study indicates that Correlation and R-squared values reach 0.99852 and 0.994961 respectively after a training of BPN. Certainly, BPN serves as an effective method of forecasting target sales. Finally, the forecast value of the next three years is worked out through situational simulation of complex production models in system dynamics. The final result of this study shows that the optimum manpower should be 10 workers for the years 2011-2013, as well as the projected result will be a rise in production yield of up to 2.54%. It is the most profitable scenario for the company. Introduction The increase in demand for smart phones and tablet personal computers push up the demand for active matrix organic light emitting diodes (AMOLED) and the development of coating. The thin film sputtering process is the most important in the production of semiconductor and panel. The common feature of semiconductor and panel industries is that their demand in market is very much uncertain, and that there has been more supply than demand due to very fast economic vicissitudes throughout the world, thereby affecting the upstream suppliers of target industries [1]. It is very important for upstream suppliers of materials to plan production ahead to meet the instant needs of massive and short-term deliveries in optoelectronic industries. This study uses target industries as an example in selecting the sales history of the past seven years, and applies the back-propagation network (BPN) for the purpose of forecasting the sale of chrome target for the years 2011-2013. This study sets up a causal feedback loop diagram, a stock-flow diagram and a simulation result through Vensim software. This study also chooses technicians’ experience, how much the employees identify with the company, and the customers’ perceptions of products’ quality as the soft variables, and checks the production information of the case company before undertaking various dynamic simulation through the system model established. The main purpose of this study is to assess and confirm what the most effective policy is for production and human resources. Back-Propagation Network Alyuda NeuroIntelligence 2.1, the BPN software, is used in order to set up model of sales forecast of target for the case company over the years 2011-2013 periods. First, the input layer and the output layer have to be defined; second, the sales figures for the years 2004-2010, the BPN software and the necessary network parameters are all keyed in so as to establish a forecasting

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model, of which the forecasting capability will be tested before the establishment of the proposed model [2]. Sales data for the years 2004-2010 indicates the monthly figures as shown in Table 1. BPN software is input for learning and training. This study achieves the best effect when the learning rate is 0.1. With the increase of learning cycle, the values of BPN will be adjusted, so that the difference between target value and the output of BPN will become smaller and smaller [3]. Once such difference almost no longer changes, the BPN training is stabilized; namely, completed, after 20000 learning cycles. Input and output variables are reflected between -1 and 1 [4]. The neural network architecture parameters are indicated as shown in Table 2. Table 1. Monthly sales for the years 2004-2010 2004 2005 2006 2007 2008 2009 2010 1.26 1.89 2.61 2.25 1.35 1.08 0.81 January 0.84 1.26 1.74 1.5 0.9 0.72 0.54 February 2.1 3.15 4.53 3.75 2.25 1.8 1.35 March 0.56 0.84 1.16 1 0.6 0.48 0.36 April 0.42 0.63 0.87 0.75 0.45 0.36 0.27 May 0.42 0.63 0.87 0.75 0.45 0.36 0.27 June 1.68 2.52 3.48 3 1.8 1.44 1.08 July 1.68 2.52 3.48 3 1.8 1.44 1.08 August 4 2.4 1.92 1.44 September 2.24 3.36 4.64 1.12 1.68 2.32 2 1.2 0.96 0.72 October 2 1.2 0.96 0.72 November 1.12 1.68 2.32 1 0.6 0.48 0.36 December 0.56 0.84 1.16 14 21 29 25 15 12 9 Total Table 2. Neural network architecture parameters Parameter Setting 12 neurons Input Layer 8 neurons Hidden Layer 1 neuron Output Layer 20000 Learning Cycles 0.1 Learning Rate System Dynamics Basically, this is the method of simulating the manpower demand of the company concerned for the next three years (2011-2013) based upon the Vensim software of system dynamics [5]. The two steps to go through including: first, determining which of the variables will be the level; second, incorporating the relevant causal variables progressively into the stock-flow diagram; finally, a system of dynamic simulation will then come out [6]. The Causal Feedback Loop Diagram and the Stock-Flow Diagram are described as follows:

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Fig. 1 Causal Feedback Loop Diagram Fig.1 starts with the inner loop. When the factory accumulates lots of products yet to be manufactured, goods being produced in the production line also increase. As the quantity of finished products increase, goods delivered also increase; in the meantime, higher delivered quantity also implies the increase in orders properly processed, and the decrease of goods yet to be produced. If the quantity of delivered products increase, the manpower required for production will also increase; thus leading to the increase of manpower gap. As manpower gap gets larger, the workload of employees will also be heavier; thus leading to the decrease in training and education of manpower. But technicians will be more experienced through the exposure of employees’ education and training, thus improving the production quality and the production yield and enhance the customers’ perceptions of products quality. Once more and more customers endorse the quality of products of a certain company, order placed with the company will increase accordingly; thereby enabling the company not only to adjust higher the projected orders for the next few months, but also increase the stock for materials [7].

Fig. 2 Stock-Flow Diagram

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Fig.2 starts with the running the company’s sales figures for the past years through the BPN, the monthly sales forecast for the years 2011-2013 can be found in Table 4, altogether 35 monthly figures which excluding the first month is used as the period of preparation. The simulation is ignited by inputting preliminary forecast of products quantity, which will be revised by the change in customers’ perceptions of products quality to become the secondary forecast, the latter forecast will be closer to reality [8]. The 36 projected sales figures will be matched by quantity of confirmed finished products. Such difference will again be adjusted and revised, so as to ensure that production quantity will be the same as the quantity of products delivered [9]. Total manpower refers to the maximum manpower required for the manufacturing of goods. Temporary man power will be an important basis for the company to adjust its man power in order to cut cost when orders are affected by seasonal factors or reasons beyond its control. When the manpower gap widens, increase in workload will affect the implementation of education and training program of its work force, resulting in the reduction of production yield. The alteration of technicians’ experience can also tell the impact of technicians’ quality upon the production yield. The sense of identity of employees and workers will also affect the morale of work force. The rate of alteration in the quality of products is very useful in assessing the fluctuation of product qualities over the years [10]. Forecasting Result After repeated training and testing the correlation and the R-squared of fifty sets, the average Correlation and the R-squared values of this BPN model are 0.99852 and 0.994961 respectively, as shown in Table 3. It means that the model proposed by this study is highly relevant. Table 4 shows that the gap between the forecasting sales of target for the years 2011-2013 and the actual sales of 12 tons after the financial crisis of the year 2009 is very little. It indicates that the future business environment of the target industries will remain very difficult. Table 3. Correlation and R-squared Target Output AE 17.857143 18.019282 0.209511 Mean 6.530067 0.413499 Std. Dev. 6.770283 9 10.22153 0.023635 Min 29 28.956847 1.22153 Max Correlation: 0.99852 R-squared: 0.994961 Table 4. Sales forecast for the years 2011-2013 2011 2012 2013 0.96 1.17 1.08 January 0.64 0.78 0.72 February 1.6 1.95 1.8 March 0.44 0.52 0.48 April 0.33 0.39 0.36 May 0.33 0.39 0.36 June 1.32 1.52 1.44 July 1.32 1.56 1.44 August 1.76 2.08 1.92 September 0.88 1.04 0.96 October 0.88 1.04 0.96 November 0.44 0.52 0.48 December 11.235 12.972 12.079 Total

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Dynamic Simulation Based upon the manpower statistics of this company and general perception of target industries, this study conducts a simulation test of its manpower planning by considering such elements as production yield, wages, pressure from work and the sense of identity by workers of the company, and sought to find out which will be the best human resources policy between 2 and 16 workers. Policy 1 assumes that current workforce is 2, initial temporary worker is 0, monthly payment for current employee is 28,000 dollar/month ($/m), and 25,000 $/m for temporary employee, and the simulation period is 12 months. The result shows that temporary employees are increased to 10 to ensure punctual delivery of goods. Higher wages for permanent worker is reduced because of lower wages for temporary workers, but total cost goes up due to low productivity of temporary workers. The disadvantages include: manpower cost hikes by $9,389 in the 35th month, sharp decrease of production yield, decline of competitive edge, low morale and increased possibility of worksite accident induced by excessive workload and reduced education and training. Worse still, this policy may even mean the loss of orders to other companies, and the eventual bankruptcy of this company. This policy is no good. Policy 2 assumes that current workforce is 8, temporary worker 0, while other things are being equal. While total manpower is 8, customers’ perceptions of the quality of products will be higher than 80% in the 22nd month. Lighter workload and better education and training of employees tend to decrease the probability of having to repeat the same production process due to inferior quality and high competitiveness in terms of employees’ mindset and products quality. Policy 3 assumes that current workforce is 10, temporary worker 0, while other things are being equal. While total manpower is 10, cost for permanent manpower increases a lot and wages surpasses Policy 2 by $56,000 in the 22nd month. The advantages include: production yield may be higher than Policy 2 by 2.54% in the 22nd month; workers will be able to produce goods of excellent quality in a zero-worry environment, thereby increasing market share and company’s profit through words of mouth among customers. Indeed, this will be the most conducive to the sustainable operation of this business. Furthermore, in a situation of employing 12-16 workers, the result will be the same as Policy 3, except that a rapid increase of wages indicates excessive supply of manpower. This scenario, therefore, will not be discussed. Conclusion Pursuant to the orders forecast through BPN, the 2nd quarter of each year is usually an off season and the 3rd Quarter is usually the best season for business. The forecast by dynamic simulation indicates a few things: Policy 2 employs 8 persons, and it is highly competitive in terms of workers’ psychology, quality of products and the saving of wages up to $56,000 in contrast to the scenario of employing 10. But there is one thing unique in high tech industries: every 1% in the improvement of production yield means a multiple percentage of growth in profit. So its optimum manpower should be 10 workers for the years 2011-2013, then the projected result will be a rise in production yield of up to 2.54%, this is also the most profitable scenario for the company. This study suggests that further study may be applied to other industries facing the same uncertain future by taking advantage of the precise forecast capability of BPN and the dynamic simulation of system dynamics. Future researchers may add more items for consideration, such as trade volume and percentage of profit, so as to implement a more sophisticated simulation in terms of business policy. The results of this study confirm that the goals for the organizations are always the same: increased profit, better competitive edge and sustainable business operation. Hopefully, experiences accumulated can be passed to next generation and the proposed model can be applied to different industries, so as to ensure maximum output and minimum input, and to strengthen the sustainable competitiveness of businesses.

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Acknowledgements The authors would like to thank Mr. York Tsai, Mrs. Lillian Lai, Mr. Benny Chu and Mr. Tommy Huang at Polema S.A. Taiwan Branch who kindly provided the data and suggestions to improve this work. References [1]. C.H. Tam, S.C. Lee, S.H. Chang, T.P. Tang, H.H. Ho and H.Y. Bor: Ceramics Int. 35(2) (2009) 565. [2]. S.Z. Hashim, M.O. Tokhi and I.Z. Darus: Proc. of the IEEE Int. Conf. on Mech. (2004) 171. [3]. T.Y. Pai, T.J. Wan, S.T. Hsu, T.C. Chang, Y.P. Tsai, C.Y. Lin, H.C. Su and L.F. Yu: Comp. and Chem. Eng. 33(7) (2009) 1272. [4]. C. Purna, Y.R. Nayak, R. Satyaji and K.P. Sudheer: Water Res. Mgmt. 20 (2006) 77. [5]. F. Ceresia: The 27th Int. Conf. of the Sys. Dyn. Soc. Albuquerque, New Mexico, USA (2009). [6]. D.E. Rumelhart, G.E. Hinton and R.J. Williams: Paral. Dist. Proc. 1 (1986) 318. [7]. B. Widrow and M.E. Hoff, Jr.: IRE WESCON Conv. Rcd. (1960) 96. [8]. M.C. Jackson: Sys. Thinking. John Wiley & Sons, Chichester, U.K. (2003). [9]. E.F. Wolstenholme: Sys. Enquity. John Wiley & Sons, Chichester, U.K. (1994). [10]. K. Warren: Compet. Str. Dyn. London Business School, U.K. (2002).

Applied Mechanics and Materials Vols. 479-480 (2014) pp 1213-1217 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.479-480.1213

Using RSSI Simple Localization Method to Implement the Context-aware and Social Recommendation System Mu-Yen Chen1, a, Ming-Ni Wu 1, b, Hsien-En Lin 1, c 1

National Taichung University of Science and Technology, Taiwan

a

[email protected], [email protected], [email protected]

Keywords: Apriori, Context-Awareness, Indoor-Localization, RFID, Recommendation

Abstract. This study integrates the concept of context-awareness with association algorithms and social media to establish the Context-aware and Social Recommendation System (CASRS). The Simple RSSI Indoor Localization Module (SRILM) locates the user position; integrating SRILM with Apriori Recommendation Module (ARM) provides effective recommended product information. The Social Media Recommendation Module (SMRM) connects to user’s social relations, so that the effectiveness for users to gain product information is greatly enhanced. This study develops the system based on actual context. Introduction Take the retail industry as an example. Retailers can analyze the massive transaction records to define the undiscovered associations between each commodity and classify the type of consumers for each related commodity. The consumer psychology and habit of each type of consumer can then be defined. Retailers can use such association to arrange different marketing strategies aiming for different types of consumers. It is found that consumers [2], in physical shopping environments, are strongly dependent on information present in such physical environments. Consumers will use the handheld PDA to read the RFID tag on commodities via RFID reader; PDA will then provide and recommend relevant information of the commodities to consumers as to enhance the visibility of information for consumers in a physical shopping environment. The purpose of this study is to integrate the concept of context-awareness, association algorithms, and social media to establish the Context-aware and Social Recommendation System (CASRS). The systems comprise the following concepts and technologies listed in Table 1 and will be illustrated by module system. Through integrating the following modules, one complete context-aware and social recommendation system is established. Table 1 Modules of the Established System in the Present Study Concept of the System Required Technology Name of Modules Establishing a context-aware Simple Indoor Positioning Method based on the signal strength of RFID shopping environment positioning mechanism Recommendation based on Apriori Recommendation based on Association Rules Algorithms Association Rules Taking FACEBOOK® as an example; Connecting to social media connecting to API to obtain user to simulate Virtual Social social networking Networking

Simple RSSI Indoor Localization Module (SRILM) Apriori Recommendation Module (ARM) Social Media Recommendation Module; SMRM

Literature review RFID positioning mechanism has been extensively studied in recent years. In 2000, Hightower and Borriello proposed the SpotON Indoor Positioning Technology [3].The record of these RSSI was then used as data to analyze and infer the positions of the tags. There are varieties of positioning methods that are based on RSSI and each method has distinctive advantages and

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disadvantages. Take LANDMARC positioning mechanism [1].The cause of the shortcoming is that LANDMARC positioning requires all three pieces of hardware equipment including RFID Reader, Reference Tag, and Tracking Tag to maintain indoor positioning accuracy [7]. There are four major models of data mining: Data Classification, Data Association, Data Clustering and Sequential Patterning Mining[6]. The Association Rule was proposed by Agrawal et al. in 1994 [4]. The main purpose is to find the relation between commodities from massive transaction databases. Classic association rule is applied in the Market Basket Analysis (MBA); the relations of commodities in customers’ baskets are analyzed to understand their buying habits and to help the enterprises indentify the mostly commonly purchased commodity groups. Among community media, the persisting concerning center must be that virtual community has replaced the mode of traditional sociality. Bickart in his 2001 research found that [5], when consumers face consumer decision-making, they will inquire and search via virtual community for the opinions of other consumers with similar shopping experience as the basis for decision-making. On the other hand, some consumers will take the initiative to provide relevant shopping experience in virtual community for shopping information exchange behavior on SNSs [8]. Architectural framework of a CASRS system Context-aware and Social Recommendation System (CASRS) are mainly made of multi-device platform, RFID, Software as a Service (SaaS) concept, and community media layers. Hence consumers, that is to say the users, can quickly access or share shopping information. The following provides a brief description of the conceptual deployment of the system, as shown in Fig. 1; and the primary user context are defined as follows.

Fig. 1 Context-aware and Social Recommendation system Provide consumers with ubiquitous recommended context of shopping information via computing technology Consumers will identify himself/herself through multi-platform interface operating system and RFID labels. Through Apriori relational rule algorithm, compute the product information of a desired consumer, and provide the information to consumer via multi-platform interface. In this way, consumers can obtain omnipresent commodity recommending information via entity shopping environment. Provide consumers with community media applications Consumers may be connected to virtual SNSs via multi-platform interface, may understand shopping information about others, or recommend / share the information of purchased products to others. System implementation and testing Simple RSSI Indoor Localization Module (SRILM) The RFID localization module of this system is mainly based on SpotON indoor positioning technology provided by scholars Hightower and Borriello in 2000 and is based on RSSI signal [3].

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It uses RSSI as principle for positioning technology, and signal strength between RFID reader and label to judge the distance between the label and the reader. However, directivity parameter is not included in this method for evaluation. Active RFID, for example, comparing to passive RFID, has greater advantage in detecting distance range. We define its reading range in a simple way here. As long as user holds the label, and within the detection range of RFID reader, we can conclude that the label is within reading range; and can meet the simple positioning requirements for consumer location area of this study. Calculation algorithm steps of Simple RSSI Indoor Localization Module (SRILM). This study assumes that n users are in the installation environment, = [ , , ⋯ ⋯ , ]; and every user holds a RFID label representing his own identity expressed as . In addition, in the deployment environment, reader m is represented as = [ , ,⋯⋯, ]. has a certain signal coverage and is expressed as . When label is detected by reader and signal is looped back, it means that label is within signal coverage of reader . In other words, location of is . This study uses the process as follows to explain simple RFID indoor localization. Step.1: The signal intensity of label in the environment being detected by a reader, can be represented as a vector, such as =[ , ,⋯⋯, ], where is the reader signal strength value against . A bigger value in represents is closer to the corresponding reader. of signal intensity in label . It represents the Step.2: Find the maximum value corresponding reader covering range when position is at . Step.3: If has same maximum value at several locations, it means that label is located is located at the junction of more than one area. between multiple reader coverage; and Apriori Recommendation Module (ARM) Association rule must meet the two pre-set parameter values: minimum support and minimum confidence. The product of the total number of transactions in the minimum support and database is the minimum support count.L An itemset contains k items is called k-itemset and L is used to represent the itemset of the collection of all large k-itemsets. Confidence(A→B) =

( ∪ )

(1)

( )

The algorithm is a step-by-step approach to identify the relationship of the database items. When the most items appear and the number of occurrences is the highest group, the combination of this group is the main rules of these data with important parameters as the maximum itemset size, minimum support and minimum probability. Probability that is conditional probability refers to the accuracy of this rule. The equation of counting the possibility that B happened in condition A is as Eq. 1 below.

Shelf 1 Recommended List

Min Sup.

Transaction records

Apriori

Recommended Rules

Classification By shelf

User 1

Shelf 2 Recommended List

. . . Min Conf.

User 2

. . .

Shelf n Recommended List User n

Fig. 2 Recommend Process of Apriori Algorithm

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In this study, the association rules between commodities are mainly analyzed from purchasing records of customers, so Apriori algorithm is adopted to calculate the relationship between commodities to recommend the calculated results to customers and the system will recommend the result by the rules after the operation to consumers. The system adopts SQL Server Analysis Service, SSAS of Microsoft SQL Server on Apriori operation with the operation process as Fig. 2: Step.1: Enter Transaction Records to the database to filter out the information to be calculated. Step.2: Before performing Apriori operation, the two parameters of the minimum support and minimum confidence shall be inputted by the management personnel. Step.3: Process Apriori operation on the filtered information and have the management personnel identify the better association rules by adjusting the minimum support and minimum confidence. Step.4: After the execution of Apriori algorithm, save the recommendation rules as the basis of recommending goods to customers. Step.5: Classify the results of recommend rules according to the shelves categories of goods. Step.6: The recommendation list of goods categories generated after classification will be stored based on the shelves categories of goods. System Test In order to prove the feasibility of the system architecture framework, prototyping is adopted and the overall system is completed by actual programming construction. Kiosk: requires Windows XP or above versions. Android Smart phone / Tablet PC: requires Android version 2.2 or above version. Apriori algorithm: requires built-in Business Intelligence Analysis Services in SQL Server 2008 R2 for operations. (Server): Windows 7 64-bit. (Database): SQL Server2008 R2. The study adopts Active Reader and Active Tag, as well as smart phones based on Android 4.0 as shown in Fig. 3. Users log in CASRS via mobile phones and the system will recommend products based on data registered in users’ mobile phones and the computing of Apriori, and then users will receive the information on their mobile phones. Then through Readers deployed in the environment, Tags held by users will be detected to retrieve the RSSI signal information. Locations of users will be determined through the SRILM positioning mechanism. The system will then send out Apriori featured products information according to users’ location, and will give notices as shown in Fig. 4.

Fig. 3 User context

Fig. 4 CASRS recommendation

Conclusion This study proposes an integrated Apriori relation rules that can be applied to product recommendation, an integrated RFID positioning technology that can be used in mobile recommendation and multi-platform presentation, and a complete context-aware environment that can be used in physical store environment. Customers may acquire real-time product information and “featured products” information through handheld smart devices and Kiosks. The list of

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"Featured Products" is obtained by computing the relationships between products using Apriori algorithm in data mining; RFID Active Readers deployed in the environment use SRILM positioning mechanism to keep track of the location of users with Tag. The system will screen out product recommendation information based on users’ location and present the information on the smart handheld devices for users' reference. Limitations of this study will be explained in two areas. The SRILM positioning mechanism can be compared with other positioning mechanism in terms of their application, but not in terms of their positioning accuracy. We can compare their implementation costs, building complexity, and maintenance easiness in application level. Such comparison can effectively prove the value of the positioning mechanism. This study presents a theoretical framework that can effectively reduce the building cost of RFID positioning mechanism. However, since no actual implementation has been conducted in the industry, there might be problems undiscovered. Acknowledgments The authors thank the support of National Scientific Council (NSC) of the Republic of China (ROC) to this work under Grant No. NSC-101-2622-E-025-002-CC3 and NSC-102-2622-E-025-001-CC3. The authors also gratefully acknowledge the Editor and anonymous reviewers for their valuable comments and constructive suggestions. References [1] L.M. Ni, Y. Liu, Y.C. Lau and A.P. Patil; LANDMARC: indoor location sensing using active RFID. Wireless networks, 10(6), p.701-710, (2004). [2] T. Kowatsch & W. Maass; In-store consumer behavior: How mobile recommendation agents influence usage intentions, product purchases, and store preferences, Computers in Human Behavior, 26(4), p.697–704, (2010). [3] J. Hightower & G. Borriello; SpotON: An Indoor 3D Location Sensing Technology Based on RF Signal Strength, University of Washington CSE Technical Report, (2000). [4] R. Agrawal & R. Srikan; Fast algorithms for mining association rules, Proceedings of the 20th international conference on very large data bases, p.478-499, (1994). [5] R. Gross & A. Acquisti; Information revelation and privacy in online social networks, Proceedings of WPES’05, p.71-80, (2005). [6] J. Han, M. Kamber & J. Pei; Data mining: concepts and techniques. Morgan kaufmann, (2001). [7] P. Prasithsangaree , P. Krishnamurthy and P. K. Chrysanthis; On Indoor Position Location with Wireless LANs , Proceedings of the 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communication, Vol.2, p.720-724, (2002). [8] S. Morton; The state-of-the-art of research in management support systems. The Information Systems Research Challenge. Harvard Business School Press, Boston, MA, p. 13–41, (1984).

Keywords Index 1064nm Nd:YAG Laser 2D Haar Discrete Wavelet Transform 3D Color Image Encryption 3D Image Encryption 3SAIHT 5-Axis Machine Tools

143 911 948 958 870 333

A Abdomen ABWR Accelerated Corrosion Test Accelerated Weathering Accelerometer Account Theft ACF Cutting Process Active Islanding Detection Method Activity Level Assessment Activity Recognition Actuator Adam Adjacent Measurements Administrative Innovation Advanced Boiling Water Reactor (ABWR) Aggregator Aging Offshore Platform AILC Air Film Al2O3 Aluminum Film Aluminum Oxide AMCA Test Chamber Amplitude-Dependent ARX Analysis Anesthetic Depth Angle of Arrival (AOA) Annular Fins Heat Transfer Annular Slot Anti-Slip Scheme Antireflection Appendicitis Apriori Arduino Area under the ROC Curve

445 548 13 1119 406, 818, 938 916 353 580 818 818 324 338, 396 1185 1202 1051 978 1185 737 380 35 96 80 401 1155 1081 468 996 294 289 742 105 445 1213 661 445

Artificial Neural Network (ANN) Artificial Photosynthesis Assessment Asymmetric Atomic Layer Deposition Attention Attenuated Total-Internal Reflections (ATR) Attitude Control Authentication Auto-Tuning Automatic Cell Classification Automatic Optical Inspection Axial-Flow Fan

445 100 1185 324 80 517 682 753 963 268 491 636 279

B B-Spline Back-Off Time Back Propagation (BP) Neural Network Back-Propagation Network Balance Barrier Layers Battery Energy Calculations Bayesian Network (BN) Beam-Column Joint Bevel Gear Biaxial Piezoelectric Actuated Stage Bicycle Suspension System Binary Offset Carrier (BOC) Binomial Theorem Bio-Heat Transfer Bio-Hydrogen Production Bio-Signal Sensor Biomedical Signal Bispectrum Blade Blind Signature Block Matching (BM) Bluetooth Body Model Body Sway BOP Braces Breathing Frequency

729 973 585 1207 617 80 503 906 1170 369 692, 697 338 865 855 496 451 137, 713 468 468 319 968 883 1018 475 406 314 1170 457

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Bridge Management Bridge-Vehicle System Brushless Motor Buckling Buckling Moment Buckypaper BWR Bypass Clearance

1180 254 427 1175 1133 20, 110 543 192

C Camless Engine Carbon Nanotube (CN) CBR Cell Characterization Center-Based Structure Centrifuge Shaking Table Test Child Development Chinese Chess Game Circular Saw Blade CLAHE Clamp Circuit Climbing-Stair Clinical Scoring System Closed Forms Cloud Computing Clustering Algorithm CMAC CMOS-Camera CO Sensor CO2 Inhalation CO2 Reduction Coarse Sun Sensor Coastal Regions Cogging Force Cognitive Radio (CR) Coherence Phase Bandwidth (CPB) Cold-Formed Sections Collapse Detection Color Segmentation Competing Risk Model Composite Electroplating Films Composite Material Compound Optical Film Compression Set Computational Fluid Dynamics (CFD) Computational Integral Imaging Computational Workload Distribution

360 35, 264 1001 595 763 1139 480, 517 773 289 870 535 304 445 823 1023, 1081 788 612 137 702 627 100 753 1097 197 778, 1027 878 1144 1180 839 1066 60 687 155 55 279, 401 948 805

Computer-Assisted Language Learning (CALL) Computer Crime Computerized Numerical Control (CNC) Concentration Polarization Concrete Conductivity Connection Test Construction Interface Contact Lenses Context-Awareness Contour Positioning System Convergent-Divergent Microchannel Conveyor Air Bearing Corrosion Risk Coupled-Inductor Coupled Type Planetary Gear Reducer Crack Control Cross-Shaped Core Current-Reused Cyborg Cyclic Loading Test

928 923 396 373 1115 40 1101 1160 166 1213 503 220 380 1101 535 309 1115 197 1010 672 421

D Damage Damping Isolator Dark Fermentation Data Acquisition DC Servo Motor Dead Space Dean Vortices Decoding Deep Foundation Deep-Ponding Irrigation Defect Examination Definite Integrals Degradation Deployment Depot Stent Depth-Converted EIA Design Deterioration Condition Deterioration of External Wall Dielectric Property Diesel Engine Different Foundation Levels Differential Evolution

1185 244 451 503 768 627 220 719 1109 1086 636 823 1119 646 225 958 575, 672 1124 1105 3 570 1109 989

Applied Mechanics and Materials Vols. 479-480 Differentiation Term by Term Theorem Differentiation with Respect to a Parameter Direct Adaptive Control Direct Heating within Die Direct Normal Irradiance Discrete Logarithm Problem Discrete-Time Switched System Discrete Wavelet Transform (DWT) Disk Piezoelectric Actuator Disk-Type Motor Displacement Distance Estimation Distributed Routing Distribution System Disturbance Rejection DMX512 Protocol Double CAN Bus Double Layer Heat Sink Double Points Double-Walled Carbon Nanotubes Drillship Drought Periods Introduction Drug-Eluting Stent Drug Reservoir Dual-Phase Lag Mode Ductility Durability Dye-Sensitized Solar Cell Dynamic Dynamic Analysis Dynamic Risk Management Dynamic Scaling Mutation Dynamic Traffic Circumstances Dynamic Voltage Scaling

800 823 612 25, 30 595 963 983 508 692 390 697, 708 503 783 210, 559 934 1032 641 411 259 121 314 1086 225 225 496 1175 1119 69 385 365 1097 989 778 901

E E-Health E-Identity Document E-Payment E-Ticket Earth Horizon Sensor Earthquake Loading ECG EDR Effective Rainfall Efficiency EGS

713 1038 1038 1038 753 1109 457 457 1086 284 284

Eigenanalysis Electric Scooter Electric Vehicle (EV) Electric Wheelchair Electricity Generation Electrode Electromagnetic Electromagnetic Valve Electron-Beam Vapor Deposition Electronic Circuits Electrostatic Actuator Elliptic Curve Cryptography Elman Neural Network (ENN) Embankments Embedded Micro-Voids Embedded System Emergency Alarms Empirical Mode Decomposition (EMD) Energy Absorption Energy-Dissipated Building Energy Dissipation Energy Dissipation Capacity Energy Efficiency Energy Efficient Routing Energy Harvester Energy Minimization English Learning Enhance A* Searching Algorithm Environmental Equal Channel Angular Extrusion Equation of Motion Equipment Failure Analysis Expert System Etching Eurocode Evaluation Algorithm Event-Related Cross Phase Coherence Event-Related Spectral Power Exoskeleton Expression Generation Extension Method

1221 530 365 978 304 553 324 524 360 96 1180 431 968 570 239 155 656 1180 486 599 1149 1170 1175 788 783 524 839 928 773 1081 181 385 1001 69, 105 1144 773 517 480 672 834 1197

F Face Recognition FCS Fe Doped TiO2 Feature Extraction Feature Localization

883 641 100 834 834

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Feature Point Detection Fermentation Fiber Bragg Grating (FBG) Field Emission Field-Programmable Gate Array (FPGA) Financial Benefit Fingerprint Finite Element (FE) Finite Element Analysis (FEA)

Finite Element Method (FEM) Finned Heat Sink Flexible Job-Shop Scheduling Problem Flexible Substrates Flow Pattern Flow Separation Fluence Flux Density Force Control Forging Formant Feature FRAPTRAN Frequency Analysis Friction Friction Coefficient Friction Effect Friction Factor FRP Sheet Fuel Cell (FC) Fuzzy Delphi Method Fuzzy Inference Method Fuzzy Inverse Kinematic Mapping Fuzzy Linguistic Fuzzy Logic Control Fuzzy Sliding Mode Control

883 319 687 264 607 553 810 181 187, 197, 202, 289, 329, 360, 369, 390, 524, 599, 1144 230, 254 192 989 80 279 220 143 360 742 369 1006 543 1045 8 421 268 249 1170 934 1128 1128 729 1128 565 742

G Ga-Doped Zinc Oxide (GZO) Gait Analysis Gait Pattern Gantry Crane Gate Location Gaussian Mixture Model Gaussian Random Process Gear Mechanism Gel Abrasive

40 475 475 314 126 1006 254 234 86

Generalized Inverse Genetic Algorithm (GA) Geneva Mechanism Geographic Information System (GIS) Geometric Imperfections Geometric Series Geometric Space Transformation Gesture Recognition Giant Magnetostrictive Sensors Gibbs Sampling Global Navigation Satellite System (GNSS) Global Optimization Global Warming GMM-Formant Gold Nanoparticles (GNP) Google Apps Engine Google Cloud SQL Google Earth’s Elevation Profile Grain Size Graphic Processing Units (GPUs) Gray Scale Mask Green Energy Management Grid-Connected Inverter Ground Vibration Guiding Vane Gyroscope

729 202 259 1056 1133 849 724 938 667 906 865 126 553 1006 702 1081 1081 503 8 805 155 1032 580 239 401 406

H Hard Real-Time Systems Harmonic Heat Distribution Heat Exchanger Heat Pipe Heat Transfer

901 210 143 284 284 192, 249, 274, 411 Heterodyne Interferometry (HI) 682 Hidden Ceiling Fan 279 Hidden Markov Model (HMM) 938 Hierarchical Management 763 High Capacity Dry Storage System 421 High Concentration Photovoltaic 595 Module High-Rise Housing 1124 High-Speed Trains 239 High Voltage Gain 535 HMI 343 Home Networking 656 Home Security 661

Applied Mechanics and Materials Vols. 479-480 Hot Forging Housing Human Computer Communication Human-Computer Interaction (HCI) Human Demonstration Human Resource Hybrid ABS Hybrid Fuel Hybrid Fusion Hybrid Method Hybrid Peer to Peer Network Hydrocarbons Hydrodynamic Stability Hydrogen Heat Mass Transfer Hydrogen Storage Hydrothermal Hymn Histogram Hyperbolic Functions Hysteresis Hysteretic Nonlinearity

25, 30 1071 938 938 617 1207 622 575 1027 431 968 100 45 294 75, 100 64 943 849 1149 348, 667

I III-V Group Solar Cell Image Contrast Enhancement Image Correction Image Fusion Image Processing Immune Algorithm Impact Impinging Jet In-Line Fan Inclined Surface Machining Indoor-Localization Inertia Effect Inference Infinite Series Forms Influence Distance Information Dissemination Inhale-Return Phenomenon Injection Molding Innovation Fit Innovation Management Innovative Design Instantaneous Modal Parameters Integer Frequency Offset Integrals Integration Term by Term Theorem

595 870 834 870 491, 636 861 599 274 401 333 1213 268 1001 800, 828 239 973 279 126 1202 1038 1197 1155 878 849 849

Intelligent Fuzzy Controller Intelligent Gripper Intelligent System Inter-Trial Phase Locking Interaction between Adjacent Structures Intermittent Gas Jet Internet of Things (IOT) Interrupted - Pulsating Flow Interval Time-Varying Delay Inverted Pendulum IPv6 ISO/IEC 17025 Item Relational Structure Theory Item Response Theory Iterative Computing Method ITO

1223 934 742 565 480 1109 91 661 373 983 406 953 149 1193 1193 1066 64

K Karhunen-Loéve Expansion Key Clinical Attributes Key Distribution Kinematic Analysis Kinematic Design KNN Knowledge Acquisition

254 225 651 234 309 906 1001

L LabVIEW Language Anxiety Laplace Transform LAPUR6 Laser Laser Drilling Laser Measurement Laser Percussion Drilling Latent Power Theorem Lateral Bending Lateral Load Lead-Free Piezoceramic Leaf Spring Leaflet Thickness Learning Scheme Leibniz Differential Rule Leisure Benefits Leisure Internal Motivation License-Plate Location Life Cycle Assessment LifeMOD®

692 928 496 548 299 91 708 299 309 1133 1115 3 687 463 889 823 795 795 911 1071 338

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Light Emitting Diode (LED) Limiting Flux Behavior Linear Quadratic Regulator Linear Taper Liquefaction Load Balancing Load Capacity Low-Noise Amplifier Low Power Low Speed Target LRTS

1032 373 202 133 1076, 1139 805 380 1014 513, 1010, 1014 844 210

M m-Health Magnetic Abrasive Finishing Magnetic Field Magnetic Gear Magnetic Gear Set Magneto-Rheological Fluid Magnetorheological Brake Magnetostatic Field Analysis Manufacturing System Maple Masking Probability Maximum Likelihood-Estimation (MLE) Maximum Power Point Tracking (MPPT) Measurement Uncertainty MEMS Metal Hydride Micro-Beam Micro-Channel Micro-Controller Unit Micro Machining Micro Metal Forming Microstructure Microwave Absorption Missing Data Mixed-Integer Non-Linear Programming (MINLP) Mixing Index Mobile Agent Mobile-C Mobile Device Communication Mobile Payment Mobile Robot Modal Strain Energy

137, 713 86 230, 299 230 187 416 622 390 1023 800, 823, 828, 849, 855 1066 170, 897 570 149 431 294 431 411 607 299 8 115, 427 20 906 805 220 758 1081 968 1038 773 1185

Modal Testing Moderating Variable Modified Discretization Modulated Fiber Laser Module Temperature MOPSO-CD Morphological Analysis Morpholoy Motion Control Motion Planning Moving Camera Calibration Moving Least-Squares MR Brake Multi-Agent System Multi-Axis Multi-Hop Broadcast Multibody Multilayer Perceptron (MLP) Multiple Function Acoustic Horns Multiple Improper Integrals Multiple Perspectives Multiple Poles Muscle Activity MWCNT

289 795 496 91 595 810 491 64 607 729 170, 897 1155 416 1081 396 973 338 491 329 828 1038 416, 622 475 20, 110

N Nano-Titanium Nano Titanium Dioxide Nanoindentation Nanoindentation Test Natural Frequency Spectra NC Program Transform Near Space Net Present Value Network Security Neural Muscular Drive NI Motion Controller Card NIMBY Conflict Index NIMBY Curves NIMBY Phenomenon Nitrile-Butadiene Rubber (NBR) Node under Test (NUT) Nonlinear Nonlinear System Nonlinear Vibration Nonlocal Elasticity Theory Nonparametric Item Response Theory Norm Distance

50 50 60 96 13 333 844 590 923 627 768 1128 1128 1128 55 953 861 612 121 121 1193 486

Applied Mechanics and Materials Vols. 479-480 Nuclear Power Plant (NPP) Numbered Music Notation

1076 943

O Object Tracking Octa-Band Offset Offshore Crane Offshore Structure OMR Optical Design Optical Fiber Sensor (OFS) Optical Property Optical Scale Optimization Optimum Local Threshold Organizational Innovation Organizational Lag Orthogonal Frequency Division Multiplexing (OFDM) Orthogonal Particle Swarm Optimization Oscillating Flow Oscillation Move Oscillatory Connections Output Feedback Control

897 436 259 314 314 943 166 687 844 692 166, 202, 861 1027 1202 1202 878 353 192 274 517 612, 889

P Partial Derivatives Partial Least-Square Regression Particle Segment OperationMachine Assignment Payback Year PC-Based Controller PCB Performance Analysis Permanent Magnet Transverse Flux Linear Synchronous (PMTFLSM) Persistence Method PET Phase Noise Phasor Measurement Phishing Phishing Email Photo Diode Photoelectric Properties Photonic Crystal (PC) Photophysical Properties Photoplethysmography

800 667 989 590 768 524 575 197 585 80 513, 1010 530 916 916 724 50 133 115 137, 486

Photovoltaic (PV) Photovoltaic (PV) System Physical-Parameter Identification Physicochemical Analysis Physiological Signal Monitoring PID Controller Piezoelectric Piezoelectric Actuator Piezoelectric Buzzer Piezoelectric Energy Harvester Piezoelectric Property Pile Bending Moment Pile Foundation Pile-to-Pilecap Connection Pin-Fin Heat Sink Pinwheel Tasks Planar Inverted-F Antenna Plane Fitting Planetary Ball Mill Planning Tools Plasma Clean Plasticity Poling Poly(3-hexylthiophene) Polymer Liquid Films Polymeric Material Polyurethane Prosthetic Heart Valve Pond Irrigation System Porosity Porous Material Portal Power-Aware Management Power-Aware Scheduling Power Quality (PQ) Power System Stability Power System Stabilizer Precision Machining Preload Adjusting Structure Pressure Principal Component Analysis (PCA) Prism Assembly Probabilistic Scheduling Program Configuration Propagation Proposed Program Pseudo-Inverse Filter Pseudo-Single-Degree-of-Freedom PSO Algorithm

1225 590 570, 585 1149 1119 1081 768 324 697 692 348 3 1139 1139 1115 274 901 436 839 35 646 353 86 3 115 45 1119 463 1086 380 380 1056 758 901 559 530 530 268 692 380 166 682 1160 805 239 1109 948 1149 737

1226

Applied Science and Precision Engineering Innovation

Pull-in Voltage Pulse Duration PV Generation System

431 143 559

Q QFD QRS Characteristic Series Quadruped Walking Machine Quaternion

1197 457 385 170, 897

R Radial Basis Function Network Radial Basis Function Neural Network Radio Frequency Identification (RFID) Radio Interference Random Material Properties Rapid Prototype Rare Earth Material Rational Functions Ray-Tracing RBR Recommendation RecurDyn Reduction Tube Redundant Robot Reflective Surface Reinforced Concrete (RC) Beam Reinforced Concrete Apartment Reinforced Concrete Containment Vessel (RCCV) Reliability Renewable Energy Renewable Energy Generation System Renovation Work Resistance Heating Resistivity Resonance Respiratory Signal Response Spectrum Response Surface Approximation Response Surface Method (RSM) Reverse Monte Carlo RGB-D Sensor Rheological Property Ribbed Rectangular Convergent/Divergent Channel Robot Arm

570 585 1213 996 121, 254 401 427 855 161 1001 1213 365 599 729 299 1133 1124 1051 1066 553 580 1124 25, 30 13 289 457, 627 1045 126 353 844 677 86 249 768

Robot Suit Robotic Systems Robust Exponential Stability Robustness Root-Finding Rossby Number Routing Protocol

672 737 983 1027 170 45 1018

S Safe Basin Erosion Safety Scaled-Down Model Scatternet Formation Schedule Risk Management Secondary Optical Element Secret Sharing Seebeck Coefficient Seed Seismic Hazard Analysis Seismic Qualification Seismic Rehabilitation Seismic Testing Self-Certified Signcryption SEM Semi-Supervisor Learning Sense of Happiness Sensor Calibration Sensor Network Serious Leisure Traits Shaking Table Shaking Table Test Shallow Foundation Signal Tracking Silicon Nanostructures Silicon Nanowire Similarity Measuring Simulation Simultaneous Localization and Mapping (SLAM) Singular Points Singularity Robustness Sintering Sinusoidal Walls Site Response Analysis Site Selection Sizing Optimization Skin Aging Sliding Window of Measurements Slope Angle

215 672 1051 1018 1160 161 978 110 69 1061 1045 1170 1051 968 110 943 795 677 747 795 1051 1045 1109 865 105 264 174 365, 1160 677 259 729 3, 35 220 1076 1056 289 143 737 503

Applied Mechanics and Materials Vols. 479-480 Slope Stability SMA Beam Small Aircraft Small Displacement Small Scale Effect Smart Cards Smart Grid (SG) Smart Handsets Smart Meter Smart NOx Sensor Smart Pixel Mapping SNMPv3 Sobel Mask Operator Soft Die Software as a Service Sol-Gel Solar Energy Solar Farm Solar Orientation Azimuth Solar Panel Cleaning System Solar Power Generation Forecasting Solar/Gas Somatosensory Stimulation Song Classification Spectral Analysis Spectrum Sensing Spent Fuel Pool Spray Coating Squeeze Film Damping Effect Stability Stainless Steel (SS) Steel Grid Shear Wall Stent Fatigue Life Step-Stress Accelerated Degradation Testing Stepping Stepping Motor Drive Stereo Matching Stiffness Stirling Stochastic Bifurcation Stochastic Chao Strain Hardening Strength Prediction Stress Corrosion Cracking (SCC) Stresses String Structural Health Monitoring (SHM)

1056 215 641 682 121 963 651, 747 436 651 719 958 953 911 30 1023 40 724 553 724 565 585 575 475 1006 719 778 543 702 431 548 1097 1175 225 55 697 607 839 1144 575 348 215 60 1144 1097 319 708 1149, 1180

Sub-Threshold Supervisory Control Support Vector Machine (SVM) Surface Area Surface Permanent Magnet Surface Plasmon Resonance (SPR) Surface Tension Sway Measurement SWCNT Switching Signal Design System Dynamics (SD) System Security

1227 475 661 810 64 427 682 702 406 75 983 1086, 1207 923

T Taguchi Method Taguchi's Parameter Method Target Industry Technical Innovation Telehealth Tennis Test Test Bench Model Test Node (TN) Testbed TFT-LCD Thermal Performance Comparison Thermoelectric Thin-Walled Tubes Threshold Thrust Tile Time Difference of Arrival (TDOA) Time Ton Time-Varying System TiO Titanium Alloy Toluene Tooth Surface Structure Top-Seat Flange Cleat Connection Torque Ripple Torsion Torsional Rigidity Townhouse TRACE Train Value Equation Transmission Coefficient Transmission Hub Transmittance

166, 181 197 1207 1202 713 708 149 202 953 747 353 249 110 599 878 197 1105 996 697 889 69 181 702 427 1144 187 75 1133 1105 543 309 20 234 40

1228

Applied Science and Precision Engineering Innovation

Tree-Based Routing Triangular Segmentation Trusted Third Party Tuning Range Two-Reflector Solar Concentrator

783 834 651 513, 1010 161

U Ultra-High Vacuum Ion Beam Sputter Ultra Wide Band (UWB) Ultrafiltation Ultrasonic Ultrasonic Welding Uncertain Duration United States Institute for Theatre Technology (USITT) Unscented Kalman Filter Urban Areas URL UV Spectroradiometer

50 1014 373 451 329 1160 1032 753 1101 916 149

V Valve Height VANET Vehicle Hill Climbing Ability Vehicle-to-Grid (V2G) VerilogHDL Vibration Vibration Stimulation Video Matching Virtual COM Port Driver Virtual Controller Virtual Machine Tool Virtual Reality (VR) Virtualization Viscoelastic VLSI Volcano Voltage Controlled Oscillator Voltage-Lift Capacitor

463 973 503 978 508 244 475 174 1023 343 343 343 1023 244 508 1061 513, 1010 535

W Walking Mechanism Wastewater Sewer System Waveguide Crossing Wearable Sensor Web Server Weight Monitoring Weld Test

385 1128 133 818 1023 268 1101

Welded Steel Frame Wetting Property Wheelchair Whole-Body Motion Imitation Wireless Wireless RF Interface Wireless Sensor Network (WSN) Without Substrate Worm Wrapper Local Search

1101 105 304 617 656 773 646, 758, 763, 783, 788 155 923 989

X X-Ray Diffraction (XRD)

20

Z Ziegler-Nichols Method ZigBee ZnO

934 1032, 1180 69

Authors Index A Abd Majid, M.Z. Abidov, A. Afzal, A. Ahn, S.W.

553 100 220 249

B Bae, G.T. bin Ahmad Muezzin, F.N.

35 411

C Cai, F.Z. Cao, Y.C. Chan, C.T. Chan, S.Y. Chan, V.K.Y. Chang, C.C. Chang, C.I. Chang, C.J. Chang, C.W. Chang, H.C. Chang, H.Y. Chang, R.C. Chang, S.B. Chang, S.J. Chang, T.P. Chang, W.F. Chang, W.H. Chang, W.Y. Chang, Y.C. Chang, Y.J. Chang, Y.N. Chang, Y.P. Chang, Y.S. Chang, Y.T. Chang, Y.Y. Chao, Y.W. Chau, H.H.K. Chau, Y.F. Chen, B.H. Chen, C. Chen, C.H. Chen, C.K. Chen, C.S.

565 202 818 724 1038 8 953 279 1006, 1061 627 805, 1097, 1101, 1124 80 396 324 121, 254 436 742 580, 585 1014 91, 299 724 839 1071 996 517 75 768 1032 75 906 636 457 559, 590, 612

Chen, C.T. Chen, C.W. Chen, C.Y. Chen, D.C. Chen, D.R. Chen, F.C. Chen, H. Chen, H.S. Chen, J. Chen, J.D. Chen, J.H. Chen, K.N. Chen, K.Y. Chen, L.A. Chen, L.C. Chen, L.H. Chen, M.Y. Chen, P.C. Chen, P.H. Chen, R.S. Chen, S.H. Chen, S.J. Chen, S.L. Chen, S.W. Chen, T. Chen, T.C. Chen, T.H. Chen, W.N. Chen, W.W. Chen, Y.C. Chen, Y.D. Chen, Y.J. Chen, Y.L. Chen, Y.S. Chen, Y.Y. Chen, Z.S. Cheng, A. Cheng, F.H. Cheng, F.S. Cheng, H.C. Cheng, H.L. Cheng, H.Y. Cheng, J.K. Cheng, P.J. Cheng, T.C.

682 758, 818 105, 1105 181 901 385 844 373 324 983 69, 115 126, 289 548 234 69, 115 923 1213 1207 524 133, 983 548 916, 923 795, 1023 543, 1086 1139 627 50, 264 607 1185 155, 161, 385, 1051 187 155, 239, 524 788, 1081 30, 901 1023 617 13 839 25, 30 166 724 333, 343, 436 365 45, 319, 496 264

1230 Cheng, T.J. Cheng, X.Z. Cheng, Y.J. Cheng, Y.S. Cheong, W.K. Cheung, L.F. Chew, K.W. Chi, C.T. Chi, C.W. Chiang, C.C. Chiang, C.J. Chien, C.J. Chien, C.S. Chiu, S.Y. Cho, D. Cho, S.J. Choi, B.C. Choi, B.Y. Choi, W.H. Chou, C.C. Chou, C.Y. Chou, Y.C. Chou, Y.T. Chu, T.L. Chu, Y. Chuang, C.N. Chuang, H.J. Chuang, K.C. Chueh, T.H. Chung, C.C. Chung, C.H. Chung, C.Y. Chung, W.Y.

Applied Science and Precision Engineering Innovation 210, 559 844 401 25 411 747 503 677 329 60, 687 719 737 457 989 1109 948, 958 468 35 656 719 480, 517 105, 1081 451 13, 1051 682, 1032 737 590 1207 651 1010 646 773 1139

D Dat, L.V. Deng, J.H. Ding, I.J. Doan, V.D. Du, R.X. Du, X.P.

360 369 166, 1006 530 599 844

F Fan, W.Q. Fang, W.C. Feng, C.C. Fu, L.M. Fu, T.C. Fu, Y.S.

1027 60 889 595 421 64

G Gau, W.H. Ge, G. Goi, B.M. Guo, J.H. Guo, M.M. Guo, Y.G.

289 215 503 768 1027 938

H Han, C.C. Han, G. Han, K. Han, T.H. He, K. Her, S.C. Ho, C.C. Ho, C.Y. Ho, M.C. Ho, Y.H. Hong, C.M. Hong, Y.C. Hou, H.T. Hsia, S.Y. Hsiao, H.M. Hsiao, R.S. Hsieh, C. Hsieh, C.F. Hsieh, C.H. Hsieh, C.W. Hsieh, J.C. Hsieh, J.F. Hsieh, L.C. Hsieh, M.H. Hsieh, M.Y. Hsieh, T.S. Hsieh, W.L. Hsieh, Y.C. Hsiung, P.A. Hsu, C. Hsu, C.H. Hsu, C.T. Hsu, F.H. Hsu, F.T. Hsu, J.C. Hsu, J.M. Hsu, K.C. Hsu, K.S.

729 406 1109 1010 599 96 91, 299 590 480, 517 1001 570 390 80 451 225 646 480 508 353 805 284 259 309 1076 279 687, 834 590 861, 1014 805 1023 8, 463, 535, 989 210, 559, 590 916, 923 524 91, 299 973 64 396

Applied Mechanics and Materials Vols. 479-480 Hsu, L.P. Hsu, M.T. Hsu, S.C. Hsu, S.Y. Hsu, W.S. Hsu, W.T. Hsu, Y.T. Hu, C.S. Huang, B.H. Huang, B.W. Huang, C. Huang, C.C. Huang, C.F. Huang, C.H. Huang, C.I. Huang, C.S. Huang, G.D. Huang, H.M. Huang, J.L. Huang, K.Y. Huang, M.C. Huang, P.H. Huang, P.W. Huang, S.C. Huang, S.J. Huang, S.M. Huang, S.Y. Huang, T. Huang, T.B. Huang, T.Y. Huang, W.C. Huang, Y.S. Huang, Y.X. Huh, S.C. Hung, K.C. Hung, W.Y. Hwang, Y.L.

928 513, 1010, 1014 513 380 401 192 513, 595 810, 810 225 244 373 421, 565, 1045, 1139 480, 517 565, 570 491 1155 416 210 60 1105 1149 530 928 149 742 661 149 1097 636 380 149 883 274 35, 314 911 1139 289, 365, 916, 923, 928

J Jainudin, N.A. Jang, J.S.R. Jean, J.H. Jeng, T.M. Jeong, C.K. Jeong, J.H. Jeong, S.S. Jhu, P.S.

553 943 636 192, 274 314 137, 445, 713 249 80

Jhuang, C.S. Jian, B.S. Jie, M.S. Juan, Y.J. Jung, Y.G.

1231 570 230 656 1124 314

K Kaewkannate, K. Kalkan, I. Kang, Y.H. Kao, F.H. Kao, Y.C. Ke, Y.L. Kim, D.J. Kim, D.W. Kim, G.N. Kim, H. Kim, H.J. Kim, K.J. Kim, K.Y. Kim, M.S. Kim, S. Kim, S.H. Kim, S.J. Kim, S.M. Kim, S.T. Kim, W.S. Ku, Y.Y. Kuo, C.L. Kuo, C.N. Kuo, J.L. Kuo, W.H.

406 1133 463 682, 1032 333, 343 244 1170, 1175 475 35 1170, 1175 314 1115 220 1170 406 475 100, 468, 713 137, 143, 406, 445, 468, 713 948, 958 1115 719 91, 299 197 353 968

L Lai, C.K. Lai, J.C. Lai, L.H. Lai, Y.T. Lan, C.H. Lan, T.S. Lay, S.R. Le, T.P. Lee, C.J. Lee, C.T. Lee, H.C. Lee, J. Lee, J.H.

607 8 369 1160 1207 1207 682 360 1139 983 702 778, 865, 878 143, 1115, 1133

1232 Lee, J.M. Lee, K.P. Lee, M.R. Lee, M.S. Lee, P.J. Lee, R.C. Lee, S. Lee, S.K. Lee, S.M. Lee, S.R. Lee, W.K. Lee, Y. Lee, Y.C. Lee, Y.H. Lee, Y.L. Lee, Y.M. Leong, C.K. Leong, J.C. Li, B.Y. Li, J. Li, J.Y. Li, M. Li, Q.X. Li, S.C. Li, T.T. Li, W.J. Li, W.Y. Li, X.G. Li, X.W. Li, Y.J. Liao, C.T. Liao, C.Y. Liao, J.D. Liao, W.C. Liao, Y.P. Liaw, S.K. Lien, C.H. Lin, C.C. Lin, C.H. Lin, C.J. Lin, C.R. Lin, C.S. Lin, D.B. Lin, D.T.W. Lin, H.E. Lin, H.I. Lin, H.P. Lin, H.T.

Applied Science and Precision Engineering Innovation 304 1071 565 249 963 911 137, 445, 713 958 570 778, 865, 878 747 778, 865, 878 963 1144, 1170, 1175 1144 396 503 595 768, 773 1202 115 202 55 436 575 661 543 1066 948, 958 181 1124 91 64 1081 682 687 983 818 559, 590, 687, 702, 934 729, 870, 923 729 805 646 284 1213 617 646 543, 548

Lin, H.Y. Lin, J.M. Lin, J.W. Lin, K.C. Lin, K.H. Lin, L.C. Lin, L.K. Lin, S.C. Lin, S.F. Lin, S.L. Lin, S.W. Lin, T.K. Lin, T.T. Lin, W.S. Lin, W.T. Lin, Y.B. Lin, Y.C. Lin, Y.D. Liou, K.T. Liu, A.L. Liu, C.C. Liu, C.F. Liu, C.H. Liu, C.J. Liu, C.T. Liu, C.Y. Liu, F.S. Liu, H.C. Liu, J.F. Liu, J.H. Liu, J.J. Liu, J.L. Liu, K.C. Liu, N.T. Liu, P.T. Liu, V.T. Liu, Y.C. Liu, Y.S. Liu, Y.X. Liu, Z.H. Liu, Z.J. Lo, S.W. Lu, C.L. Lu, H.C. Lu, M.C. Lui, K.S. Luo, C.J. Luo, X.

870 934 622, 1128 1101 149 682 1128 279, 380, 401 491 457, 627 239 1149 595 264 13, 421, 1045, 1051 133 86, 783, 996 486 1101 682, 1032 431 338, 708 274 480, 517 818 1155 1185 1193 133 20, 110 1160 968 45, 319, 496, 818 1197 805 535 742 338 1027 524 844 174 989 1185 480, 517 747 599 575

Applied Mechanics and Materials Vols. 479-480

M Ma, H. Mao, H. Miao, H.Y. Mohamad Zin, R. Mohammad, S. Mohammad, S.N. Mou, S.C. Mustaffar, M.

641 599 20, 110 553 1144 553 692, 697 553

N Nguyen, Q.A. Nien, C.C.

416, 622 524

O Omar, W. Ouh, S.C.

553 268

P Pan, C.T. Pan, C.Y. Pan, J.H. Park, J.H. Park, J.S. Park, J.W. Park, J.Y. Park, S.H. Park, S.Y. Peng, C.H. Peng, C.S. Peng, G.D. Pong, P.W.T.

155, 524 1061 641 170, 897 35 1175 1175 170 137, 143, 445, 713 294 763 883 747

1185 575

R Ray, D.T. Ren, P.W.

50 234

S Saleh, A.L. Saravanan, L. Seo, M.J.

1115 1144 380 50 239 724 834 570 570 1202 360, 416, 622 149 543, 548 795 166 788 463 436 788 778, 865, 878 284 753, 834 329 475 304 115 742 768, 773 968 1155 565 565, 570 50, 719 565 1032

T

Q Qin, J.F. Quan, Y.K.

Seo, Y.W. Shek, P.N. Shen, S.C. Shen, Y.H. Shen, Y.J. Shen, Y.S. Sheu, J.S. Shi, B.R. Shi, B.Y. Shi, C.S. Shiao, Y.J. Shieh, J.Y. Shih, C.K. Shih, H.M. Shih, J.M. Shih, S.J. Shih, W.C. Shih, Y.L. Shih, Y.N. Shim, J. Shin, L.D. Shou, H.N. Shu, K.M. So, H.J. Soong, R.C. Su, C.I. Su, J.Y. Su, K.L. Su, P.C. Su, W.C. Su, W.H. Su, Y.F. Su, Y.H. Su, Y.T. Su, Y.Z.

1233

553 20, 110 143

Tahir, M.M. Tan, C.S. Tang, H.C. Tang, I.T. Tang, Y.W. Tasi, L.R. Tsai, C.H. Tsai, F.T. Tsai, H.C. Tsai, L. Tsai, L.J. Tsai, M.K.

1144 1144 309 436 486 687 595, 1139 80 1193 60, 86 210 1180

1234 Tsai, S.F. Tsai, S.H. Tsai, S.L. Tsai, T.H. Tsao, C.C. Tsao, Y.T. Tsay, T.S. Tseng, C.H. Tseng, G.R. Tseng, H.R. Tseng, J.G. Tseng, T.H. Tseng, W.T. Tu, S.L. Tung, S.C. Tzeng, S.C. Tzou, G.Y.

Applied Science and Precision Engineering Innovation 69 636 607 508 953 607 338 491 299 651, 978 244 530 187, 197 50 661 192, 274 181

U Ueng, W.D.

126

V Vu, H.H.

463

W Wang, A.C. Wang, C. Wang, C.C. Wang, C.H. Wang, C.S. Wang, C.Y. Wang, F.S. Wang, G.W. Wang, H.C. Wang, H.P. Wang, H.S. Wang, I.T. Wang, J.F. Wang, J.R. Wang, J.Y. Wang, L.C. Wang, L.Z. Wang, S.C. Wang, S.F. Wang, S.H. Wang, S.L. Wang, S.M.

86 672 40, 45, 75, 105, 294, 319, 496 3, 451, 795 916 702 259 69 1001 1023 911, 1001 1056 1149 543, 548 906 20, 110 55 758, 763 682, 1032 60, 1160 938 268

Wang, S.S. Wang, T.C. Wang, W.C. Wang, W.T. Wang, X.H. Wang, Y.C. Wang, Y.H. Wang, Y.J. Wang, Y.N. Wang, Y.P. Wang, Y.T. Wei, C.L. Wei, J.H. Wong, K.K.Y. Wong, P.K. Wu, C.T. Wu, F.H.F. Wu, H.C. Wu, L.W. Wu, M.H. Wu, M.N. Wu, R.S. Wu, S.C. Wu, S.L. Wu, T.Y. Wu, Y.C.

758, 763 338 1160 973 55 737 96 329 595 1149 677 343 1032 747 202 1197 943 155 225 916 1213 1086 385 304 225 13, 50, 187, 230, 234, 390, 401, 421, 702, 1045, 1051, 1061, 1076, 1139

X Xie, Z.C. Xie, Z.Z. Xu, G.Q. Xu, G.W. Xu, J. Xu, L.

202 64 575 192 215, 348, 667 1185

Y Yan, K.Q. Yan, W.M. Yang, C.D. Yang, D.P. Yang, H.C. Yang, H.N. Yang, K.W. Yang, S.C. Yang, T.C.

758, 763 284 983 1185 155 225 463 677 1119

Applied Mechanics and Materials Vols. 479-480 Yang, T.S. Yang, W. Yap, Y.S. Yau, N.J. Ye, J.W. Ye, S.Y. Yeh, C.T. Yen, C.T. Yen, C.Y. Yen, H.C. Yen, K.H. Yen, S.J. Yoo, S. Yoon, S. You, C.C. You, P.S. Yu, B.S. Yu, C.H. Yu, C.M. Yu, C.Y. Yu, H. Yu, H.C. Yu, K.W. Yu, S.F. Yu, S.K. Yu, T.C. Yu, Y.B. Yu, Y.K. Yuan, K. Yue, Z.G.

369 1032 294 1180 166 468 225 166, 268, 1006 40 401 672 989 778, 865, 878 778, 865, 878 161 861 427 800, 823, 828, 849, 855 1018 343, 870 906 427 983 1086 729 133 1018 1193 1066 1185

Z Zakaria, R. Zhan, W.B. Zhang, Q.X. Zhang, S.B. Zhang, X. Zhang, Z.G. Zhong, J.H. Zhou, Y.R. Zhu, Z.W. Zhuang, Y.R.

553 575 667 641 55 938 783 1128 348, 667 697

1235