Proceedings of the 2019 DigitalFUTURES: The 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2019) [1st ed.] 978-981-13-8152-2;978-981-13-8153-9

Table of contents :
Front Matter ....Pages i-xii
Front Matter ....Pages 1-1
Simulation and Optimization Method of Tensegrity Structure with Elastic Membrane as Tension Material (Zongxu Yang, Koki Okumura, Kaoru Suehiro)....Pages 3-16
From Ang to Steel-Wood Composite Cantilever Beam - Modern Translation of Roof Overhangs in Structural Performance-Based Design (Philip F. Yuan, Jinxi Jin, Li Han)....Pages 17-26
Rocky Vault Pavilion: A Free-Form Building Process with High Onsite Flexibility and Acceptable Accumulative Error (Chengyu Sun, Zhaohua Zheng)....Pages 27-36
Study on Optimizing the Cold-Adapted Form of Large Space Public Buildings (Yong Huang, Longwei Zhang, Minyi Zhang)....Pages 37-48
Applying Lost Foam Casting Aluminum and Computational Design into the Fabrication of Complex Structure Joint (Tianyu Guo)....Pages 49-71
Carbon Natural: Using Molecular Logics as Inspiration in Micro-Bamboo Structures (Ralph Spencer Steenblik)....Pages 72-81
Parametric Design of Personalized 3D Printed Sneakers (Qiang Cui, Fei Yue)....Pages 82-92
Front Matter ....Pages 93-93
Research on Virtual Reality-Integrated Design of Sports Architecture Based on BIM (Wei Xiao, Xuan Zong, Wei Zang)....Pages 95-103
Interactive Performance and Immersive Experience in Dramaturgy - Installation Design for Chinese Kunqu Opera “The Peony Pavilion” (Qianhui Feng)....Pages 104-115
Discussion on Interactive Environment Design Based on Multi-sensory and Behavior in the Background of Digital Future (Hongling Li, Hexuan Dong)....Pages 116-123
Artificial Intelligence Applied to Brain-Computer Interfacing with Eye-Tracking for Computer-Aided Conceptual Architectural Design in Virtual Reality Using Neurofeedback (Claudiu Barsan-Pipu)....Pages 124-135
Reference Building Energy Modeling: A Case Study for Green Office Buildings in Shanghai (Weipeng Guo, Zhi Zhuang, Jiawei Yao, Philip F. Yuan)....Pages 136-144
A Visualization Based Analysis to Assist Rebalancing Issues Related to Last Mile Problem for Bike Sharing Programs in China: A Big-Data Case Study on Mobike (Ercument Gorgul, Chaoran Chen)....Pages 145-153
Integration of Wind Simulation and Skin Tectonic in Architecture Design Taking the Henan Science and Technology Museum as an Example (Linxue Li, Kangning Ge)....Pages 154-166
Front Matter ....Pages 167-167
Form Finding and Evaluating Through Machine Learning: The Prediction of Personal Design Preference in Polyhedral Structures (Hao Zheng)....Pages 169-178
Study on Performance-Oriented Generation of Urban Block Models (Chengyu Sun, Jian Rao)....Pages 179-188
Artificial Intelligence Design, from Research to Practice (Wanyu He, Xiaodi Yang)....Pages 189-198
Comparison of BESO and SIMP to Do Structural Topology Optimization in Discrete Digital Design, and then Combine Them into a Hybrid Method (Gefan Shao)....Pages 199-209
Application of Algorithmic Generation to Kindergarten Design (Shuqi Cao, Zilin Zhou, Ziyu Tong)....Pages 210-218
Computational Methods for Curved Surface Modeling Based on Muria-Ori (Zhengtao Wang, Fulong Jia, Zhonggao Chen, Guohua Ji)....Pages 219-231
A Computational Approach for Knitting 3D Composites Preforms (Yige Liu, Li Li, Philip F. Yuan)....Pages 232-246
Data-Optimizing on Minimal Surface Pavillions: Analysis of the Whole Process of Design and Optimization of the Minimal Surface Pavillion Series “Flora” (Jiong Xu, Ying Zhang, Yangchen Zhao, Xiao Zhang)....Pages 247-256
Why Processing is Not Swarm Intelligence (Bing Zhao)....Pages 257-264
Theories and Algorithms of Complexity Science Used in Digital Design (Pengyu Zhang, Weiguo Xu)....Pages 265-274
The Age of Intelligence: Urban Design Thinking, Method Turning and Exploration (Xi Peng, Pengkun Liu, Yunfeng Jin)....Pages 275-284
Front Matter ....Pages 285-285
Designing an Architectural Robot: An Actuated Active Transforming Structure Using Face Detection (Ji Shi, Yujie Wang, Shang Liu)....Pages 287-302
Advanced Timber Construction Platform: Multi-robot System for Timber Structure Design and Prefabrication (Hua Chai, Liming Zhang, Philip F. Yuan)....Pages 303-311
Developing an Interactive Fabrication Process of Maker Based on “Seeing-Moving-Seeing” Model (Chun-Yen Chen, Teng-Wen Chang, Chi-Fu Hsiao, Hsin-Yi Huang)....Pages 312-321
Design Optimum Robotic Toolpath Layout for 3-D Printed Spatial Structures (Philip F. Yuan, Zhewen Chen, Liming Zhang)....Pages 322-330
Application of Robotic Arm Technology in Intelligent Construction (Yue Tong, Zhen Xu)....Pages 331-345
Urban Memory Accessor: Mechanical Design of Interactive Installation Based on Arduino (Wenhan Feng, Yueyue Wang)....Pages 346-354
Path-Optimizing Agent-Based Earthwork System: a Microscopically Precise Earthwork System that Is Adaptable to Any Form of Landscape (Zixiao Ji, Yuqiong Lin)....Pages 355-363
On-Site Automatic Construction of Partition Walls with Mobile Robot and Computer Vision (Hao Meng, Zhihao Liang, Pengcheng Qi)....Pages 364-372
Back Matter ....Pages 373-374

Citation preview

Philip F. Yuan · Yi Min (Mike) Xie · Jiawei Yao · Chao Yan Editors

Proceedings of the 2019 DigitalFUTURES The 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2019)

Proceedings of the 2019 DigitalFUTURES

Philip F. Yuan Yi Min (Mike) Xie Jiawei Yao Chao Yan •

•

•

Editors

Proceedings of the 2019 DigitalFUTURES The 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2019)

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Editors Philip F. Yuan College of Architecture and Urban Planning Tongji University Shanghai, China

Yi Min (Mike) Xie School of Engineering RMIT University Melbourne, Australia

Jiawei Yao College of Architecture and Urban Planning Tongji University Shanghai, China

Chao Yan College of Architecture and Urban Planning Tongji University Shanghai, China

Funded by College of Architecture and Urban Planning (CAUP), Tongji University, China ISBN 978-981-13-8152-2 ISBN 978-981-13-8153-9 https://doi.org/10.1007/978-981-13-8153-9

(eBook)

© Springer Nature Singapore Pte Ltd. 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Committees

Honorary Advisors • Prof. Dr. Jiaping LIU, Xi’an University of Architecture and Technology, China • Prof. Dr. Zhiqiang WU, Tongji University, China • Executive chief architect, Weiping SHAO, Beijing Institute of Architectural Design, China • Prof. Dr. Guoqiang LI, Tongji University, China • Director, Bernard STIGLER, Centre Georges-Pompidou, France • Prof. Dr. Philippe BLOCK, ETH Zurich, Switzerland • Prof. Dr. Achim MENGES, University of Stuttgart, Germany • Prof. Dr. Antoine PICON, GSD, USA • Prof. Dr. Patrik SCHUMACHER, Zaha Hadid Architects (ZHA), UK • Prof. Dr. Yi Min (Mike) XIE, RMIT University, Australia

Organization Committees • Prof. Dr. Philip F. YUAN, Tongji University, China (Workshop Coordinator) • Prof. Dr. Neil LEACH, Tongji University, China (Conference Coordinator) • Prof. Dr. Yi Min (Mike) XIE, RMIT University, Australia (Paper Selection Coordinator) • Prof. Dr. Guohua JI, Nanjing University, China (Award Coordinator)

Scientific Committees • Director, Bernard STIGLER, Centre Georges-Pompidou, France • Senior Associate, Shajay BHOOSHAN, Zaha Hadid Architects (ZHA), UK

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• Prof. Dr. Philippe BLOCK, ETH Zurich, Switzerland • Adjunct assistant Prof. Biayna BOGOSIAN, University of Southern California, USA • Prof. Dr. Jane BURRY, Swinburne University of Technology, Australia • Prof. Dr. Mark BURRY, Swinburne University of Technology, Australia • Associate Prof. Dr. Matias Del CAMPO, University of Michigan, USA • Associate Prof. Dr. Tengwen CHANG, National Yunlin University of Science and Technology, Taiwan, China • Assistant Prof. Dr. Benjamin DILLENBURGER, ETH Zurich, Switzerland • Prof. Dr. Fabio GRAMAZIO, ETH Zurich, Switzerland • Prof. Dr. Tim HEATH, University of Nottingham, UK • Associate Prof. Dr. Weixin HUANG, Tsinghua University, China • Prof. Dr. Guohua JI, Nanjing University, China • Prof. Dr. Neil LEACH, Tongji University, China • Associate Prof. Dr. Hyejin LEE, Tongji University, China • Prof. Dr. Guoqiang LI, Tongji University, China • Prof. Dr. Linxue LI, Tongji University, China • Prof. Dr. Jiaping LIU, Xi'an University of Architecture and Technology, China • Associate Prof. Dr. Wes McGee, University of Michigan, USA • Assistant Researcher, Dr. Xianchuan MENG, Nanjing University, China • Prof. Dr. Achim MENGES, University of Stuttgart, Germany • Prof. Dr. Antoine PICON, GSD, USA • Prof. Dr. Patrik SCHUMACHER, Zaha Hadid Architects (ZHA), UK • Executive chief architect, Weiping SHAO, Beijing Institute of Architectural Design, China • Prof. Dr. Xing SHI, Southeast University, China • Associate Prof. Dr. Chengyu SUN, Tongji University, China • Prof. Dr. Kostas TERZIDIS, Tongji University, China • Prof. Dr.-Ing. Oliver TESSMANN, Technische Universität Darmstadt, Germany • Prof. Dr. Makoto Sei Watanabe, Tokyo City University, Japan • Dr. Xiang WANG, Tongji University, China • Prof. Dr. Zhiqiang WU, Tongji University, China • Prof. Dr. Yi Min (Mike) XIE, RMIT University, Australia • Prof. Dr. Leiqing XU, Tongji University, China • Prof. Dr. Weiguo XU, Tsinghua University, China • PhD Candidate, Chao YAN, Tongji University, China • Associate Researcher, Dr. Jiawei YAO, Tongji University, China • Prof. Dr. Philip F. YUAN, Tongji University, China • Associate Prof. Dr. Zhi ZHUANG, Tongji University, China

Preface

About DigitalFUTURES Shanghai “DigitalFUTURES” is an annual academic event series consisting of conferences, workshops, and exhibitions hosted by the College of Architecture and Urban Planning, Tongji University. Started in 2011, the aim of the “DigitalFUTURES” is to promote theoretical and scientific researches on computational design and robotic fabrication among academic institutions and encourage collaborations and interactions internationally.

2019 Conference Theme 2019 is the year in which Ridley Scott set his cult movie, Blade Runner (1982). Blade Runner depicts a future where bio-engineered robots—or ‘replicants’—have infiltrated human society, where cars fly, facades of buildings are alive with advertising, and corporate life is dominated by the hi-tech Tyrrell Corporation. Fast forward to what is actually happening in 2019. We don’t have replicants, but everyday life has been colonized by AI personal assistants, such as Siri, Alexa and Google Assistant. We don’t have flying cars, but we do have Maglev trains floating on magnetic fields and self-driving cars. And we don’t have the Tyrrell Corporation, but corporate life is dominated by hi-tech companies, such as Google, Amazon, Apple, Microsoft and Tencent. And facades of buildings in cities like Shanghai come alive at night with animated LED displays beyond anything that Ridley Scott could have imagined. We live in a world of smartphones, smart buildings and smart cities, a world dominated by intelligent systems—artificial intelligence, augmented intelligence and swarm intelligence; a world where AI robots clean our buildings, and intelligent devices control our environment; a world where AI filters our spam, sorts our

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images on Instagram, recognizes our friends on Facebook, and translates our messages on WeChat. The future, it seems, is already here. The theme for the 2019 DigitalFUTURES is ARCHITECTURAL INTELLIGENCE. The conference and workshops explore how artificial intelligence inform our designs, how robots fabricate our buildings, and how augmented reality and virtual reality help to visualize their potential. Step into the future! Come to Shanghai, one of the world’s most technologically advanced cities, with its Maglev trains, and super tall buildings with their animated LED facades. Come to DigitalFUTURES 2019, the world’s most progressive conference and workshops joined by some of the world’s most talented designers and researchers. June 2019

Prof. Neil Leach Prof. Philip F. Yuan College of Architecture and Urban Planning Tongji University Shanghai, China

Contents

Material Intelligence Simulation and Optimization Method of Tensegrity Structure with Elastic Membrane as Tension Material . . . . . . . . . . . . . . . . . . . . . Zongxu Yang, Koki Okumura, and Kaoru Suehiro From Ang to Steel-Wood Composite Cantilever Beam - Modern Translation of Roof Overhangs in Structural Performance-Based Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Philip F. Yuan, Jinxi Jin, and Li Han

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Rocky Vault Pavilion: A Free-Form Building Process with High Onsite Flexibility and Acceptable Accumulative Error . . . . . . . . . . . . . . Chengyu Sun and Zhaohua Zheng

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Study on Optimizing the Cold-Adapted Form of Large Space Public Buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yong Huang, Longwei Zhang, and Minyi Zhang

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Applying Lost Foam Casting Aluminum and Computational Design into the Fabrication of Complex Structure Joint . . . . . . . . . . . . . . . . . . Tianyu Guo

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Carbon Natural: Using Molecular Logics as Inspiration in Micro-Bamboo Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ralph Spencer Steenblik

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Parametric Design of Personalized 3D Printed Sneakers . . . . . . . . . . . . Qiang Cui and Fei Yue

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Data Intelligence Research on Virtual Reality-Integrated Design of Sports Architecture Based on BIM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wei Xiao, Xuan Zong, and Wei Zang

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Interactive Performance and Immersive Experience in Dramaturgy Installation Design for Chinese Kunqu Opera “The Peony Pavilion” . . . 104 Qianhui Feng Discussion on Interactive Environment Design Based on Multi-sensory and Behavior in the Background of Digital Future . . . . . . . . . . . . . . . . 116 Hongling Li and Hexuan Dong Artificial Intelligence Applied to Brain-Computer Interfacing with Eye-Tracking for Computer-Aided Conceptual Architectural Design in Virtual Reality Using Neurofeedback . . . . . . . . . . . . . . . . . . . 124 Claudiu Barsan-Pipu Reference Building Energy Modeling: A Case Study for Green Office Buildings in Shanghai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 Weipeng Guo, Zhi Zhuang, Jiawei Yao, and Philip F. Yuan A Visualization Based Analysis to Assist Rebalancing Issues Related to Last Mile Problem for Bike Sharing Programs in China: A Big-Data Case Study on Mobike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Ercument Gorgul and Chaoran Chen Integration of Wind Simulation and Skin Tectonic in Architecture Design: Taking the Henan Science and Technology Museum as an Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 Linxue Li and Kangning Ge Computational Intelligence Form Finding and Evaluating Through Machine Learning: The Prediction of Personal Design Preference in Polyhedral Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Hao Zheng Study on Performance-Oriented Generation of Urban Block Models . . . 179 Chengyu Sun and Jian Rao Artificial Intelligence Design, from Research to Practice . . . . . . . . . . . . 189 Wanyu He and Xiaodi Yang Comparison of BESO and SIMP to Do Structural Topology Optimization in Discrete Digital Design, and then Combine Them into a Hybrid Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Gefan Shao Application of Algorithmic Generation to Kindergarten Design . . . . . . . 210 Shuqi Cao, Zilin Zhou, and Ziyu Tong

Contents

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Computational Methods for Curved Surface Modeling Based on Muria-Ori . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Zhengtao Wang, Fulong Jia, Zhonggao Chen, and Guohua Ji A Computational Approach for Knitting 3D Composites Preforms . . . . 232 Yige Liu, Li Li, and Philip F. Yuan Data-Optimizing on Minimal Surface Pavillions: Analysis of the Whole Process of Design and Optimization of the Minimal Surface Pavillion Series “Flora” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Jiong Xu, Ying Zhang, Yangchen Zhao, and Xiao Zhang Why Processing is Not Swarm Intelligence . . . . . . . . . . . . . . . . . . . . . . . 257 Bing Zhao Theories and Algorithms of Complexity Science Used in Digital Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 Pengyu Zhang and Weiguo Xu The Age of Intelligence: Urban Design Thinking, Method Turning and Exploration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275 Xi Peng, Pengkun Liu, and Yunfeng Jin Robotic Intelligence Designing an Architectural Robot: An Actuated Active Transforming Structure Using Face Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287 Ji Shi, Yujie Wang, and Shang Liu Advanced Timber Construction Platform: Multi-robot System for Timber Structure Design and Prefabrication . . . . . . . . . . . . . . . . . . 303 Hua Chai, Liming Zhang, and Philip F. Yuan Developing an Interactive Fabrication Process of Maker Based on “Seeing-Moving-Seeing” Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312 Chun-Yen Chen, Teng-Wen Chang, Chi-Fu Hsiao, and Hsin-Yi Huang Design Optimum Robotic Toolpath Layout for 3-D Printed Spatial Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322 Philip F. Yuan, Zhewen Chen, and Liming Zhang Application of Robotic Arm Technology in Intelligent Construction . . . 331 Yue Tong and Zhen Xu Urban Memory Accessor: Mechanical Design of Interactive Installation Based on Arduino . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346 Wenhan Feng and Yueyue Wang

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Path-Optimizing Agent-Based Earthwork System: a Microscopically Precise Earthwork System that Is Adaptable to Any Form of Landscape . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355 Zixiao Ji and Yuqiong Lin On-Site Automatic Construction of Partition Walls with Mobile Robot and Computer Vision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364 Hao Meng, Zhihao Liang, and Pengcheng Qi Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373

Material Intelligence

Simulation and Optimization Method of Tensegrity Structure with Elastic Membrane as Tension Material Zongxu Yang1(&), Koki Okumura1, and Kaoru Suehiro2 1

2

Graduate School of Human-Environment Studies, Kyushu University, Motooka 744, Nishi Ward, Fukuoka City, Japan [email protected], [email protected] Faculty of Human-Environment Studies, Kyushu University, Motooka 744, Nishi Ward, Fukuoka City, Japan [email protected]

Abstract. In this study, the form-finding process and structural analysis of tensegrity was simulated through the simulation program based on Dynamic Relaxation method, taking the temporary tensegrity tent “Memboo (Membrane + Bamboo)” as an example (hereafter referred to as “this structure”), which uses a membrane material as the tension material designed by Suehiro Lab Bamboo team. Then, using genetic algorithm, the possible optimized shape of the tensegrity structure is simulated. On this basis, experiments using 1/4 and 1/2 models of this structure is implemented to verify simulation results. Workflow is formed using the software Rhinoceros and the parametric design platform Grasshopper, which are frequently used by architectural designers. In Chap. 16, the form-finding process of this structure is simulated by the particle motion simulation plug-in “Kangaroo 2” (abbreviated to K2 hereinafter). In Chap. 17, structural analysis is done by using “K2 Engineering”. In Chap. 18, measuring experiments are conducted and the results obtained by simulation and the experiments are analyzed. In Chap. 26, optimization solution using the Genetic Algorithm plug-in “Octopus” is obtained. In Chap. 8, the application of this simulation program is discussed. This research aims at grasping structural characteristics of a membrane tensegrity structure and designing optimization by simulation. Keywords: Tensegrity Evolutionary algorithm




Membrane




Form-finding




Dynamic relaxation




1 Research Background and Purpose The tensegrity structure, summarized as a set of discontinuous compressive components interacts with a set of continuous tensile components to define a stable volume in space by Anthony Pugh in 1976 [1], has various advantages such as: deployability, movability, reliability, controllability and reusability, which contribute to its high applicability as temporary construction or large-span spatial structure. When a membrane element is chosen to be the tension material, the space inside the structure can be © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 3–16, 2020. https://doi.org/10.1007/978-981-13-8153-9_1

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easily formed and has more integrality compared to using the cable element. However, the complexity of the variable form of the membrane tensegrity and the relationship between each tensile and compressive component is the cause of difficulty in grasping the form of membrane tensegrity and its structural characteristics. Also, there are some uncertainties during construction due to the influences of various reasons such as the inaccurate pinned joint angles. In order to apply it to construction, methods should considered to grasp the optimum state and deformation under the influence of load when a designing tensegrity structure. In this research, it is considered significant to apply tensegrity to architectural application so that the result of structural analysis of tensegrity and the result of optimized design of variable form can be obtained and edited quickly (Figs. 1 and 2).

Fig. 1. Comparison with workflow of past research and this research

Fig. 2. Method of this research

2 Research Object 2.1

“Memboo” Structure

This structure (Fig. 3) is used as the function of a temporary outdoor tent for a Yakitori stall at the Kyushu University Festival. Therefore, the work space inside was requested to be protected from the weather. Although there are already numerous researches about using tensegrity as shells and spatial structures or foldable constructions or robots, research about temporary tent using tensegrity still remain nearly blank.

Simulation and Optimization Method of Tensegrity Structure

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Fig. 3. “Memboo” structure with illumination

This structure is a section of a polygonal geometry using Circuit Pattern1, when the naked strut of its peripheral part is pinned to the basement, a vault-like space will be formed. By adopting such a method, it is possible to get a floor area as a temporary building. Moreover, the quantity of tensile components of the membrane tensegrity is less than the cable using tensegrity. What’s more, the difficulty of construction and the self-weight of the structure will reduced because of that (Fig. 4).

Fig. 4. Comparison of tensegrity structure with cable element and membrane element

2.2

Construction Process

Generally, the tensegrity is not stable until the axial force is imported. Before the construction of this structure, the compressive components are inserted into the pocket joint (Fig. 5) of the sewed membrane to form pre-tension. And then the structure is formed when frapping the base wire (Fig. 6). For the temporary tent, the compressive components of the structure are made of 1.8 m and 2 m light local bamboo, and the main tensile component is made of elastic membrane called Shade Azul, all these materials contributes to the high deployability of this structure.

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Fig. 5. The detail of membrane pocket joint

Fig. 6. Process of how to form tension in this structure

3 Simulation Process 3.1

Principle of K2

K2 is a physics motion simulation plug-in for particles in Grasshopper developed by Daniel Piker. Based on Dynamic Relaxation (DR) method [2], the particle in K2 follows the second law of Newton. In the simulation, K2 will calculate the resultant force resulting from each residual force on the nodes that are in motion (hereinafter the concept of particle, node, mass, point are the same), and then K2 evaluates the motion and displacement of nodes and updates the new position after the interval accordingly. By repeating this process, convergence will occur when the moving distance of all nodes falls within the set value (in this research, the convergence value is set to 1  10−10 m in order to compromise calculation speed and accuracy), and then the simulation ends with the convergence [3]. 3.2

Discretization of Simulation Model

Since the analysis target of K2 is finite particles and simulation of continuous entities (curves or surface or solids) is inappropriate, it is necessary to discretize the membrane tensegrity structure into Mass-Spring System (MSS) [4], and each node will be connected with compression part, the tension part and the sewed part (Fig. 7).

Simulation and Optimization Method of Tensegrity Structure

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Fig. 7. Discretization of different elements

Because this structure uses an elastic membrane material as the tensile component, it is necessary for the membrane to be discretized into a mesh. The discretization drawing comes from the design drawing and the nodes of the compression parts should be also on the mesh grid points to form the MSS. Since it is necessary to sew some parts of the membrane to import pre-tension, some zero rest length wires which are set as rigid are arranged in advance on the sewing positions according to the design drawing. After the discretization process, the base wires are frapped and the axial forces of the tensile and compressive components are imported (Fig. 8).

Fig. 8. The design drawing and discretized drawing in plan

Since this structure is a section from the entire Circuit Pattern geometry, the four foot points are not in one plane and can’t suit to a rectangle foundation theoretically. In the simulation, other controls must be added to satisfy the design requirements, such as the angles of the base wires and the anchoring forces fixing the structure to the foundation. 3.3

Simulation Result

After the above settings, the simulation can be started. When the length of the base wires are gradually shortened through the sliders, the structure rises. When the displacement of each node ultimately becomes smaller than the convergence value, the simulation is completed and form-finding process finishes. Hereby in this structure, it takes 5050 times for iteration (Fig. 9). When comparing the original length with the convergence length from the simulation result, the displacement of the compressive and the tensile components can be obtained.

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Fig. 9. Process of simulation in different iteration times

4 Structural Analysis 4.1

Principle of K2 Engineering

K2 Engineering is an analysis plug-in based on the Dynamic Relaxation method using K2’s iterative solver. The merit of the DR method is that DR does not require computation and inversion of the global stiffness matrix, but instead seeks equilibrium in each node explicitly and simultaneously by assigning mass, acceleration and a method of damping to the nodes. The axial and bending stiffness of K2 Engineering are calculated based on Hooke’s law and Barnes/Adriaenssens model respectively [5]. It is possible to simulate accurate structural properties by providing an adequate Young’s modulus for the target since the displacement of the structure will always minimize the potential energy and K2 also minimizes the total energy of the system. This method was validated in the research on Form-Active Hybrid Structures (FAHS) [6]. 4.2

Structural Analysis Program and Results

Because the data of the simulated structure are discretized points and lines, the input of material properties (density, thickness, cross-sectional shape, Young’s modulus) is required for structural analysis (Fig. 10). By setting support and load, the axial forces, bending moments and shearing forces of compression material and the tensions in mesh springs can be obtained (Fig. 11). In order to verify the results of simulation, the material properties of acrylic pipe used in the 1/2 model measurement experiment are used here and the simulation load is on the same positions as the measurement experiment (Fig. 12). For the reason of the weight can naturally hang down and be fixed without influencing the structure.

Fig. 10. Material properties of acrylic pipe used in this research. The Young’s modulus of the compression material for simulation is the acrylic pipes measured in another experiment.

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Fig. 11. Because there is no accurate Young’s modulus and Poisson’s ratio data of this membrane material of this research, approximate value of numbers are input according to the experiment model. Since the membrane is lightweight and thin, it is set as a 1 mm thick solid without self-weight.

Fig. 12. Positions of weight used for load experiment (black dots) and the number of compressive components.

5 Measuring Experiment 5.1

Method of 1/4 Model Measuring Experiment

Since form of this structure has to be changed, 1/4 scale models were considered to be appropriate in the experiment to make sure three people can easily manipulate the experiment model. Three 1/4 scale elastic membrane models are used as tensile

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components to get an average value of tension and try to find the accurate stress state. In order to get the displacement of the membranes, grids are made and drawn on the membrane in the same way as the discretized simulation model to compare the distortion of the initial state and the tensile state. Three fixed camera are used to be the standardized position to take photos for the membrane grid coordinates. Photos were also taken from every 45° around the experiment structure with the height of 0.5 m and 1.5 m to compound the whole model in Autodesk Recap. As for the compressive components, since the original structure used bamboo, which is anisotropic material so that it is improper to measure and simulation it. Therefore, substitution materials are sought to replace bamboo with isotropic property. Iron pipe, as one of the most common material, was considered to be one of the choice for its isotropous and known Young-Modulus. For the strain of the iron pipe, strain gauges were pasted on the middle points on both sides of iron pipes so that we can know the stress state and average axial force. And gauges are connected with the data logger with wires. The 1/4 experiment model was assembled the same way as the original structure. Since the tension is imported by frapping the base wires of this structure. Several patterns were designed with the change of the width and depth of the base wire expanded and shortened in 200 mm. Load was applied with the weight of 0.5 kg, 1.0 kg, 1.5 kg in 12 positions shown in Fig. 12. The 10 patterns are shown above (Fig. 13). And the 800 mm  1000 mm no load state is set as the standard pattern because this pattern is used as the real tent in the original structure.

Fig. 13. Ten patterns of experiment and the photo of standard pattern experiment

As demonstrate in Table 1, the results of the measurement of 1/4 model iron pipe is considered not ideal in summary. Although three experimental structures were used for averaging, the distortion errors of the three experimental structures were large and not suitable for averaging. Moreover, several iron pipes showed minus values which means they were in the state of tension. The possible reasons for the errors are as follows: 1. The distortion of the iron pipe under the axial force from the membrane is small because of the large Young-modulus of iron pipe, so a slight error will occupy a huge percentage in the result; 2. The iron pipe is greatly affected by temperature, though we set constant temperature from the air-conditioning, but the temperature still changed from day to night because of the long duration of the experiment and inaccurate

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constant temperature environment; 3. When changing the pattern of the experimental structures, the strain gauges might be pulled which may cause uncalibrated errors. Moreover, due to the error of Recap compounding, it was impossible to accurately synthesize the coordinate points of the membrane, so the way of measuring grid coordinates by photographing should not be considered as the proper method. Generally, the 1/4 model measuring experiment was considered as failed. From what we learned from this experiment, we decided to redo the experiment with the update of: 1. Use FARO 3D scanner to scan the membrane coordinates; 2. Use three-cable strain gauges to calibrate the temperature influence of the compression part; Table 1. Distortion of iron pipe in experiment pattern 1(above) and pattern 10(below)

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3. Change the compression material from iron pipe to acrylic pie which has smaller Young-Modulus so that it is more sensitive to stress; 4. Extend the strain gage wire to avoid being pulled when changing the pattern; 5. Change the model for 1/4 scale to 1/2 scale, which causes more stress and decreases the error percentage in the total results. 5.2

Method of 1/2 Model Measuring Experiment

The same as 1/4 model experiment, in order to measure the deformation of the different stress state of this structure, the 1/2 model experiment used 800 mm in depth, 1200 mm in width and no load as the standard pattern. The width and depth of the base wires were expanded and shortened, load was applied by the position shown in Fig. 12 to create six experimental patterns (Fig. 14). The six patterns are shown below (Fig. 15).

Fig. 14. Experiment pattern 1 and pattern 6 and grids drawn on the membrane

Fig. 15. Demonstration of elements of experiment and patterns of experiment

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Comparison Between Measuring Experiment and Simulation Results

Tension Material: Elastic Membrane The tension of membrane comes from the deformation of the grids from the original flat state to the space structure, which is the same as the discretized mesh grid for simulation. Grid coordinates were measured by 3D scanner (Fig. 15). From Fig. 16 and statistics, it can be known that the errors of simulation and measuring results are mostly from 20 mm to 60 mm, and it is clear that the errors exceeding 60 mm are almost at the edge of the structure. The possible causes of the error are analyzed as follows: 1. The structure sinks due to the weight of the strain gauges and the conduct wires, and also the weight of the membrane itself, therefore simulation coordinates are slightly higher than the measured ones. 2. Because of many sutures around the edge, the modulus of elasticity of the membrane material changes partly. 3. The manual measured model may have a slight asymmetry, which can cause small errors. In summary, it can be said that the coordinates of simulation and measurement are highly anastomosed.

Fig. 16. Coordinate goodness of fit from experiment and simulation results of patterns 1 and 6. Examining the form change under the condition of load change. The grey color points are the coordinates got from the 3D scanner from the experiment and the black points are got simulation coordinates

Compression Material: Acrylic Pipe As shown in Fig. 17, the distortion error became large gradually from the central part (12, 13, 14, 15) of the structure to the surrounding part, especially at the feet which were connected with the foundation (1, 7, 27, 30). The possible reasons are as follows: Because the width and depth of the experiment model in some patterns exceeded the right stress state, it may be forcibly fixed to the foundation (for pattern 2, 3, 5, 7, pipe number 7, 27 are in tension state because of that). Also, a change in the elastic modulus of sewing the membrane also causes an error of the compression material distortion of the edge portion. What’s more, it is explicit that the symmetry of this structure is well reflected from the simulation results.

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Fig. 17. Comparison of distortion from experiment and simulation. Three-cable strain gauges are used to eliminate electrostatic and temperature influences. In pipe number 13, since it is considered that the wrong attachment method of the strain gauges causes obviously large data error, and here, correction is made using the number 18 pipe’s data which is at the symmetrical position of number 13 pipe.

6 Optimization Methods Using Evolutionary Algorithm The optimization result will be meaningless to practical use when using the single purpose convergent genetic algorithm like “Galapagos” because it will converge to the initial state of the structure when obtaining the extremum of the structural axial force. For this reason, a multi-objective GA is required to control the optimization direction in order to avoid the structure return to an extreme state. Unlike the traditional singlepurpose convergent genetic algorithm, “Octopus” is a multi-objective GA plug-in based on SPEA-2 [7] and HyperE [8] algorithm, which can seek Pareto optimal solutions under multi genes and fitnesses. Since this structure uses elastic membrane and is a large deformation structure, if the parameters of this structure are changed, the shape of the structure will be changed, too. Parameters like gravity, the length and amount of compressive components, elastic Modulus of the membrane and etc. can all influence the shape of the structure. This time, the optimum stress state of the structure is obtained by adjusting the depth and width of the structure within the range of the design requirement. There are situations in the trial construction compression when material loses pressure and is stretched and falls from the membrane pocket. So in real situation, there is rarely the case that minimum or maximum can be reached in tensegrity structure because the minimum or maximum will always be reached in bad space shape like depth 0 mm width 0 mm, because in this kind of circumstance, the structure is certainly in an extremum state.

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Therefore, it is significant to set multiple suitable fitness for the structure to avoid GA to converge in an inappropriate value. The Pareto optimum stress state of the structure is a good choice. Fitnesses are set that the maximum tension and maximum pressure are made as small as possible, at the same time the minimum of tension and compression is made sure to be larger than 0, so that the compression part is not pulled and the tension is not compressed. Here an example can be obtained as one set of result using the settings in Fig. 18.

Fig. 18. Settings of genes and fitness and one of the possible optimized result

7 Summary and Future Prospects With the development of computer technology and algorithm design, various complex graphics and structures can be simulated and accurately calculated. Although the tensegrity structure has rarely been used as a building structure for the past half century for the reason that its calculation and analysis has always been a challenge. Through the method of this research, architects begin to be able to quickly simulate and calculate the form and stress state of the tensegrity structure and optimize it. From the above, it is considered that the simulation based on the Dynamic Relaxation method can grasp the characteristics of the membrane material tensegrity structure well and the optimized solution of Evolutionary Algorithm is meaningful for

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practical construction. Furthermore, it can be said that the workflow of this research can be widely used within the range of the tensegrity structure design after the actual measurement verification. However, it is also necessary to examine the results by taking various external factors into account to increase the precision when the applying to design and construction. Although the method of this research was used in other projects for other tesegrity pattern (Diamond pattern) (Fig. 19), experiments are still not conducted to verify the accuracy of the simulation. But for the application on fast-built temporary tent, this research can be a reference to design and construct it. And further studies and experiments should be done to improve the accuracy of both the simulation and the construction.

Fig. 19. Diamond Pattern of tensegrity temporary tent

References 1. 2. 3. 4. 5. 6.

7. 8.

Pugh, A.: An Introduction to Tensegrity, California (1976) Day, A.S.: An Introduction to Dynamic Relaxation (1965) Piker, D.: Kangaroo Manual (2014) Nealen, A., Müller, M., Keiser, R., Boxerman, E., Carlson, M.: Physically based deformable models in computer graphics. In: EuroGraphics (2005) Barnes, M.R., Adriaenssens, S., Krupka, M.: A novel torsion/bending element for dynamic relaxation modeling. Comput. Struct. 119, 60–67. Elsevier (2013) Quinn, G., Deleuran, A.H., Piker, D., Brandt-Olsen, C., Tamke, M., Thomsen, M.R., Gengnagel, C.: Calibrated and interactive modelling of form-active hybrid structures. In: Proceedings of IASS Annual Symposia, IASS 2016 Tokyo Symposium: Spatial Structures in the 21st Century—Bending Active and Flexible Structures, vol. 16, pp. 1–9 (2016) Zitzler, E., Laumanns, M., Thiele, L.: SPEA2: Improving the Strength Pareto Evolutionary Algorithm. TIK-report (2001) Bader, J., Zitzler, E.: HypE: an algorithm for fast hypervolume-based many-objective optimization. Evol. Comput. 19(1), 45–76. MIT Press (2011)

From Ang to Steel-Wood Composite Cantilever Beam - Modern Translation of Roof Overhangs in Structural Performance-Based Design Philip F. Yuan(&), Jinxi Jin, and Li Han Tongji University, Shanghai, China {philipyuan007,jinjess,1810137}@tongji.edu.cn

Abstract. Roof overhangs is one of the spatial elements of traditional Chinese architecture. This paper takes roof overhangs in Archi-Union Architect’s project of Shuixidong Linpan Culture Exhibition Center in Anren, Sichuang as an example and explores the modern translation of roof overhangs under structural performance-based design. In the traditional wood structure, ang in dougong is based on lever principle and can achieve balance of deep roof overhangs. The steel-wood cantilever beam in the project inherits the structural principle and takes steel beam as a lever to achieve deep roof overhangs and improve joint performance. Material optimization, section optimization and joint optimization of steel-wood cantilever beam are realized under digital design tools. Modern translation of traditional space elements based on the structural principle makes us think the changes the design thinking and design method under digital technology. Keywords: Structural Performance-based design
Steel-wood composite cantilever beam
Dougong
Overturning moment
Material optimization

1 Introduction Driven by the latest digital technology, architectural digital design is developing toward performance-based design. Sets the optimal structural performance as goal, Structural performance-based design is the design process of the structural calculation, simulation and performance optimization (Yuan et al. 2017), which emphasizes a comprehensive consideration of structural logic and construction logic. Under the latest structural performance-based design thinking and design methods, what’s “the traditional element” we should inherit and how to inherit? In addition to form and abstract cultural symbols, if we considered “the traditional element” from the point of space which is widely discussed in modern architecture, “deep roof overhangs” was a major feature (Han 2014), which extended Chinese people’s living interface from the indoor to the space under the overhangs space, and then into the outdoor (Zhou 2014). Deep roof overhangs shows that timber has excellent performance in terms of horizontal stretching and creates a completely different shape and intention from the western stone structure system. Dougong, the structural conversion layer between roof system and column system, is a typical © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 17–26, 2020. https://doi.org/10.1007/978-981-13-8153-9_2

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symbol of traditional Chinese architecture. In the practice that extracted the form of dougong (such as imitation antique architecture and architecture modelled on forms), we can see the disconnection between traditional wooden frame and modern construction. Liang Sicheng once suggested that “traditional Chinese architecture seek new forms with modern new materials” (Liang 2001). In the design practice of Archi-Union Architect’s Shuixidong Linpan Culture Exhibition Center in Anren, Sichuang (Fig. 1), this possibility was explored in structural performance-based design thinking and design method. Ang, as a component of dougong, is used to achieve balance of roof overhangs. The structural rationality of ang lies in the use of level principle. Shuixidong Linpan Culture Display Center inherits ang’s lever principle and uses steel-wood composite material to achieves 5 m cantilever beam. It realizes the modern translation of traditional spatial elements “deep roof overhangs”.

Fig. 1. Shuixidong Linpan Culture Display Center in Anren, Sichuang uses steel-wood composite material to achieves 5 m cantilever beam

2 Ang and Deep Roof Overhangs This section explains the role of dougong in deep roof overhangs, the role of ang in the balance of dougong and the whole roof. At the same time, the appearance and development of ang are reviewed. As an indispensable structural component of dougong system under deep roof overhangs, the rationality and necessity of ang will be explained from the perspective of structural principles. 2.1

Dougong and Deep Roof Overhangs

In traditional Chinese architecture, the rafters used for roof overhanging can be regarded as cantilever beams. Cantilever beams have large negative bending moment at the support. The negative impact of bending moment is first reflected in the test of the material of wooden rafters, and then in the balance of dougong and roof at the joints on the top of columns. Dougong exerts an upward concentrated force on the rafters, greatly improving the internal force of rafters (Fig. 2). With the help of dougong, rafters can achieve deep roof overhangs without increasing cross-sectional area.

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Fig. 2. Dougong exerts an upward concentrated force on the rafters

The joint on the top of column of tradition wood structure is a hinge and cannot withstand bending moments. If roof overhangs is deep enough, negative bending moments will cause rotation of dougong to the outside. 2.2

Ang and Level Principle

The stability of dougong is achieved by ang, which uses level principle. Level principle is also called “condition of level balance”. To balance the lever, two bending moments on both sides of the support point must be equal. The weight of the rafter is placed at one head of ang and forms the power, which cause bending moments at the joint on the top of column. The other end of ang is pressed under the upper components, a resistance bending moments is formed for the pressure of the upper components. At the joint on the top of column, The resistance bending moment is balanced with the power bending moment, and achieve the stability of dougong (Fig. 3).

Fig. 3. Ang realizes roof overhangs using the level principle

2.3

History Development of Ang

In the early Northern and Southern Dynasties, A bucket of three liters (the simplest dougong) achieve the eaves by the rafter (Fig. 4(a)). With the increase of roof breaking and the depth of roof overhangs, in order to overcome the overturning force moment, the section of rafter needs to be increased, and one end of the rafter should be fixed in a comparatively strong part (Fig. 4(b)). At the end of Six Dynasties, ang appears. Based on the lever principle, ang can achieve steady and balanced of roof overhangs (Fig. 4 (c)) (Han 1988). At the end of the Six Dynasties, the golden hall of the Falongsi in Japan (Fig. 5, left) achieved deep roof overhangs with the help of huge ang, which is supported by the

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Fig. 4. Appearance of Ang to achieve steady and balanced of roof overhangs

stretched beam head (Han 1988). After the Northern and Southern Dynasties, in order to meet the needs of the layer component and highlight hierarchy, dougong development out of a bucket of five layers named 8 puzuo dougong. In Tang Dynasty, in the main hall of Foguangsi in Wutai Mountain (Fig. 5, right), beam head can only holds down the first and second layer huagong (component of dougong) and gong in the upper layers directly support the weight of the roof overhangs and have the tendency to lean forward. Ang is used in the upper layers to avoid the tendency to lean forward (Wang 1996).

Fig. 5. The golden hall of the Falongsi and main hall of Foguangsi

3 From Ang to Steel-Wood Composite Cantilever Beam In traditional Chinese construction, small crude wood is used to achieve the whole structure connected by Sunmao. Glued wood is widely used in modern wood structures, and the size and shape of glued wood is more flexible. At the same time, steelwood composite structure, as a type of modern wood structure, which combines the mechanical properties of the wood and steel and expand the practical scope of wood construction. Deep roof overhangs of Shuixidong Linpan Cultural Exhibition Center is achieved by steel-wood composite cantilever beam, which is a modern translation of ang based on level principle.

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Steel-Wood Composite Beam

In terms of material properties, the compressive strength, strength of extension, bending strength of wood is small. In the design of wood structure, in order to achieve the predetermined bearing capacity, the size of wood component isrelative large. The strength and elastic modulus of steel are about 20 times that of wood, and the density of steel is about 15 times that of wood. The components made of steel are often slender. Instable failure of steel structure is the main form of steel structure damage. However, wood components are not easily instable failure due to their large size. A suitable steelwood composite structural system can achieve ideal bearing capacity, bending stiffness and ductility of the entire structural system, which is practical and economical (Li 2016). Thin-walled steel and wood connect to each other through split bolt or high strength structural adhesive to form a steel-wood composite beam. Steel is the main force material for the composite beam, wood provide enough stiffness for the composite beam to avoid premature buckling instability of steel. Currently, form of steel-wood composite beam includes: the steel and wooden boards are webs of each other (Fig. 6

Fig. 6. Form of steel-wood composite beam

(a)), H-shaped sections (Fig. 6(b)(c)), T-shaped sections (Fig. 6(d)), box-shaped sections (Fig. 6(e)), etc. Some projects explore the use of steel-wood composite beam, including Shui’anshanju in China Academy of Art by Wangshu, ghost stone multifunctional hall in Japan (Gao 2018). 3.2

Steel-Wood Composite Cantilever Beam Based on Lever Principle

The innovative design of steel-wood composite cantilever beam was reflected in two aspects. On the one hand, the research of steel-wood composite beam is usually limited to a single component, lacking the research of combination of beams, combination of columns, the overall structural performance (Wang 2011). The steel-wood composite cantilever beam in the project consider its mechanical characteristics in the overall structure system and breaks through the limitations of current research on steel-wood composite beam. In the overall structure, round pipe steel column realizes transparent space. In terms of design process of roof, firstly, it is assumed that the roof is all steel structure. Then the beam with less stress are replaced by wood. The wood beam is checked separately. In the final roof design, the ring beam and beam at the corner are square steel beams, and the main beam is achieved by the innovative design of variable cross-section glulam beam and variable cross-section H-beam (Fig. 7).

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Fig. 7. The overall roof structure system

On the other hand, the steel-wood composite beams are designed in an innovative way to translate the principles of dougong. The H-beam is connected with the square steel ring beam by welding. To avoid torsion of the square steel ring beam, the design hopes to avoid bending moment generated by deep roof overhangs. H-beam uses an innovative design method to translate the level principle of ang in dougong. The steel-wood composite cantilever beam in the project takes full advantage of the difference stiffness of wood and steel. The steel beam in the upper part has large stiffness, provides upward concentrated force on the overhanging glulam beam and improves the negative bending moment of wood beam. The steel beam assists the timber beam to achieve a deep roof overhangs. At the same time, steel beam improve the bending moment at the beam-column joint using the level principle. One head of steel beam bear the weight of roof overhangs, the other head of steel beam bear the downward force of the internal wooden beam, achieving the balance of the whole roof (Fig. 8).

Fig. 8. Steel-wood composite cantilever beam realize roof overhangs using the level principle

The design of steel-wood composite cantilever beam takes into account the overall structural characteristics and the difference in mechanical properties of steel and wood. The bending moment of the cantilever beam is translated into tension in the upper steel

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beam and pressure in the lower square beam. Steel under tension avoids yielding and instability. Compressive capacity of the large cross section is fully utilized. As a level, steel beam make full use of high strength of steel to avoid sacrificing the space under the cantilever beam. The design integrates space, form, structure and material.

4 Design Optimization After establishing the basic design strategy, based on structural simulation analysis and manufacturing techniques, materials, components and joints are further optimized to achieve a rational spatial form. 4.1

Material Optimization

In traditional wooden structures, the proportion and angle of roof overhangs is clear regulated. Under digital technology, making full use of different stiffness and strength of steel and wood, the steel-wood cantilever beam can be flexibly adapted to different depths and angles of the roof overhangs. The length of the steel beam on the outside is adjustable to meet the cantilevered wood beams. And then the length of the steel beam on the inner side is adjustable to achieve the balance of the overall level. Based on different strength and stiffness of steel and wood, the design of steel-wood cantilever beam make full use of material. Under the appropriate proportion of the roof overhangs, bending moment of wood beam is in good condition (Fig. 9(a)). Under the condition of deep roof overhangs, the bending moment of wood beam is too large to beyond the material limit (Fig. 9(b)). By adjusting the length of steel beam in the lateral to adapted to timber beam, the internal force of wood beam is improved (Fig. 9(c)). Then by adjusting the length of steel beam in the inner side, the bending moment in the joint is improved using level principle (Fig. 9(d)).

Fig. 9. (a) Bending moment of wooden beam under normal overhang; (b) bending moment of wooden beam under deep overhang; (c) the internal force of wood cantilever beam is improved by steel beam in the lateral; (d) the bending moment in the joint is improved using level principle

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Section Optimization

Section optimization of the main beam consider the respective characteristics of steel and wood. Interaction of steel and wood should be taken into consideration as well. The H-beam is variable section H-section, and its height is gradually changed from 0 to 420 mm. On the one hand, it enables the neutral surface of the entire composite beam to achieve continuous gradual change. On the other hand, this is in accordance with the internal force of the material. The manufacture and fabrication process of modern glulam makes it suitable for structural performance-based optimization. Section size and section form can be optimized according to internal force. There are many factors which should be considered in the optimization of wood beam. The minimum height of the beam should be less than 200 mm. The shape of wood should meet the needs of the overall roof form, etc. However, topology optimization of Millepede provide guidance for wood section optimization (Fig. 10). Finally, the cantilever beam used in the project is a bidirectional variable cross-section beam- the upper surface is straight and the lower surface is curved, which comprehensively consider structural logic and construction logic. On one hand, the lower curved surface is the result of structural optimization. The height of section is in harmony with the bending moment and can reduce selfweight and save materials. On the other hand, the upper straight surface is beneficial for the construction of waterproof layer and insulation layer of the roof and the overall roof form. Bi-directional variable cross-section beam is simple and reasonable, it realizes deep roof overhangs with the least amount of material. The overall shape is lightweight and novel. Combine the H-shaped steel beam with variable section and glulam beam with variable section, the difference in strength and stiffness between steel and wood is fully utilized and finally deep roof overhangs from 3 m to 5 m is achieved.

Fig. 10. Topology optimization of Millepede provide guidance for wood section optimization

4.3

Joint Optimization

In traditional Chinese architecture, sunmao is widely used for timber connection. In terms of structural performance, sunmao cannot bear heavy load due to low rigidity. With the development of new technology, high-strength metal joints are widely used for timber structure. Steel plate insertion connection is used in between the wood beam and the steel beam in this project (Fig. 11), the design of the novel connection is reasonable, fireproof and beautiful, force transmission is clear and good rigidity is achieved. Also it is easy to be constructed. Welding between steel beam and steel column can increase the stiffness of beam-column joints.

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Fig. 11. Steel plate insertion connection is used in between the wood beam and the steel beam

5 Fabrication and On-Site Assembly Digital model directly guides factory prefabrication and on-site construction. A designconstruction process based on data model is explored. Based on the complete geometric data of the digital model, digital factory prefabricate and numbered non-standard timber components and steel components. The components are encoded in the factory and transported to the site to assemble. On-site construction is based on the data model, which effectively improves the construction efficiency, realizes the control of cost and time.

6 Summary Using steel-wood structure to explore the space of roof overhangs is a modern expression of traditional Chinese architecture under contemporary technology. Innovation structural system, component form and joint design of steel-wood structure expand the formal language and application range of timber structure. Modern technology opens up more possibilities for traditional Chinese roof. In the project of Shuixidong Linpan culture display center, the lightweight and elegant roof reconstructed the intention of Chinese traditional roof, combine traditional Chinese architectural elements and the forefront nonlinear aesthetic. Large-scale Roof overhangs creates a profound space artistic conception. The roof floats on the open space of the natural environment, formed the unique experience of space and architectural language. At the same time, in the project, modern translation of traditional space elements based on the structural principle makes us think the changes the design method and design thinking under digital technology. Under digital technology, the structural performance-based design gradually replaces “formalism” design. For the inheritance and innovation of traditional architecture, we should deep mining the basic principle of tradition architecture and combine new materials, new technology, new technology to achieve innovation and development.

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References Han, B.: Architecture Mother Tongue: Tradition, Region and Homesickness. Life, Reading, Xinzhi Sanlian Bookstore (2014) Zhou, Y.: Spatial Expression of Horizontal and Vertical Wood Structures in Chinese Traditional Architecture. Time + Architecture (3) (2014) Liang, S., Fei, W., Liang, C.: Image Chinese Architecture History (2001) Yuan, F., Chai, H., Xie, Y.: Towards the performance integration of architecture and structural design. Arch. J. (11), 9 (2017) Han, B.: The Origin and Development of Dougong. Ming Clerical Bureau (1988) Wang, L.: Saying “Ang”. Anc.T Arch. Technol. (04) (1996) Li, D.: Research on flexural behavior of steel-wood composite beams (2016) Gao, J.: Research on the spatial shape design of modern wooden structure roof (2018) Wang, X., Chen, Z., Bai, J., et al.: Research status and development prospect of steel-wood composite structure. In: 2011 National Steel Structure Academic Annual Conference Proceedings (2011)

Rocky Vault Pavilion: A Free-Form Building Process with High Onsite Flexibility and Acceptable Accumulative Error Chengyu Sun(&) and Zhaohua Zheng College of Architecture and Urban Planning, Tongji University, Shanghai, China [email protected], [email protected] Abstract. As huge flexibilities occur on the real construction site, participation of human builders is still necessary even if the project is carried out with a high level of digital fabrication technology. Unpredictable onsite issues are impossible to be completely programmed into the computer, but it can be perfectly solved with human builders’ skills and experience. In this paper, a fabrication project –namely Rocky Vault Pavilion– uses a hybrid fabrication paradigm to take advantage of both the human manual operation and real time computer guidance in an onsite free-form building project through a cycling humancomputer interactive process. The demonstration uses a Hololens-Kinect system in a framework of typical project-camera. As human builders perceive, decide, and operate the irregular foam bricks in a complex onsite environment, the computer will keep updating the current free-form through 3D scanning and prompt the position and orientation of the next brick through augmented display. From a starting vault, the computer always fine tunes its control surface according to the bricks installed gradually and keeps following a catenary formula. Thus, the hybrid fabrication actually benefits from the flexibility of human judgements and operations, and an acceptable accumulative error through computer guidance concerning the structural performance and formal accuracy. Keywords: Computer aided interaction
Mixed reality

architectural

design




Human-computer

1 Introduction In the early development of digital fabrication, robotic arms are used to fabricate components and install them to the right positions and orientations with much better accuracy than traditional manual fabrication. However, designed for controlled factory environments, these systems can hardly provide the human builders’ flexibility dealing with various uncertainties onsite (Bock 2007). Thus, how to improve the paradigm for onsite fabrication becomes one of the hotspots in digital fabrication researches. There seems to be three tracks of explorations to improve either the accuracy or flexibility or even both, namely Guided Manual Fabrication, Adaptive Robotic Fabrication, and Hybrid Fabrication (Table 1). In a Guided Manual Fabrication paradigm, human builders will have the visual guidance about the current operation on real objects through augmented displays. It is © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 27–36, 2020. https://doi.org/10.1007/978-981-13-8153-9_3

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still ultimately the builders, who solve all the onsite uncertainties. The performance of manual operations can be improved through the visual guidance. Its early applications (Fig. 1A) can also be found in some onsite assembling projects (Reiners et al. 1998; Tang et al. 2003). Although the guidance is very helpful in many cases, without realtime evaluation on the effects of manual operations for its generator, they can only provide rough guidance such as objects’ relationship in a layout, directions, orders, etc. rather than high precision spatial hints essential for accumulative error control in the case of a sequential fabrication process. In an Adaptive Robotic Fabrication paradigm, robotic machines that are controlled by a man-made program handle all the uncertainties onsite through its sensors evaluating the operation effects and the changes of the environment in real time. With a 3D scanner attached on the robotic arm (Fig. 1B), the system can better manage the uncertainties caused by slight size differences among the regular bricks (Dörfler et al. 2016). Although the system manages to reduce onsite uncertainties to some extent, its flexibility is still greatly constrained by the complexity of programming. In a Hybrid Fabrication paradigm, human builders and programmed machines interact with each other throughout the process. The former manages the onsite uncertainties with manual decisions and operations. The latter keeps offering visual guidance in a real-time cycle according to any aims preset in the program, such as to keep accumulative errors as low as possible. The visual guidance is provided through a set of technologies such as 3D scanning, point cloud matching, parametric model refreshing, artificial decision making, spatial projecting, various performance simulating, etc. Typically, in a sequential fabrication process, the above interaction makes it possible to compensate the errors from previous manual operations with the guidance for following operations (Zoran et al. 2013). As a preliminary sample in building fabrication, Yoshida’s system (Yoshida et al. 2015) continually scans the whole pavilion of chopsticks (Fig. 1C), refreshes its stress distribution, and projects guidance of 2D patterns in a manual-invoke rate while still allowing human builders to make their own decisions according to both the guidance and the onsite uncertainties. In this paper, a hybrid fabrication project with a high rate of interaction is introduced, which tries to build a free-form pavilion of irregular foam bricks according to structural optimization result. Firstly, a Kinect-Hololens system with a WIFI-based workflow provides an almost real time interaction and a more friendly 3D visual guidance. Secondly, due to the involvement of the builders, the huge uncertainties from

Fig. 1. (A) AR screw-fixing instruction with and without occluding door (Reiners et al. 1998); (B) Mobile robotic brickwork (Dörfler et al. 2016); (C) STIK pavilion (Yoshida et al. 2015)

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Table 1. Comparison of digital fabrication paradigms. Paradigms

Human Onsite involvement flexibility Guided manual Yes High fabrication No Low Adaptive robotic fabrication Hybrid Yes High fabrication

Equipment cost Low

Accuracy Accumulative error Low Linear

High

High

Constant

Building unit Regular & irregular Regular

Low

Medium

Almost constant

Regular & irregular

irregular bricks are solved easily. Thirdly, a control surface keeps refreshing itself according to the bricks installed and the structural performance, which generates the guidance and leads to an acceptable accumulative error finally.

2 Methods Human builders are more flexible than programmed computers in dealing with uncertainties onsite. However, computers are more powerful than human builders in finding the most structure-efficient form and keeping its accumulative error at an acceptable level. To explore the above Hybrid Fabrication paradigm, a team of students set up a human-computer interactive process (Fig. 2) that uses irregular foam bricks to

Fig. 2. Human-computer interactive process

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simulate irregular shapes of building waste found in the real world in order to build a structure-optimized vault pavilion under computer guidance in almost real time. During the interaction process (Fig. 3), the computer system calculates the most suitable brick to install currently from a brick pool and its visual guidance. After seeing the guidance through a Hololens helmet, a human builder makes his own decision on installation details and executes the operation subjectively. With every manual operation, the computer scans all the bricks installed through a Kinect automatically and recalculates the current form of the design as a parametric model. The updated form will be used in the following brick selection and visual guidance generation (Fig. 4). Notably, unlike the design in traditional building process –which is fixed before fabrication–, the parametric model in hybrid fabrication process is only a start point of design which holds all the designer’s aims and site’s constrains. During the interactive process, the design can update itself according to the parametric model and results gradually made by the builders while following the aims and constrains tightly. In this way, the human builder’s flexibility upon uncertainties onsite and the computer’s accuracy in accumulative error control are both approached.

Fig. 3. The hybrid fabrication process of the project

2.1

Designing the Vault Pavilion and Matching the Augment View

(1) Generating the 3D form of the vault pavilion with RhinoVAULT The project starts with a 2D pattern given by the designer, which describes the supports and the openings. Afterward, a 3D form of the vault pavilion is generated by

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Fig. 4. A scenario of the project

RhinoVAULT. The vault pavilion stands on four feet that supports the weight of the vault itself which include three big feet and a smaller one at the center (Fig. 5). The construction of the vault starts from the feet simultaneously and finally converges at the top. In order to orient the coordinates of the point cloud by a scanner from the camera space to the world space, seven infrared-perceivable markers are placed around the vault. At one time, in whatever perspective, at least one of them should be detected by the Kinect. (2) Matching the digital vault with the real site through Hololens Before fixing the markers on the ground, the builders could preview the vault’s shape overlapping with the surrounding environment displayed in Hololens (Fig. 6) through which the builders can have a rough perception of the relationship between the vault and the site. The markers are located with a full-size printed plan on the ground according to the coordinates in Rhino.

Fig. 5. The vault pavilion generated

Fig. 6. A view in hololens

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Calculating the Guidance About the Next Brick

(1) Finding the position of the next brick on the vault The foam bricks are proposed to be installed in a layer by layer manner. There is always a marginal layer under operation, which is at the top of the last built layer or the ground. The rough position of the next brick is calculated as the initial position for the following physical simulation. It follows a set of conditions that the brick should be closest to the builder according to his position from the helmet and it should be next to a brick installed in the marginal layer if there is. If the current marginal layer is full of bricks, it becomes a built layer and a new marginal layer is ready for installation. (2) Scanning the bricks for a sample pool A set of foam bricks are scanned with a constructed light 3d scanner and they serve as a sample pool for the brick selection in the next step. The size of the sample pool should be balanced with the accuracy, the fluctuation of the size of bricks, and the efficiency. (3) Selecting the brick from a sample pool with ICP algorithm For each position to install a brick, a sample pool of 24 pre-scanned foam bricks searches for a suitable brick. An algorithm called Iterative Closest Point (ICP) is used to evaluate the fitness level between the installed surrounding bricks and the alternative brick from the pool. Finally, the brick with best fitness level will be selected. (4) Calculating the orientation of the brick with Kangaroo With a selected foam brick in a position, its orientation is calculated through physical simulation in Rhino Kangaroo. When it keeps the brick unchanged and pushes the brick to the pre-installed surrounding bricks to a stable status, the orientation of the next brick is found. 2.3

Installing the Irregular Foam Brick

(1) Perceiving the guidance and the site conditions through Hololens The builders can perceive the guidance and the real conditions of the site through the helmet at the same time. A program for Hololens display is coded in a Unity3D project, which shares the same coordinate with the digital model in Rhinoceros. The updated geometry in the computer would be transmitted to the helmet though a server. (2) Making subjective decisions on the operation It is the human builder who installs the bricks according to the computer guidance (Fig. 7). The positions of the brick could be slightly adjusted by the builder in case there are subjective judgments according to the onsite conditions which are not included in the calculation. (3) Operating the irregular foam bricks The builder can slightly move or rotate the brick to the suitable position. Acute changes of the position and the orientation would break the loop (Fig. 8).

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Fig. 7. Installation of a brick: In the left 3*3 grid, The blue ones are bricks installed on the marginal layer; The white ones are other layers installed.

Fig. 8. The builder is installing one brick according to the visual guidance in Hololens.

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2.4

Recalculating the Vault

(1) Scanning the actual positions and orientations of the installed bricks through Kinect After one layer is installed, the bricks would be scanned by the Kinect together with its closest markers so that the point cloud coordinate could be oriented from the camera space to the Rhino space. An ICP calculation of the point cloud with the corresponding bricks is executed to update the bricks’ positions. The height of marker should also be updated according to the height of the bricks in order to descend the deviations caused by deflection. (2) Checking the deviation and updating the vault After being scanned, the digital model is checked with its deviation from the real vault installed. If a threshold is reached, the 2D pattern would be trimmed by the projection of the current marginal bricks. The original vault would be replaced with the updated vault recalculated from the trimmed pattern with RhinoVAULT following a catenary formula (Fig. 9).

Fig. 9. Ten versions of vault recalculated

3 Results The final free-form vault (Fig. 10) is stable with non-rigid connections between the adjacent bricks which indicate that the hybrid fabrication paradigm proposed in this paper is feasible. Its deviation does not noticeably increase as the height increases (Fig. 11), which means the accumulative error is almost constant within an acceptable level.

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Fig. 10. The final vault

Fig. 11. Deviation analyze

4 Conclusions and Future Works Through an interactive process, a project following Hybrid Fabrication paradigm takes both advantages of the high flexibility from human operations and acceptable accumulative error controlled through computer guidance. The position of the foam brick is calculated by computer and the guidance is suggested to the builder though an augment helmet. After one layer of installation, the bricks on site would be scanned and the design would be updated to adapt the renewed site as well as the builder’s adjustments. This paradigm effectively restrains the accumulative error and increases the speed of calculation. Meanwhile, through recursive updates, final vault pavilion achieves the most approximation between real construction and its digital counter-part.

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However, there are still some anomalies to discuss, such as the difference between passive deviations caused by human operation and the active adjustments which may be a key question for the Hybrid Fabrication paradigm. In the future, some comparative experiments will be conducted to investigate the limitation of the paradigm. Meanwhile, real small-scale projects and a multi-thread arrangement of a building team will be explored. For irregular bricks with heavy weight and larger size, robot arms are going to be considered to help builders deliver and hold the bricks. Also, problems with supporting suspending parts in the real size will be solved by optimizing structures. Acknowledgements. This study is supported by the National Key Research & Development Program of China (Grant No. 2016YFC0700200) and a project of National Natural Science Foundation of China (Grant No. 51778417).

References Bock, T.: Construction robotics. Auton. Robots 22(3), 201–209 (2007) Dörfler, K., Sandy, T., Giftthaler, M., Gramazio, F., Kohler, M., Buchli, J.: Mobile robotic brickwork. In: Robotic Fabrication in Architecture, Art and Design 2016, pp. 204–217. Springer International Publishing (2016) Reiners, D., Stricker, D., Klinker, G., Müller, S.: Augmented reality for construction tasks: doorlock assembly. Proc. IEEE ACM IWAR 98(1), 31–46 (1998) Tang, A., Owen, C., Biocca, F., Mou, W.: Comparative effectiveness of augmented reality in object assembly. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 73–80. ACM (2003) Yoshida, H., Igarashi, T., Obuchi, Y., Takami, Y., Sato, J., Araki, M., Miki, M., Nagata, K., Sakai, K., Igarashi, S.: Architecture-scale human-assisted additive manufacturing. ACM Trans. Graph. (TOG) 34(4), 88 (2015) Zoran, A., Shilkrot, R., Paradiso, J.: Human-computer interaction for hybrid carving. In: Proceedings of the 26th Annual ACM Symposium on User Interface Software and Technology, pp. 433–440. ACM (2013)

Study on Optimizing the Cold-Adapted Form of Large Space Public Buildings Yong Huang, Longwei Zhang(&), and Minyi Zhang School of Architecture and Urban Planning, Shenyang Jianzhu University, Shenyang 110168, China [email protected] Abstract. Introduction Aiming at the adaptability of large-space public buildings in severe cold regions of China, this paper studies the design of site environment and form. Simulations of Environmental Factors Through the numerical simulation method of human-computer collaborative site environment factors, it makes a comprehensive quantitative analysis of the wind environment, light environment, thermal environment and other factors in the built area, and predicts the correlation between buildings and environment. Climate Adaptation Conditions Climate is the most important factor affecting building shape of environmental conditions. The most influential climatic factors are sunshine, temperature, wind, rain and snow. The feedback from buildings to these environmental factors takes on different forms according to different regions. This study mainly considers the cold adaptation factors of cold regions. Topological Optimization of Architectural Form Combined with engineering practice, through the application of multi-objective optimization algorithm and parameter coupling analysis, the interactive feedback and multidirectional link between building parameters and environmental performance numerical simulation analysis can be realized. Finally, several comparison schemes are formed. The architect provides a visual dynamic model, which realizes the scientific judgment and optimal decision-making in the design process. Conclusion Based on digital technology, a method of “simulationcalculation-optimization” for shape and topology optimization of large-space buildings in cold regions is proposed, and a systematic method of shape optimization of large-space buildings with goal orientation is constructed. Keywords: Large space Topological optimization


Architectural form
Cold adaptation

Environmental factors

1 Introduction In China’s cold regions, winter is long, extreme climate is frequent, environmental carrying capacity is limited, building energy consumption is more prominent than other climate regions. With the continuous improvement on urbanization level, people’s special social demand for large-space public buildings is increasing day by day. © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 37–48, 2020. https://doi.org/10.1007/978-981-13-8153-9_4

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Therefore, according to the cold climate characteristics, it is of great theoretical and practical significance to study the adaptability and optimization methods of large-space public buildings for promoting the development of green buildings. In this study, the method of “simulation-Calculation-optimization” was used to solve the optimization problem of the cold-adapted form of large space buildings. Relying on the Jilin People’s Grand Theatre located in the cold region of northeast China, we focus on optimizing the cold-adapted form of the non-linear roof composed of two-layer hyperboloid (Fig. 1).

Fig. 1. Site-plan of Jilin People’s Grand Theatre

2 Simulations of Environmental Factors In the past, traditional site analysis in the design process often showed some drawbacks, such as too subjective, not facing the real environment objectively, insufficient quantitative analysis and so on. With the development of powerful data processing and spatial analysis capabilities of GIS, the efficiency of designers and the scientificalness of environmental analysis can be improved. The spatial analysis of GIS, CFD wind direction analysis and Ecotect light simulation software system can fully analyze the site conditions, so that when we design the site, we can effectively quantitatively analyze the objective and real data information, increase the objectivity and scientificalness, and reduce the subjective assumption.

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Climate Factor Simulation

Ecotect is a comprehensive technical performance analysis aided building physical simulation tool. It can be simulated from solar radiation, sunshine, lighting, shading into indoor and outdoor thermal radiation, wind field and so on. It covers many aspects of building physical environment, such as sunshine, light environment, wind environment, economy and visibility. The simulation and analysis of light, heat and wind environment in Jilin city are based on Ladybug under Grasshopper platform. The corresponding calculation module is compiled with Ladybug. The annual comfort map and comfortable light environment interval map, temperature and solar radiation visualization chart and temperature of Liaodong Bay can be obtained by inputting the corresponding EPW data of solar path, sunshine and wind environment in Jilin city. Humidity chart and wind rose chart (Fig. 2). The maximum energy consumption of cold buildings is thermal energy consumption. The large span and large volume of the Grand Theatre make the outer surface area of the building increase, thus increasing the chances of convective heat transfer between interior and exterior, resulting in the increase in building thermal energy consumption, especially in the long and cold winter, which will lead to the further increase in building heating energy consumption. The indoor space of the Grand Theatre is large and its functions are complex. If air conditioning system is used to adjust the indoor wind environment, it will take a huge amount of energy to reach the standard. Therefore, it is particularly important to the early stage of large space architecture design to quantify the wind environment, light environment, thermal environment and other factors in the built area, and to predict the relationship between architecture and environment. 2.2

Site Comprehensive Factor Simulation

Through the systematic description of topographic maps, contour maps and corresponding topographic data by GIS software, the corresponding basic analysis is carried out. The elevation, slope, water system, vegetation, ecosystem and external restrictions of the site are analyzed and evaluated objectively and truthfully. According to the generated three-dimensional topographic basic data, the site environment is analyzed, and the most suitable site, the building form parameters of the ground, is obtained. The topographic analysis maps made by GIS topographic analysis software clearly show the relationship between land and water, and the general relationship between land and land slope. Site design is often not so accurate in choosing the scope of construction land. Quantitative analysis of construction land makes the design more rational and provides more scientific guidance of architectural design in the early stage. GIS topographic analysis software can avoid the problem of inadequate consideration of site factors, can maximize the use of local natural environment and climate conditions conducive to the establishment of buildings adapted to nature, reduce the input of active energy consumption.

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Fig. 2. a. Sunshine track of Jilin, b. Dry bulb temperature (°C) – Hourly in Jilin, c. Direct normal radiation (Wh/m2) – Hourly in Jilin, d. Wind rose of Jilin

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Location Selection and Architectural Layout

Site analysis is the main factor affecting the orientation and shape relationship of the building, and is the process of determining the orientation, shape design and environmental connection of the building. In site design, the selection of building location is mostly a perceptual judgment, and there is no real rational analysis of the base environment, slope direction, hydrological vegetation and other data. Reasonable building shape can not only reduce the impact on the surrounding environment, can really integrate into the environment, but also create a good site external climate environment. Architectural layout is the expression of architectural form of macro scale, describing the organizational relationship of architectural groups. Optimizing the layout of large space buildings is of great environmental significance. On the one hand, a reasonable layout system of building groups and space formation can shape a good external space environment of buildings, on the other hand, it can also play an active role in improving the quality of urban environment. From the point of view of the relationship between the figure and the base, the architectural layout includes two basic elements: the building monomer and the open space between the buildings, which complement each other and are inseparable. The purpose of layout optimization of large space buildings is to coordinate the relationship between buildings and open space by adjusting the layout of buildings.

3 Climate Adaptation Conditions Climate is the most important factor affecting building shape of environmental conditions. Different climates put forward different requirements for building shape. The most influential climatic factors are sunshine, temperature, wind, rain and snow. The feedback from buildings to these environmental factors takes on different forms according to different regions. This study mainly considers the cold adaptation factors of cold regions. 3.1

Light Adaptability

Lighting environment is one of the most influential factors of building shape, mainly including solar radiation and lighting. In winter, large-space public buildings in cold regions should obtain as much solar radiation as possible to save building heating energy consumption, while in summer, selective shading should be carried out to avoid the indoor environment discomfort caused by local space exposure. Therefore, the main objective is to achieve passive light adaptability of building in winter and summer by adjusting building shape. The evaluation index of building light adaptability is mainly the amount of sunshine radiation obtained by buildings (Fig. 3). The amount of sunshine obtained by different parts of buildings is different. Therefore, it is necessary to accumulate the amount of sunshine radiation obtained by building surface when calculating the total amount of sunshine obtained by a specific building form. The calculation of this

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process is so heavy that it is difficult for manpower to complete. Therefore, it needs to be measured and calculated by sunshine performance simulation software [1].

Fig. 3. Solar radiation rose of Jilin

3.2

Thermal Adaptability

Temperature is an important part of environmental conditions, and it also has a significant impact on building shape. Temperature factors reflect a strong periodicity and regionality, and the great differences between temperature in different regions and seasons create the diversity of architectural forms. For example, in the cold areas of the north, thick and concentrated building forms are often adopted to avoid heat loss, while in the south, flexible building forms are adopted to enhance ventilation effect and avoid building overheating. Temperature adaptability of building shape is one of the important indexes of building shape optimization. The interface area between the building and the outdoor space should be reduced as much as possible under the condition of sufficient use space. This characteristic is embodied in the shape coefficient of the building. The core objective of temperature adaptability optimization is to adjust the shape coefficient of the building to obtain the smallest possible shape coefficient. 3.3

Wind Adaptability

Wind is an important climatic factor affecting the stability of architectural form. Wind is a non-linear fluid system, which has many parameters such as direction, velocity and pressure, and its influence mechanism on building shape is complex. The influence can be summarized as three types: first, when the wind acts on the building interface, it produces wind pressure, which makes the building envelope and supporting structure subject to wind load; second, when the wind contacts the building, it is affected by the reaction of the building, the direction and speed change, and the wind field around the building is formed; third, when the wind acts on the building, it will empty with the ventilation holes of the building interface and the internal space. Air exchange produces ventilation effect [2]. The adaptability of building form to wind environment is embodied in three aspects: reducing the damage of wind to building envelope and supporting structure, avoiding unfavorable wind environment and enhancing natural ventilation effect.

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The relative quantitative indexes include wind pressure, wind speed around building and ventilation exchange rate. 3.4

Snow Adaptability

Rainfall, snow and other precipitation phenomena also have a significant impact on the building shape. The adaptability of the building to precipitation is mainly reflected on the impact on the roof shape. In areas with scarce precipitation, roofs are gentler; in areas with abundant precipitation, roofs are steeper. In cold areas, because of the large amount of snow, the lower temperature and the difficulty of snow melting, the roof slope is larger. The influence of snow on building shape is mainly realized by load. Rainfall belongs to dynamic load and its value is generally smaller. Snow belongs to static load, and can be accumulated. If the snow exceeds a certain limit, it will cause great harms to the safety of building structure. There is a large amount of snow in cold area. Adjusting the shape of large space building to make the roof smooth and continuous and obtain the best inclination angle is conducive to eliminating the snow on the top and reducing the snow load of the building. In cold and snowy areas, snow loads need to be calculated to avoid structural damage caused by excessive snow cover.

4 Topological Optimization of Architectural Form The essence of topology is to study the invariant nature of objects in altered condition. Therefore, the main focus of application of the method of topology in architecture design is the operation method of continuous change of form and the invariant characteristics between building elements. The shape optimization of large-space buildings follows the basic principle of “simulation-calculation-optimization”, that is, calculating the shape objectives of large-space buildings on the basis of parametric topological model, and then using optimization algorithm to carry out multi-dimensional optimization. If the optimization scheme meets the design requirements, the process will end; otherwise the optimization cycle will continue [3]. 4.1

Building Topology Model

Topology, born out of geometry, is a branch of mathematics that studies morphological or spatial continuity. Topological theory tries to break the thinking frame of European geometry and create some unique non-linear architectural forms and spatial patterns from the perspective of spatial relations. As Klein, the founder of topology, said, “We should focus on how objects change under the basic nature of a population, rather than on the object itself.” Topology studies the properties of geometric figures that remain unchanged under continuous deformation. Based on the principle of topology, the proposed topological model uses nodes and associations to express the topological structure of architectural form, and uses them as variables to control the form, so as to obtain greater degree of freedom, controllability and simulation efficiency. The topological structure of architectural form is the logical

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structure formed by the connection between the nodes that control the generation and change of architectural form. Topological structure is the basic link to building morphological topological model. After defining the number, state, location and sequence of nodes and associated variables, the topological structure becomes the topological model of expressing architectural morphology. Variables such as shape, size, height, proportion and so on, which affect the building formation and evolution, can be called control variables of building form. Parametric design makes architectural creation an open mode with high degree of freedom and extensibility. Parametric design also endows the scheme the ability of automatic optimization. Through genetic algorithm, annealing algorithm and other optimization algorithms, it can drive the automatic evolution of the scheme for specific conditions, and make the scheme closer to the expected goal of creation [4]. In the shape optimization of Jilin People’s Grand Theatre, its shape is summarized as the topological graph shown in Fig. 4 through the parametric platform. The change of the coordinates of any node will cause the topological deformation of the building, and the topological optimization of the building is realized by adjusting the coordinates of the nodes. The constraints on building shape optimization are mainly the spatial layout of the building. The key to optimization is to adjust the building shape accurately so that it can achieve good environmental adaptability while fully satisfying the requirements of function and space.

Fig. 4. Topological model of the architectural form

4.2

Application of Digital Algorithms

The shape optimization of large space buildings includes many objectives, and cold adaptation is an important aspect. When determining the objective function of optimization problems, specific problems should be analyzed, and the most typical and dominant indicators should be chosen as the objective function according to the objective conditions such as different regions, different environments, different building types and different use requirements. Multi-objective optimization problems should also ensure that the dimensions of each objective are as clear as possible to avoid nesting and excessive interference. The shape optimization of large space buildings is a typical multi-modal problem with many variables, large solution space and complex constraints. Heuristic algorithms have great advantages in solving such problems. The research shows that the genetic algorithm has obvious advantages in dynamic adaptability, probabilistic search strategy and not easy to fall into local optimum when there

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are many variables. Nowadays, multi-objective genetic algorithm is also mature, so we use genetic algorithm as the optimization algorithm of large space building layout. Genetic algorithm is one of the most widely used heuristic algorithms with the best comprehensive performance. It has the advantages of low continuity of objective function, global search to avoid falling into local optimum and fast formation of multiobjective Pareto solution set in architectural form optimization [5]. In this paper, multiobjective genetic algorithm is used to optimize the sustainable performance of building form. The optimization tool is Octopus, a multi-objective genetic algorithm tool based on Grasshopper platform. It encodes genes by real numbers, and its genetic strategy and evolutionary parameters can be set artificially. In addition, this tool can also realize the visibility and controllability of the optimization process. Genetic algorithm has the characteristics of self-organization and self-adaptation, fast speed, high efficiency, wide search range, and it is not easy to fall into the local optimal solution. It has innate advantages in solving the problems of green building shape optimization, such as many variables, huge solution space and so on [6]. 4.3

Man-Machine Cooperative Optimization

The method of topological optimization of building shape is to adjust the topological composition of the shape, enhance the environmental adaptability of the building, and improve the green performance of the building itself, so as to achieve the goal of energy saving and environmental protection. It is based on multi-objective balanced optimization. The coordinates of each control vertex of a building form are taken as shape control variables. The objective of optimization is to adjust the shape of the building more conducive to snow removal of winter and maximize sunshine (Fig. 5), maximize the space efficiency of the building, and control the shape coefficient of the building. In operation, the connection between nodes is allowed to be curved, that is to say, the architectural form is allowed to change greatly. Although this change is essential at the architectural level, it only adjusts the type of connection with the topological level, which belongs to local changes. This optimization strategy has a higher degree of freedom, a larger solution space and a greater opportunity to find a better solution.

Fig. 5. Adjust the shape to adapt snowfall and bearing

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In the architectural form optimization problem, the optimization objectives are independent and the interaction mechanism is complex, so it is difficult to calculate the weight by the conventional mathematical formula. After reaching a predetermined optimization goal or a predetermined number of iterations, the multi-objective genetic algorithm will generate Pareto boundaries containing a series of feasible solutions according to the optimization objective. The schemes located on the boundary are all optimization schemes to achieve the objectives of building space utilization and environmental adaptability. These optimization schemes do not necessarily perform best on a particular optimization objective, but they achieve the balance of each objective. In the process, the creator can make a comprehensive judgment on the optimization goal according to his personal demands, and finally choose the scheme which accords with the design intention. This process integrates the rational thinking and perceptual judgment of the designer on the basis of the highly accurate calculation of the optimization goal by the computer. It gives full play to the fast computing ability of the computer while respecting the subjective wishes of the designer, and achieves the balance between the two objectives. In Jilin People’s Grand Theatre, there are three architectural form variables to modify the cold adaptability: the first variable is the height of the central hall, which ranges from 30 to 45 (m). The second variable is the height of the eaves, including the eave of the main entrance and the eaves on both sides. The eave height of the main entrance ranges from 15 to 25 (m), and the eaves height of the both sides ranges from 2 to 10 (m). The third variable is the updip angle of the roof, which ranges from 2 to 7.5°.

Fig. 6. Solar radiation analysis in winter and summer

Based on Grasshopper platform and Octopus multi-objective genetic algorithm, the building shape optimization of Jilin People’s Grand Theatre was carried out to improve the building’s adaptability to sunshine, temperature and precipitation. Finally, four optimization schemes are generated as shown in Figs. 6 and 7: scheme 1 has the best illumination adaptability, scheme 2 has the best shape coefficient, scheme 3 has better wind adaptability, and scheme 4 achieves the comprehensive optimum of each objective. Through the man-machine collaborative optimization of scheme 4, the effect of photothermal wind in the Grand Theater is further improved, and the quality of photothermal environment is significantly improved (Fig. 8).

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Fig. 7. CFD analysis of dominant wind direction in winter

Fig. 8. Jilin People’s Grand Theatre a-Aerial view b-Exterior

5 Conclusion Based on the principle of “simulation-calculation-optimization”, a systematic method of objective-oriented large-space architectural form optimization is constructed by taking large-space architectural form as the research object and aiming at realizing the cold adaptability of large-space architecture. This method is of great theoretical and practical significance in promoting the development of large space buildings.

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Acknowledgement. This research was supported by the Key Program of the National Natural Science Foundation of China (No. 51738006) and the Program of Science and Technology of Ministry of Housing and Urban-Rural Development (No. 2017-K1-007). The research was also supported by the Basic Scientific Research Project of Institutions of Higher Learning in Liaoning Province (No. LJZ2017024).

References 1. Zhang, L.W., Zhang, L.L., Wang, Y.T.: Shape optimization of free-form buildings based on solar radiation gain and space efficiency using a multi-objective genetic algorithm in the severe cold zones of China. Sol. Energy 132(6), 38–50 (2016) 2. Zhang, L.W., Zhang, L.L., Huang, Y.: Optimization research on enclosing system of largespace building based on digital technology. J. Shenyang Jianzhu Univ. Nat. Sci. 31(3), 474– 484 (2015) 3. Jin, J.T., Jeong, J.W.: Optimization of a free-form building shape to minimize external thermal load using genetic algorithm. Energy Build. 85, 473–482 (2014) 4. Huang, Y., Zhang, L.W.: Parametric design and completion of the architectural creation. New Archit. 162(5), 31–35 (2015) 5. Caruso, G., Kämpf, J.: Building shape optimisation to reduce air-conditioning needs using constrained evolutionary algorithms. Sol. Energy 118, 186–196 (2015) 6. Kämpf, J., et al.: Optimisation of building’s solar irradiation availability. Sol. Energy 84, 596–603 (2015)

Applying Lost Foam Casting Aluminum and Computational Design into the Fabrication of Complex Structure Joint Tianyu Guo(&) Bartlett School of Architecture, UCL, London, UK [email protected]

Abstract. Lost foam casting employs polystyrene as the pattern material, and has been used for architecture construction industries extensively in the past. However, when it comes to being a pattern material, polystyrene is restricted with regards to geometry development. Using a series of comparison experiments for the numerous types of foam, it was found that a type of soft and elastic foam tube, which was able to be cut and deformed flexibly, had suitable physical characteristics for lost foam casting, which is a low-tech and popular fabrication method with a simple process and high production efficiency. On the other hand, recyclable aluminum was the pouring metal material used, due to its high availability and low price. Following this, based on the material behavior, the possible language of foam tube was explored. By cutting, deformation and different variations, foam tube is able to be developed for a number of organic geometries. Besides, due to foam tube’s characteristics, it is able to be morphed into a number of ranges and angles, and this is useful when it comes to building a joint system, joined with other types of pipe material, and subsequently architecture design. Simultaneously, the outcomes of Topology Optimization generation were used to control the geometry design during the conceptual design step of large scale complex structures, with sound structural rationality as well as aesthetic. By introducing this new design methodology, this thesis emphasizes the rethinking of the relationship between joints, complex structure and architecture from the view of joints, and advocates architects to extend the boundary of architecture continuously. Keywords: Lost foam casting
Materiality
Computational design methodology
Architecture joint
Complex structure

1 Introduction There has been a quick progression in the field of computer aided design tools in recent times, which have allowed designers and architects to be able to create simulate complex geometries and building structures. Ongoing advancement in digital fabrication methods and increasing accessibility across all industries has created new possibilities for architecture in the 21st century. Faster digital simulation has allowed for the calculation of physical phenomena, and accurate forecasting of potential results is more reliable and rapid than it has been before. With specific systems like 3D printers and © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 49–71, 2020. https://doi.org/10.1007/978-981-13-8153-9_5

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robotics, the fabrication of increasingly complex structures is much easier (Fig. 1), but there are now new problems that need solving. Currently, most shapes can be quickly manufactured by digital fabrication technique, but there are still certain issues related to the cost of construction, restricted material selection and large scale limitation. Furthermore, completely automated fabrication systems usually require designed to pursue linear production methods, with limited flexibility or opportunities to use their initiative. As machining has high cost and time requirements, the process of creating objects is usually held back to the last stage of the design period, often producing predictable, pre-simulated outcomes. On the other hand, in the context of wide-scale construction, the monotonous architecture design styles have become an inescapable phenomenon (Fig. 2), which is the shame of architects and designers. Architecture is a part of physical environment, and architecture is also composed by complex structure and several joints simultaneously. Therefore, as architects, we should attach importance to the design methodology from the view of materiality, and rethink the relationship between joints, complex structures and architecture integrated, so as to expand the diversity of physical environment. Under these circumstances, a compounded design and fabrication methods are examined, where tactile interaction with materials and for initiates being the basis for all research activities. When messiness and failure are taken into account as common aspects of this process, there is a clear benefit for the using both hand craft and digital tools, where computer-controlled design and manufacturing activities can be used to produce superior results. Through conducting research into these methodology and semi-automated processes, a development of fresh, crafted aesthetic is encouraged, which can portray the changes made from architecture mostly focused on representation and tools related to an architecture which provides new ideas of craftsmanship, intuition and a post-digital design sensibility. This article is divided into four sections. Firstly, it is a general introduction of the relationship between architecture joints and complex structures with certain analyses about existing architecture projects. Secondly, it indicates the advantage and potential of aluminum casting in the joint fabrication of complex structures. Thirdly, it points out the conclusion which applying foam tube and lost foam casting into the fabrication of joints based on a series of material experiments. Fourthly, it is about the exploration of foam tube geometry and the creation of joint system. Finally, it describes the generation process of complex structures through the utilization of topology optimization.

Fig. 1. The fabrication of complex structures by robotic 3D printing.

Fig. 2. The view of Hong Kong from Lion Rock, Mark Leong, 2013.

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2 Architectural Joint as Part of a Complex Structural System 2.1

Architecture Design and Structural Systems

Research into architecture has followed numerous different paths. Sir Roger Scruton stated that architecture is distinguished from other art forms through the function involved, the localized quality, the technique, the public and neutral character, and the seamlessness with decorative arts (Scruton 1979). Specifically, the topic of structural systems describes architectural aesthetics as well as technological elements. Through the application of innovative technologies and different materials, particularly with complex buildings, architectural style and design approaches have also evolved. Simultaneously, the progression of architecture technology means that the link that exists between material and design is closer, so that advancements to architecture technology and structural system can bring about different types of architecture form. 2.2

Complex Structures and Architecture Joints

One of the core aspects of complex structures design is the application of suitable architecture joints. Vaults and arches are thought to be significantly expressive within a complex structure, due to the material itself bring about less use when contrasted with similar structures, as well as the geometric design of the architecture joint. The assembly of joints between each other produces a wide space that has a strong visual impact. Axial forces are critical, in this regard. By making important choices regarding joints and material assembly, the forces that pass through the material are controlled. Joints are set up in order to have axial forces with no bending occurring, to limit the requirement of materials needed inside the structure itself. An example of this can be seen with certain 15th and 16th century works, such as the Chapelle du Palais in Paris (Fig. 3), the central nave of the Winchester Cathedral in Winchester (Fig. 4) and the Cathedral Church of Christ in Oxford (Fig. 5), which are all clear depictions of architecture joints in complex structures. Contemporary projects have been examined with regards to joint use as key elements for handling complex structural problems. Examples include Pier Luigi Nervi’s Palazzetto Dello Sport in Rome (Fig. 6), Frei Otto’s tensile structure design for the 1972 Summer Olympics in Munich (Fig. 7) and Robert Maillart’s Salginatobel Bridge in Schiers (Fig. 8), which concentrate on the close link new material application, complex structure and joint design.

Fig. 3. Apse of the Saint Chapelle du Palais, Fig. 4. Nave of the Winchester Cathedral, Paris, 1248. Winchester, 1394–1450.

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Fig. 5. Choir of the Cathedral Church of Fig. 6. Palazzetto Dello Sport, Pier Luigi Christ, Oxford, 1478–1503. Nervi, Rome, 1957.

Fig. 7. Roofing for main sports facilities in the Fig. 8. Salginatobel Bridge, Robert Maillart, Munich Olympic Park for the 1972 Summer Schiers, 1926. Olympics, Frei Otto, Munich, 1968–1972.

2.3

The Roles of Joint in Architecture

In architecture, the joint plays multiple roles, the most obvious case is the structural, but it has also been tectonics, ornament, and symbolism. Architecture joint is the connection between each component of the building, and it is a part of integrated architecture structure system, ensuring the stability and reasonability of whole structure. The design of architecture joint should take advantage of material characteristic and select related fabrication technique so as to construct the joint with reasonable mechanical property. Besides, architecture joint is also a part of form, and it can influence space organization and form aesthetics, even it could be the symbolism of local culture. It should be noted that architecture joint has been taken into account with regards to the function of load transmission and decoration in western culture, as well as eastern classical architecture.

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2.3.1 The Joint in Classical Architecture When it comes to Ancient Greek and Roman architecture, there are certain characteristics that stand out in the design of Orders (Fig. 9). Firstly, from the structural perspective, orders are built to support the heavy slab of temple, passing the load of slab from the top to the base. Secondly, for tectonics, as the column is made from limestone and as such can withstand compression well but lacks tension protection, high density columns must be set up as a grid, with a small span distance. Thirdly, for ornament, the capital design of orders also has decorative function, with the transition from the simplest (Doric order) to the most elegant (Corinthian order) with two rows of acanthus leaves and four scrolls. Besides, ancient Greek and Roman architecture often involves an ordered portico made up of regular columns. Simultaneously, the scale of all components of the entire building, covering Base, Shaft, Capital, Stylobate and Pediment, can be found through column diameter. Lastly, from the symbolism perspective, the Architectural Order of a classical building is in line with the mode or key of classical music, the grammar or rhetoric of a written composition. This is set through specific modules such as intervals of music, bringing about expectations in an audience in line with the language (Diderot 1751). Dougong is a unique structural element of interlocking wooden brackets, which is a critical component of classic Chinese architecture (Fig. 10). Structurally, Dougong has progressed into a structural network of connected pillars and columns into the frame of the roof. This allows for greater weight support to the horizontal beams, covering vertical columns or pillars, through shifting the weight on horizontal beams across a greater area to the vertical columns. This is an action that can happen numerous times, as the levels go up. Joining numerous sets of interlocking brackets or Dougong limits how much strain the horizontal beams come under when shifting the weight to a column. Multiple Dougong mean that structures have more flexibility, and can stand up to earthquake damage to a greater extent. From a tectonics perspective, Dougong is constructed with timber, a soft material that can be manipulated easily. The components are joined together with no glue or fasteners needed, because of the accuracy and quality of the carpentry. When it comes to ornament, Dougong adds a decoration aspect to structures in a classic example of Chinese integration of artistry and function, allowing it to be hung under eaves, looking like graceful baskets of flowers in addition to holding up the roof (Sicheng 1998). Standing as an assistant joint of complicated wooden structures, Chinese Dougong maximizes the capabilities of the connection of the beam with the column, and establishes a cantilever space, which is the transition space between outside and inside, below the roof. On the other hand, west order is a more critical component within the stone structural system. This holds up beam and the load from the slab directly, and also the stone structure system is more robust and long-lasting than wood is. As a result, development and adaptation was extensive, as seen following the Roman times, where arches, with their aesthetic geometry and solid structural properties, allow orders to be part of the entire system, increasing the lifespan of orders. Therefore, the relationship between materiality and joint has already close in classical architecture.

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Fig. 9. The illustration of the Five Archi-Fig. 10. The Chinese ‘Order’, plate 2 of A Pictorial tectural Orders in Encyclopédie, 1751. History of Chinese Architecture, Sicheng Liang, 1984.

2.3.2 The Joint in Contemporary Architecture For contemporary architecture, the advancement of concrete and steel applications has allowed architects to design complicated structures involving a new type of joint. After the middle of the 18th century, cast iron was a commonly used building material. However, the fact that it can break easily mean it was only suitable for structural elements being compressed. The world’s first cast iron bridge built in Coalbrookdale, England was similar to stone arch bridges, with the key difference being that, because of the significant compression strength, not as much material was needed (Schober 2003). To meet the needs of construction following World War II, concrete was established as the most commonly used architecture material. Concrete is a type of fluid composite material, which has significant stability, is economic and is malleable. mold casting allows concrete joints to be created easily in numerous shapes. In Pier Luigi Nervi’s Palazzetto Dello Sport, the design of Y-shaped concrete joint is a great example of how malleable concrete is and how it can be applied. This design is distinct due to its sixty-meter diameter dome, supported by 48 radial Y-shaped concrete flying buttresses, where the upper arms move outwards to establish the rim decoration, and the externally curving dome shows the extensive rhomboidal ribbing internally. Due to the flexible properties of concrete, these flying buttresses joints are created with concrete casting extremely thin, offering the bottom support area the lightness visualization (Nervi 1965).

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Following this, due to the advancement of concrete material, iron structures are not as beneficial, over time. During the 1960s, new steel alloys with low-alloy and lowcarbon were created, through modern casting methods, and this was significantly different to historic characteristics of cast steel being brittle, porous and difficult to weld, which can be employed under compression alone. The quality needs were all covered by this new material, such as strength, viscosity, being easily welded and corrosion resistance. Cast steel allows for aesthetic, flexible forms to materialize, and these can be manufactured even with complicated nodes with numerous High Speed Steels involved. Potentially, the shape of the joint can be fit to the specific needs accurately, and the wall thickness to the flow of forces from the entering High Speed Steels accounted for. As cast steel properties are not impacted by the direction of stress, it is a material considered suitable for joints fabrication in three-dimensional. In the Centre Pompidou project, a High-Tech style architecture, substantially sized large-scale steel joints, named gerberette, can be seen from the exterior (Fig. 11). Since they are clearly seen as part of the facade, these parts show the progression of the modern industry and how machinery can be aesthetic. A gerberette joint is cast by steel (Fig. 12), and it displays its ‘self-explanatory’ nature, wrapping around a column, on top of a pin connection. This cantilevers a short distance to the building, adding in a floor truss and the longer cantilever on the exterior holds up the front facade and rear installations. Solid steel rods connect the ends of the gerberettes with each other, and the ground. Facade bracing is linked with the frame at the column pins (Rice 1994). When contrasting concrete joint and steel joint, these two types have different benefits and flaws, within a complex structure. Both of them can turn into a fluid material, be poured and cast without difficulty for any shapes in line with the mold. As a result, there is strong potential for three-dimensional geometry. When it comes to the concrete joint, the various components, such as cement, aggregates and water, are widely found and not costly, in addition to being able to handle compressive stresses efficiently. However, a concrete joint has weak tension, and since it weighs a lot, it is not always suitable for long-span and cantilever structures. On the other hand, in the case of the steel joint, clearly this is much lighter than other types of joint. In addition, a steel joint can be manufactured without difficulty, and is thus the preferred joint for wide-scale construction, where steel components are able to be substituted, assembled and taken apart easily. This type of joint can be installed in a short time, and used rapidly afterwards. On the other hand, the highly cost of steel joints is a clear disadvantage which cannot be ignored. As a result, across the last thirty years, steel casting procedures have progressed substantially, allowing for production of high-quality castings, which can deal with the extensive needs of structural applications. Thus, employing steel castings in construction is the standard selection, and widely found (Herion 2010).

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Fig. 11. Gerberette joints and facade system of the Centre Pompidou, Renzo Piano, Richard Rogers and Gianfranco Franchini, Paris, 1977

Fig. 12. Steel Casting Greberettes of Centre Pompidou, Renzo Piano, Richard Rogers and Gianfranco Franchini, Paris, 1977

3 Advantage of Aluminum Casting in Complex Structure Joint Fabrication 3.1

The Supercities of Aluminum

It is considered that aluminum is a suitable choice for joint fabrication in the context of complex architecture structure. These materials have a unique set of properties which decide their suitability for the architecture material choice. It should be noted that the benefit of aluminum is that it is able to be used for the manufacturing of low-tech and economy joints, creating a weightless complex structure with a particularly aesthetic, flexible geometry, and shiny finish. In most cases, since aluminum melts at 660 °C is lower than steel’s melting point of 1300 °C, the former can be melted into liquid more easily, for the purpose of casting, and so the equipment involved does not have to be very professional, and a small table kiln could potentially be enough. Also, aluminum is can be deformed by hand or machine easily, meaning that overall it is considered more advantageous for low-tech and popular craft fabrications. Therefore, comparing with steel, aluminum has more potential and less limitation to create complex geometry base on the current manufacture technology. Aluminum has an appealing texture, as it shines after minimal polishing, whereas steel has a rougher surface. This means that aluminum’s appearance can meet decorative needs of contemporary architecture design more easily. In addition to the low density, aluminum does not weigh as much as steel, and these can be easily installed at a site all together after factory prefabrication, meaning that there is less transport, time and labor costs. Thus, aluminum joints are considered suitable for non-permanent, or assembly architecture. After selecting architecture materials, economic and recovery aspects must be taken into account. Aluminum accounts for roughly 8% of the Earth’s crust, and is the most widely found element, surpassed only by oxygen and silicon, meaning it is the most abundant metal (Zhiqiang 2007). The costs of steel and aluminum constantly change

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due to worldwide supply and demand. However, aluminum is usually cheaper (per pound) than steel. Additionally, due to the smaller weight and expense of aluminum, it is used in the manufacturing of cars, and electronic products, to a great degree. Thus, aluminum is also recycled easily, and by melting and casting, aluminum is able to act as an architecture construction material. 3.2

Casting Method for the Fabrication of Complex Architecture Joint

During the process of casting, liquid material, such as metal or concrete, is poured into a mold of a hollow cavity in the shape of what the manufacturer intends to produce, then cooled and turned solid. This solidified part is known as the cast, released or broken out of the mold to finish the process. This process is usually employed for manufacturing complicated shapes that could be challenging, or too expensive, to create in other ways. For metalworking, casting is a suitable method to create complex structure joints, due to the fact that these joints always move load across a number of directions, requiring sound mechanical properties. As a result, metal casting technique can create solid metal with complex geometry (DeGarmo 2003). 3.2.1 Permanent Mold Casting Permanent mold casting is a way of casting metal that uses re-usable molds, made of metal themselves. Gravity is usually used to fill the mold, or in other cases gas pressure or a vacuum are employed (Fig. 13). Common casting metals are aluminum, magnesium, and copper alloys. Additional materials are tin, zinc, and lead alloys, with iron and steel also cast in graphite molds. Permanent molds, which can survive more than a single casting, are still limited in their lifespan of usability. The key benefits include reusable mold, robust surface finish, strong dimensional accuracy, and excellent production rates. Additional benefits are how easy it is to bring about directional solidification through mold wall thickness alterations or through heating or cooling sections. The rapid cooling rates brought on by the metal mold facilitate a finer grain structure. Retractable metal cores are also employed to develop undercuts, with the rapid action mold intact. On the other hand, a few key downsides exist here, which are extensive tooling cost, few low-melting-point metals, restricted mold life, and limitation of diversity in terms of scale and form. The large tooling costs mean that this process is not financially viable for small production runs. Once steel or iron is cast, mold life is very small, and for lower melting point metals, the mold life is longer but is still impacted by thermal fatigue and erosion, meaning it lasts 10,000 to 120,000 cycles (DeGarmo 2003). Moreover, because the permanent mold, which is already a very complex system, must be made by the negative geometry of final cast, it is good for massive production, but it also restricts the scale and geometry of joint for the complex and customized structure system. For instance, in the Reichstag Building of Berlin by Foster & Partners in 1999, in order to achieve the connection between main structure and rod, there is a set of permanent casting joint with two small and simple members and a identifiable bolt. In this case, the fabrication method influenced the organization of structure system, and one connection joint needed to be designed partially and simply (Fig. 14).

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Fig. 13. The schematic of the lowpressure permanent mold casting process.

Fig. 14. The connection joint by permanent mold casting of Reichstag, Berlin, Foster & Partners, 1999.

3.2.2 Lost Foam Casting Lost foam casting, which is a kind of evaporative pattern casting, was first seen in 1958, when an American, H.F. Shroyer, used plastic foam as a pattern, which was machined from a block of expanded polystyrene, and held by bonded sand during pouring (Howell 1993). This way, the mold is complete with no need for sampling, and once molten metal is poured into molds to spontaneous combustion, and the foam pattern can be replaced by liquid metal completely. Once frozen, the metal cast is created (Fig. 15).

Fig. 15. The diagram of the traditional lost foam casting process.

Employing lost foam castings in contemporary building construction is common practice, where cast steel components have been seen in big fair and exhibition halls, in airport passenger terminals, and in the roof structures of various stadiums. For numerous situations, aesthetically pleasing supporting structures are facilitated by using hollow structural sections and cast steel joints. This kind of branching support system by lost foam casting can be seen in the atrium of University of Guelph Science Building by Young & Wright (Fig. 16). Clearly, the benefit of lost foam casting is that there is no scale limit, due to the joint size being based on the foam pattern size. Foam pattern is able to be manufactured at any scale via the CNC machine. Also, dimensional accuracy is high, the surface finish is high quality, and there is no need for a draft, with no parting lines produced. Contrasted against different casting methods, lost foam casting has excellent production efficiency with no need for complex processes of permanent mold fabrication. Even though the lost foam casting joint is able to meet most of the needs of modern architecture design, this method does not suffice for future architecture form and

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unpredictable functions. The key disadvantage for lost foam casting is the fact that polystyrene foam (pattern material) can only be turned into linear or monotonous geometry by CNC machines. In this fabrication method, the materiality and material behavior of foam, which is very flexible and soft, is not utilized well. The form of joint can be built into any shape in computer and milled by CNC machine easily, however this work-flow is lack of the design intention about material behavior and character, and foam is only treated as a alternative material by metal instead of the definer of form. Thus, it is necessary to develop a new lost foam casting fabrication system which is respecting the material behavior of foam, so as to face the new challenging of complex geometry and structure in the future.

Fig. 16. The fabrication process of branching support in University of Guelph Science Building, from CNC foam pattern to assembly, Guelph, Young & Wright

4 Applying Foam Tube and Lost Foam Casting into the Fabrication of Aluminum Joint 4.1

Material Experiment and Selection

4.1.1 Flexible Pattern Material Selection: Foam Sheet, Foam Block and Foam Tube Different flexible foam types were gathered to ascertain the most suitable for lost foam casting.

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Firstly, foam block was tested. Three types of foam block were tested first. Foam is recommended to be burned directly with aluminum during lost foam casting, and so the burn test was conducted. Polystyrene and Blue polystyrene were the easiest to be burned, and allowed for casting into the smoothest surfaces. However, because the foam block only can be cut or sculptured, the most obvious drawback of foam block was the limitation of plasticity. Following this, the foam sheet was evaluated, and it was very soft and easy to burn. Following the series tests (e.g. grasp, rotation, push and pull), it was seen that foam sheet can create geometric shapes the easiest, but it was also seen that it was too soft to deform through sand pressures during lost foam casting. Foam tube was tested next (similar to the foam block and foam sheet), with the shape test, showing that foam tube is soft and can be hand-shaped, motivating the researcher to conduct bend, twist, fold and rotate tests (Fig. 17). Foam tube can be crafted into numerous different shapes by hand following cutting, and because of its softness, it can be bent or rotated. More complex geometry with multiple subdivisions can be developed through extra cutting times (Fig. 18). Besides, because the foam tube is hollow, comparing with other kinds of foam, it has more assembly potential with any other straight pipes.

Fig. 17. Test of foam tube physical property, Tianyu Guo

Fig. 18. Hand craft of foam tube geometry creation, Tianyu Guo.

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4.1.2 Cast Material Selection: Kiln Dry Sand, Play Sand, Sharp Sand and Building Sand Sand is critical in the new direct lost foam casting method. In order to make sure the final cast of foam tube has a organic shape and good finish, it is important to find a type of sand which has the good porosity feature, so as to remove the air-escape channels, which will influence the finish of flexible foam tube’s organic shape (Fig. 19). Thus a sand test was conducted at the beginning of the research. The humidity, plasticity and porosity of four sand types were analyzed. Following the results kiln dry sand, with its great porosity and limited humidity, was superior for heat dissipation (Fig. 20).

Fig. 19. Air-escape channels are on the out side Fig. 20. Physical property test of sand, Tianyu Guo. of cast piece, Max Lamb, 2007–2015

During the further test, foam tube was used, in order to ascertain the suitability of kiln dry sand. Every test employed a same foam pattern, created by a hot wire foam cutter. The results showed that kiln dry sand is the most suitable, allowing cast surfaces to stay in good condition (Fig. 21). Therefore, the foam tube and the kiln dray sand were selected to the further casting test.

Fig. 21. Initial casting test through using different kinds of sand, Tianyu Guo.

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The Process of Casting Foam Tube into Aluminum Through Lost Foam Casting

Following identification of the appropriate pattern material and mold material An entire work-flow of casting fabrication was designed. This process can be divided into four stages: foam pattern crafting; setting; pouring and collection. Firstly, the foam tube requires fabrication according to the designed geometry, being immobilized into the boundary box in order to maintain the entire geometry and connected parts in a precise position. According to previous research into foam tubing material behavior, a foam tube section is cut from the middle, rotating each part separately, followed by gluing of the upper part together again, as a means of creating the tube with a twisted and organic geometry in the middle. Mindful of the further assembly potential including other components, the pattern should be cast not only with moments but also in an accurate position. A boundary box was designed and fabricated by laser cutting with various holes, with the end area of the foam tube able to be plugged into the corresponding hole, in order to maintain a correct position when covered with sand. Additionally, one boundary box comprised of six wooden surfaces and four supporting beams. In accordance with this low-technology and convenient technique, it will be straightforward for anyone to cast any geometry that they require (Fig. 22).

Fig. 22. Boundary box design, Tianyu Guo.

Secondly, a completed foam pattern with boundary box required setting into a sand container that was full of kiln dry sand. The foam pattern is complete covering with sand is a crucial aspect of an effective casting process. Therefore, during the sand pouring process, the container needs to be shaken continuously, ensuring sand can reach into all of the areas, including those with the most complex geometry. Thirdly, liquid aluminum must be directly poured into the foam pattern. A small table kiln was utilized to melt recycled aluminum, with the aluminum transforming into a complete liquid at 800 °C. Liquid aluminum requires pouring under uniform velocity and continuously, otherwise cracks will appear in the final cast. Lastly, the final cast should be collected following cooling. The foam pattern should have been completely exchanged for the liquid aluminum, thus realizing the transition from the soft foam to the solid aluminum. Following collection of the final casting from the sand container, it may be polished to achieve a shiny finish (Fig. 23).

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Fig. 23. Fabrication work-flow of lost foam casting, Tianyu Guo.

5 The Exploration of Material Behavior and the Creation of Joint System 5.1

The Material Behavior of Foam Tube

Following the successful casting experiment, the material behavior of foam tube was investigated. In ‘On Growth and Form’, Thompson proposed that the evolution of species formation is a manner of natural dynamic growth, with the new species formed having similar biological characteristics with the original (Thompson 1942). The material behavior of foam tube is comparable to Thompson’s theory, meaning that foam tube can produce natural deformations based on the original status, following a series of hand craft sequences. This research originated with an assessment of a single foam tube, which was dissected through the central section in order to permit the bottom section to be rotated and inserted into the central cut. Following these craft sequences, the foam tube became slanted at a specific angle that differed from the original. Meanwhile, a more crucial factor was that with the different lengths that were cut, different ranges from the natural slant foam tubes were seen, without any additional manual deformation. Moreover, if the foam tube is cut additional times, this form of influencing relationship between the cutting length and deformation ranges still exists. Consequently, the foam tube can produce more complex geometries with various subdivisions (Fig. 24).

Fig. 24. The material behavior study of single direction language, Tianyu Guo.

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The Creation of Joint System

Based on the existing literature into material behavior, a joint system is posed by the innovative geometry, comprising of four categories: Unidirection; Surface; Branch and Multiple Direction (Fig. 25).

Fig. 25. The Integration of joint system, Tianyu Guo.

5.2.1 Uni-Direction The feature of Unidirection is that the foam tube connects one point to another; however it can also produce slanted or curved geometry with different angles in the middle (Fig. 26). 5.2.2 Surface Subsequently, the regular impression of tube geometry was attempted to break further, achieving surface language. The foam tube was dissected from the top, with both parts spread out in order to stick into a surface. Furthermore, joints were also created which had further subdivisions, by controlling the cutting times (Fig. 26). 5.2.3 Branching The building of the relationship between two or more tubes was initiated. This was begun due to the strong impracticality of building an intricate architectural structure with the joints using just a single direction. Consequently, as a means of attaining the geometry that can branch from one point to multiple points, the researchers cut multiple individual tubes in the bottom section and amalgamated them (Fig. 26). 5.2.4 Multiple Directions After the foam tubes were branched from one to multiple, the joint that could extend out multiple directions in a three-dimensional space was continued to design. For example, the researchers prepared two foam tubes with a half cutting from the top to the middle, then glued them together. Following rotation, the aggregation possessed four directions, which could also be bent into different angles. Furthermore, through a similar crafting method, a joint with three and six directions could be manufactured (Fig. 26).

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Fig. 26. Final cast of four types of joint, Tianyu Guo.

6 The Parametric Generation of Complex Structures 6.1

Topology Optimization

Following the design of joint system, topology optimization for architecture was engaged in, aiming to reduce the amount of material used in building structures, while maintaining equivalent performance properties. In the automotive and aeronautical industries, optimization processes seeking to economics weight and resources are a common practice, crucial for achieving superior flying and driving performance. Contrasting a tower building and a car’s structural elements performance per cubic meter, the building element is exposed to a multitude of stresses, while concurrently being vastly underdeveloped. A greater amount of financial resources, physical materials and waste capacity are expended on building constructions above any other global activity. However, contemporarily, outdated building regulations and code tables for isotropic building structure profiles are utilized and planned with. Topology optimization processes aimed at material distribution describe the material’s location, however, they provide no manufacturing information. In terms of topology optimization assumptions and equal distribution of material mass, we propose substituting the solidity of profile with an advanced geometric method (Fig. 27). Topology optimization is a mathematical approach seeking to optimize material layout within a given design space, according to a specific set of loads and boundary conditions, such that the subsequent layout conforms to a prescribed set of performance objectives. Topology optimization has been implemented through utilizing finite

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element methods for the analysis, alongside optimization techniques based on the method of moving asymptotes, genetic algorithms, optimality criteria method, level sets, and topological derivatives. Topology optimization is utilized at the conceptual level of the design process, in order to produce a conceptual design proposal that is subsequently fine-tuned for performance and manufacture ability. This negates the requirement for time consuming and fiscally draining design iterations, therefore diminishing design development time’s general associated expenditure, while enhancing design effectiveness. Topology optimization within architectural design is the utilization of topology optimization techniques, specific to optimized shapes’ morphology. Topology optimization provides considerable potential within architectural design, in terms of being a driver of design innovation, alongside the convergence of the architectural and engineering disciplines (Bendsoe 2002).

Fig. 27. The topology optimization process. From an initial set up pf design and non-design space, the optimization software computes an optimal distribution of material in relation to design criteria.

6.2

The Generation of Facade Structures

Given that the cast material is aluminum, which is sufficiently strong enough to carry heavy additional loads, a new type of facade structure was proceeded to design through the application of Topology Optimization. As a means of generating a structure diagram for the facade, the generation environment required setting. A 0.9 m  0.8 m  2 m box was modeled as the unit facade structure’s design area, followed by the application of a surface load that simulated a glass section or any different material on one side, alongside four point supports that represented the connection points with other components on the other side. After the model was completed, a plug-in of Grasshopper named Millipede was used to generate the structure diagram. Millipede recognized the loads and the supports as volume, therefore spheres were created as representative of these elements. The half

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section of the spheres that were intersected inside the boundary box were recognized as the loads, alongside supports regions inside the entire design area. Nevertheless, the resultant model from the Millipede optimization was a particularly direct representation of the model assembly’s structural behavior, while the geometry was extremely rough and not particularly suitable as an architectural element. Therefore, the joint design was taken advantage in to refine the geometry, thus attaining a more satisfying form with regard to aesthetic and fabrication variables (Fig. 28). Furthermore, the structure of typology chair and table were designed in the same methodology and fabricated successfully, which can hold relative load and person, proving the feasibility of this joint system in term of mechanics (Figs. 29).

Fig. 28. Topology optimization of unit structure prototype of facade, Tianyu Guo

Fig. 29. Physical fabrication of facade support unit structure, prototype chair and prototype table, Tianyu Guo

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Lastly, the facade structure comprised of multiple single structural prototypes that were refined according to the diagram of topology optimization generation. Due to the deformation ability of the joints, the entire facade structure was able to deform, following the glass with waved geometry. Furthermore, this facade structure could also be connected with the other architectural components assembled as joints and straight pipes, for example columns, beams and slabs (Fig. 30).

Fig. 30. Design proposal of complex structure in architecture scale, Tianyu Guo

6.3

Architectural Scenario with Complex Structures

Finally, all kinds of joints and current structure prototypes were utilized to design the architectural scenario which has a villa function. Farnsworth House by Mies van der Rohe in 1954 (Fig. 31) became a initial reference, and the site is same as Farnsworth House, which is in the Illinois, US (Fig. 32).

Fig. 31. The Farnsworth House, Mies van Fig. 32. Illinois, US, Site plan of architectural scenario, Tianyu Guo der Rohe, 1954

Applying Lost Foam Casting Aluminum and Computational Design

Fig. 33. Explosion diagram of structure assembly, Tianyu Guo

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Fig. 34. External perspective, Tianyu Guo

This villa design started from two simple massing with different scales, then two massings were divided into three parts for different functions. After the function distribution, there was the deformation in in the overlapping area so as to create the main entrance and routes. After that, the structure of entire building was divided into several parts: column, facade, floor, slab and beam, and each part was assembled from the joint system and straight rod element, which was base on the mechanics diagram and structure optimization (Fig. 33). In this case, the entire exposed structure was not structure only, but also a part of design language, and individual joint with organic geometry reflected the general design language and material behavior (Figs. 34 and 35). This case indicated how the power of low-tech lost foam casting technique integrated with new computational design methodology, and the application potential in the architecture joints system.

Fig. 35. Internal perspective, Tianyu Guo

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7 Conclusion During this research, an original design methodology was implemented, in order to rethink the relationship between materiality, joints, complex structures and architecture. In the context of volume construction, monotonous architecture design styles appear to have become a predictable phenomenon, with the loss of diversification a significant tragedy for architecture and cities. As a fundamental aspect of complicated structure and architecture, the role of joints requires reconsideration, in order to avert monotonous and non-designed joints. Meanwhile, despite the emergence of digital techniques extending the possibility of complex geometric design and fabrication methods, architects may be induced to overlook the significance of materiality. Resultantly, in this project, the exploration of joints initially began with a series of experiments concerning materials selection and fabrication techniques. Consequently, this research incorporated foam tube, which has high plasticity properties, with the lost foam casting technique, which is a low-tech and high-efficiency method, thus creating an innovative joint system characterized by abundant diversity in relation to geometry, subdivision and multiple directions. Consecutively, Topology Optimization, as an assistant parametric design technique, was incorporated into the preliminary design stage of complicated structural designs, in order to provide architects with guidelines for design that utilizes a joint system. In fact, this design methodology can be considered differently. In terms of the lost foam casting method, the diversity of joints is dependent upon the geometric creation ability of the pattern material; foam tube is not the sole option available, for example it could be replaced by various other flammable and flexible materials. Furthermore, due to restrictions on hand crafting, aluminum provides the most appropriate material for this research. However, considering the requirement of materials strength during practical construction projects, it is evident that other kinds of metal, for example iron, steel and cooper, may provide alternative casting materials during lost foam casting. Moreover, through utilizing robotic arms, foam may be bent and rotated more precisely and efficiently, rather than adopting the hand craft and boundary box system. Nevertheless, this investigation also faced certain limitations. One problem concerns error mitigation. Because the cast cannot be absolutely the same as the pattern in lost foam casting, these uncontrollable errors will result in certain problems during fabrication of parts at an architectural scale. Secondly, imperfections were seen in terms of the geometric design. This means that certain parts of the joint pattern have excessive deformation; these will become the weakest sections of this joint following casting. Consequently, the geometric design of joints should be given consideration regarding both aesthetics and mechanics, being tested rigorously prior to volume construction.

References Bendsoe, M.P., Sigmund, O.: Topology Optimization: Theory, Methods and Applications. Springer, Berlin Diderot, D.: Encyclopédie (1751)

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DeGarmo, E., Black, T., Kohser, R.: Materials and Processes in Manufacturing. John Wiley & Sons Inc, New Jersey (2003) Herion, S.: Castings in tubular structures – the state of the art. Struct. Build. 163, 403–415 (2010) Howell, S.: Evaporative polystyrene metal casting technology: current technique and potential application. APT Bull. J. Preserv. Technol. 25(3/4), pp. 60–63 (1993) Nervi, P.L.: Aesthetics and Technology in Building. Harvard University Press, Cambridge (1965) Rice, P.: An Engineer Imagine. Artemis, London (1994) Schober, H.: Steel Castings in Architecture and Engineering. Modern Steel Construction, April 2003 Sicheng, L.: Architecture History in China. Baihua Edition, Tianjin (1998) Scruton, R.: The aesthetics of architecture. Princeton University Press, New Jersey (1979) Thompson, D.: On Growth and Form. Cambridge University Press, Cambridge (1942) Zhiqiang, L.: Characteristics and application of the aluminum alloy in the architecture structure. Shanxi Architecture 33(29), 163–164 (2007)

Carbon Natural: Using Molecular Logics as Inspiration in Micro-Bamboo Structures Ralph Spencer Steenblik1,2(&) 1

88 Daxue Rd, Ouhai Qu, Wenzhou Shi 325060, Zhejiang Sheng, China [email protected] 2 134 Greenwich Ave, New Haven, CT 06519, USA

Abstract. This article outlines a scientific or iterative research process, designing a proto-architectural molecularly inspired micro-bamboo system, followed by some case-study examples of actualized instantiations of the system at scale. Turning to one of the most effective and strongest molecular structures, carbon, as inspiration for its particularly versatile, tribrachidium nature, and utilizing micro-bamboo for its mass-produced ubiquity, this effort created some unexpected novel opportunities, and has a multiplicity of possibilities. Keywords: Bamboo Tensegrity


Molecular mimicry
Tessellation
Structural system


1 Introduction Where does inspiration come from? There is precedent for the idea that inspiration is the sum of one’s experience filtered through the subconscious, and nonlinearly related to the present challenge or opportunity. As Steve Jobs so aptly describes: “Creativity is just connecting things. When you ask creative people how they did something, they feel a little guilty because they didn’t really do it, they just saw something. It seemed obvious to them after a while. That’s because they were able to connect experiences they’ve had and synthesize new things. And the reason they were able to do that was that they’ve had more experiences or they have thought more about their experiences than other people. Unfortunately, that’s too rare a commodity. A lot of people in our industry haven’t had very diverse experiences. So they don’t have enough dots to connect, and they end up with very linear solutions without a broad perspective on the problem. The broader one’s understanding of the human experience, the better design we will have” [1] (Fig. 1). I remember visiting an installation of a ‘Fly’s Eye Dome’ (1976) at LaGuardia Place across the street from The Centre for Architecture in Manhattan [2]. The installation coincided with “Starting with the Universe” at the Whitney. The ‘Fly’s Eye Dome’ is an example of one of Buckminster Fuller’s Geodesic domes. His dome structures inspired generations. Buckminsterfullerene is a molecular structure discovered by Curl, Kroto, and Smalley, and resulted in a Nobel Prize in 1996 [3]. The discovery team saw the resemblance to domes such as the ‘Fly’s Eye Dome’ and therefore named the newly discovered molecule after Fuller. The process was the

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Fig. 1. Current design iteration of the Micro-Bamboo joint and strut system organized in a printready optimized configuration.

geodesic design first, and the molecule discovery later, but there have been many examples of the reverse process. Such is the process of this research project currently in development here at Wenzhou-Kean University. The project is a part of the WKU-Labs Urban Design Think Tank, and in conjunction with the WKU Media Lab. The Urban Design Think Tank is focused on an idea of global localism. This means focusing on using local materials to inspire design solutions. The Think Tank is interested in micro solutions perpetuated toward solutions that can meet larger, urban problems as is illustrated through the following idea: The whole can only be greater than the sum of its parts if the parts are sufficiently compelling on their own. Thus we have an urban design think tank looking at experimental building systems. The think tank is also actively engaged in urban and master planning projects around the world. The aspiration is that these small scale solutions can be applicable in future efforts at this larger scale. We are engaging the full range of the design professions in order to tap into potentials that might not otherwise be possible. This article outlines the scientific or iterative research process of designing a protoarchitectural system upon which further exploration can grow. The exercise was not a primary or secondary priority, but a tertiary exploration as a simple distraction from more pressing duties at hand. In this paper there will be an exploration of several of the many iterations followed by some case-study examples of actualized prototypes of the system at scale.

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2 The Building Blocks of a System The project began as the development of a children’s toy design, possibly inspired by the work of the Eames [4]. It has gone through several iterations beginning with a simple wooden cube and dowel strut system. Where the dowels could intersect with the cube through a prescribed number of sides through appropriately sized holes, in a similar to a Tinkertoy. The node becoming an important part in determining the form of the final object. By standardizing the lengths of the dowel strut connectors it allows for connectivity between nodes throughout the system. These two aspects are important in the development process. Although there is a constructible simplicity in this original system there is a material over-use factor. Where there is a greater amount of material used in the system than is actually required for the desired performance. This became one aspect of future development of the system. Additionally the rectilinear limitation of the system harkened to an earlier time and did not reflect any sort of advancement beyond woodworking techniques, available for centuries. As I was developing the system it became important to familiarize the potential juvenile user with contemporary processes, techniques, and thought. Thus the first iteration became less than satisfactory according to my criteria and the process moved on to the second major iteration (Fig. 2).

Fig. 2. First iteration of the Micro-Bamboo project.

The original intention was to achieve a simple constructability, which has remained a core tenet of the design exercise throughout the process. Although the original iteration of the system, on its own has merit, the opportunity to develop a system with possibly more potential is a reality because of access to rapid prototyping methods. This shift in manufacturing processes allowed for a move away from pre-made or off the shelf parts, toward completely bespoke units, specifically made to address the needs of the system; allowing custom angled struts for increased levels of complexity within the system without a sophisticated increase in the nature of the parts of the system. Additionally, the decision to move from dowel struts toward rectilinear ones enabled a specified directionality in the connections. Greater care had to be taken to ensure the strut and node connection dimensions because of the plasticity of the material and increased quality variation within the parts produced.

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Fig. 3. Second major iteration, with multiple angled struts

With the shift toward a rapid prototyping process came an awareness of time between iterations based on print times and material consumption. These two factors began to directly drive the process in a commanding way. You can see the transition between Figs. 3 and 4 in terms of strength to weight ratio. Prior to the iteration found in Fig. 4, one of the surfaces on the struts was removed to create five sided struts with an exposed interior. Another shift was toward making the struts exhibit aspects of the node behavior, by integrating a secondary connector into the strut. This allowed struts to connect directly to other struts without the need of an additional node. This makes for compelling configuration results when a number of nodes and struts are composed together. The chevron form in the strut connector along with the angled receivers at the top of the node accommodates additional angular aspects of a composed collection of nodes and struts.

Fig. 4. Third iteration of the system, focused on complexity through node like struts

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3 Molecular Shift Eventually after a few trial and error cycles, the realization came that this iterative process, purposefully avoiding generative evolutionary design techniques, although faster than molecular evolution, had too many generations of lag to ever hope to catch up to the existing wisdom embedded in molecular physics. Some of these attempts included Euclidean explorations which clearly expressed a typical and unsatisfying space frame tectonic. These studies can be seen in the upper portion of the collection of images in Fig. 5. I turned to what I knew as one of the most effective and strongest molecular structures, carbon. One significant aspects of carbon that make it particularly versatile is the multiplicity of configurations made possible by the tribrachidium (or tri symmetrical) nature of the form. The three dimensional radial repetition of the form proved difficult to model accurately without the aid of parametric techniques. Concurrently, I was exposed to what I am calling micro-bamboo which takes the form of mass produced ubiquitous chopsticks, made from bamboo waste product, in general use here in Wenzhou, China. This provided a convenient strut material. Again the material choice focused on effectiveness with a high strength to weight ratio, while maintaining accessibility. I found myself at the local supplier emptying their stock of chopsticks as if opening an eating establishment. These material choices meant that I had as much of my base building blocks as desired without any sort of bottleneck limiting the system scale. The limiting factor became how quickly printed parts could be extracted from the printer and how strong the nodes can be. Therefore when designing the node, optimization was critical. These optimizations may seem decorative, yet they are essential to the performance of the node. The node

Fig. 5. This drawing shows the shift away from Euclidean toward molecular logics.

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needed to achieve the necessary strength out of the system as the earliest versions of the node did not have the strength necessary to meet the torque demands from the struts. The micro-bamboo strut material is quite flexible, placing the failure likelihood on the node. A series of structural fins were added to the node. The tribrachidium fins add surface area for directional and gravitational load transfer. The fins were limited to the material coursing previously mentioned. This required them to be thicker than initially desired for proportional considerations, yet in the end proved to be important structurally. Using a more course printing setting allowed for more rapid print times, but this required part optimization to align with material logic, in a similar way to brick coursing. A series of voids were subtracted from the node, not only do the voids reduce printing time and material use, they also allow verification that the struts are fully seated, and allow the assembly team to choose the seated relationship between four struts. Additionally the voids or apertures create convenient tensegrity configuration opportunities, see Figs. 6 and 7.

Fig. 6. First carbon based node design iterations, prior to more accurate parametric engagement

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With adequate nodes developed, the team was able to begin assembling early versions of the system. Initially there were no preconceived configurations identified. In fact the system was left in the hands of several groups unfamiliar with it entirely. Allowing the team to assess the success of the system as a means of making volumetric form. After the initial carbon inspired nodes were made there were more than ten major iterations, and there is still additional fine tuning to maximize potentials within the system. Some of these include additional voids to further limit material use and print time (as well as increase tensegrity applications), print direction logistics, and additional directionality for node connection. Strut extenders effectively doubled the volume of the system without a substantial increase in parts or part types. See Fig. 8.

Fig. 7. Small scale instantiation utilizing a tensegrity and cantilever configuration

Fig. 8. Manually optimized node and strut iterations

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Fig. 9. Part of the project team after sub-hour exhibition installation

4 Conclusion and Anticipated Opportunity At scale the system has been erected for several exhibitions. Figure 9 illustrates the first of these installations. The pentagonal dodecahedron unit of this particular installation is an instinctive method of assembly due to its simple and comprehensible geometric form. The redundancy in this installation configuration of the system compliments the inherent flexible elasticity of the node and strut pentagonal dodecahedron unit. One unit can almost be bounced on the floor resiliently returning to its original form. This first installation was quite successful, resilient, and strong, well proportioned, with a clear concept of unitized form. After a few installations there was a desire to again maximize the part to whole volume of the installation. As mentioned previously, one of the benefits of a carbon inspired node design is the multiplicity of available assembly configurations. There are more efficient unit types than the instinctive pentagonal dodecahedron unit. Exploring unit types allowed the team to achieve greater part to whole efficiency. Figure 9 shows an implied nonagon taking the node count per equivalently dimensioned unit from twenty nodes and thirty struts down to eight nodes and nine struts. The efficiency of the more spars nonagon unit is of course structural resilience (Fig. 10).

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Fig. 10. Implied nonagon unit, more efficient than the pentagonal dodecahedron configuration

Yet it seems that the structural capacity of two linked nonagon units could be greater than one of the dodecahedron units and still require less nodes and struts. In addition to the opportunities beyond a singular unit configuration. There are opportunities to mix unit types, possibly creating a best of both worlds scenario for structural optimization. One way we have begun to test this is through allowing the strut to continue all the way through the node, creating eight, not four, potential strut connections per node. Additionally the system is flexible enough that transitioning between unit types with an installation has been successfully tested. There are novel opportunities provided by breaking the regimented regularity of the system, by leaving some units incomplete, or through arranging the nodes and struts in configurations outside of the implied logics found in the system. For example, as shown in Fig. 7 incorporating tensegrity logics into the system it moves into a hybrid or collection unit configurations within the greater composition. These opportunities provide fertile ground for novel applications beyond the monotony of the single unit system. The team believes the hybrid approach is the key to a compelling application of the system – allowing the system to be whimsically accommodating to user needs and preferences. Other future opportunities include incorporating aspects of cladding through translucent synthetic material, and motorized articulation of the system, see Oliveira [5]. Further abreast still is the opportunity to scale up using alloy for full scale application.

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References 1. Wolf, G.: Steve Jobs: The Next Insanely Great Thing. Wired, Conde Nast. www.wired.com/ 1996/02/jobs-2/ (1996) 2. Sheridan, J.: Bucky’s 113th Birthday: Savoring the Gift of Global Awareness. Center for Architecture. www.centerforarchitecture.org/news/buckys-113th-birthday-savoring-the-giftof-global-awareness/. Last accessed 8 July 2008 3. Press release. NobelPrize.org. Nobel Media AB 2019. https://www.nobelprize.org/prizes/ chemistry/1996/press-release/. Last accessed Sat. 04 May 2019 4. Lange, A.: Serious Fun. WHY Magazine (2019) 5. Oliveira, M.C., Skelton, R.E.: Tensegrity Systems. Tensegrity Systems, pp. 15–16. SpringerVerlag US (2009)

Parametric Design of Personalized 3D Printed Sneakers Qiang Cui(&) and Fei Yue Academy of Art & Design, Tsinghua University, Beijing 100000, China [email protected]

Abstract. This paper explores the case study of personalized sneakers which considers physical factors, performance structures in integrated design methods, and the correlation between different structures and physical properties. Data plays a vital role throughout the research process and supporting the various steps including problem solving and verification. Some points and abstract forms that were difficult to quantify in sneaker design are also clearly shown through the data analysis. As a reasonable application of 3D printing technology, the design is based on foot support and motion protection requirements and responds to conditions of material and structural distribution. Keywords: Parametric design


3D printing
Product design

1 Introduction With the development of science and technology, advanced tools represented by 3D printing technique have penetrated into the work of designers. On one hand, it allows designers to be freed from the constraints of traditional production processes, and on the other, it accelerates the product development cycle and offers the possibility to meet the individual needs of users. ‘3D-printed body architecture’ is a new concept, which could be defined as 3Dprinted designs by architects for clothing, shoes, food, chairs and other items either for the human body, or at the scale of the human body [1]. This project as a 3D-printed body architecture design practice is mainly aimed at the individual weight, feet type, running posture and the complete data-driven 3D printing sneakers design. The design acquires the morphological data of the user’s feet through threedimensional scanning, and obtains the pressure data of the dynamic distribution of feet from monitoring of the motion process. The corresponding structure is generated by the parameters combined with the weight data, which disperses the feet pressure to ensure stability for a completely individual design.

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2 Related Work Sports brands such as Adidas [2], New Balance [3] and Under Armour [4] have used algorithms to generate structures that can only be reached by 3d printing. They have obvious advantages in lightweight and shock absorption performance, and full of scientific and technological sense. However, there is not much improvement beyond the single change in styling. In other words, it is still based on the traditional shoemaking standard, which means that it is produced according to the shoe size. In addition, there are some customized sneakers designed by independent designers. For example, conceptual sneakers developed by FeetZ and One/1, fashion shoes designed by Zaha, their models are based on the user’s foot shape, and It’s not just about the look of the shoes. Due to the relatively simple data analysis, the advantages of 3d printing are not fully utilized. Therefore, the exploration of the relationship between data and design still has great research value.

3 Data Collection and Analysis With the development of information technology, big data and data collection hardware equipment, data has important value for product design at this stage. Especially, for wearable products, data as the core of parameterization can meet exercise habits of different users and realize personalized customization services. There are two main types of data that are crucial to the design of shoes: one is the 3D model of the user’s feet, and the other is the pressure distribution of user’s sole movement. The mainstream method of collecting user feet data is using a 3D scanning device and collect the pressure distribution through pressure test board. In this project, data collection was mainly include foot data, plantar pressure data, plantar heat map and upper deformation values (Fig. 1).

Fig. 1. Data of user’s foot in 3D Models and the Pressure distribution figures

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Foot Model

Whether the person is walking or exercising, the shape, size and pressure of feet are constantly changing. But it is undeniable that the human feet cannot be directly grafted into shoe production, so the determination of last is the primary task in shoe production. Many productions rely on personal experience or some “templates” that have been summarized to decide shape of the last. Thanks to parametric modeling techniques, it is flexible to create the corresponding shoe lasts according to the key points of different foot types. 3.2

Plantar Pressure Data

The distribution of foot pressure is visualized in the form of RGB. Before analyzing the pressure map data, it needs to create grids to measure the accuracy of analysis results. The denser the grids are, the more data extracted and the higher the accuracy is [5]. The pressure data is extracted by the value of the pressure map RGB corresponding to the center point of the grid (Fig. 2). The greater the R value (red), the greater the force, and the greater the B value (blue), the smaller the force. When all the points acquire the force data, the elevation analysis can be established according to the pressure value. The larger the pressure is, the higher support point is.

Fig. 2. Foot pressure distribution and conversion

3.3

Performance Data

The core of sneakers lies its functional characteristics, these mainly include the following points: lightweight, breathable, elastic, shock absorption, slip resistance and stability (Fig. 3). (1) Supportability ensures that the feet are not easily sprained during sports. (2) The purpose of the rebound is to reduce energy consumption during sports and give energy feedback to the human body.

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(3) The purpose of all cushioning is to reduce the impact of the ground to human body, thereby reducing the damage to human body in exercise.

Fig. 3. Regional function of sneakers in different situation

Shoes with a good sole structure are relatively soft during compression and strong enough during the rebound phase. Shoes are functionally classified as the sole with different structures, which need to be satisfied with the corresponding functions (Fig. 4). For the area that need rebound, a structure with good elasticity is generated; for areas that require cushioning, a structure with good shock absorption performance is generated; a structure with good stability is used in an area that needs support, so that the performance advantage of the sole can be maximized.

Fig. 4. Data overlay in shoe sole part

Fig. 5. Lattice filling in different parts of the sole

4 Module Construction The vamp part of this parametric model automatically generates bionic form by inputting user’s foot model. The sole part of this parametric model automatically generates three-dimensional lattice structures by inputting motion data of users. Each

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one of those little elements is designed specifically for a purpose, which maximize the advantages of parametric design and 3D printing. 4.1

Unit Module

The unit module refers to each individual part that constitutes the entire sole, and more types will feed the richer sole shape (Fig. 5). There are two types of unit module: the lattice structure and the shell structure. The shell structure, such as minimum surface, has good geometric performance, so it can meet the needs of lightweight, and the infinite minimum surface (IPMS) can be extended infinitely for minimum surfaces. Since Schwarz described the first minimal surface of the cycle, a large number of three-layer periodic minimal surfaces have been discovered, which Schoen added [6]. The second approach defines a unit module as lattice, which is a spatial truss of skeletal lines, and thickened by pipes along these lines. In theory, from a completely random (for example, 3D Voronoi structure) to a strictly ordered three-layer periodic orthogonal grid, any set of lines can form a lattice (Fig. 6). With a lattice structure, it is possible to reduce the weight by 40% when the same strength is reached. Moreover, compared with the shell structure, the lattice structure can be well applied to Selective Laser Sintering (SLS). This is why the design of the sole is filled with a lattice structure.

Fig. 6. Cell structure mode

4.2

Fig. 7. Unit modules experimental test

Unit Module Construction

There are two ways to thick the skeletal lines, FRep-based construction method and BRep-based construction method. The BRep-based construction typically constructs two rings of points at either of end each line with a predefined offset from its end points and connects the rings to form cylinders [7]. For each node, collect all the ring points,

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calculate the convex hull polyhedron, and the faces between the cylinders are added to the final mesh. This works well in many cases, but when the angle between the two connecting lines is small, it will lead to self-intersection of the model surface. The FRep-based structure treats the thickening as a union of multiple cylinder functions and then using the marching cubes algorithm [8] for constructing the mesh. Since the FRep construction method has good topological performance, this study used this method to thick the skeletal lines. The skeletal lines is thickened according to the value of the pressure applied to form a solid structure. 4.3

Unit Module Test

In this study, different unit modules were generated for experimental testing, and the performance of modules with various structures was found to be different. In theory, Cube topologies tend to have high elastic and low shear moduli while Octet topologies have high shear moduli and surface-volume ratios but low permeability [9]. At the same time, this study marks the elasticity, support, shock absorption, weight and other related data of each module to find the relationship between morphology and performance (Fig. 7).

Fig. 8. Two ways in sole framework

4.4

Fig. 9. The types of sole in topography

Construction of Sole Framework

After the unit module is designed, a corresponding framework is required as the frame arrangement of the sole. There are two ways to design a sole framework. One is to fill the sole with the point cloud, and 3D Voronoi structure is created based on the position of the points. The second is to fill the twisted lattice with the shape of the sole, and the twisted lattice will change its shape as the shape of the sole changes (Fig. 8). The structure in our design is based on twisted lattice rather than point cloud. The reason for choosing the lattice filling is that this method has better morphological shaping properties and more shapes can be produced by relying on this method. The lattice structure of the pattern will be distributed along the structural line of the mesh surface of the sole, and different grid surface wiring will affect the performance and appearance of the overall structure (Fig. 9). The number of lattices should be controlled within a certain range to satisfy the functionality of the sole, and the unit structure needs to be filled into each unite module to generate the entire sole structure.

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Vamp Design

In the design of the vamp form, it is necessary to take into account the corresponding functions of the upper, such as bending, gas permeability and support, and to generate a shape that satisfies the function in the corresponding functional area. For the design of the vamp, the biological texture is selected, which is close to the skin texture of the human body. The construction of the upper line simulates the process by which cells divide into intact organisms. A reaction diffusion algorithm [10] is applied to generate the desired morphology by controlling the key parameters of the reaction diffusion equation (Fig. 10). Different bio-textures bring corresponding functions, such as vertical texture to ensure good support, and the open point texture ensures breathability, which feeds the functional area of the upper. The upper is functionally partitioned, and each functional area contains specific cells A and B, the pattern of the upper are generated through the self-organization process of the above cells. With the different data of each person, so the shape of the upper surface generated by self-organization will also have a certain difference (Figs. 11 and 12). The sole structure is calculated simultaneously with the texture of the upper, and the marching cubes algorithm can naturally integrate the two into one. The design concept of the form is mainly organic, which is similar to the natural form and is quite different from the angular man-made. Finally, the mesh-smoothing algorithm is used to reduce the grid noise and smooth the shape.

Fig. 10. The reaction diffusion algorithm

Fig. 11. Generation of upper form

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Fig. 12. Detailed functional description in different parts

5 Simulation and Production It is necessary to perform finite element analysis on the model before printing to detect which areas do not meet the force requirements or are easily damaged. The finite element analysis method of the sole structure can simulate the weight bearing range, elasticity and strength of the structure at the design stage and improve the accuracy of the 3D printed sole structure design. 5.1

Finite Element Analysis of Sole Structure

Sole structure analysis and optimization applied the Karamba finite element analysis plug-in (FEA) based on the Rhino’s Grasshopper platform. The basic process of analysis is as follows: – First, the FEA model that can be analyzed by finite element, which is constructed according to the parameter model. The structure of the sole is converted into a beam, and the surface of the shoe is converted into a shell. – Then set the support of the sole model, that is, the point where the support structure of the sole is in contact with the ground. The load of the sole is set, and the pressure value acting on each area is extracted according to the pressure data of the sole of the user. – Set the necessary parameters such as material density, section and node of the sole structure. – Finally, the finite element analysis algorithm needs to be selected to calculate the model, output the calculated model parameters, and finally the results of the calculation can be visualized (Fig. 13).

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Fig. 13. Functional diagram of sole

When the finite element model is constructed, it is important to choose the appropriate algorithm. Different algorithms correspond to different analysis results. Karamba provides several different algorithms for parsing structural models. To calculate the shape variables of the sole model under the pressure of the user’s sole, the Analyze algorithm [11] is used. The algorithm not only calculates the deformation of the model, but also outputs the strain potential energy. The strain potential energy is the instability generated after the deformation of the structure. These parameters can also be used to optimize the structure of the model. Under the premise of meeting specific requirements, the weight of the sole is related to the reliability of the resulting structured, and the lighter quality means the excellent structure. 5.2

Production and Testing

It is very necessary to check the model for open edges and broken faces before model outputting. If there are three sides sharing one edge, or two faces without a joint edge and only one vertex shared, this will be a non-standard mesh face, which will not be able to process production. The most common file formats for 3D printers are formats in obj and stl. In addition, laser-sintering technology(SLS) is determined to ensure the accuracy of model printing. The processed material is identified as a TPU material because of its soft texture and excellent skin-friendly properties, which is very suitable for sports footwear. After the production of the product, the performance test of the sneakers is carried out in the Sports Biomechanics Laboratory of Beijing Sport University. The 3D printing customized sneakers fit the standard of professional sports footwear by comparing the dynamic stability data, static stability data and exercise pressure data. (Compared with the experimental data of the ASICS brand professional running shoes GT2000, as shown in Figs. 14, 15 and 16).

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Fig. 14. Comparing experimental data of GT2000 and 3D printed sneakers

Fig. 15. 3D printed sneakers (Upper)

Fig. 16. 3D printed sneakers (Sole)

6 Conclusion This paper describes a 3D printing product design methodology that customizes the sneaker design by data-driven. The generated personalized sneakers focus on data analysis, explore the complex relationships between various design elements and build parametric models. This design process can also be applied to the design of other customized wearable products in the future, such as clothing, sports protective equipment and medical equipment. In the future, our research can be extended from ordinary materials to programmable materials and biological materials, which can leverage the power of computation to derive unique, high-performing solutions to customized wearable products.

References 1. Leach, N.: What is 3D-printed body architecture?. Arch. Des. 87(6), 6–15 (2017) 2. Andy Chiu: Exploring the adidas Futurecraft 4D. Available via DIALOG. https://hypebeast. com/2017/11/the-sneaker-lab-andy-chiu-adidas-4d-futurecraft (2017). Last accessed 15 Jan 2019

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3. Jessica: Data-Customized Midsoles with New Balance. Available via DIALOG. https://n-er-v-o-u-s.com/blog/?p=7048 (2015). Last accessed 15 Jan 2019 4. PJ BROWN: Under Armour Changes the Footwear Game with Generative Design and 3DPrinted Shoes. Available via DIALOG. https://www.autodesk.com/redshift/3d-printed-shoes (2016). Last accessed 15 Jan 2019 5. Bao, R.Q.: Python for Grasshopper: Programming Allows Designers More Creative. Jiangsu Phoenix Science and Technology Press (2015) 6. Rossman, W.: Infinite periodic discrete minimal surfaces without self-intersections. Balk. J. Geom. Appl. 10(2), 106–128 (2005) 7. Bernhard, M., Hansmeyer, M., Dillenburger, B.: Volumetric modelling for 3D printed architecture. In: Hesselgren, L., Kilian, A., Sorkine Hornung, O., Malek, S., Olsson, K.-G., Williams, C.J.K. (eds.) AAG – Advances in Architectural Geometry, pp. 392–415 (2018) 8. Lorensen, W.E., Cline, H.E.: Marching cubes: a high resolution 3D surface construction algorithm. ACM SIGGRAPH Comput. Graph., 163–169 (1987) 9. Egan, P.F., Gonella, V.C., Max, E., Ferguson, S.J., Kristina, S., Manuel, G.A.J.: Computationally designed lattices with tuned properties for tissue engineering using 3D printing. Plos One 12(8), e0182902 (2017) 10. Turk, G.: Generating Textures on Arbitrary Surfaces Using Reaction-Diffusion, pp. 289– 298. ACM (1991) 11. Preisinger, C., Heimrath, M.: Karamba—a toolkit for parametric structural design. Struct. Eng. Int. 24(2), 217–221 (2014)

Data Intelligence

Research on Virtual Reality-Integrated Design of Sports Architecture Based on BIM Wei Xiao, Xuan Zong(&), and Wei Zang Tongji University, 1239 Siping Road, Shanghai, China [email protected] Abstract. This paper integrates VR technology with BIM and applies it to sports architecture design study, with regarding to the characteristics of large volume, great investment, high technical requirements and complex functions of sports architecture. VR’s advantages on immersion, perception and interaction meet the design requirements of complex space of sports architecture, break through the bottleneck in the current design process and provide an inspection method for the design scheme to eliminate blind spots. This paper focuses on the design optimization methods of space form, sight, path and signposts of sports architecture based on VR technology. By using VR to represent a built environment, the building information can be displayed hierarchically according to the research objective. By applying VR technology as a study tool to represent a building, architects can examine the space, experiment on design factors through virtual spatial experience. And a closed-loop design framework of “designsimulation-perception-feedback-design” facilitates to provide a basis for design decision-making, which will offer an innovative idea for the development of architectural design methods. Keywords: Building information model


Virtual reality
Sports architecture

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BIM

Building Information Model (BIM) is a shared information resource platform that provide a reliable basis for decision-making in the whole life cycle of a building from concept to demolition. Different beneficiary parties of a project can insert, extract, update and modify information in BIM to support and reflect the collaborative work with corresponding responsibilities at different stages of a project. It deepens the interdisciplinary cooperation and communication during the architectural design process, which has profound effect on architectural design. The advantage of BIM is achieved with the help of the integration of multidisciplinary and multi-dimensional information rather than the representation of objects. Therefore, BIM requires users to have comprehensive professional competence to understand and operate, which may hinder the communication among participants from different professions. To solve this problem, various 3D graphics display technologies are utilized to visualize the abstract and complex data information in a more © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 95–103, 2020. https://doi.org/10.1007/978-981-13-8153-9_8

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acceptable and vivid way such as images or models. Researches have been conducted on the visualization design based on BIM [1]. At present, BIM is mostly used in construction management, operation and maintenance of buildings in China. Therefore, the researches of BIM visualization also focus mainly on the construction coordination, progress control, fire monitoring and equipment management in buildings, bridges and water conservancy projects [2]. In recent years, with the development and popularization of Virtual Reality (VR) technology, the virtual simulation of BIM with VR has become a new hotspot in BIM visualization researches. VR is used to create real-size immersive virtual environment to inspect structural components, equipment layout, pipeline collision etc. In the field of architectural design, scholarly work on the possibilities of architectural design combining BIM and VR is on the rise [3]. Wenqiang Guo from Beijing Jiaotong University, taking “i-YARD 2.0” solar energy experimental house as an example, discussed the virtual interactive design and immersive experience platform based on BIM and VR [4]. 1.2

Virtual Reality

Virtual Reality creates full-scale immersive experience that simulates real environment with stereoscopic vision, auditory and tactility technologies. VR has been around for the last three decades. In 1982, US force’s Armstrong Medical Research Laboratories developed Visual Coupled Airborne System Simulator (VCASS) for battle simulation [5]. But it is not until recent years, with the rapid development of electronic equipment, high density display and 3D graphics technologies, that VR head-mounted display headset for civil use begin to develop rapidly and popularize, and attracts more attention from the mainstream. Today, it is widely applicated in the fields of gaming, entertainment, education, medical, construction and design etc. VR has the characteristics of immersion, interaction and imagination that equipped VR with incomparable superiority [6], especially in the application of architecture. At present, VR is applied in three main aspects in the field of architecture: 1. Architectural display. VR provides a new way to present the design proposal, the immersive experience create a new perspective that make the architectural space more vivid and understandable, so it is mostly used in the presentation of architectural schemes or commercial housing. 2. Spatial perception. Head-mounted display headsets allow users to roam and experience space in full-scale immersive virtual environment from perspectives closest to the physical world, which enable VR to be used in architectural teaching and experimental research to achieve adjustable experimental settings that are too costly and time-consuming to arrange in physical buildings. 3. Virtual interaction. With VR hand controllers, human-machine interaction with virtual environment is possible that certain levels of details in the model can be inspected and selected according to architects’ purposes [7], and the key factors such as forms, materials and colors can be inspected and modified to make comparison.

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2 Sports Architecture 2.1

Characteristics and Difficulties of Sports Architecture Design

With the economic progress and the improvement of people’s living standards in China, people’s needs for sports and recreational activities has increased, and the number of sports buildings is increasing accordingly. From less than 3,000 sports facilities in 1949 to 615,000 in 1995 and 850,000 in 2005. By the end of 2013, according to the 6th National Sport Venue Census in China, there were 1.646 million stadiums and gymnasiums in China [8], with an increase of 844,600 compared with 2005. In recent years, with the successive hosting of the Beijing Olympic Games and different levels of sports competitions, both the kinds and number of sports architectures in China have increased significantly. The successful bidding of the 2022 Beijing Winter Olympic Games has further injected momentum into the development of sports architecture. Sports architecture is the important public building in the city that reflects the city image and culture context. Therefore, higher requirement for the appearance is placed upon sports architecture. Meanwhile, the characteristics of sports buildings, such as large volume, great investment, high technical requirements and complex functions, increase the complexities and difficulties of design, so that architects can hardly fully control the design only by personal experience. The difficulties in inspection and feedback in the early and middle stages of the design tend to cause problems in future use after completion, which can only be reformed after construction, leading to a waste in money and resources, while as the difficulties in designing the complex space still exist. 2.2

Application of VR Technology in Sports Architecture Design

The adoption of VR technology in the design of sports architecture can meet the needs of complex space design in sports architecture. By providing designers with multidimensional immersive space experience, VR breaks through the bottleneck in the current design process and provides measurement and criterion for design evaluation. By creating a realistic architectural use scenario to simulate the completed building in full size in early design stage with VR, architects are allowed to deliberate on the space from the perspective closest to future users. Similarly, VR can provide a controlled simulated environment for examining hypothetical design on aspects of space form and users’ behavior to optimize sports architecture design in advance. Through the spatial perception experiments and participants’ satisfaction analysis, the digitalized design basis is established for architects to better cope with the elaborated and humanized design trends of sports architecture, improve design quality and avoid the shortcomings in future use. In view of the characteristics of complex space, large-span structure, complex pipeline arrangement and difficult construction, sports architecture requires close coordination between various professions. VR’s immersive experience provides a platform easier for cross-professionals to understand than 2D drawings and 3D models, thus enhances collaboration among architects, users, builders and investors.

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In addition, the combination of BIM and VR in-put peripheral devices realizes human-machine interaction. During the virtual experience, architects can make direct modification to the elements of the project such as colors, scales and materials and get the result immediately, which is conducive for design comparison and optimization, and form an efficient design process. With a sense of immersion and flexible interaction with hand controllers, the hierarchical presentation of BIM with VR enhances architect’s ability to operate and perceive virtual building model.

3 Application of BIM and VR Technology in Sports Architecture Design VR can be used to optimize the design of space form, sight, path and signposts according to the characteristics and difficulties of sports architecture design. With virtual model established based on BIM, the building information can be displayed hierarchically according to the research object. By setting up the corresponding research plan, recording and analyzing data, the deficiencies in the space can be found and improved, and a closed-loop design framework of “design-simulation-perceptionfeedback-design” is developed to provide the basis for design decision-making. 3.1

Space Form Design

3.1.1 Research Contents The basic requirement of sports grounds in stadiums and gymnasiums is to hold one or more kinds of sports activities, so the scale is restricted to the needs of the sports. In addition to the common ball games, more and more specific architecture for lesserknown sports, i.e., ice hockey, bicycle and shooting are becoming fashionable, enriching the form of sports architecture. Moreover, because of its large size and high level, sports architecture is regarded as city image that reflects city’s culture context and economic strength so that architects will spend a lot of effort in exterior appearance design of sports architecture. While large-span structure brings more possibilities for the form innovation, it also increases the difficulties in design. How to integrate internal and external space form as a whole is a major challenge for sports architecture design. At present, the general design principles of spatial form are mostly applicable to general-sized buildings, which are likely to cause confusion in judging the spatial design of mega-sized architecture such as sports architecture. On the one hand, the space form of sports architecture is difficult to handle because of the extra-large volume due to its huge functional space. On the other hand, because the scale of large-span structures is much larger than that of structures in general-sized buildings, the spatial effect will also be affected and may bring negative feelings to users if arranged improperly. Thus, how to create comfortable behavior space for users and a good transitional space between large and small-scale functional space are essential in sports architecture design, which involve overall controlling on the spatial shapes, interfaces, materials and colors. The immersive technology of VR provides simulation experience platform and design reference basis for the space form design optimization and an inspection method to detect problems in the design from the user’s point of view.

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3.1.2 Application of VR Technology in Space Form Research From the beginning of the concept, VR has been used to simulate virtual environments for various tasks that are either life-threatening or money-consuming such as combat and astronaut training. In recent years, the popularization of VR in the game industry also benefits from the fact that VR generate the most realistic sensory stimulation for players to live a second life. As personal experiencing is the best way to perceive architecture space, VR technology facilitates the understanding of human cognition and spatial conception, therefore, it has been effectively used in researches on the relationships between factors in the built environments and occupants’ cognition and spatial preference i.e., square scale, street green view ration [9], colors and materials. Chui-Shui Chan experimented on the user’s perception in the virtual environment created by VR, and studied the effect of different materials and colors on the user’s perception in an office [10]. The research on space form of sports architecture covers five major dimensions: shape, interface, scale, material and color. At present, occupants’ cognition and preference researches mainly belong to the field of environmental psychology. As the actual architectural space is affected by multiple factors, the BIM-VR model can adjust each variable separately and enable participants to be surrounded by different simulated environment to record their overall perception towards the environment. Combined virtual digital model and eye tracking devices, the user’s eye trajectory, gaze time and interest area within the design space are recorded and analyzed. The experimental data of cognitive performance, psychological status and satisfaction degree of participants in space are analyzed to reveal the spatial defects. Further verification can be carried out after adjustment to form a set of optimization-feedback design mechanism (Fig. 1).

Fig. 1. The framework of space form design research with VR

3.2

Sight Design

3.2.1 Research Contents High-level sports competitions are very enjoyable that will attract many sports enthusiasts to watch, so most sports architecture should provide not only proper grounds for sports activities, but also the stands for audience to watch the game. Meanwhile, because of the operational reasons, the sports grounds can also be used to

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organize performances when not holding any competitions. The multi-functional auditorium is considered in the architecture programming stage of newly-built sports architecture. Due to the fact that different performances have different sight standards, architects are required to design space that meets different visual requirements. Once dealt with inappropriately, problems will rise in actual use. Sight design usually includes three major aspects: sight distance, sight angle and stand slope, which affect the viewer’s visual clarity, range and comfort during the game and performance. Different kinds of sports and performances require different sight design, even though architects have summarized a set of effective principles for sight design through long-term practice, there will still be unpredictable situations in actual use, for example, the interruption of sight by structure, equipment and balustrades for certain seats, which is detailed and rare, yet still cause discomfort for audiences. With the diversification of performance forms and stage effects, clear sight is no longer the only criterion to affect the quality of performance-watching, as the creation of atmosphere become equally important, especially in fierce sports competitions and concerts. The steeper the stand is, the easier it is to increase the sense of participation and excitement of the audience, but it will cause certain deficiencies in comfort and sight clarity correspondingly. As a result, architects need to analyze and deliberate in order to achieve a balance between sight and atmosphere, which is difficult to achieve only by inspecting drawings and models if architects can’t get “real” access into the designed auditorium space. The immersive experience of VR technology can make up for this shortcoming. 3.2.2 Application of VR Technology in Sight Design Research With the virtual model built with VR, architects are able to “enter” the design before it is actually built so that the auditorium space can be inspected from a realistic view of future users at every aspect. BIM provides building information data covering the whole life cycle which means architects can not only deliberate the space form and sight design with VR at early design stage, but also have a final check on the auditorium performing effect after structure, pipelines, lightings, LED screens and sound equipment are assembled by different professions and operation departments at later design stage, thus to avoid potential problems caused by relevant equipment. By changing the space function in digital models, the layout of grounds and stages, as well as the arrangement and numbers of athletes and actors can be switched according to various kinds of competition (basketball/table tennis/badminton) and performance (concert/gala) to examine on the clarity of vision, the degree of interruption by frontrow audience and equipment, the degree of head rotation and body movement in order to have a clear view, and the sense of involvement and participation during the game or performance with observation points set up in every zone of the stands to get virtual experience. When the design defects are discovered, the interaction function of VR enable architects to make adjustment to the virtual model directly and further verify the design elements such as stand row distance, rise of the stand floor, seat size and space form. With this flexible method, space can be evaluated in early design stage for architects to obtain direct and efficient design feedback (Fig. 2).

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Fig. 2. The framework of sight design research with VR

3.3

Path and Signposts Design

3.3.1 Research Contents When competitions or performances are being held in the sports architecture, large numbers of people will be gathering inside the building. Consequently, how to navigate audience to their destination efficiently, avoid the crossing and blocking of streamlines, and evacuate quickly when emergencies occur are the most essential problems in the path and signposts design study of sports architecture, which can be divided into three aspects: walking distance, signposts and evacuation. Sports architecture is large and multi-functional, so architects should pay special attention to the rationality of streamline layout in plan arrangement to avoid any inconvenience caused by long walking distance for users. When arranging the seats in the auditorium, the entrances should be evenly placed to reduce the distance to different area, as well as the interference to other audiences during seat-seeking. At the same time, the exits and passages of the auditorium should meet the emergency evacuation requirements. In large public buildings, explicit and clear space identification system is of equal importance because it not only provides navigational aids, but also integrates with the building and improve the overall space quality. The two key points in the large-scale performance architecture with crowd gathering, way-finding and evacuation have already been researched on and a set of mature design methods have been developed to secure people’s safety in emergency by calculating evacuation distance and width. However, with the diversification and innovation in space form, unpredictable design blind spots may occur in complex plan layout besides satisfying the evacuation calculation, which are hard to discover without careful space inspection and path simulation. In the design of signposts system, users’ visual perception, psychology and behavioral in the architecture should also be taken into account. Only when good information of the space identification is perceived and accepted that response will be positive and productive, which is difficult to verify without real environment experience. And VR can offer powerful supports for architects to improve the quality of signposts.

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3.3.2 Application of VR Technology in Path and Signposts Design Research The virtual space based on VR allows users to “walk” in it, and the path simulation can be built for architects to find problems in streamline arrangement and signposts design based on the virtual model of the design scheme, by recording the time and behavior characteristics during the way-finding process to the target places or seats of the participants who are unfamiliar with the project. And by tracking the participants’ spatial observation order and attraction in the traffic nodes with eye-tracking devices, the rationality of streamline and traffic node design is evaluated to reduce the excessive length and improve the space design of traffic node. According to the feedbacks from participants, the patterns, colors and position of the signposts system are adjusted to achieve the best perception effect. In addition, the adoption of VR technology can also simulate the movement of a wheelchair in space, so as to check and optimize the barrier-free design in sports architecture (Fig. 3).

Fig. 3. The framework of path and signposts design with VR

4 Conclusion The spatial complexity of sports architecture brings challenges for architects. The combination of advantages of information integration of BIM and immersive experience of VR can not only breaks through the application limitation of VR that it is currently used mostly in design presentation, but also expands the application scope of BIM from the current emphasis on construction and management to architectural design evaluation and optimization, and better integrates BIM with the whole design process. The complementary advantages of BIM and VR can meet the characteristics of sports architecture design, and provide design inspection and evaluation methods in three main aspects: space form, sight, path and signposts. The instant feedbacks provide evidence for design decision-making, thus blind spots and flaws in design are eliminated and pre-construction optimization is realized to provide a new architecture design method.

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References 1. Wei, Y., Charles, C., Robert, G.: Integrating BIM and gaming for real-time interactive architectural visualization. Autom. Constr. 20(2011), 446–458 (2011) 2. Ruilong, G., Yichen, C.: A visual analysis of the research hotspot and evolution of BIM in China. J. Xi’an Univ. Archit. Technol. (Natural Science Edition), 8, 578–584 (2017) 3. Reza, Z., Eloi, C.: Virtual reality-integrated workflow in BIM-enabled projects collaboration and design review: a case study. Vis. Eng. 6 (2018) 4. Wenqiang, G.: The Research of Architecture Visualized Design Methodology and Practice Based on BIM and VR. Beijing Jiaotong University, Beijing (2017) 5. Namrata, S., Sarvpal, S.: Virtual reality: a brief survey. In: International Conference on Information, Communication & Embedded Systems (ICICES 2017) (2017) 6. Grigore, C., Philippe, C.: Virtual Reality Technology. Wiley, Hoboken (2003) 7. Yari Mirko, A., Enrico, A., Daniele, M.: Virtual reality experience for interior design engineering applications. In: 26th Telecommunication forum TELFOR 2018 (2018) 8. Official Site of General Administration of Sport of China. http://www.sport.gov.cn 9. Leiqing, X., Ruoxi, M., Zhen, C.: Fascination streets: the impact of building facades and green view. Landsc. Archit. 10, 27–33 (2017) 10. Chiu-Shui, C.: Does color have weaker impact on human cognition than material. In: Computer-Aided Architectural Design Futures, pp. 373–385 (2007)

Interactive Performance and Immersive Experience in Dramaturgy - Installation Design for Chinese Kunqu Opera “The Peony Pavilion” Qianhui Feng(B) The Bartlett School of Architecture, University College London, London, UK [email protected]

Abstract. This thesis proposes a new form of theatre using the design of a spatial interactive installation that will assess the relationship between performance, space and audience, thereby providing the audience with a thoroughly immersive experience. Through the use of digital technology and computer programming a new narrative and immersive space may be created. I shall investigate the process of a performance based interactive installation which will support the development of the dramatic space. For this project I have selected the traditional Chinese Kunqu Opera THE PEONY PAVILION, as my research example. THE PEONY PAVILION tells a love story through the medium of dream beyond space and time, even beyond life and death. Nonetheless, the employment of digital technology can result in a new and better theatrical interpretation; the coming together and fusion of classical drama and contemporary digital art has the potential to give the opera a new lease of life. As well as using this spetial interactive installation in connection with this particular opera, it will unleash the potential in the dramatic possibilities of body, space and time. Furthermore, to achieve an interactive experience for the participant and immersion in the dramatic world, the installation can also be seen in a wider context and not only in the parameters of this one particular art form.

Keywords: Interactive performance Digital technology · Computing art

1 1.1

· Immersive experience ·

Introductions Interactions in Dramaturgy

As Causey states in his book, THEATRE AND PERFORMANCE IN DIGITAL CULTURE (2006): “Technology tends to form a new perspective of dramaturgy beyond the traditional theatre, and performance can be transformed from two aspects: first, technology simulates the art of performance into an c Springer Nature Singapore Pte Ltd. 2020  P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 104–115, 2020. https://doi.org/10.1007/978-981-13-8153-9_9

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inter-disciplinary format, opening minds; and mix-technology can combine performance, dance and installation art into a new performance space.” In this case, dramaturgy becomes a practical bridge between art and technology, and expands its potential uses beyond the confines of theatre. In other words, it breaks down the disciplinary boundaries of art to and allows it to expand into other areas. Interactive performance has become more significant in contemporary dramaturgy. In order to proceed with an investigation into this new type of interactive artwork, it is necessary to explore and name its elements. Salter (2010) labelled them as: body, space, time, and technology (Fig. 1).

Fig. 1. Elements of dramaturg (Chapple and Kattenbelt 2006)

1.2

Immersions in Dramaturgy

Historically, stage and auditorium have tended to be separate. In immersive and interactive theatre however, the space tends to be designed holistically: as an area shared by audience and performers alike. To my mind, this enhances the immersive potential of theatre. The concept of immersive theatre emerges from the use of spatial perception in dramaturgy. Punchdrunk has been closely associated with the term “immersive theatre”. Asked how to define the term “immersive”, Punchdrunk’s founder Felix Barrett explains that it is bound up in allowing the audience to exist within the performance space, thus influencing the drama. “It’s the creation of parallel theatrical universes within which audiences forget that they’re an audience, and thus their status within the work shifts” (Cao et al. 2014). In immersive theatre, many elements allow an audience to participate in a performance rather than just observing it. These elements include lighting, sound, physical presence, space and technology; all of which can directly impact upon the experience and perception of the audience.

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Technology and Tests Spatial and Embodied Augmented Reality

The fusion of live performance with virtual performance is termed “mixed reality performance”, a phrase which conveys the meaning, not only of the coming together of the real and the virtual but also of the actor and the audience member (Benford and Giannachi 2012). Mixed reality performance represents a new development in the world of artistic experimentation, where it is combined the use of a plethora of digital technologies and differing performance styles to compare and contrast the real and virtual worlds, and allow them to influence each other (Beira 2017). Through analysing and streamlining the interaction between the individual and their respective surroundings within design-augmented areas, artists have created embodied interactions which are referred to as mixed-reality performances’ (Beira 2017) (Fig. 2).

Fig. 2. Spatial and embodied augmented reality

2.2

Image Generating in Computer Programming

Computer programming allows us to create and generate visualisation through various means. Visualisation of movement specifically can be generative, for instance, augmentable visualisation that changes depending on movement. As such, designers are able to uncover new possibilities or dynamics through working with visualisations (Hansen 2011) (Fig. 3). An important aspect is the flexibility of the visuals or sketches themselves as to continually create further engaging visualisations, the ability for them to be changed and reassembled is necessary. Through the use of augmentable visuals, movement in regards to semiotics can be altered and further explored in relation to the context in which it is being used.

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Fig. 3. Coding dreaming space interactions

2.3

Projection and Visualisation

The emotion which are expressed by a dancer during their performance provides valuable and unique data, which can then be analysed and later used within digital environments and provide visual artists with frameworks with which real-time events can be created. These can then be used within an augmented environment which are generated by video projections. Projector-based augmentations are comprised of video projections and aesthetic programming. These facilitate an immediate change in the relationships between body and space, both of which are integral aspects of dance and as such, allows the complexity of the performance to increase. This framework in particular has helped create the laboratory-based environment, in addition to creating a space which was digitally-enhanced that blurs the lines between the physical and the projected light and sound aspects. The projections are entwined with the human bodies that interact with them which allows the animated to become an extension of the human dancers (Fig. 4). 2.4

Body Tracking

Technology is an infinitely crucial aspect in regards to the continued research of body movement and motion tracking. Studies of the possibilities of the movement of the body simultaneously informs the design principles of ergonomics as well as the utilisation of digital technology, visualising and tracking. Within the realms of digital performance, the body’s movements are interpreted via the use of motion tracking. Movement being processed by technology is becoming increasing common, especially in interaction design which can be seen most prominently in field of videogames such as Microsoft’s Xbox Kinect. Combining visual sensing with projection in live digital visuals is the modern day equivalent of the use of perspective within painting. It is essentially an illusion, but can also be the foundation and

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Fig. 4. Related experiments between body and performance

point of a piece of work itself, simultaneously an impressive sight to behold as well as a platform which facilitates a new form of art itself (Fig. 5).

Fig. 5. Tracking patterns this test is to track patterns which follows the motion of human arms. Input: TouchDesigner Output: Kinect and projection

3 3.1

The Installation Design Research Concept of Reinterpretation Chinese Kunqu Opera the Peony Pavillion

Kunqu opera is a traditional Chinese performance art which has existed for more than 600 years. It encapsulates many different forms of art such as literature, music, dance, martial arts and drama, and as such, has greatly influenced the history of these respective disciplines. One of the most famous plays of Chinese history is The Peony Pavilion which involves a young girl who dies as a result of the unrequited love of a stranger she has met only in her dreams. However, the power of another young man’s love revives her.

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This story originated over 400 years ago during China’s Yuan dynasty and has since been recreated using contemporary art techniques, many instances do not focus particularly on the story itself, but more on the spirit and themes of the story itself. Namely the pursuit of ideals, individuality, liberation, pursuing ones dream and to awakening to the reality of life. My project, which was based on one of the most exciting scenes of “Peony Pavilion”, is designed to bring new interactive and immersive art forms to the audience with a fresh experience that allows the viewer to be completely immersed in Du Liniang’s dream. Walking freely in the magnificent dreamscape as designed by myself, the audience can feel the spirit of the story and feel complete immersion. 3.2

Physical Installation Design

The idea of space unit design is based on the storyline spot, Chinese classical private gardens, and it uses the principle of garden design to create an abstract spatial installation. The total area is about 15.6 * 10.7 m, and it is composed of 99 vertical hanging gauzes, 0.6 * 4 m each, a 2700-m wide and 4-m tall white string stage elevation, five HD projector and three kinects. It can be mainly divided into two parts: the main watching area and performance interaction area. The main watching area is in an enclosed space before entering the interaction area. The performance interaction area includes the central stage and audience interaction area, with an 8.4 * 8.4 * 4-m space designed with three intercluded vertical gauzes. By using tinny strings and veils, the stage is divided into dream and reality spaces, and it interacts with performers by showing digital images through projection. The audience can walk through the gauzes around the stage, watching performance from different angles, and taking part in the drama. By proper using of kinect, TouchDe signer, unit programming and projection interaction, this device reimagines the relationship between performers, audience and space, thus to create a magical interactive theatre (Figs. 6, 7). Site-specific performance generates a considerable level of interactivity, because the audience member is invited actively to participate in the drama, or dynamically to influence its progress, make decisions and come to conclusions about the action. This notion of the audience member being within rather than outside the action, confers responsibility onto the audience member, with regard to making meaning. 3.3

Design of Interactivity

Computing Visual Images and Animations Computer programming in regards to the design processes of dramaturgy is effective way to realize visual imagery and animation. As such, I have utilised computing in regards to processing through which I have created an abstract visual animation based on the storyline. To create and sufficiently encapsulate the idea of a dream-like space, I have used various types of abstract visual effects (Fig. 8).

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Fig. 6. Axonometric analysis

Fig. 7. Axonometric analysis

Real Bodies and Virtual Bodies To find ways to create an interaction between virtual and physical bodies is more efficiently to enhance the dramatic tension. The physical body of the real actor and the virtual body are mutually dependent. The virtual body is an abstracted image of lines, shapes or other forms generated by the performing, physical body of the actor. In my opinion, the creation of this virtual body attempts to establish a form of communication with the performer himself; but this visualisation needs to be related to the text and to the drama itself: visual effects should not be indulged in for their own sake.

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Fig. 8. Visual effect shot

In my research I have done a number of tests whose aim was to establish connections between the organic body and electronic media, making use of the interactive relationships between performers and their environment. I used Leap Motion and Kinect to track the body’s movements; and TouchDesigner to generate the creation of colour, pixels and skeleton. In a series of experiments to simulate the physical body I set up a system which could generate images in virtual space. Using virtual body movements, light, colour and lines interacting with the actor’s performance, the space was transformed into a four-dimensional form which rotated and morphed, thereby challenging the audience’s perception (Fig. 9). Projection Mapping and Interaction Throughout this project, I have utilized 3d projection mapping design within a three-dimensional space to convey the plot, in addition to giving form to the characters on stage. Through using Kinect to interact with the actors, as well as computer graphics, humancomputer interaction technology, sensor technology, and artificial intelligence, these aspects combined provide a more visual, auditory, tactile, and sensory stimulating experience. Depth sensors have also been used alongside 3D projection mapping in the preliminary investigation of using augmented environments. Alongside this, current choreographic research in relation to the interaction design process has also been analysed which has helped formulate concepts relevant to such a design (Fig. 10).

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Fig. 9. Body motion and augmented reality in 2 s

Fig. 10. Principles of interaction

3.4

Immersive Augmented Environment of Chinese Classical Garden

In contrast to the traditional dramaturgy of the Peony Pavilion, I have created an immersive space which participants can interact with. The concept of the space it self is that of a classical Chinese courtyard, however in this case it is more abstract in style. The dream sequence in the garden which involves the characters Du Liniang and Liu Mengmei is the focus of the piece (Fig. 11). The representation of the garden is generated from a point cloud model reconstructing a section of 19th century businessman Hu Xueyan’s villa, including a classical Chinese courtyard garden. First, the photographic documentation of the actual site is collected through taking onsite pictures or extracting frames from camera videos. These pictures should have enough overlap and detailed information allowing a more inclusive and precise reconstruction. Then the stills are processed by software RealityCapture to build the point cloud model (Fig. 12). With this model, the file can be exported as xyz format, recording each point’s three-dimensional coordination as an individual parameter that could be used in any other point based software. Thus, an abstract animation representing the Garden can be made to create an immersive argument environment.

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Fig. 11. The dream interrupted

Fig. 12. Abstract point cloud of chinese garden

The audience are free to walk wherever they choose to within the space and whilst doing so, their bodies are tracked which allows them to interact with their virtual selves, the actors and even the projection effects (Fig. 13). This means that the audience are aware and a part of creating the meaning of the performance itself. The dramaturgy of the piece itself creates the vocabulary of discussion alongside identifying various register shifts’, in addition to negotiating deliberately ambiguous or unclear structures of contemporary work. Conversely, contemporary work could also be seen as exposing and expressing its own respective dramaturgical processes, and thus draws on and defines the dramaturgical sensibility of the writer and director as well as the audience themselves. At its most basic level, the live encounter within the interactive space is potentially represented by the relationship between the actor and the audience which presupposes interaction and critique to a certain extent, in addition to shared imaginative engagement. This allows the audience to enter a state of imagination, and share the feeling of creation that exists within all art forms.

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Fig. 13. Interact with the opera

4

Conclusion

In summary, this report focused on achieving interactive performance within an immersive environment via the utilisation of digital methods and visual art. It also aimed to create sensorial and experiential visual feedback through the use of advanced media design as well as co-creating an interdisciplinary ex-change and link between the performance, space, audience and the dramaturgy. As a result of this study, I have reached the conclusion that to create a new form of dramaturgy, the use of digital methods is incredibly helpful due to its immersive and interactive nature which essentially opens up an infinite amount of new possibilities to this previously fairly rigid and traditional art form. In the future, I aim to create a practical guide for the artistic, conceptual and technical implementation of mixed-reality performance. Within this guide, I plan to outline visual programming and media design relating to sensing technologies (input) and projection-based augmentations (output). In addition, a theoretical and critical analysis of the performances in dramaturgy via the use of reporting and analysing creative applications will also be included alongside mapping strategies of motion tracking systems as well as projectorbased augmentations. Finally, I also seek to further explore augmented reality’s potential within the context of contemporary dance performance through projector-based augmentations to increase the level of interaction between the space, actors and audience.

References Beira, J.F.: 3D [Embodied] projection mapping and sensing bodies : a study in interactive dance performance (2017) Benford, S., Giannachi, G.: Interaction as performance. Interactions 19(3), 38–43 (2012) Cao, M., et al.: Engaging the Body in Immersive Theatre: Sleep No More and the Rhetoric of Arrhythmic Experience (2014)

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Chapple, F.M.N., Kattenbelt, C., International Federation for Theatre Research.: Theatre Intermediality Working Group: Intermediality in Theatre and Performance. Rodolpi, Amsterdam (2006) Hansen, L.A.: Full-body movement as material for interaction design. Digit. Creat. 22(4), 247–262 (2011) Salter, C.M.N.: Entangled: Technology and the Transformation of Performance. MIT Press, Cambridge, Mass, London (2010)

Discussion on Interactive Environment Design Based on Multi-sensory and Behavior in the Background of Digital Future Hongling Li and Hexuan Dong(&) School of Architecture & Urban Planning, Huazhong University of Science and Technology, Wuhan, Hubei, China [email protected] Abstract. With the rapid development of Internet and artificial intelligence technology, interactive design gradually permeates people’s lives and brings new interactive experiences to people. Throughout the current situation of interactive design at home and abroad, the interactive design for the space environment is often based on the individual will of the designer to enhance its interactive experience, but the research on the inner emotional needs and sensory experience based on environmental behavior is relatively insufficient. Starting from human sensory experience and spatial environment behavior, this paper further explores intelligent spatial information entities, discusses interactive factors between human and environment, and reveals interactive design of human and spatial environment based on multi-sensory perception and behavior. In the context of the digital future, it provides reference for the design and research of interactive space environment in smart cities. Keywords: Interactive environment
Interactive design Multi-sensory environment
Environmental behavior




Contemporary living environment discipline is facing a huge transformation and challenges, and we are in a new era of humanism entrance. From Renaissance to Modernism, a universal value has gradually been established. However, with the rapid development of the Internet and artificial intelligence, new digital media and other technologies have brought us closer to personalization than ever before. The subject’s emotion, memory, senses and interaction with the environment require us to reunderstand the laws of the space environment, especially the laws related to the human subject in space. Therefore, the tools, methods and even thinking modes of human settlement environment disciplines need to be expanded, and they should be better coordinated with other disciplines to obtain more accurate, more exquisite and more supportive design methods for interaction between human and environment, so as to return people to the center of space.

© Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 116–123, 2020. https://doi.org/10.1007/978-981-13-8153-9_10

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1 New Expression of Space Environment Under Digital Future Trend The booming of digital technology has had an important impact on the concept of space and environment. On the one hand, digital technology has promoted the development of complexity science and aroused people’s attention to the complex function between architecture and environment. The randomness of the interaction between buildings and the environment leads to a large number of data that are difficult to summarize by laws. The information capacity of the data cannot be compressed. How to deal with these high-capacity data quickly becomes a difficult problem in design [1]. On the other hand, digital technology transforms the relationship between human and space environment into more objective and scientific data analysis, deepening designers’ understanding of the complex interaction between human and space environment. At the same time, computer simulation technology has promoted the development of system theory, and the research on the system characteristics of the interaction between human and space environment has been deepened. From the point of view of synergetics, the subsystems in the parent system interact and cooperate with each other. If a subsystem trend is dominant, it will push the whole system from disorder to order [2]. As a long-term evolutionary system in nature, human beings have the trend of dominance in the large-scale system composed of space environment, which can control the development of building subsystems, thus promoting the overall system of human settlement environment from disorder to order. Designers should take the impact of the space environment as the basis for the adjustment and optimization of the scheme, so that the design scheme generates a systematic tendency of the concept of the space environment under the constraint of multi-sensory behaviors of people, thus making the design logic more dense and maintaining the integrity and interactivity of the space environment. In this process, digital technology as a new tool and method has played a very good role [3]. 1.1

Touch-Centered World and Internet of Things

In the early days of science fiction futuristic fantasies, people have always dreamed of controlling the world around us by touching or waving their hands. Many years of science fiction inspiration have become a reality as technology and human-machine interactions have evolved. Now that we live in a world of touch-centric worlds and the Internet of Things, people have more and more demanding experiences in interactive environments, and there are more ways in which space environments can interact with people. 1.2

Immersive Experience

Immersion makes people focus on the current situation and feel happy and satisfied. Immersive experience often includes both human sensory experience and human cognitive experience. Sensory experience mainly makes people feel pleasant or exciting,

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such as amusement parks and Disney theme parks that have certain challenges to people. Cognitive experience matches one’s skills with challenges, such as chess, mine clearance and other strategic games. Facts have proved that only activities that contain rich sensory experience and rich cognitive experience can create the most engaging flow. Immersive design can make use of the design of situation, immersion, role, atmosphere, plot, rhythm, etc. to make people more interactive with the environment. 1.3

Multi-sensory Environment

Space environment design can not only attract people visually, but also stimulate people with all senses, including human touch, hearing, taste and smell. For example, the exhibition of “Emotion Museum” in new york City uses audience’s senses to design five exhibition areas based on human vision, touch, hearing, taste and smell. Each area has its own unique interactive multi-sensory experience. From the perspective of the process of human understanding of the world, it is a combination of hearing, vision, touch, perception and various senses, which function at the same time. Dirkhov said in his article “Skin of Culture-Electronic Cloning of Real Society:” Our understanding and understanding of words is a process of understanding another thing through one thing, a process of touching and feeling many levels with more than one sense organ at a time. It has become clear that touch is not skin but the interaction of various senses” [4].

2 The Transformation Power of Technical Media in the Context of Smart Cities 2.1

Update and Development of Technical Media

McClure did not point out in his book “Understanding Media” that “artificial technology is the extension of human body. People have completed the extension of body space in the mechanical age: the development of electronic technology has extended our central nervous system” [5]. At first, people only rely on the strength of their limbs to transform the world. Later, mechanical technology separately strengthened the strength of individual limbs, which accelerated our progress in transforming the world. In reality, human behavior is transmitted from the central nerve to each limb part after the brain sends out instructions, and each part carries out work in coordination after receiving instructions, thus human beings can do many pioneering work. The invention of electronic technology can play a role similar to that of central nervous system. After the machine is implanted, people can issue instructions through the instruction function of information electronic technology and the driving function of power electronic technology. The machine accepts, executes and feeds back the instructions. The single mechanical function is connected by the electronic central nervous system and operates cooperatively according to the instructions in the brain or computer. From printing to the internet, “new technologies create a completely new human environment, and the new environment must completely reprocess the old environment” [6]. Artificial technology is the medium through which people know the environment.

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The media has introduced our understanding to a new scale. The change of scale brings about structural changes, and structural changes cause changes in life. Internet and computer technology will lead the transformation of space environment design. 2.2

Smart Space Information Entity

Modern cognitive geography regards the human brain as a computer-like information processing system. They think that the information processing system of the human brain is made up of four parts: sensors, reactors, memories and processors. First of all, the space environment inputs information to the sensory system, i.e. receptors. Then, the sensor converts the information. Before entering long-term memory, the converted information should undergo symbol reconstruction, identification and comparison through the control system. The memory system stores symbol structures that can be extracted. Finally, the reactor reacts to the outside world. As a result, the cognitive process of human beings to the world is effected by comprehensive senses. Only by fully recognizing the human brain as an information processing system and scientifically constructing the intelligent space environment as an information entity can a smart interactive space environment be designed.

3 People’s Multi-perception and Behavior 3.1

People’s Five Senses

People’s five senses are: vision, hearing, smell, taste and touch. The design method of space environment shapes the environmental characteristics of human sensory experience through materials, light, color, space characteristics and modern interactive technology, and generates happiness through interaction with people. 3.2

Environmental Behavior

The word “behavior” is interpreted in the Oxford dictionary as: “the performance or function of people, animals, plants, chemicals, etc. under certain specific circumstances” [7]. Fox proposed in “Interactive Architecture Will Change Everything” [8] that “the organic model is an imitation of life, development and reciprocity”. The so-called environmental behavior refers to the science of summarizing and analyzing the dynamic changes of the relationship between human and objective environment. Environmental behavior involves a relatively large number of disciplines, and is different from environmental psychology. Based on the specific analysis of environmental impact factors, this paper grasps the impact of such factors on human life, and then improves the space environment and optimizes the construction effect of the space environment through appropriate research methods [9]. In the process of interactive design, the intelligent application function of the design should be brought into full play so as to enrich people’s interactive experience. Vending machines are not limited by time and place, and can realize full-time sales activities. At the same time, they do not need to waste a lot of human resources,

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have relatively low application cost, support various payment methods, meet various behavioral needs of the crowd, and are accepted and recognized by most people [10]. From the application characteristics, it can be seen that environmental behavior research shows that great importance is attached to the harmony between human and space environment, so as to optimize the design effect and improve the satisfaction of space use. 3.3

Emotional Effects

Emotional design is divided into instinct, behavior and reflection. In environmental interactive design, besides satisfying people’s instinctive visual pleasure and ensuring the smoothness of people’s behavior process, people’s preferences, experience and culture are fully considered in the design process and transformed into special symbols, thus establishing emotional connection. A good design that triggers emotional effects lies in subtle influences. People do not need to understand the design intent, but emotions have been affected. In the space environment, people naturally make choices according to the designer’s predetermined trajectory. Narration is the key to creating emotional responses. Design can be transferred to human actions or emotional responses not only through visual images, but also through the overall feeling of space and time (Fig. 1).

Fig. 1. From WeChat public number Tencent ISUX

4 Interactive Design of Space Environment Based on Multiperception and Behavior 4.1

Interactive Factors of Environment

4.1.1 Environmental Factor When we define “interactive environment”, the established physical space itself is the reason why it becomes an environment. Whether the environmental boundary is closed

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or open, inside or outside, it has natural light or artificial light, even the time of day, temperature or weather will have a great impact on the interactive design of the space environment. Just as lighting plays an important role in environmental considerations, so does sound. If it is in a public space with heavy traffic, the design should be coordinated with the environmental noise. If a sound device is needed to convey the story, it should be used in a quiet space. 4.1.2 Material Factor The buildings and structures around the environment will not only affect their structures, but also the technologies used. For example, when the processor and the display are running at the same time, the consumption and heat dissipation of the energy released by the operation must be considered, while the environment may need to install ventilation devices to maintain the comfort of the space under certain material factors. 4.1.3 Functional Factor The purpose and scope of the construction of interactive space environment, the audience’s data and information will all become the functional parameters of the space environment. The perception, discoverability and exploration of the space environment as well as the sensory experience and immersion environment can be used for shaping interactive environments with different purposes. CMS database input, API push information, statistics collected in real time and details of machine learning intelligence expansion can all control data in a variety of ways, including voice, touch, gesture, motion sensors, temperature sensors, game handles and objects, devices, artificial intelligence, mixed reality, augmented reality, and even brain waves. No matter what the input and output are, there are many possibilities for functional interaction methods in the space environment with the consideration of multi-dimensional space and time. 4.1.4 Physical Factor Static or dynamic physical environment factors in the space environment affect the design form and function interaction. Through the combination of digital space and specific objects, people can be guided to actively participate in the design of humancentered interaction, so that people can interact with the surrounding space environment as naturally as in daily life. 4.1.5 Emotional Factor In order to attract people to participate in the interactive environment on the emotional level, the information provided by the design must be intuitive and clear. No matter what story the space environment tells, it is important to design from the perspective of social and cultural responsibilities. It is not only necessary to consider the cultural boundaries of the crowd, but also to trigger different emotional thoughts of the crowd. At the same time, if people are designed as narrators of the story, their interactive participation can be increased, and the interactive emotional connection between people and the space environment can be further deepened.

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Environmental Interactive Design

Environmental interactive design based on multi-sensory behavior must first attract the crowd, which can be attracted by the focus of the environment. Whether in the visual, tactile, auditory and other sensory levels, or by mobilizing the crowd’s behavior or emotions, the attraction of interactive design is the key, and then design relevant content to attract the crowd to participate. Through design experience, they can experience emotional reactions, and then actively explore and think to discover and experience other interactive content in the space environment.

5 Conclusions In the beginning of “Theory and Design in the First Mechanical Age” [11], Banham looks forward to the second mechanical age, which is characterized by miniaturization and homemaking of machinery, and is different from the era characterized by big machine capitalism in the first mechanical age. At present, China is in an era of peoples innovation, which also requires designers to take on more roles as innovators. Designers cannot only rely on electrical equipment engineers to put forward the idea of intelligent buildings, and the thinking of space behavior opened by interactive environment points out the direction for designers to move forward. The interactive design mode of human and space environment gives full play to the advantages of digital technology, realizes the process of generating space environment shapes from human multi-sensory behaviors, and can optimize and interactive the concepts and methods of environment design. The progress of digital technology platform will push the interactive design mode of human and environment to a higher level and transform the theoretical mode into a complete design scheme.

References 1. Gleiniger, A., Vrachliotis, G., Bellut, C.: Complexity: Design Strategy and World View. Birkhäuser (2008) 2. Wu, T.: Research on Self-Organization Methodology. Tsinghua University Press (2001). (in Chinese) 3. Kotnik, & Toni: Digital architectural design as exploration of computable functions. Int. J. Archit. Comput. 8(1), 1–16 (2010) 4. Dekhof: Cultural Skin: Electronic Cloning of Real Society. Hebei University Press (1998) (in Chinese) 5. McLuhan, M., Mcluhan, M.A., Lapham, L.H.: Understanding Media: The Extensions of Man. MIT Press (1994) 6. Laurel, B.: Art of Human-Computer Interface Design. The Art of Human-Computer Interface Design. Addison-Wesley Longman Publishing Co. Inc (1990) 7. Originally by Hornby, & = AS Hornby. Oxford Advanced Learner’s Dictionary. Ox-ford University Press (2002) 8. Fox, Michael A., Chen, Y.: Interactive architecture will change everything. Decoration 3, 44–51 (2010)

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9. Xu, M., Jiang, W.: Application and research of interactive product design based on fuzzy comprehensive evaluation. Comput. Age 2, 40–41 (2015). (in Chinese) 10. Xue, X.: Environmental Behavior. Engineering Technology (Full Text) (1), 00286–00286 (2017). (in Chinese) 11. Banham, R.: Theory and Design in the First Machine Age. Mit Press (1980)

Artificial Intelligence Applied to BrainComputer Interfacing with Eye-Tracking for Computer-Aided Conceptual Architectural Design in Virtual Reality Using Neurofeedback Claudiu Barsan-Pipu(&) College of Architecture and Urban Planning, Tongji University, Shanghai, China [email protected]

Abstract. This paper proposes a new method of integrating the latest technologies joining brain-computer interfaces (BCIs) with eye-tracking (E-T) and applying this combination to conceptual design for architecture using AI-driven neurofeedback (NFB) to help identify the designer’s intent and respond dynamically to it. Using integrated state-of-the-art E-T and BCI solutions for the latest head-mounted display (HMD) devices, this paper aims to provide an insight into the applicability of these solutions and their potential benefits and pitfalls to creating innovative conceptual design instruments. By harnessing artificial intelligence (AI) within a Game Engine (GE) context, the proposed solution tries to create a new procedural design-interaction approach that uses neurofeedback to learn and adapt to its user’s design intent without the need to truly understand the complex decision-making processes taking place inside the designer’s mind. While limited in its scope, this approach raises some interesting topics and questions that are discussed in more detail in the last section of the paper. Keywords: Brain-Computer interface (BCI)
Eye-tracking (E-T)
Virtual reality (VR)
Neurofeedback (NFB)
Artificial intelligence (AI)
Conceptual architectural design

1 Introduction Current development of Virtual Reality (VR) technologies, both on the hardware and software fronts, has led to the creation of new tools for early stage design, with most of these instruments finding direct applicability in the architectural field. While many of these tools focus on VR’s immersive and true to scale spatial exploration capabilities for architecture, systems that harness the true potential of VR for the conceptual design phases for form generation have begun being developed over the last years as the technology became more widely available, such as Gravity Sketch, Mindesk VR or Maquette VR. Designing in VR, beyond the obviously beneficial immersive aspect, faces an important challenge, as the traditional methods of interaction and operation cease to work, being replaced by VR controllers or hand tracking systems that impose a different type of user experiences, that may be either lacking in precision or in © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 124–135, 2020. https://doi.org/10.1007/978-981-13-8153-9_11

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long-term usability due to fatigue. As this need for a paradigm shift in user interaction in virtual environments became more apparent, technologies such as Eye-Tracking (ET) and Brain-Computer Interfacing (BCI) have recently started to be used to support new ways of interacting with digital virtual forms and entities.

2 Related Work Because of their early adoption of VR technologies, Game Engines (GEs) such as Unity or Unreal Engine have been used to develop both commercial and research applications. In [1] a synthetic design approach integrates VR with agent-based modelling. By combining a GE front-end with a powerful procedural back-end based on SideFx’s Houdini and introducing the concept of High-Level Parametric Conceptual Design Entities (HL-PCDEs) in [2], Neomorph VR, a new VR conceptual design tool, is being proposed. The potential of using E-T in VR environments for both interaction control and cognitive and computational challenges [3] is being explored as new VR technologies integrate support for E-T directly within the HMD (TobiiVR, aGlass, Fove). Being able to precisely follow the gaze [4] and fixations [5], especially in VR contexts provide the user with new means of hands-free, controller-free interaction while also gathering important feedback on areas of interest [6], and even on elements of emotional response by monitoring subtle pupil diameter changes [7] not related to the HMD’s display contrast shifts. In [8], the Emotiv [9] EEG system is proposed for BCI-only user interaction in VR worlds. Complementing E-T, more recent experimental BCI technologies such as Neurable’s EEG solution [10] provide all-in-one VR integrations for an extra layer of interaction and neural feedback. While limited in the ability to measure the valence aspect of the emotional spectrum [11], the 6 dry-electrodes solution allows more comfort (by not requiring conductive gels or saline solutions), a good EEG signal acquiring of the brain waves with a denoising algorithm that makes possible using the technology in normal (non-laboratory) conditions and precise measurement of the arousal aspect [12] via a proprietary algorithm. In combination with either TobiiVR or aGlass E-T solutions, the arousal response can be associated with specific visual elements, thus enabling a more precise spatial evaluation of the respective elements. Given that the ideation task at hand is not a simple design evaluation problem, as is the case with most EEG-based application, but a conceptual design task in a dynamic environment, in order to achieve the desired adaptive response, two Machine Learning (ML) methods are being explored, both using neurofeedback as the driving reward mechanism. Reinforcement Learning (RL), a ML method introduced in 1979 [13], consists of two main elements, the environment (VR in this case) and the Agent that formulates the policy in this model, as opposed to supervised learning methods where the designer generates the policy. The agent’s direct interactions with the environment via state assessment and chosen action is based on a reward-maximization model (Fig. 1 - left). Imitation Reinforcement Learning (IRL) is similar in structure with RL but uses a Reward Estimator (RE) that is based on an expert behavior model, in this case the

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designer’s (Fig. 1 - right). The Proximal Policy Optimization (PPO) reinforcement learning model [14] is being employed due to its more simplified implementation as part of Unity’s ML-Agents package [15] that provides the ideal experimental playground as it is integrated within the GE and provides a Python bridge to TensorFlow for training.

Fig. 1. Reinforcement Learning (RL) model (left) and Imitation Reinforcement Learning (IRL) model (right) in VR responsive environments

3 Methods 3.1

Research Question

This paper proposes to investigate a first experimental application of how these systems, used in conjunction with Artificial Intelligence and Gaming Technologies, can help create new Conceptual Design Tools for architecture using neurofeedback. The scope of this research is proving that such a system can be built and that it allows for early stage design investigations in VR using just BCI for all types of interactions and design decisions and proving the validity in the context of neurofeedback-driven conceptual design using two ML approaches: Reinforced Learning and Imitation Learning. Built upon the author’s previous investigations into VR-based conceptual design environments and on the paradigm of HL-PCDEs, the proposed system investigates harnessing the power of the Graphical and ML components provided by the Unity GE front-end in conjunction with a powerful procedural back-end build upon SideFX’s Houdini. Seen as just an initial step of a larger research endeavor, possible research directions stemming from this initial investigation will be detailed in the Further Investigations subchapter at the end of this paper. 3.2

AI Powered High-Level Parametric Conceptual Design Entities (HL-PCDEs) Using Neurofeedback

The main problem with most conceptual design applications is that they rely on manipulation of low-level components (primitives, points etc.) for formal micromanagement that usually require precise user input, using either a mouse, a digital-pen, VR controllers or other types of devices. While these approaches have their definite

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benefits, since they allow for accurate (localized or global) manipulations, in order to create a BCI-driven input system, new types of manipulators and new corresponding dynamic entities need to be created that operate at a higher design level. Originally introduced by [2], HL-PCDEs were designed to address the conceptual design problem in Immersive Virtual Reality Environments (IVREs) by providing complex, datadriven entities that embed complex algorithmic elements that interact with each-other based on compatibility layers and can be influenced by affectors (AFF). Ample presets provide rapid and intuitive usage scenarios that help designers understand potential usages without needing to understand the underlying computational algorithms, and that can be extended with custom presets resulting from parameters alterations. As described in the original paper, the HL-PCDEs are built around SideFX’s Houdini Digital Assets (HDAs) and allow for complex geometric and data attributes to flow thorough, be generated or suffer alterations. Different HL-PCDEs can build complex conceptual chained systems for advanced, high-level conceptual design tasks. For a more in-depth understanding of the HLPCDEs please refer to the original reference in [2], as the rest of this paper will only illustrate how these structures are used by the proposed neurofeedback-based BCI design system. The Smart Affectors (SAs) component of HL-PCDA is proposed to be extended in the current paper with the capability of using AI in order to respond in real-time to the designer’s conceptual design intent. The AI-driven SAs can be positioned and moved using E-T + BCI, while their effect on their associated HL-PCDEs is based on the Smart Presets (SPs) dynamically chosen and adjusted by the AI system in response to the EEG-based neurofeedback. For the present study, two types of HL-PCDAs will be used as to show potential applications of the proposed system: one focusing on morphological exploration, the other on volumetric pattern distribution, using Orientation Maps as a base construct. Each HL-PCDA entity will contain several SAs, each using SPs and having an area of Influence and a specific Intensity, that in this case will control proportionally all the sub-parameters of the respective design entity. The Influence and Intensity are relative to each SA, and different SAs (agents) can be used in the same design exploration process (SA can have different behavior and learning methods). Please note that the end-goal of the system is to maximize the number of exciting conceptual ideas it produces, with respect to the designer’s neural feedback. A more detailed description of how this is achieved will be provided over the next paragraphs of this chapter. 3.3

Experiment Description

The VR experiment is built inside Unity GE, using the ML-Agents package with a Python bridge to TensorFlow for training and a Houdini Engine (HE) bridge to SideFX’s Houdini. HE ensures live, bi-directional information exchange between the GE front-end and the procedural, Houdini-based, back-end. An HTC Vive setup with the Neurable EEG strap and aGlass E-T solution is being used. Using only E-T and the BCI interactions, the designer can operate on two types of HL-PCDEs: a morphological one and a volumetric pattern distribution one via a set of point SAs, although a similar concept could be used for curve or surface SAs. These affectors can be created and

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positioned using an E-T controlled UI, by fixating a specific number of milliseconds on the UI elements or to be able to select and move the SAs. For each iteration, the Action Vector (AV) that contains the SP, Influence and Intensity will be altered based on feedback received from the model. Since the SPs are discrete but contain the same parameters between presets, the system will interpolate to obtain a continuous domain, i.e. a value of 2.7f for the SP will correspond to a linear interpolation between SP2 and SP3 with a 0.7f weight. Based on the type of RL (RL or IRL), the Reward Function (RF) or the Reward Estimator (RE) will provide the reward and punishment values for each type of training [15]. To create the Expert Behavior for IRL, the designer will use E-T to control all the AVs parameters (SP, Influence, Intensity) that will create BCI measured Arousal (a) values considered to correspond to an “exciting” design. While the Arousal value does not directly match an exciting design, for the purpose of this experiment we consider that an increase in Arousal up to a normalized value of 0.2f is considered to correspond to an exciting or intriguing design. This is the premise to consider for the RF’s or RE’s output values. The Influence component of the AV is here expressed as the Complex Falloff Radius around a center point and it’s related to the Falloff Curve defined in the SP. The Intensity component of the AV corresponds to a normalized value 0f..1f that controls the normalized intensities of all the HL-PCDE’s parameters that fall under the SA’s influence.

Fig. 2. Overview architecture of the prototype (left) and the actor-critic training loop, with the critic using either reinforced learning or imitation reinforced learning (right) focusing on maximizing reward for high arousal designs (max a) that would correspond to exciting conceptual design proposals in a simplified architectural context

3.4

Technical Overview—The Prototype Setting

The prototype illustrated in Fig. 3 uses a 6-channels Neurable EEG device with six dryelectrodes sensors, 300 Hz sampling rate, 8-bit digital trigger input installed on an HTC Vive Gen. 1 HMD with aGlass DKII E-T and the HTC VR Wireless Adapter. Two standard Gen. 1 Lighthouse VR area tracking sensors were used (not shown in Fig. 3). The dual monitors display the VR mirror and the Houdini environment. Due to Neurable’s denoising features, both sitting and standing experiences produced similar

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arousal levels. The Desktop computer used for this experiment has a i7-7820X CPU, 64 GB DDR4 RAM, GTX1080Ti 11 GB GPU, running Windows 10 Pro, Unity 2018.3, ML-Agents v0.7, Python v3.6, CUDA v9.0, cuDNN v7.0.5, TensorFlow GPU v1.7.1, Houdini & Houdini Engine Indie 17.5, Steam VR 1.3.19, Neurable SDK v2.0.1, aGlass Runtime 3.1.0.2.

Fig. 3. The prototype setup configuration, using HTC Vive with the vive wireless adapter, neurable DK1 EEG headset, aGlass eye-tracking solution and powered by unity game engine and Unity’s ML-agents AI package. Top-left: sitting configuration, top-right: detail of the HMD solution, bottom-left: standing configuration, bottom-right: real prototyping environment.

Fig. 4. The actor-critic model, showing the actors’ state-action input-output layers with two hidden neuron layers (left) and the state-value input-output layers with two hidden layers for the critic (right)

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The ML model used in this research is based on Unity’s ML-Agents [15] built on a PPO [14] model, with an Actor-Critic Neural Network [16] with two hidden layers (256 HUs), see Fig. 4.

4 Results The proposed system is based on E-T & BCI interface only. As shown in Fig. 5, a morphologic and volumetric pattern distribution HL-PCDEs with SAs and SPs are being used as base. Expert Training for IRL is being done via E-T for controlling the location, influence and intensity of the SAs to generate desired elements while the BCI is monitoring the EEG response (arousal). In Fig. 6, the RL and IRL paths are compared. Figure 7 showcases some of the best designs results obtained using the IRL

Fig. 5. The Morphologic HL-PCDE with its associated SAs, Influence and Intensity (top), detail of the volumetric pattern orientation HL-PCDE with different SPs, shown as orientational arrows (bottom-left) and a combination of the two HL-PCDEs showing one E-T highlighted SA in the VR Environment (bottom-right).

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Fig. 6. VR Environment Snapshots of the neurofeedback driven conceptual design process evolution stages for the two HL-PCDEs (top row) using RL (middle row) and IRL (bottom row).

Fig. 7. VR snapshots of results of the proposed conceptual design method developed based on IRL method, corresponding to similar top arousal values a (top row shows max arousal results)

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Fig. 8. VR snapshots of evolving results of the proposed conceptual design method developed based on RL method, corresponding to increasing arousal values a (bottom-right shows max arousal result) using the proposed neurofeedback system

Fig. 9. VR snapshots of the volumetric pattern distribution HL-PCDE applied on top of the morphological HL-PCDE (SAs are not shown)

path, while Fig. 8 illustrates design convergence for RL. Figure 9 shows a resulting VR high-level entity ready to be populated with various 3D patterns from a volumetric pattern HL-PCDE using the AI driven neurofeedback process.

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5 Discussion A first prototype of an AI system allowing conceptual design in VR based solely on BCI and E-T, using HL-PCDEs at its core is being proposed. VR is used due to its highly immersive aspect, providing an ideal spatial awareness environment that allows the designer to operate at various scales and focus on the task at hand, without the interferences of the outside environment. Built on a Unity GE platform and using Unity’s ML-Agents AI library with a Houdini procedural back-end, the prototype illustrates the feasibility of using today’s VR, E-T and BCI technologies in an integrated system and powered by RL and IRL techniques. Examples of applying BCI only interactions on morphological and volumetric pattern distribution HL-PCDEs featuring multiple AI-driven SAs and SPs are being produced, and a comparison of the two AI techniques used is being presented. The proposed system manages to converge in both scenarios (RL and IRL) after more than 500 K training cycles, IRL demonstrating more rapid convergence, but with less exciting results, since it uses the Expert Behaviour as a reward reference, while RL takes longer to converge, but produces more exciting (unexpected) results. 5.1

Limitations and Challenges

While the Neurable EEG system provides an integrated VR solution for the HTC Vive headset, used in conjunction with the aGlass E-T hardware, the limited number of electrodes as well as their scalp distribution, while relevant for the arousal scale provides only limited-precision readings via its six electrodes, and does not allow properly measuring the valence scale for more complex emotional responses. For this purpose, a solution with more dry-electrodes that would be scattered over the entire scalp region would be needed, while also providing means to use a VR headset in the process. Even so, accurate emotional feedback (arousal & valence) would be difficult to obtain for the desired design task, as there is no single emotion that can uniquely describe what a “good” design feels like, or the various degrees of satisfaction or dissatisfaction that could be expressed. The precision of the aGlass VR E-T system, while considered good enough for the purpose of this experiment, is lacking additional precision and information, such as pupil dilation, that could help bring relevance and complement the arousal measured by the Neurable EEG system. For this reason, the Tobii VR E-T solution would provide a much better quality of tracking and the additional missing pupil data. Even though the proposed system proves that it is a valid first step forward into the direction of new conceptual design instruments that no longer require standard input methods and where AI can become a partner in the conceptual design process, it also reveals some of the limitations pertaining to its applicability range as well as other potential restrictions. First off, the system requires the usage of HL-PCDEs as its basis of operations, and thus falls under the inherent limitations of the HL-PCDEs themselves, such as not being able to address the entire design solution space, or in this case being limited to point Smart Affectors (while in theory complex curves or surfaces could be implemented in a similar way). The SPs range could also be a limiting factor if there are not enough elements or not sufficient variation is exhibited by the potential

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SPs in such a way that the AI system could propose interesting, variate and innovative design solutions. A large database of HL-PCDEs with a large set of SPs and SAs would be required in order to scale up the presented prototype. One last important aspect relates to the current limitation of the prototype to a single designer’s BCI interactions, where a thorough assessment of multiple users and the associated difficulties in finding the arousal baseline as well as obtaining relative and relevant results by comparison with a control group should be performed. 5.2

Future Explorations

Empathic computing, powered by AI, is a field that is becoming more and more relevant to the design arena as it allows new, more in-depth insights into the way design translates into human emotions and how this aspect could be directly integrated into the design process from its early stages. Refining the way, the emotional response of systems such as the one presented in this paper to the extent of allowing profound comprehension of the empathic implications of various aspects of perception should be investigated together with the development of new, more reliable and more integrated technical solutions for VR and non-VR architectural and urban environments. Behavioural modelling using Massive Multi-Agent System (MMAS) could be developed as an extension in future investigations. Using BCI and ML to dynamically control the behaviour of MMASs could yield unexpected results, as the emergent and self-organizational characteristics of such systems that could learn, adapt and innovate in conjunction with the designer/architect could be directly explored and tested. Investigating the potential of cooperative design strategies where multiple designers could contribute to the RL or IRL of such systems should be investigated as to reveal the possible advantages for the ideation process, especially when integrating more complex environmental factors, going beyond the morphological design space into more physically and sociologically intricate environments. Acknowledgements. The author will like to thank Adam Molnar and Brian Selzer from Neurable Inc. for supplying the Neurable EEG Dev Kit that enabled this research. Furthermore, the author expresses his gratitude for the feedback provided by Prof. Neil Leach, as the PhD supervisor for the “Digital Futures” Ph.D. Program, CAUP, Tongji University, Shanghai (CN), where this academic investigation took place.

References 1. Huang, X., White, M., Burry, M.: Design globally, immerse locally: a synthetic design approach by integrating agent-based modelling with virtual reality. In: CAADRIA 2018, Beijing, pp. 473–482 2. Barsan-Pipu, C.: Neomorph, V.R.: A multi-user virtual reality conceptual design platform for architecture and urbanism using procedural game technologies. In: TMCE 2018, Las Palmas de Gran Canaria, pp. 237–250 3. Kiefer, P., Giannopoulos, L., Raubal, M., Duchowski, A.: Eye tracking for spatial. Spat. Cogn. Comput. 17, 1–19 (2017)

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4. Goldberg, J., Kotval, X.: Computer interface evaluation using eye movements: methods and constructs. Int. J. Ind. Ergon. 24, 631–645 (1999) 5. Jacob, R.J., Karn, K.S.: Eye tracking in human-computer interaction and usability research: ready to deliver the promises. In: Mind 2003 2(3) 6. Zhang, L.M., Jeng, T.S., Zhang, R.X.: Integration of virtual reality, 3-D Eye-tracking, and protocol analysis for re-designing street space. In: CAADRIA(23), Beijing, vol. 1, pp. 431– 440 (2018) 7. Chen, H., Dey, A., Billinghurst, M., Lindeman, R.W.: Exploring pupil dilation in emotional virtual reality environments. In: ICAT-EGVE, Adelaide, pp. 1–8 (2017) 8. Sherstyuk, A., Vincent, D., Treskunov, A.: Toward natural selection in virtual reality. IEEE Comput. Graph. Appl. II(30), pp. 93–96 (2010) 9. Emotiv. EMOTIV (2019). https://www.emotiv.com/ 10. Neurable Inc. Neurable (2019). http://www.neurable.com/ 11. Jatupaiboon, N., Pan-ngum, S., Israsena, P.: Real-time EEG-based happiness detection system. Sci. World J. (2013) 12. Lin, Y.P., Wang, C.H., Wu, T.L., Jeng, S.K., Chen, J.H.: EEG-based emotion recognition in music listening: a comparison of schemes for multiclass support vector machine, pp. 489– 492. Speech Signal Process., Acoustics (2009) 13. Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction Cambridge. The MIT Press, Cambridge (2016) 14. Schulman, J., Dhariwal, F., Radford, P., Klimov, O.: Proximal policy optimization (2017). arXiv:1707.06347 15. Juliani, A., Berges, V.P., Vckay, E., Gao, Y., Henry, H., Mattar, M., et al. Unity: A General Platform for Intelligent Agents (2018). arXiv:1809.02627 16. Konda, V.R., Tsitsiklis, J.N.: Actor-critic algorithms. Adv. Neural Inf. pp. 1008–1014 (2000)

Reference Building Energy Modeling: A Case Study for Green Office Buildings in Shanghai Weipeng Guo, Zhi Zhuang(&), Jiawei Yao, and Philip F. Yuan College of Architecture and Urban Planning of Tongji University, Siping Rd. 1239, 20092 Shanghai, China [email protected] Abstract. Buildings energy consumption accounts for about 30% of China’s primary energy. In order to achieve sustainable development in the future, it is essential to reduce building energy consumption by improving energy efficiency and utilizing new technologies. Reference building energy models can serve as starting points for energy efficiency research, as they represent fairly realistic buildings and typical construction practices. This paper a general methodology for the creation of reference buildings is illustrated. A case study of a reference building for green office building stock in Shanghai is shown. The process concerning the building definition and modeling was carried out by EnergyPlus. The model can be used as a foundation for subsequent research on building energy efficiency assessment, building energy consumption impact factors analysis, urban building energy consumption prediction and so on. Keywords: Reference building model Office building


Building energy simulation


1 Introduction Building consumes about 40% of primary energy in the developed countries like the United States and European countries and about 25%–30% in developing countries like China. Therefore, it is significant to reduce energy use in the buildings section through energy conservation and efficiency improvements, aimed to achieve a sustainable development in the future. Different countries set energy goals for new and existing buildings. For example, in the 2016 multi-year program plan, the U.S. Department of Energy’s Building Technologies Office set a goal to reduce the energy use intensity of buildings by 30% by 2030 and 50% over the long-term and China has also set corresponding development goals: by 2020, 30% of new-built buildings need to meet lowenergy building standards. In addition, for new-built buildings, 30% of energy use need to be covered by renewable energy and 30% of existing buildings need to be retrofitted with the target on energy-saving. However, in the field of energy-saving research, the research object is in most cases the construction that cannot be studied experimentally in the laboratory and from a physical point of view, building is a system that can be influenced by a large number of parameters. In this case, building performance simulation (BPS), which is also called building simulation, building energy modeling, or energy simulation, has played a growing role. BPS uses computational mathematical © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 136–144, 2020. https://doi.org/10.1007/978-981-13-8153-9_12

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models to represent the physical features, the operation, the control strategies and the energy system [1]. Energy demand, indoor environmental quality (including thermal and visual comfort, indoor air quality and moisture phenomena), HVAC and renewable system performance, urban level modeling, building automation, and operational optimization are important aspects of BPS [2–4]. A large number of researches [5] show that computer simulation prediction is a very effective method of building energy consumption and load forecasting. In addition, the calibration of the model is very important in the simulation of building energy consumption. Westphal and Lamberts [6] corrected EnergyPlus model to predict the annual energy consumption of the building by defining the parameters that have the greatest impact on the end of the electricity. The prediction result is only 1% lower than the measured one. Since the calibration of the model is very cumbersome and time consuming, it is quite complicated to establish and apply an accurate physical model simulation method. Especially when the data of some parameters are not available, the inaccuracy of the input may lead to inaccurate result. Reference building energy models can serve as starting points for energy efficiency research, as they represent fairly realistic buildings and typical construction practices. Therefore, using a reference model in the simulation has the advantage of not requiring accurate input. It can be used in follow-up researches, such as assessment of building energy efficiency measures at the early stages of early design, analysis of key factors affecting building energy consumption, calculation of urban building energy consumption and so on. Therefore, this paper presents the establishment of the reference office building physical energy model in Shanghai by investigating the basic parameters of the building block in Shanghai.

2 Methodology The data collected for creating reference buildings can be gathered into four main areas of investigation as listed below: (1) form, (2) envelope, (3) system and (4) operation. Data from each one of these four areas form a sub-set of the features of a building. There are too many office buildings in Shanghai and it is impossible to survey all of them. Therefore, we focus on new-built office buildings which usually apply the stateof-art technologies in the buildings. In this paper, we survey several new-built Green Building Labeled (GBL) office buildings in Shanghai in order to obtain the basic parameters and information for containment structures, air conditioning systems and energy-saving technologies. In the end, a reference office model for Shanghai was set up based on this information and its validation is also discussed. During the survey, it is found that there is one office building in some of the survey projects but some contain more than one office buildings, with similar architectural form. Therefore, the survey data needs to be preprocessed: for projects with only one office building, the survey data is completely retained; for projects with multiple office buildings, the survey data of different forms of office buildings are retained, and other identical forms are excluded. After screening according to the above preprocess method, 32 office buildings of different forms all over Shanghai were obtained. Table 1 shows the summarized parameters considered. The building model input parameters are based on the survey results, which are discussed in the next section.

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No. 1

Information Form

2

Envelop

3

System

4

Operation

Parameters included Total floor area, number of floors, floor height, building orientation, aspect ratio Construction and thermal properties of exterior walls, roof/floor and windows, window to wall ratio HVAC system type, component efficiency, control setting, lighting fixtures Schedules, Plug load, lighting and occupancy densities

By using the software Sketchup and OpenStudio, the office reference building modeling was carried out by EnergyPlus. The Chinese Standard Weather Data (CSWD) of Shanghai was used for weather data [7, 8].

3 Survey Results and Discussion 3.1

Building Form

The minimum floor area of the office buildings is 1629 m2, the maximum aboveground area is 48891 m2, and the average floor area is 17193 m2. Among them, 22 buildings have an above-ground area of 20,000 m2 or less (Fig. 1). On the one hand, the total area of the building can represent the size of the building. On the other hand, the total area of the building does not show feature of the standard floor of the building. Therefore, it is necessary to count the single-floor area of the buildings surveyed. After the processing, the single-floor area of the samples ranges from 325.8 to 4770.0 m2, with an average of 1180.2 m2. The floor area distribution shown in Fig. 2(a).

Fig. 1. The distribution of building floor number and height

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Fig. 2. The distribution of building floor area and orientation

The orientation of the building affects the building’s sunshine and the gain of the sun heat, which have an influence on the energy use. The surveyed buildings are oriented from southeast to west. The orientations ranging from south by east 22.5° to south by west 22.5° are defined as south. The orientations ranging from south by east 22.5° to southeast are defined as southeast. The orientations ranging from south by west 22.5° to west are defined as west. The rests are defined as southwest oriented. The building orientation dates are shown in Fig. 2(b). Among them, the south-facing buildings accounted for the most, accounting for 50%; the southeast-oriented buildings accounted for 28%; the west- and south-west buildings accounted for less, 9% and 13% respectively. 3.2

Building Envelop

The U-values of the exterior wall for all the surveyed buildings are insulated and shown in Fig. 3(a), resulting in that the U-value ranges from 0.46 to 0.97 W/m2 °C and the average U-value is 0.68 W/m2 °C. 28 buildings have the exterior wall with the U-value

Fig. 3. The distribution of U values of building exterior wall and roof

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ranging from 0.50 to 0.90 W/m2 °C. Similarly, the U-values of the roofs for all the surveyed buildings are insulated and shown in Fig. 3(b), resulting in that the U-value ranges from 0.27 to 0.69 W/m2 °C and the average U-value is 0.50 W/m2 °C. 25 buildings have the roof with the U-value ranging from 0.40 to 0.60 W/m2 °C.

Fig. 4. The distribution of window type and window to wall ratio

The exterior windows of all the surveyed buildings are double glazed. 27 of them combine double glazing with paint or film to improve the thermal performance of the exterior windows. The U-value of the surveyed exterior window ranges from 2.1 to 3.2 W/m2 °C, with an average U-value 2.5 W/m2 °C. 27 buildings have the exterior window with the U-value ranging from 2.1 to 2.7 W/m2 °C. The building window to wall ratio not only affects the overall thermal performance of the building envelope structure, but also affects the efficiency of indoor natural lighting. It is a significant parameter for a building regarding the building energy use. The window-wall ratio of the surveyed buildings is ranging from 0.20 to 0.70, with the average value 0.43. Only one surveyed building has a window-to-wall ratio of less than or equal to 0.20. There is no office building in the survey with a large-scale glass curtain wall (Fig. 4). 3.3

Building Equipment System

As the HVAC cooling type distribution is shown in Fig. 5, the chiller for cooling and boilers for heating are the typical HVAC system type. In addition, the VRF system is also popular and widely applied in the newly built GBL buildings due to its easy operation. 3.4

Operation Setting

By the survey, it is found that all the office buildings met the energy efficiency design of Chinese standard [9]. Therefore, the schedules of occupants, lighting and plug load equipment can be set as Fig. 6.

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Fig. 5. The distribution of HVAC system type

Fig. 6. The schedule of occupant, lighting and electronic equipment

4 Reference Building Modeling 4.1

Modelling

According to the survey results above, the mode value of the number of the floors, the average value of the floor height, the mode value of the orientation and the average of the window-to-wall ratio are selected. The average value of the single-floor area is slightly adjusted. Those parameters are set as the building form parameter in the reference model. The detailed parameters are shown in Table 2. The internal space of the benchmark model is simplified. Considering that in the area, which is closer to the outer window, natural light can be fully utilized, while the area farther from the outer window can only use artificial lighting, the internal space of the model is divided into five areas: four outer areas and one inner area. Figure 7(a) shows the dimensions of its inner and outer zones and Fig. 7(b) shows the physical model of the established benchmark model. Meanwhile the other input parameters are set as Table 3 shown based in the literature [10]. The schedules of occupants, lighting and electronic equipment are set as Fig. 6. According to the monthly average outdoor temperature in Shanghai, the cooling period of the reference model is determined from May to September and the heating

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W. Guo et al. Table 2. The building form parameters for the reference building model Parameters Orientation Floor Floor height (m) Single-floor area (m2) Total floor area (m2) Length to width ratio Window to wall ratio

Value South 9 floors above ground, 2 floors underground 4.3 1152 12672 2:1 0.43

Fig. 7. The physical reference office building model

period is from December to March. The baseline model uses air conditioning system during the working hours of the cooling and heating periods and the indoor temperature setting is shown in Fig. 8.

Table 3. Other input parameters for the reference building model Parameters Lighting density (W/m2) Plug load density (W/m2) Occupant density (m2/P) U-value (W/m2 °C)

Value 11 15 14 exterior wall: 1.0 roof: 0.7 exterior window: 2.8 (SC = 0.45) Fresh air volume (m3/h P) 30 HVAC system Heating source: gas boiler (η = 0.89) Cooling source: chiller (COP = 4.4) Terminals: fan coil + fresh air system

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Fig. 8. Indoor temperature setpoint during the heating and cooling period

4.2

Validation

In order to verify the reliability of the model, the actual energy consumption data of office buildings in the literature is used as the reference. In the literature [11], the annual total energy consumptions of 101 samples range from 37.6 to 234.1 kWh/m2, with an average annual total energy consumption per building area of 114.0 kWh/m2. According to simulation result of the reference model in EnergyPlus, the annual total energy consumption per building area is 93.9 kWh/m2, which is 17.6% different from the result in the literature. It can be considered that the established reference office building model is reasonable.

5 Conclusion In this paper, the basic parameters, enclosure structure and HVAC system of new-built green office building block in Shanghai are investigated and an office reference building energy model is set up. The simulation results of the reference model show that the simulated annual energy consumption per building area is in good agreement with the average energy consumption of actual office buildings in Shanghai. It is considered that the established model is reasonable and can be used in subsequent research. Acknowledgments. The study was supported by the National Key R&D Program of China (Grant no. 2017YFC0704200).

References 1. Hong, T., Langevin, J., Sun, K.: Building simulation: ten challenges. In: Building Simulation, vol. 11, no. 5, pp. 871–898. Tsinghua University Press (2018) 2. Clarke, J.A.: Energy Simulation in Building Design, 2nd edn. Butterworth-Heinemann, Oxford (2001) 3. Hensen, J.L., Lamberts, R.: Building performance simulation for design and operation. Spon Press, Abingdon, Oxon (2011)

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4. Clarke, J.A., Hensen, J.L.M.: Integrated building performance simulation: progress, prospects and requirements. In: Building and Environment. Fifty Year Anniversary for Building and Environment, vol. 91, pp. 294–306 (2015) 5. Al-Homoud, M.S.: Computer-aided building energy analysis techniques. Build. Environ. 36 (4), 421–433 (2001) 6. Westphal, F.S., Lamberts, R.: Building simulation calibration using sensitivity analysis. In: Building simulation. In: Ninth International IBPSA Conference, pp. 1332–1338 (2005) 7. Hongxing, Y., Lin, L., Chen, L., et al.: Selections of typical meteorological year and example weather year and their effects on building energy consumption. Heat. Vent. Air Cond. 01, 130–133 (2005) 8. China Meteorological Bureau, Climate Information Center, Climate Data Office and Tsinghua University, Department of Building Science and Technology. China Standard Weather Data for Analyzing Building Thermal Conditions. China Building Industry Publishing House, Beijing (2005) 9. GB National Standards. Design Standard for Energy Efficiency of Public Buildings. Beijing, China Architecture & Building Press. GB 50189-2015, 89p (2015) 10. Cheng, S., Lei, L.: Research on the construction of integrated energy consumption prediction model for office building in severe cold zone. Arch. J. 2014(S2), 86–88 (2014) 11. Xu, Q., Zhi, Z., Zhu, W., et al.: Analysis on energy consumption statistics data of large-scale public buildings in Shanghai. In: Urban Development Research - The 7th International Conference on Green Building and Building Energy, Urban Development Research Editorial Department, Beijing, pp. 322–326 (2011)

A Visualization Based Analysis to Assist Rebalancing Issues Related to Last Mile Problem for Bike Sharing Programs in China: A Big-Data Case Study on Mobike Ercument Gorgul1(&) and Chaoran Chen2 1

College of Architecture and Urban Planning, Tongji University, 1239 Siping Road, Shanghai 20092, China [email protected] 2 College of Design and Innovation, Tongji University, 281 Fuxin Road, Shanghai 20092, China [email protected]

Abstract. This paper is a study about visual analysis of spatiotemporal patterns of popular free floating bike sharing system (FFBSS) Mobike in Shanghai. Mining of over 32 million data points revealed strong cyclical variations on temporal patterns of usage between weeks; however weekday and weekend patterns differ. By using a geohash index based spatial data, we developed another visualization to encode the location of each shared bike ride. Through that, we found that the spatial distribution of Mobike shows a strong linear pattern, confirming that it is mainly used to solve the “last mile problem”. Emergence of vacant rectangles in the visualization informs the specific locations with intense traffic of checking in and out of individual bikes, providing an efficient tool for management of rebalancing. Keywords: Shared bike Geohash


Visualization
Rebalancing
Last mile problem


1 Introduction Fast urbanization brought many challenges to big cities, as growing population created more demand to infrastructure. Transportation can be seen as one of the areas that experienced the impact of this growth. Higher traffic and increased travel resulted with decreased accessibility [1]. Development of shared bike systems enabled sustainability of the existing transport network by extending the accessibility of it to door-to-door [2]. Currently there are 1950 programs and approximately 14,860,200 self-service public use bicycles and e-bikes available for use in cities around the world [3]. Historically, there have been four generations of public bike sharing systems. Starting with free bikes in the 60’s and coin operated bikes in early and mid-90’s [2]. Past decades’ advancements in technology led to third generation of systems -docked bikes- that can be checked in and out from their designated stations electronically. This enabled first time, collection, storage and analysis of real-time usage data possible [4]. Built upon the technology of third generation systems are the demand-responsive © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 145–153, 2020. https://doi.org/10.1007/978-981-13-8153-9_13

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fourth generation systems that are dockless, traceable via GPS and fully integrated with real-time technology and infrastructure [5]. The ease of use of third and fourth generation systems made shared bicycle programs popular around the world. Since 2009, the annual growth on use of shared bikes as mode of transport is around 37% [1]. Currently, Asia represents the world’s fastest growing bike sharing market alongside with Europe and America. With over 61,000 bikes and 2500 stations, China constitutes the majority of that growth [6]. Much of this expansion is backed by Chinese government’s policies in order to reduce emissions [7]. A large number of cyclists, extensive and sophisticated bicycle transportation infrastructure with separated bike lanes, bikes traffic lights, on and off-road parking [8], as well as a history of bike use habit might have contributed to this growth. A 2005 travel survey conducted in Beijing illustrate that 71.6% of all bicycle trips in the city cover less than five kilometers [9], signaling the importance and demand of “last mile problem”, indicating the starting/ending node of a trip before and after a public transit stop. To serve such demand as much as possible, it is significant for public shared bike operators to detect the usage patterns from temporal and spatial distribution, e.g., when will people choose to use shared bikes and whether or not there are any routine or anomaly caused by any reason (such as special events, weather, etc.) for user behavior. These types of information enable operators effectively rebalance the distribution of shared bike among locations. In this paper, we choose to work with datasets from Mobike, a well-known, 4th generation FFBSS in China as the target of our study. Using web crawlers, we collected over 32 million points of data from Shanghai area, covering dates from March 10th to June 1st, 2017. Mined data contain the ID information of order, user and bike, along with trip starting time, start & ending location and bike type. Given the abundant data, we proposed an analytical framework to detect the usage pattern during a 3-week period from a spatiotemporal perspective. Following is a summary of sections on this paper: 1. Building and preprocessing of a comprehensive dataset through geohash index, 2. Visualization and analysis of temporal data; generation and validation of hypothesis, 3. Analysis of spatiotemporal patterns through data visualization encoded by a geohash index based spatial data mode, 4. Insights from the implementation phase of ouranalytical framework and future plans for improvement.

2 Background Research One of the important problems with FFBSS is that the operational staff has little control over the distribution of bikes [10]. As users are always moving them around, maintaining a specific ratio of bikes through physical movement or offering incentives to users to where to drop on and off becomes critical [5]. This operation of redistributing bikes across the network using a fleet of vehicle(s) is known as bike rebalancing [11]. Find a way to provide easy to understand visual analytics using geohash technique on understanding locations of rebalancing is our aim to place this work, relative to prior research done to-date.

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As a solution for the first/last mile problem in many cities with public mass transit systems, FFBSS can provide means of transportation between existing hubs of these systems and desired destinations [12]. However due to one-way and short time usage, highly dynamic spatiotemporal movements cause imbalances in the distribution of bikes [13]. Rebalancing can alleviate this situation. Rebalancing at night, when user intervention is negligible, is called static rebalancing. If user intervention is considered, the problem is called dynamic rebalancing [11]. Fishman, Washington and Haworth emphasized the rebalancing of shared bikes as a major problem since it could be costly for the operator both from organizing the distribution of bikes as well as well as catering to demand [12]. Rebalancing has gradually attracted the attention of many researchers. Sizable amount of previous studies focused on dealing with this issue [14] from static rebalancing [11, 15, 16], to dynamic rebalancing [13, 17, 18], as well as combined solutions [19] perspective. However all these examples above and more encountered during our literature review treated this as mathematical and computational problem, with minimal use of visualization. Aside from the aforementioned research, we choose to focus on assisting the operator to quickly detect the spatial imbalance of shared bikes through visualization of data. 2.2

Visual Analytics

Data generated by shared bikes every day have a large amount of information. Majority of notable research on looking to balancing of FFBSS data have been statistical or computational analyses such as incentivizing users for rebalancing [20]; a heuristic methodology generating routes and number of deployment to pick up locations [21]; and aforementioned vehicle routing for rebalancing [15]. We do believe that this large amount of data needs a better representation. Applying visual analytics to the raw data can not only inspire new ideas to solve a problem, but also reveal knowledge intuitively to help decision making [22]. Previous research proposed some visualization and analytics tools used in the analysis of bike-sharing system. Borgnat et al. used static visualization to show the incoming and outgoing traffic flow of shared bikes [23]. Oliveira et al. presented an interactive visualization system to explore the dynamics of public bike-sharing systems and identify several patterns in temporal and spatial domains [10]. Oppermann et al. proposed an interactive visualization system to explore and understand collected data from smart city sensors [24]. Our study focus on using visualization as a tool, not only explore the usage but also identify areas that require rebalancing. 2.3

Geohash

As a geocoding system invented by Gustavo Niemeyer in 2008, Geohash encode latitude and longitude information into a short string of letters and digits. Through a grid-based, hierarchical model of the earth, where locations are represented by base 32character map, it transfers two-dimensional spatial data string into one-dimensional

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string [25]. Geohash has been widely used in auxiliating Geographical Information Systems (GIS) and location indexing. Many research related using geohash with bike sharing systems is relatively recent, including travel behavior analysis for FFBSS [26]; use of machine learning (ML) to forecast origin-destination demand [27]; and nonnegative matrix factorization (NFM) method to gain the usage pattern from after decoding the geohash-based location information [28]. In our study, we directly visualize data encoded by geohash and focus on the correlation between visual patterns of transport hubs with flow of shared bikes.

3 Methodology and Results This section will cover the methodical steps of the visual analysis from temporal and spatial perspective. Dataset used in this visualization cover entire Shanghai metropolitan area. 3.1

Time-Based Usage

As first step of visualization, a heat map is generated based on Mobike request data to find what days of the week and what time of the day has more frequent use of bikes (Fig. 1).

Fig. 1. Heatmap for the frequency of Mobike requests during 3 weeks (white blocks represent missing data)

Heat map, revealed a result that can be assumed: High traffic during the morning and evening rush hours (from 7 to 8 a.m. and from 5 to 7 p.m.). It is also worth to mention that variance of bicycle demand during workday is greater than that of during weekend.

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Fig. 2. Similarity comparison

To further compare the change between days and visualize details on similar patterns -as well as anomalies- a line chart is generated by using start time as the row and amount of requests in each minute in one week as the column (Fig. 2). It was possible to get following observations after comparing each piece of the line chart: 1. Curves on weekend are similar to each other and have some unique patterns: All of them have three peaks: 7–8 a.m., 11–12 a.m., 5–7 p.m., respectively. Peak during 5–7 p.m. is higher than peak of 11–12 a.m. and that peak is higher than the one during 7–8 a.m. 2. Curves on weekday have similarities to weekend curves with three peaks around same hours of weekend except for the day of March 22nd. Peak during 7–8 a.m. is higher than peak of 11–12 a.m. and 5–7 p.m. peak of is higher than the one during 7–8 a.m. 3. Curves on weekday are higher than those on weekend, representing higher volume of use. For example, curves between 7 and 8 a.m. during weekdays are almost twice than those on weekend. 3.2

Location-Based Usage

After analyzing temporal patterns, we turn to look into spatial factors. To validate the first/last mile problem as one of the main uses of FFBSS, it is necessary to compare trip distances. Preprocessing the latitude and longitude information through a geohash index based spatial model, we generated a 7-character string that enabled easier assessment of the distance by comparing the similarity of these two geohash strings. As a consequence of the geohash-encoding model, nearby places will often present similar prefixes (Niemeyer et al. 2019). The longer a shared prefix is, the closer the two places are. After sorting encoded data, we draw a new diagram by using geohash data, using starting point as column and destination as row, making each plotted dot representing a trip (Fig. 3).

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Fig. 3. Distance visualization encoded by geohash. A sample area has been enlarged to see emergence of “vacant rectangles” more clearly

Figure 3 reveals the emergence of a diagonal pattern, confirming the main use of Mobike within short distances. More specifically, this is due to alphabetical proximity of geohash values for pickup and drop-off locations. If 5 characters of the 7-character geohash is same, the ride will be plotted close proximity to diagonal line. Data in this diagram is informing us that 95.47% (the blue area in Fig. 3) of bike rides made with using Mobike are less than 3 km distance. One of the most important discoveries of this visualization is the emerging rectangular vacant patterns along the line (Fig. 3). As it can be seen much more in detail in Fig. 4, the left and bottom sides of these rectangular formations made out of intensified plotting of the points of pickup and drop-off respectively, indicating the check-in and -out activity in those areas. In the overall graph, larger the size of these rectangular formations, more frequent Mobike trips made from this specific area.

4 Discussion The purpose of this study was to develop a visualization that can help to provide more accurate understanding the locations of high demand and provide and efficient tool for rebalancing. The basis of our contribution stands on our effort to find a novel way of visualize bike sharing data by preprocessing the spatiotemporal information, so it can be used not only to understand the trend but also to inform operations. Specifically, the findings of our study are as follows: First, the fact that the use of Mobike is more frequent during weekdays means the major demand of Mobike is to facilitate commuting between workspace and residence.

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Fig. 4. A full scale plot of graph. In this scale, each bike trip is represented by a blue dot (indicating pick-up and drop-off locations mapped on 2 axes) can be seen more clearly

Second, during weekend, the highest peak is in the evening while during the weekday the highest peak is in both the morning and afternoon, which might imply people tend to stay at home in the morning during weekends and use shared bike during evenings. Finally, during weekdays, use of Mobike at noon is more likely to be affected by sudden change of external factors and events than that in the morning or evening. This become evident for the data on May 22nd with the disappearance of an expected peak at noontime. A quick research on historic weather and temperature record of the area revealed a rainfall and sudden cooling of temperature around noon time, providing weather conditions as a plausible reason for anomaly, something Wang, Zheng and Xue also indicated in their research previously [29]. Another one was for the sudden shift between weekend and workday flows (i.e. more traffic in weekend and less in weekday). The reason for this was the arrangement made by the Chinese government for the occasion of the highly celebrated dragon boat festival holiday, as a day of the weekend prior to holiday is swapped as a working day in order to consolidate a normally one-day holiday, into a 3-days holiday (i.e. Saturday as a workday and holiday being from Sunday through Tuesday). In parallel, we also must consider some limitations in our study: The restriction of visualization being static and lacking of association between temporal and spatial information. Future plans include adding interaction to our visual analytical framework, such as adjusting the time range of the display and correlating data display among different charts. Incorporating a scene map can also provide more intuitive experience for users to see patterns more clearly.

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5 Conclusion In this paper, we presented a case study to detect usage pattern of one of the largest FFBSS Mobike in Shanghai. Comparing over 32 million points of mined data from a 3week period, we extracted usage patterns from spatiotemporal perspective focusing on visualization of this data. Using geohash to plot pick-up and drop-off locations of individual bikes enabled us to create a visualization-oriented spatial data model that confirms the main usage of shared bikes within range of 3 km. Our methodological contribution lie in the novel way we chosen to visualize the GPS data, that enabled to detect high traffic areas visually, informing about actual coordinates of where rebalancing is needed, as vacant rectangle areas represent domains where shared bike users have same destination or origin point. These results may be helpful or interesting to other researchers who are focused on visualizing shared bike data, enabling the data to be understood easier, as well as providing a strong and efficient tool for bicycle operators to supervise and rebalance the distribution of shared bikes. Conflicts of Interest Statement. Authors declare no potential conflicts of interest in relation with authorship, study and research conducted and/or publication of this article.

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Integration of Wind Simulation and Skin Tectonic in Architecture Design Taking the Henan Science and Technology Museum as an Example Linxue Li(&) and Kangning Ge College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China [email protected]

Abstract. The building skin is a materialized interface between the nature and indoor environment, which prevents people from the harsh external environment and climate. In modern architecture, architects and engineers have turned to mechanically-oriented and environmentally-controlled designs to regulate indoor environments through HVAC systems. The climatically adaptable building skin began to peel off from the building ontology. This paper focus on the integration of wind simulation and skin tectonic in architecture design with digital tools, pointing out the potential of the combination of energy issues and digital methods in contemporary architectural theory and practice. First of all, this paper sorts out three operational mechanisms of environmentally adaptive building skin: energy isolation, energy guidance, and energy integration. Then, the paper illustrates the design route from the wind environment simulation to skin tectonic. “Environmental Response” and “Construction Realization” are the two focuses of this paper. Finally, the project of Atelier L+, Henan Science and Technology Museum in China, will be introduced with the specific operation process from wind environment simulation to skin tectonic in architectural practice. Keywords: Environmental response Tectonic


Ventilation
Architecture skin


1 Research Background Energy is an important substance driving the development of modern society. The energy consumption of architecture is particularly significant among all types of production and living activities, from construction to operation and demolition process. Therefore, the energy-saving architecture design has become the consensus of architects and the society.

© Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 154–166, 2020. https://doi.org/10.1007/978-981-13-8153-9_14

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There are two main lines of researches on architecture energy-saving technologies: one is active technology, such as solar panels, solar photovoltaic power generation, etc. integrated in the later stage of architectural design by equipment; the other is to cut down energy consumption in a passive way, combining natural ventilation and natural daylighting consciously. When digital technologies and tools are applied to architect, energy-saving designs for buildings can be calculated and simulated, but the problem is that most of the energy-saving designs are simply evaluated by various numerical values and indicators and become a kind of “retrospective” check. A possible proper way of energy-saving is to make architecture as a material organization. The order of the elements in the organization controls the flow of energy in the space and balances and maintains the form of the organization. The scientific analysis of the energy operating mechanism in the building can provide support for the organization of the building’s form, function, space, etc. achieving the integration from volume to tectonic. This paper will take one practical project as an example to show the potential of integrating environment parameters simulation and skin tectonic by the use of digital tools.

2 Architecture and Energy Operating Mechanism From the perspective of architecture energy system, all energy activities related to architecture can be classified into three categories: energy isolation, energy guidance, and energy integration. Energy isolation refers to minimize the energy exchange between architecture and environment and regarding the interior of the architecture as a fully regulated energy system. The cave dwellings and snow houses “igloo” are typical practices of energy isolation in traditional architecture. In modern architecture, efficient exterior insulation, improvement of the airtightness of window and shading system are used to realize energy isolation. The key is to improve the thermodynamic performance of the building skin. Energy Guidance in architecture and environment are in three ways: conduction, convection, radiation. The direction of energy flow is determined by the energy potential difference in spaces, and the energy is always transmitted from the high energy potential to the low energy potential. Energy guidance is to make the rational distribution of energy in the building by the law. Natural ventilation is a typical kind of energy guidance. The second law of thermodynamics states that it is impossible to extract heat from a single heat source and completely convert it into useful work without other effects. The law points to the directionality of energy transfer and the quality difference between different energies. For architecture energy systems, electrical energy and solar radiation are high-quality energy, and thermal energy is low-quality energy. Energy integration is to capture and reorganize energy within for more efficient energy use in architecture.

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3 Design Route 3.1

Environment and Climate Analysis

The first step of the design is to collect local climate and weather data and determine the relevant design parameters. By use of software, the meteorological data can be analyzed and visualized so that architect could extract important parameters directly related to building energy, including temperature and humidity, solar resources, wind environment and psychrometric chart. 3.2

Volume Design and Simulation

According to the environmental analysis and the scale and function of the building, architects can get the general layout of the building in the general planning. At the same time, architects create a rough volume and shape of the building in the digital model, as well as the opening of enclosure and the position of atrium. Then, architects attempts to find a more accurate “Environmental Response” shape of the building by using wind simulation software. The external wind environments and the need of natural ventilation intensity are differ in four seasons, so the architect needs to do wind environment simulation in winter and summer respectively. Architects need to choose the environment parameters and optimize the shape to get the final solution. 3.3

Environment-Oriented Skin Design

In the stage of architectural design, “Construction Realization” focuses on the specific form, structure and material tectonic of the building skin to obtain the best ventilation and wind environment. First, architects should fully consider the material, color, wall thermal resistance, specific heat capacity, external doors and windows and shading conditions of the building’s exterior walls, and determine the basic type and form of the skin. The responsiveness of the skin to the environment can be divided into three levels: fixed, transformative and adaptive. After the basic optimization of the skin, the passive building skin components with better energy saving and environmental protection should be preferred to enhance the natural lighting, ventilation, cooling and heating effects. Seasonal climate changes are directly related to the effective functioning of these components. Last, when passive skin components are not sufficient for comfort, architects must resort to active building skin components. Contemporary skin tectonic is increasingly moving toward a modular design. According to its working principle and corresponding climatic elements, the skin module can be divided into daylight module, energy module, ventilation module and thermal module. The design of the skin module is not a collage, but should consider the possible interaction between different modules in an energy integration system. Different skin module meet its specific needs, so that the skin modules form a positive interaction (Table 1).

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Table 1. Optimization and integration process of building skin Steps

Daylight modules Natural Lighting Window Form Window Direction Window Wall Ratio

Ventilation modules

Tectonic Environmental Regulation Strategy

Shading Sunshade Grille, Blinds Light Control Components

Natural Ventilation Controllable Ventilation Components Ventilation Wing Tablets

Mechanical Environmental Regulation Strategy

Artificial Lighting Direct Lighting Indirect Lighting

Morphology and Structure Design

Integration

Natural Ventilation Windows and Vents Air Buffer Layer

Thermal modules Thermal Isolation Orientation and Form Window Wall Ratio

Thermal Insulation Thermal Insulation Materials Thermal Storage Materials Greening System HVAC Systems HVAC System Skin Heating And Cooling Systems

Energy modules Energy Capture Light Energy Capture Thermal Energy Capture Wind Energy Capture Capture Components PV Ground Source Heat Wind Power

Energy Recycling Fresh Air Heat Recycling System Bio-Energy Recycling Manual Regulation: Simple System, Low Technology, Environmental Protection, Flexible Control Intelligent Regulation: Dynamic Interaction, Environmental Response, Real-Time Control Mechanical Ventilation System Distributed Ventilation System

4 Construction Realization: Henan Science and Technology Museum 4.1

Project Overview

The Henan Science and Technology Museum is an important practice of “energy collaborative design” thinking in public buildings by Atelier L+ . The project is located on the bank of Xianghu Lake in Zhengdong New District, Zhengzhou City, Henan Province. The construction land area is 54453 m2, the total floor area is 105000 m2, and the FAR is 1.47. The building has a height of 42 m, with four floors above the ground and one floor underground (Fig. 1).

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Fig. 1. Rendering of Henan science and technology museum

4.2

Environment and Climatic Analysis

Zhengzhou City is in the temperate continental monsoon climate zone. Under the influences of solar radiation, topographical geology, atmospheric circulation and other factors, the climate is characterized by moderate temperature, four distinct seasons, simultaneous rain and heat. The winter is the longest season in a year, the summer is second longest, and the spring is the shortest. Precipitation: The annual precipitation is 640.9 mm. The spring is dry and rainy, the summer is hot and rainy, the autumn is sunny and less rainy, and the winter is cold and less snowy. The annual precipitation is mainly distributed from June to September (Fig. 2).

Fig. 2. Zhengzhou climate Zhengzhou#Climate)

statistics

(Image

Source:

https://en.wikipedia.org/wiki/

Temperature and Humidity: According to the analysis of software, Zhengzhou has higher summer temperature and humidity, especially in the summer afternoon, and the winter temperature and relative humidity are lower than that in summer. Extreme weather often occurs in winter and summer. In one day, the highest relative humidity appears at night. The relative humidity is low throughout the year and it is generally comfortable for living. Compared with other months, August is relatively humid with an average humidity of over 72%. During this period, proper dehumidification should be applied (Fig. 3).

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Fig. 3. Annual relative humidity analysis (Image Source: Atelier L+)

Psychrometric Chart Analysis: The blue part of the chart shows the climate, while the yellow part is where the human body feels comfortable. In summer, the climate is characterized by high temperature and high humidity, while in winter, the temperature is significantly lower. Therefore, the most effective solution in the passive design of the building is: natural ventilation in the summer and passive solar energy utilization in winter with some active designs of heating (Fig. 4).

Fig. 4. Psychrometric chart analysis in summer and winter (Image Source: Atelier L+)

Solar Resources Analysis: The solar resources of Zhengzhou are abundant, and the annual solar radiation time is about 2,400 h. The best sunshine orientation is 2.5° west of south. In this case, the winter sun can be maximized while summer solar radiation should be blocked (Fig. 5). Wind Environment Analysis: According to the wind rose chart, Zhengzhou’s dominant wind direction is northeast, and the secondary dominant wind direction is southeast and southwest. In winter, the dominant wind direction is the northwest, and the secondary dominant wind direction is northeast. Consider the summer southwest wind and the winter northeast wind are in the same line (Fig. 6). The natural ventilation in summer should be designed in the southeast direction. In addition, the southwest direction could be changeable, in summer it opens to get the winds and in winter it closes to prevent the winds outside.

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Fig. 5. Solar radiation analysis (Image Source: Atelier L+)

Fig. 6. Annual wind environment analysis (Image Source: Atelier L+)

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Environmental Response Volume Strategy

To promote ventilation, the volume of the architecture should fits the wind flow to some extent. After preliminary simulation of the fluid mechanics software, we saw that at the height of 1.5 m in the pedestrian zone, the wind flow in the site is smooth without obvious vortex, and the wind speed is maintained at 0.5–2.5 m/s, in line with the human comfort requirements. When taking the factor of the influence of terrain in consideration, the results show that the terrain has a significant impact on the natural ventilation of the buildings in the site. The wind speed in the site is reduced to some extent. However, there is no obvious eddy current or obstruction (Fig. 7).

Fig. 7. Simulation wind environment in summer (Image Source: Atelier L+)

The dominant wind in winter is the northwest wind. After preliminary simulation, we saw that at the height of 1.5 m in the main pedestrian zone, the wind flow in the site is smooth without obvious vortex. The wind speed is maintained at 0.8–2.6 m/s, basically in line with comfort requirements. Compared with summer, the wind speed in winter is slightly faster. Architects can set planting in the high-speed area to reduce wind speed (Fig. 8). After simulation and feedback in the wind environment software, the entire building is streamlined in an “environmental response” shape with no clear boundaries. The building volume has a trigeminal shape, and each bifurcation is twisted by 90° in

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Fig. 8. Simulation wind environment in winter (Image Source: Atelier L+)

the cross-section, so that the roof and the wall are on the same curved surface. This “environmental response” form differs from the facade of conventional buildings. The building stretches over the lake and presents a three-dimensional progressive trend, forming a patchwork skyline (Fig. 9).

Fig. 9. Architectural form strategy in sketch and digital model (Image Source: Atelier L+)

4.4

Double-Layer Curtain Wall System

The exterior wall of Henan Science and Technology Museum is a double-layer curtain wall system. The outer layer is an open aluminium cladding with inverted sunshade components, and the inner layer is glass curtain wall.

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The glass curtain wall uses a broken bridge insulation aluminium as the frame material to prevent thermal bridge. The glass is made of LOW-E hollow tempered laminated ultra-white glass, which blocks most of the solar radiation while transmitting visible light. At the junctions of glass and frames, the backing insulation rock wool belts enhance the airtightness of the outer wall and effectively prevents cold air from infiltrating. The glass curtain wall has a heat transfer coefficient of 1.9 and a shading coefficient of 0.47 (Fig. 10).

Fig. 10. Analysis of skin structure (Image Source: Atelier L+)

The building is wrapped by a continuous aluminium cladding skin, forming an interface of energy. The skin is parameterized to control the opening rate of the curtain wall through a set of modular systems according to the different requirements of the internal function for daylighting. The non-transparent part adopts a fish scale-like aluminum panel, and the transparent part is inverted by an angle of the aluminium panel (Figs 11 and 12).

Fig. 11. Analysis of skin tectonic (Image Source: Atelier L+)

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Fig. 12. Rendering of skin tectonic (Image Source: Atelier L+)

4.5

Environmental Performance Based Skin Tectonic

Through software simulation and optimization, the panel sizes are modularized, and the overall architectural curved surface is transformed into a composition of flat panel components, and the curved panels are minimized to control the construction cost. The curtain wall frames are attached on the main structure. The opening rate of the building skin can change automatically according to different light environments and achieve effective control of ventilation (Fig. 13).

Fig. 13. Skin tectonic simulation and optimization (Image Source: Atelier L+)

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Computation and simulation are also involved at skin tectonic level. At the beginning, the structure of the curtain consists of horizontal and vertical frames, forming a square orthogonal grid. The vertical frame of the main steel structure are arranged according to a modulus of 3 m, corresponding to two vertical rows of aluminum panels. After calculating the strength and stiffness of the aluminum panel, the curtain wall support structure was optimized to a more reasonable triangular unit. The anodized aluminum panel of the epidermis is equipped with a nano-tech dustproof self-cleaning coating to cope with the dusty environment in the north China. The use of the self-cleaning coating can be regarded as “environment response” of material selection (Fig. 14).

Fig. 14. Elevation and section of skin (Image Source: Atelier L+)

4.6

Integrated Mechanical Ventilation

Built with LEED Platinum standards and national three-star green building standards, the building integrates natural ventilation and mechanical ventilation. Take the ventilation of the atrium as an example: the air conditioning system adopts layered air supply to ensure uniform distribution of cold heat; the roof is opened in spring and autumn for natural ventilation by chimney effect; the sunlight are effectively controlled by sunshade system to effectively regulate solar radiation. The air outlets are set under

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the seats, and the air ducts need to pass through the truss under the floor to reach the air outlets. While satisfying the air supply standard, the aesthetics and comfort of the atrium space are comprehensively considered.

5 Summary According to the operating mechanism of the building energy system, using thermodynamic calculation and simulation tools, applying energy and thermodynamics theory to contemporary architectural practice, to realize the transformation of the relationship between “material, energy, form, performance”, is an important method of thermodynamic architecture design. This paper focuses on the natural ventilation, taking the Henan Science and Technology Museum project as an example, and explains how thermodynamic theory and digital tools assist the design from climate parameter analysis, building volume to skin tectonic. The materialization of energy with the use of digital tools and methods will become an important opportunity for the development of architecture.

References 1. Braham, W., Willis, D.: Architecture and Energy: Performance and Style. Routedge, London & New York (2013) 2. McHarg, I.: Design with Nature. The Natural History Press, USA (1969) 3. Fathy, H.: Natural Energy and Vernacular Architecture, Principles and Examples with Reference to Hot AridClimates. The University of Chicago Press, IL USA (1986) 4. Moe, K.: Thermally Active Surfaces. Princeton Architectural Press, New York (2010) 5. Menges, A., Ahlquist, S.: Computational Design Thinking. Wiley, London (2011) 6. Braham, W.: Architecture and System Ecology: Thermodynamic Principles of Environmental Building Design. London (2015) 7. Roaf, S.: Adapting Building and Cities for Climate Change. Architectural Press, Burlington (2005) 8. Abalos, I., Ibnez, D.: Thermodynamics Applied to Highrise and Mixed Use Prototypes. Harvard Graduate School of Design (2012) 9. Moe, K.: Convergence: An Architecture Agenda for Energy. Routledge, London & New York (2013) 10. Moe, K.: Insulated Modernism Isolated and Non-isolated Thermodynamics in Architecture. Birkhauser, Berlin (2014)

Computational Intelligence

Form Finding and Evaluating Through Machine Learning: The Prediction of Personal Design Preference in Polyhedral Structures Hao Zheng(B) School of Design, University of Pennsylvania, Philadelphia, PA, USA [email protected]

Abstract. 3D Graphic Statics (3DGS) is a geometry-based structural design and analysis method, helping designers to generate 3D polyhedral forms by manipulating force diagrams with given boundary conditions. By subdividing 3D force diagrams with different rules, a variety of forms can be generated, resulting in more members with shorter lengths and richer overall complexity in forms. However, it is hard to evaluate the preference toward different forms from the aspect of aesthetics, especially for a specific architect with his own scene of beauty and taste of forms. Therefore, this article proposes a method to quantify the design preference of forms using machine learning and find the form with the highest score based on the result of the preference test from the architect. A dataset of forms was firstly generated, then the architect was asked to keep picking a favorite form from a set of forms several times in order to record the preference. After being trained with the test result, the neural network can evaluate a new inputted form with a score from 0 to 1, indicating the predicted preference of the architect, showing the possibility of using machine learning to quantitatively evaluate personal design taste.

Keywords: Machine learning Generative design

1 1.1

· Form finding · 3DGS ·

Introduction 3D Graphic Statics

Graphic Statics (2D/3D) is a geometry-based structural design and analysis method. The history of graphic statics can be tracked back to the Hellenistic Age, when Archimedes used algebraic formulas and illustrations to explain in his book On the Equilibrium of Planes that, the weight of an object is inversely proportional to the distance under equilibrium conditions in the law of levers. In 1864, after systematically combing and expanding the knowledge,Karl Culmann c Springer Nature Singapore Pte Ltd. 2020  P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 169–178, 2020. https://doi.org/10.1007/978-981-13-8153-9_15

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named this subject as “Graphische Statik” (Graphic Statics) in his book Die Graphische Statik [4], which was widely accepted by the academic community. However, 2D Graphic Statics has its own limitations. As [1] states, it has been developed as a 2D method. Thus, only 2D abstractions of 3D structures can be designed. With the development of computing power, 3D Graphic Statics attracted the attention of researchers. Under the support of computers, architects developed digital algorithms to generate 3D forms from 3D force diagrams, such as [2,3]. The computational solution of 3D Graphic Statics helps designers to generate 3D polyhedral forms by manipulating force diagrams with given boundary conditions, which is easier and more efficient than the direct modelling of forms. In the form-finding of 3D Graphic Statics, the transformation rules from force diagrams to form diagrams work similarly as the situation in 2D. Figure 1 shows the comparison of 2D and 3D Graphic Statics, where figure b) and d) are the force diagrams and figure a) and c) are the form diagrams. Each applied load Fi in the force diagram represents a corresponding load force Fi in the form diagram, both of which are perpendicular to each other. Each exterior supporting force Fei in the force diagram results in a structural member ei in the form diagram, which shows the corresponding form of a force diagram.

Fig. 1. 2D versus 3D funicular solutions and their corresponding force diagrams [2].

By generating or adjusting the polyhedral force geometries, different trusslike forms can be provided using 3D Graphic Statics. The advantage of this form finding algorithm is that the generated structures are always equilibrium under given boundary conditions. As long as the force diagram is a set of closed polyhedrons, the corresponding form can stay balanced under the action of applied forces. So when designing a form with given applied loads, architects can divide the force polyhedrons with additional interior faces to achieve complexity while keeping the form equilibrium. 1.2

Subdivision of Force Diagrams

To set up the boundary condition, a tetrahedron is selected as the original force diagram, indicating the four applied forces. In the Cartesian coordinate system, the bottom three vertexes of the tetrahedron are always on the XY plane, so

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they can be expressed as (x1 , y1 ) (x2 , y2 ) and (x3 , y3 ) without the value in Z axis, while the top vertex contains three numbers (x4 , y4 , z4 ). Based on the random coordinates of the four vertexes, different boundary conditions can be generated, further extending the methods to explore complex forms. The subdivision will happen inside the tetrahedron, keeping the directions and magnitudes of the applied forces constant. To subdivide a polyhedral force diagram, [5] proposes 8 possible algorithms, 6 of which are programmable and practical. Figure 2 shows subdivision 1, 2, and 3, which do not subdivide the original exterior faces. Different from subdivision 1, 2, and 3, subdivision 6, 7, and 8 (Fig. 3) will subdivide the original exterior faces to achieve further complexity. But since the total area and direction of each exterior face still keeps the same, the overall boundary condition does not change after subdivision.

Fig. 2. Subdivision rule 1, 2, 3 and the corresponding forms.

Fig. 3. Subdivision rule 6, 7, 8 and the corresponding forms.

Among the 6 subdivision rules, subdivision 7 is the most complicated one, resulting in 24 new cells, while subdivision 1 is the simplest one, only constructing 4 new cells. Different boundary conditions will cause similar but different force and form diagrams when applying the same subdivision rule, while different subdivision rules will result in totally different force and form diagrams. Since each subdivision rule takes one cell as input and returns several new cells as output, its possible to further subdivide the sub-cells iteratively. Figure 4 shows the result grid of the iterative subdivision, in which two subdivision rules work in turn to subdivide the force diagrams. The number means the rules that apply to the subdivision. For example, 2 indicates that only rule 2 is applied one time, while 36 means that rule 3 is applied to the original force tetrahedron and then rule 6 is applied to the sub-cells generated by rule 3. So 36 iterative subdivision rules in total are created.

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Fig. 4. 6 basic subdivision rules and 36 iterative subdivision rules.

2 2.1

Methodology Preference Test

Among a variety of generated forms, in addition to the structural performance, architects also take visual effect and inexplicit aesthetics into consideration, which is hard to express as a formula. But with the help of machine learning, programs can learn any relationships between two sets of data, including the relationship between the forms and the scores, which shows the personal preference from architects. So in order to train a computer to grade a form, a preference test was designed and given to voluntary testers, to collect the training dataset for machine learning neural network. First, a dataset of 400 pairs of force and form diagrams were generated, based on random boundary tetrahedrons and iterative subdivision rules. However, its very hard and time-consuming to ask a tester to grade them all, since the scoring process will be influenced by a variety of aspects if the testing time lasts for a long time, such as the mood of the tester and the undulation of the scoring standard. So rather than asking the tester for 400 scores, the testing system will show 200 batches of forms, and each batch contains 6 forms listing from left to right (Fig. 5). For each batch of the test, the tester will be asked to pick the favorite form from the 6 forms, and a recorder will add a score of 0.33 to the form. Since each form will be equally shown 3 times (200 * 6/400), after the whole test, each form will have a score of 0, 0.33, 0.66, or 1, showing the preference from the tester. In this way, it will be much easier for the tester to grade all 400 forms only by picking the comparative favorite form from 6 forms. The whole test takes around 10 min for a well-educated architect, average 3 s for one batch. In order to prove the feasibility of machine learning in predicting the scores in the next step, three tests will be given to the same tester. In the first test, the tester is asked to always pick the simplest form from his perspective, while in the second test, the tester is asked to do the opposite, to always pick the most

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Fig. 5. Testing batch and accumulated score system.

complex form. The reason for taking these two comparative tests is to simplify the personal preference into a degree that is easier to evaluate by common sense. If the machine learning algorithm successfully gives a higher score to the simple forms in the first model and a higher score to the complex forms in the second model, the feasibility then is proved, so that the third test is convincing, in which the tester is asked to pick forms based on his own preference. 2.2

Machine Learning

After the collecting of data from the three tests, similar to the work by [8], vector-based artificial neural network, a machine learning algorithm was used as a framework to learn the mapping from forms to scores, figuring out the rules of grading a form based on the preference test. Other neural networks such as pixel-based CNN used by [6] and voxel-based 3D CNN used by [7] are not suitable in learning the polyhedral forms, because only the 3D presentation of the line-like modelings can best describe the polyhedral forms, rather than the 2D presentation of entity-like modelings. To apply the neural network in the data learning, the first step is to transform the data according to a well-structured format, so that it can be understood digitally by the computer. In this case, to build a polyhedral form based on 3DGS, the necessary data includes the original boundary tetrahedron and the iterative subdivision rule. As Fig. 6 shows, a tetrahedron with a horizontal bottom face can be expressed as (x1 , y1 ) (x2 , y2 ) (x3 , y3 ) and (x4 , y4 , z4 ), which is a set of 9 real numbers. And the iterative subdivision rule can be expressed as a set of 12 Boolean numbers of 0 or 1, in which the first 6 numbers represent the first subdivision rule and the last 6 numbers represent the second subdivision rule. For example, (0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0) means subdivision 7 (actually the 4th rule) is applied firstly and then followed with subdivision 2. So a set of 21 numbers in total is enough to identify a form from others, and also fits the requirements of the input data in a neural network. The output data is much simpler, which only contains one real number showing the score of a form. Next, an artificial neural network with 2 hidden layers was built (Fig. 7), which contains 21 input neurons, 1 output neuron, and 2 layers of 50 hidden neurons. The activation function, which acts as a transformation rule to calculate the value in a current neuron from the previous neurons, is a sigmoid function. Since all data is real numbers from 0 to 1, the sigmoid function can achieve a

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Fig. 6. Data format of a form and its score. Left: original force diagram. Middle: generated subdivided form. Right: input and output data structure.

high prediction accuracy while keeping the slope of learning rate proper in each learning period. The formula is expressed as following, where yˆ is the value in the current neuron, x is the value in the previous neuron(s), w and b are the parameters in the network, which represent the learning ability of a network and will be figured out after the training. yˆ = Sigmoid(w ∗ x + b)

(1)

Fig. 7. Neural network structure.

To evaluate the accuracy of the predicted score to the ground truth score and activate the backpropagation to update the network parameters, a mean squared error (MSE) function is set as the loss function as following, calculating the difference between the predicted value yˆ and the true value y. n

LOSS(y, yˆ) =

1 (yi − yˆi )2 n i=1

(2)

Lastly, three separated models using the three preference datasets were trained. After 18000 epochs of training, the loss value decreased to an acceptable range near 0.00005 for one training item, which means the average difference

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between the predicted score and the ground truth score is inside the ideal range. Thus, mathematically speaking, now the three trained neural network models all have the ability to predict the score for a given polyhedral form, but they will provide different scores since they were trained by different preference test results.

3 3.1

Results Comparative Models Evaluation

Based on the trained models, for a given boundary tetrahedron, scores of all subdivision rules can be provided by the neural network, that means, the best form can be found through the searching of the 36 subdivided forms, which predicts the design preference of the tester. Before searching and evaluating by the preference model, two comparative models are analyzed to prove the feasibility of this machine learning form finding method. To test the scoring system, a randomly generated tetrahedron, as well as 36 subdivision rules, are inputted. Figure 8 shows the selected scoring result of the two comparative models. It can be obviously seen that, in the first simplepicking comparative model, the forms with higher scores are often simpler than others, while the situation in the second complex-picking comparative model is reversed, where the complex forms are often granted with higher scores. That means both models work correctly to predict the scores. So concluded from the testing and observation, it has been proved that the trained neural network has the ability to grade a polyhedral form based on the design preference from the architect who trained it.

Fig. 8. Top: evaluated scores of the simple-picking comparative model. Bottom: evaluated scores of the complex-picking comparative model.

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Preference Model Evaluation

With the conclusion above, the preference model was then used to evaluate the generated forms. Figure 9 shows the selected forms and scores of the testing boundary tetrahedron. There is no obvious tendency of the complexity of the forms since the training dataset was produced from the inexplicit personal preference of the tester. That means, in the preference model, its the boundary condition as well as the subdivision rules together that decides the score of the form. This phenomenon further proves that the complexity is not, or at least not the only factor to influence the testers preference.

Fig. 9. Evaluated scores of the preference model for the testing boundary tetrahedron.

But unlike the previous comparative models, its impossible to prove the feasibility of the preference model by a common sense of standards, unless the tester himself evaluates the forms again and compares his scores with the predicted scores from the neural network. So based on this assumption, a test on re-evaluating the forms was taken by the tester again. First, since its still hard to ask a tester to grade so many forms by different scores from 0 to 1 while keeping his standards constant during the test, four levels of ABCD were used to describe the grades of the forms, in which A means the tester feels perfect about the form, B means the tester likes the form, C means the tester feels just fine about the forms, and D means the tester does not like the form. In the same way, the predicted scores from the neural network were also translated into this grading system, in which a score higher than 0.66 will be graded as A, a score higher than 0.33 but lower than 0.66 will be graded as B, a score higher than 0.01 but lower than 0.33 will be graded as C, and the left will be graded as D. The reason to set 0.66, 0.33, and 0.01 as the boundaries to grade differently is that, in the previous preference test, a score higher than 0.66 means the corresponding form must be picked all three times, so this form must be perfect to the tester. The same reason applies to the 0.33 and 0.01 rules, which means the form must be picked twice or once. Thus, according to the result of the re-evaluation, although the two rankings are not exactly the same, two different grades for the same form do not differ more than one level. Generally speaking, around 80% of the predicted rankings are correct, which is already remarkable.

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It proves that this scoring system can be a reference to the architect when he needs to decide which form to use and develop. Using this preference model, a form finding method can be achieved, which will evaluate all 36 subdivision rules for a given boundary tetrahedron and select the form with the highest score as the best form. Figure 10 shows the outcome of the form-finding for 5 random boundary tetrahedrons. The re-evaluated grades from the same tester for those ten forms are also shown in the top right of the forms. While 3 of the 5 forms are marked as A, the rest 2 of them are marked as B, even they have the highest scores compared with other 35 forms.

Fig. 10. Form finding by the highest score for 3 random boundary conditions.

But if the top 3 forms are presented together and further selected by the tester, as Fig. 11 shows, it has a much greater chance that there is at least one form is graded as “A”. Although this is a compromised solution, it already largely narrows down the range of forms for the architect to choose.

Fig. 11. Secondary selection from the user.

4

Conclusion and Discussion

In conclusion, 3DGS is a powerful and convenient method for the architect to find a form in structural design. By subdividing the polyhedral geometries in the force diagrams, a variety of forms can be generated, each of which is quite different

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and the set of parameters to express a form is unique and distinguishable from each other. The clear data structure of the polyhedral forms makes it suitable for a neural network to learn the features and then evaluate the forms. Thus, the neural network can also learn the design preference from a specific architect, by learning the result of a preference test taken by the architect. What seems inexplicit and unclear before, now can be quantified through a test, and mathematically evaluated by machine learning. Forms with higher scores can be generated and selected among the solution space automatically, which have higher possibility to satisfy the architects personal design taste. As long as there is data, machine learning can work to learn the relationships between them. In the future, the tendency to design cooperation between human and machine will become clearer. The machine will assist the design process not only in simple repeated work but also in creative work by learning the design examples from human beings. The next step of this research is to extend the usage of machine learning to other kinds of design, and develop neural networks for learning and generating architectural geometries in different design tasks.

References 1. Akbarzadeh, M.: 3D graphic statics using polyhedral reciprocal diagrams. Ph.D. thesis (2016). ETH Z¨ urich, Z¨ urich, Switzerland 2. Akbarzadeh, M., Van Mele, T., Block, P.: Three-dimensional graphic statics: initial explorations with polyhedral form and force diagrams. Int. J. Space Struct. 31, 217–226 (2016) 3. Bolhassani, M., Ghomi, A.T., Nejur, A., Furkan, M., Bartoli, I., Akbarzadeh, M.: Structural behavior of a cast-in-place funicular polyhedral concrete: applied 3D graphic statics. In: Proceedings of the International Association for Shell and Spatial Structures (IASS) Symposium 2018. MIT, USA, Boston (2018) 4. Culmann, C.: Bericht an den hohen schweizerischen Bundesrath u ¨ ber die Untersuchung der schweiz. Wildb¨ ache: vorgenommen in den Jahren 1858, 1859, 1860 und 1863. Z¨ urcher und Furrer (1864) 5. Ghomi, A.T., Bolhassani, M., Nejur, A., Akbarzadeh, M.: The effect of subdivision of force diagrams on the local buckling, load-path and material use of founded forms. In: Proceedings of IASS Symposium 2018. MIT, Boston, USA (2018) 6. Huang, W., Zheng, H.: Architectural drawings recognition and generation through machine learning. In: Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture, Mexico City, Mexico (2018) 7. Newton, D.: Multi-objective qualitative optimization (MOQO) in architectural design. In: Proceedings of the 36th International Conference on Education and Research in Computer Aided Architectural Design in Europe, Poland (2018) 8. Sjoberg, C., Beorkrem, C., Ellinger, J.: Emergent syntax. In: Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture, Boston, United States (2017)

Study on Performance-Oriented Generation of Urban Block Models Chengyu Sun(&) and Jian Rao Tongji University, Shanghai, China [email protected] Abstract. In this study, a set of generation, simulation and optimization methods are introduced to automatically build urban block models that have better environmental performance. With the automatic generation tool called Penguin developed in Grasshopper, urban designers can translate a set of indexes including floor area ratio, building density and height limit into 3D models and visualize land-use distribution. 3rd-party simulation and optimization tools in Grasshopper such as Ladybug, Butterfly and Octopus are connected to Penguin to build an automatic performance-based optimization workflow. A real project in Shanghai, China is illustrated to depict the whole workflow with outdoor airflow simulation and solar radiation evaluation. After 12 h of evolutionary calculation, the best building layout and indexes distribution are found about 35% superior to the worst one. Keywords: Automatic generation
Multi-performance simulation
Multi-objective optimization
Urban block models
Land-use indexes

1 Introduction Urban Blocks are basic units between urban planning and design. It proposes the spatial capacity and quality by abstract land-use indexes. The consideration of various environmental performances is now also important since green city design becomes a consensus. For different urban space possibilities corresponding to a set of indexes, performance simulation and optimization is required as a screening criterion. The translation between abstract indexes and urban block models becomes necessary. For indexes distribution of each urban block under the regional project, multiple attempts are needed. In the traditional workflow, the method of manual trial and error and its huge workload limits the results and the possibility to adjust a large project. With various automated optimization algorithms, this translation should also be automated. Therefore, how to automatically generate, simulate and optimize based on multi-performance targets is necessary to find the best indexes distribution, building layout and environmental performance.

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2 Review of Related Researches The study of automatic building generation according to certain parameter settings is an earlier exploration in this field (Sönmez 2018). Such as the procedural modelling of urban environments which is also a tool based on L system (City Engine) (Parish and Müller 2001). This tool programmatically generates road patterns, buildings, facades, and facade textures using specifications provided by the user through a 2D image map. The procedural modelling of urban environments can be further developed to combine complex 3D elements (Müller and Wonka 2006). The final effect of the generated model depends on human interpretation of the actual case and the use of rules (Krispel et al. 2015). Another example is the study of the refactoring method. The refactoring method extracts the envelope layout features from the individual building models and decomposes them into main elements to construct a new model carrying the features of these 3D urban models (Merrell 2007). The refactoring method also generates largescale building layouts through constrained optimization and interactive exploration of alternatives (Bao and Yan 2013). There are also some studies that focus on automatically generating building models under performance constraints. For example, there is an automatic layout tool based on multi-agent system. It includes sun-shine constraints into the system and considers buildings as agents that can interact with each other according to constraints (Ji and Liu 2010). The agent finds the position that can satisfy respective constraints through selforganized motions. In another example, iterative optimization tools such as genetic algorithm are used to automatically arrange high-rise residential buildings under the sunshine constraints (Gao 2014). The analysis results of the Geco and Ecotect are used as fitness goal of the optimization algorithm. Building location, orientation, and levels are selected as variables for optimal adjustment. For the automatic layout problems under multiconstraints, the Pareto optimal RBFOpt machine learning tools are also applied in some studies (Li 2016). Faced with multiple constraints such as floor area ratio, fire spacing, green space, and sunlight hours in the actual design work; the ratio of the corresponding weight values of different objective functions needs to be adjusted to generate better results. The above studies have more or less limitations and cannot fully adapt to practical design work. However, they all provide useful reference in the process of seeking a configurable description of performance constraints and using the latest technology outcomes.

3 Automatic Generation Methods In order to automatically generate models from abstractive indexes, Penguin as a Rhino & Grasshopper plugin and index-to-form generation tool is developed under Ghpython (Fig. 1). Penguin only requires simple inputs such as urban block boundary, individual building units, land-use indexes, and some parameters to operate the automatic generation.

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Fig. 1. Grasshopper plugin icons of Penguin

Fig. 2. Penguin components

Penguin consists of 14 Grasshopper components from 4 subcategories, which are Blocks for block operation, Building Unit for unit selection, Penguin for automatic generation and Util for result operation (Fig. 2). Block operation module includes MatchInfo (match blocks information), WriteCSV (write blocks csv), and ReadCSV (read blocks csv). Unit selection module consists of UnitInfo (building unit information), DisplayUnit (display building unit), SelectUnit (select building unit), WriteUnit (write building unit csv), AppendUnit (append building unit csv), ReadUnit (read building unit csv). Automatic generation module includes PenguinD (Penguin FAR & Density) and PenguinH (Penguin FAR & Height). The result operation module includes Check (check generation result), AppendCSV (append result csv), and WriteModel (write model txt). Penguin divides all process functions into four modules which are block operation, unit selection, automatic generation, and result operation (Fig. 3). Each module consists of several Grasshopper components that corresponds to a different type of function. The user can freely select the required component to operate the indexes, select building units, and generate models. After generating the results, user can check the

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Fig. 3. Penguin system flow chart

indexes, export the generated data for statistics or output the generated models. On one hand, the modular system design enables different types of functions to have independent operation logic under efficient system architecture. The operation process can also be more interactive and convenient. On the other hand, the function update of Penguin can be realized by adding new functional components without having to adjust the overall system architecture. Together with Grasshopper’s huge third-party plugin Eco-sphere, Penguin can be applied to different kinds of performance analysis and algorithm optimization. 3.1

Block Operation and Unit Selection

Block operation is the first step in automatic generation system (Fig. 4). MatchInfo component is used to read the block curves and indexes information from the CAD file and associate each block curve with its corresponding index in Grasshopper. Curves that are not closed or planar will be recognized and neglected. Block curves and

Fig. 4. Block operation demo

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indexes can be written into .csv data file by WriteCSV component. Similarly, the data file can be read to obtain the block and index information with ReadCSV component. In addition, for existing data files, users can directly open the file by Excel software and edit indexes and parameters. Then read the data file in Grasshopper and there is no need to obtain information through CAD files. For unit selection, users can draw the building boundaries and set related parameters with UnitInfo component. At the same time, it is also possible to read building units in the unit database by ReadUnit component. Users can visually select them in the Rhino interface with DisplayUnit component (Fig. 5) and SelectUnit component. In addition, there are also WriteUnit and AppendUnit to create new unit data-base or add more different units.

Fig. 5. Unit selection demo

3.2

Automatic Generation and Result Operation

The automatic generation module consists of two components, PenguinH and PenguinD which are the core functions of the Penguin system. After the block operation and unit selection, users can select PenguinH or PenguinD to automatically generate models according to the index’s combination (Fig. 6). The two types of components are roughly the same in code structure. The main difference is the different indexes and the differences in some calculation logic. The generation algorithm first finds the south point of the block and calculates the horizontal angle of the bottom edge. Then it rotates the bottom edge counter clockwise towards the south direction for better sunshine performance. Penguin offsets the block curve according to the setback input to get the exact boundary available for building layout. According to the angle between south and north edges, an array of building centre lines is generated. The centre lines need to be cut by setback boundary and green space to ensure logical reasoning. The algorithm then calculates the building layout based on the indexes, unit inputs, and other control parameters. The building models are generated according to the layout and height allocation affected by trend_type and trend_dir input (Fig. 7). Users can define or select specific building unit to generate models with required features (Fig. 8). Different building units with same construction area may also result in different layouts. The generation result can be modified by not only regulation indexes

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Fig. 6. Automatic generation demo

Fig. 7. Automatic generation process

but also a series of input parameters, such as row_shift, row_angle, unit_angle, trend_type and trend_dir. The row_shift parameter can adjust misalignment effect between buildings to get better sunshine azimuth. Row_angle and unit_angle are used to manually adjust direction of centre lines and buildings. Trend_type can create height drop between buildings while trend_dir can control the distribution of higher buildings. In result operation, users can calculate the actual floor area ratio, building density, and building height range with Check component and add the generation result into the above.csv data file through the AppendCSV component. Detailed data analysis can be performed later with software such as Excel. In addition, the WriteModel component can output the blocks and models into a .txt file for further access from third-party programs.

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Fig. 8. Automatic generation result

4 Multi-performance Simulation and Optimization Methods Since Penguin is dependent on Rhino & Grasshopper and has great adaptability, the performance simulation particularly includes outdoor airflow simulation and solar radiation analysis as fitness goals. The outdoor airflow simulations are calculated by Butterfly & OpenFOAM, while radiation analysis is calculated by Ladybug. For the multi-objective optimization, Octopus is chosen since it allows the search for many goals at once, producing a range of optimized trade-off solutions between the extremes of each goal (Fig. 9).

Fig. 9. Ladybug, Butterfly and Octopus components

As methods developed for design practices, Penguin was used to optimize the landuse indexes and building layout concerning the solar radiation and airflow performances in an urban planning project in Shanghai, China. Limited by the computing power of personal computers, the optimization has a total of 4 fitness goals. Since the Octopus only searches for minimum value, all fitness goals need to be converted under

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minimum optimal principle. Two of the fitness goals are total radiation coefficient in summer and winter. Because of the climate in Shanghai, the ideal radiation result should be lower in summer and higher in winter. The other fitness goals are two sets of outdoor airflow simulations. Two prevailing wind directions in Shanghai are selected to conduct the airflow simulations. The wind velocity ratio at 1.5 m pedestrian altitude is extracted from the simulation results to evaluate pedestrian comfort. The percentage of ratio that is smaller than 1.05 in summer or larger than 2 in winter are calculated as the fitness goal. HypeE algorithm from ETH Zurich is chosen for reduction and mutation control in Octopus. The population size is 50, the mut. Probability is 0.2, the elitism is 0.5, the mutation rate is 0.9, and the crossover rate is 0.8. Each time, a set of building density, row_shift, row_angle and trend-gap inputs from Penguin component are selected as the generic data for optimization. The desktop computer has an i7-7700 K [email protected] GHz and Nvidia Geforce GTX 1080 graphics card. After 12 h of evolutionary calculation, a range of optimized trade-off solutions were obtained (Fig. 10).

Fig. 10. Multi-objective optimized trade-off solutions

As you can see in Fig. 10, the solutions closer to the origin point has better performance in outdoor airflow simulation and solar radiation analysis than solutions far from the origin point (Fig. 10). The optimized solutions have the same floor area ratio which is 2.0. The better solution’s generic data is 0.123 in density, 0.0 to 0.535 in row_shift, −6.0 or 0.5 in row_angle and 3 to 5 in trend-gap. Compare solutions with the fitness goals, the radiation results of optimized solutions are 4.38% superior in summer and 18.64% superior in winter, while the airflow results are 15.8% superior in summer and 74.84% superior in winter (Fig. 11). Although solutions that are marked as elitism are not exactly same with each other, adding them together can still provide similar layout features of this optimization. At this point, it also shows striking similarities with the actual trial-and-error layout results.

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Fig. 11. Multi-performances after optimization

5 Conclusion and Outlook The above research develops automatic generation algorithm with multi-performance simulation and multi-objective optimization methods. This study uses Rhino and Grasshopper as the platform, uses GhPython to develop the Penguin automatic generation system, uses Ladybug to simulate solar radiation and Butterfly to simulate outdoor airflow, and uses Octopus for the multi-objective optimization method. Compared to other published automatic layout methods, the following features are obtained. Strong adaptability to various land shape: This method uses a series of parameters to describe specific layout problems. Various design features in actual projects can all be addressed in the new method. Together with the data file, the time for the solution to be solved in the latter layout will be greatly advanced. Popular interface to 3rd-party simulation and evolution tools: This study is developed in Grasshopper’s open source environment. Therefore, adding new functions to Penguin only needs some new components under the same system architecture. Due to the huge third-party plugin Ecosphere, various kinds of analysis and optimization can be applied without plat-form restrictions. This study also makes up for the data transmission between automatic generation algorithm, performance analysis platforms and multi-objective optimization algorithm. In the real project demonstrated, Penguin has been able to generate results with better performance in the 12-h calculation of the personal computer and opened a new direction for research in this field. For example, how to optimize the calculation process

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and shorten the solution time to meet the needs of practical applications? If other performance indexes are included, can it work for other performance automatic layouts? These issues are the direction of future efforts. Acknowledgements. This study is supported by a project of National Natural Science Foundation of China (Grant No. 51778417) and Shanghai Tongji Urban Planning & Design Institute Co., Ltd.

References Yang, F., Qian, F., Liu, S.: Evaluation of measurement and numerical simulation of outdoor thermal environmental effect of planning and design strategies of high-rise residential quarters. Build. Sci. 29(12), 28–34 + 92 (2013) Sönmez, N.O.: A review of the use of examples for automating architectural design tasks. Comput. Aided Des. 96, 13–30 (2018) Parish, Y.I., Müller, P.: Procedural modeling of cities. In: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, pp. 301–308 (2001) Müller, P., Wonka, P.: Procedural modeling of buildings. ACM Trans. Graph. 25(3), 614–623 (2006) Krispel, U., Schinko, C., Ullrich, T.: A survey of algorithmic shapes. Remote Sens. 7(10), 12763–12792 (2015) Merrell, P.: Example-based model synthesis. In: Proceedings of the 2007 Symposium on Interactive 3D Graphics and Games, pp. 105–112. ACM (2007) Bao, F., Yan, D.M.: Generating and exploring good building layouts. ACM Trans. Graph. 32(4), 122 (2013) Ji, G., Liu, H.: Automatic planning of residential quarter under insolation condition based on multi-agent simulation. In: Proceedings of the 15th International Conference on Computer Aided Architectural Design Research in Asia, pp. 165–174 (2010) Gao, F.: High-Rise Residential Automatic Layout Based on Sunshine Effect. Nanjing University (2014) Li, T.: Building Form Generation Methods Based on Solar Irradiation. Nanjing University (2016)

Artificial Intelligence Design, from Research to Practice Wanyu He(&) and Xiaodi Yang Xkool Tech. Co. LDT., B210 Vanke Design Commune, Liu Guang Rd, Nanshan, Shenzhen, China {in,x}@xkool.org

Abstract. As artificial intelligence (AI) technologies continually evolve, they penetrate multiple industries and extend a variety of applications such as image discrimination, voice assistant and smart translator etc. Inspired by the trend of AI, this paper reflected on the traditional design approaches in urban and architecture field, and tried to address the essential problems in the existing ways by combining pioneer design approaches (associative design, algorithmic design) and machine learning, deep learning methods. Taking the feasibility and limitations of the associative design and algorithmic design into account, an artificial intelligence design approach was explored and demonstrated with corresponding practical cases. Based on outcomes of research and practice, this paper further discussed the possibility and application scenarios of AI design in the future. Keywords: Artificial intelligence design
Algorithmic design Associative design
Machine learning
Deep learning




1 Reflection on the Traditional Design Approaches Urban planning, urban design and architectural design have long been considered to be the design of material spaces at different scales. In recent decades, due to the increasingly complex and ever-changing material environment, the neomaterialism philosophical thought has gained wider recognition, and design based on material space and aesthetics has been increasingly questioned: whether design is only related to material spatial perception or conscious aesthetic experience? Should the systematic logic hidden behind be the scope of design? Many architects and design companies have been actively exploring reflections on the nature of the discipline and even the future of the discipline, as mentioned by Koolhaas in his recent speech in Melbourne: “Our contemporary world is extraordinarily complex that a construction company alone is already inadequate to produce enough wisdom to understand and deal with different conditions, unknown situations and complex contexts [1]. He believes that narrow architecture or architectural design can no longer meet the fast changing and complex needs of the contemporary world. However, urban planning, urban design and architectural design are still in accordance with traditional design methods and approaches. © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 189–198, 2020. https://doi.org/10.1007/978-981-13-8153-9_17

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The traditional design approaches are based on the binary concept of “functionality and form” in architecture with a long history [2]. The design basing on the logic that prioritizing functionalities or forms may not reach every aspect of a matter, but it was directly effective in the slow-paced traditional society. However, in the face of the world after the industrial revolution, those approaches have gradually exposed their problems that they are not able to adjust to the fast-changing environment and meet the diverse needs. Cities or buildings can only test their performance and efficiency after being materialized. If the design has large defects, there is almost no effective remedy. Although the original intention of a design tends to pursue higher efficient and more comfortability, the barely satisfied material results lead to disappointment in the use experience, imbalance in resource allocation, and loss of design “power” [3]. Reflecting on the traditional design approaches and admitting that design is not only about the binary relationship between function and form, but more about the “milieu” [4], on which the structure construction, system design, and formal expressions are based – even expressions are no longer “hard-coding” that is end-to-end and difficult to adapt to changes. Thus, traditional design methods, design approaches, and design tools no longer satisfy these demands. There is no paradigm in the original disciplinary system that can interact with multiple social logic systems, environmental performance, and variable needs in the same context. However, the interaction of multiple logics is already happening every day: in the complex ever-changing real world, in the problem-solving brain of architects… What the discipline really lacks is the design approach and technical means of combing, analyzing, disassembling, and reconstructing these logics and interactions.

2 Exploration of New Design Approaches In fact, various attempts and discussions have been conducted in the construction industry. From the “pre-computer form” expressed by Frank Gehry’s firm to parametric design, associative design (referred to as “AD”, also known as “collaborative design”), algorithmic design and “multi-agent system” are all new approaches exploring new possibilities of design from different perspectives. However, in these explorations, it’s clear that two main camps have been formed: one wants to better control the formal results through new technical means to complete the “design” in the sense of traditional architecture; the other wants to adopt new technologies, especially computer language to explore the logic and expression forms behind the design. 2.1

Associative Design

The associative design research topics held by the Berlage Institute in Rotterdam are more inclined to the aforesaid latter camp: using quantifiable parameter systems to control non-quantifiable parameter changes, i.e. through building associative models basing on correlative geometries, the interactive and mutually influenced relationships between various logical entities can be described and defined, on the top of which design objects can be built [5].

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Fig. 1. a. AD5: water autonomy, land value; b. AD5: water autonomy, top view of design result; c. AD5: water autonomy, bird-eye view of design result; d. AD6: the architectural manifold and its intensified grid, land value graph; e. AD6: the architectural manifold and its intensified grid, top view of design result; f. AD6: the architectural manifold and its intensified grid, bird-eye view of design result

The research project was led by Professor Peter Trummer and experienced the associated geometry exploration period (AD1, AD2) from 2004 to 2005, which is to control three-dimensional geometries through two-dimensional graphics stitching to achieve coordinated control of planar graphic changes; the development period of twodimensional associated geometries from 2006 to 2007 (AD3, AD4), that is, by controlling the associated geometries of two-dimensional architectural planes to generate different three-dimensional results under unified logic and apply the differences to the urban regional scale; the mature period (AD5, AD6) from 2008 to 2010, which introduced the land value system on the original basis, such that the associated geometries were no longer controlled by the sensibly adjustable parameters, but logically synergistically associated with a certain weighting requirement of the land, which made the design more objective to some extent, and associated geometries also evolved into three-dimensional forms in this period (Fig. 1a–f). It is worth mentioned that the technical means adopted by the AD1 * AD5 series was not “Grasshopper”, but the “TopSolid” used in the industry, combined with “Rhino-Monkey” to achieve desired results.

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The Potential of Deep Neural Networks

In addition to the above-mentioned taking parameters as an objective input condition for design process, it has huge potential to apply artificial intelligence (AI) in the field of architectural design. AI usually refers to computer vision, natural language processing technologies basing on machine learning, or composite AI technologies such as autopilot technology. After years of research and accumulation, major breakthroughs have made in machine learning field. The most attractive one in recent years is deep learning neural networks and their applications. The study of Van Gogh’s “Starry Night” (Fig. 2) [6] is a great enlightenment for finding new architectural design approaches. In that study, the painting characteristics from different scales, including brush strokes, colors, layout, etc. was first analyzed and labelled. Then these properties was passed through convolutional neural networks (CNN) into multiple neural network layers [7], thus establishing an algorithm model with “Starry Night” style. Meanwhile, a given base picture was also disassembled into the same granularity in the same dimension and scale, which established the model of the base picture. When the two models are fused together, a new morphological result picture with the given base graph and “Starry Night” drawing style is generated.

Fig. 2. A deep neural network algorithm of artistic style

Inspired by the “Starry Night” study, the authors came with an idea for the application of artificial intelligence, which is, to establish two different model systems. One is the algorithm model system that generates design results, and the other is the

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judgment system or parameters constraining model generating. In the next section, detailed implementation of this AI design approach will be illustrated by 3 practical cases.

3 Practice of New Design Approaches Based on the aforesaid reflections and research, this section demonstrated three practical cases in the urban design and architectural design industry. Apart from showing the latent application possibilities of AI design, these cases also represented the more and more intelligent trend in this field. 3.1

The Global Open Competition of Shenzhen Bay Eco-Tech City

In the global open competition of Shenzhen Bay Eco-Tech City at the end of 2011, the authors tried to make some attempts on their own thinking: first, the response to the complex environment must become a part of the system; second, possibilities of optimizing the algorithm model should be explored. In the short three weeks design process, the authors leveraged the surrounding environment information to quantitatively analyze and judge the value of the land, and on the other hand designed an algorithm model that could meet the logical and architectural function requirements. The details are described below. By synthesizing spatial functionalities and milieu data around the target land, especially traffic data, the heat map expression (Fig. 3) of land value was obtained: on the pixelated land grids, the color indicated the magnitude of value, the higher value,

Fig. 3. SZ Bay Eco-Tech City, land value graph

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the warmer the color, and vice versa. These land value parameters were exactly the constraints as the basis of a design. It implied the population density and building density that could be accommodated on different area of the land, thus the location and volume of building space could be determined under corresponding demands. Next, the combination of high-density and multi-functional requirements in the region was transformed into a more specific architectural space algorithm model by the logic system design. This algorithm model transformed the functional requirements of the project into three-dimensional streamlines and building spaces, forming a continuous and open three-dimensional urban space by the architectural logic (Fig. 4) [8].

Fig. 4. SZ Bay Eco-Tech City, partly axonometric

The most critical step of this project was to combine the land value with the algorithm model through collaborative logics to generate the spatial design result. Using the logic of the associative design, the correlation between the land value and the algorithm model was established. When the algorithm model was applied to grids of the parameter system of the land value, the result was derived from the “collision” between building models and different corresponding parameters. The result is, for example, the spatial distribution logic generated in accordance with the heat map in the three-dimensional space of the land. 3.2

Shenzhen Public Service Bureau’s 100 Fire Stations Project

Although the above project did not fully breakthrough the end-to-end “hard-coding” design pattern in practice, it provided a new idea: by designing and establishing algorithm models for different types of buildings, perhaps to some extent, the “softcoding” design can be implemented.

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In the 2014 Shenzhen Public Service Bureau’s 100 fire stations project, attempts were made to solve the demands for four types of fire stations by dozens of different bases by designing four different types of fire station prototypes and establishing a collaborative model basing on the constrained relationship between fire stations and bases to complete four algorithm models (Fig. 5). The value map of each base and the corresponding fire station type can be conveniently obtained through big data mining, rather than separately analyzing each base and designing each fire station. In a sense, this method implements another semi-automatic “semi-soft-coding” design.

Fig. 5. Shenzhen Public Service Bureau’s 100 fire stations project

However, up till this point, the exploration of algorithmic design has basically entered a bottleneck period, whether a pioneering architectural firm such as Zaha Hadid Architects, or an academic leading authority like Professor Neil Leach has reached a turning point in the need to continue to explore in new directions. On the one hand, they attempt to find a more automatic and even more intelligent “soft-coding” design approach, on the other hand, they assume that design can respond to the complex environment from as more aspects as possible. 3.3

The XKool AI Architectural Design Platform

The breakthrough was made in XKool1 AI Architectural Design Platform which has an AI “brain” mainly composed of two parts. They are denoted as “design brain” and

1

XKool Technology Co., LTD. (hereinafter referred to as “XKool”).

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“evaluation brain” respectively. The former one is to “think” about how to generate a design scheme by adversarial training on massive data to output possible superior schemes. The “evaluation brain” is for value evaluating, that is, involving land conditions and the surrounding environment to evaluate and weight the generated schemes in different dimensions thereby determining the best choice. In the “design brain”, there are three different neural networks for generating architectural layouts: a. the rapid generation neural network basing on basic design logic - “Babel”; b. the training neural network based on expert architectural design logic - “Parthenon”, i.e. a CNN with more convolution kernels and corresponding neurons after training with million-level mature design schemes; the self-elevation network - “Colosseum”, which is a Generative Adversarial Network (GANs) trained on the basis of “Parthenon”, by which more design schemes are generated to compare and gamble with each other and finally produce the triumphant results. In the “evaluation brain”, the calculation results and the Monte Carlo simulation results are averaged with weight. The Monte Carlo Tree Search (“MCTS”) [9] continually repeats the search in four steps: selection, expansion, simulation and backpropagation. In the XKool AI Design Platform, search simulation is set to stop at a reasonable time period (in theory, the more abundant the time is, the better the result is). Finally, the 9 neural network nodes with the most search times are returned as the top 9 best results (Figs. 6, 7).

Fig. 6. Design results from the XKool AI Design Platform

Although a large number of mature design schemes are used as training data when training the expert network “Parthenon”, mature solutions may not be best solutions, and in fact there is no perfect design, so outputs of the trained expert neural network are not absolutely superior, but relatively mature. CNN can well identify the relationship between features, which is a consideration of architectural design in terms of its

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Fig. 7. Blind test of XKool AI design results, no obvious difference between black-white human design and XKool blue-red design

integrity. Multiple CNNs are trained with different parameters and then participate in the post-processing of ensemble learning “reassembling” and “bagging”, such that the generated schemes can be better evaluated. In the closed beta stage of XKool’s platform, the top-grade scheme rate reached about 70%. Subsequently, the relative mature models are trained into generative model in the “Colosseum” network using GANs [10] and the results are superimposed in highdimensional space to find the optimal solution of the coincident parts. Through continuous refinement of the training model and enhancement of the pertinence of different weights, the generative model and evaluation model can be divided into models with lower-level granularity. Keeping the accumulation of urban data and adversarial generation, after 5 months of training, the high-quality product rate of XKool’s beta version was increased to about 80%.

4 The Future of Artificial Intelligence Design Associative design and algorithm design had a catalytic effect in intelligentializing urban and architecture design process, but the limitations and nature conflicts between these approaches and the fast-changing requirements cannot be ignored. In the future, AI design would become a more and more important trend. This paper suggested two main development directions here. First, knowledge graph technologies would change the way of knowledge transfer [11]. Knowledge graph has changed the way in which expert skills are obtain and fasten up the process, especially in medical field. This approach is equally applicable in areas such as urban and architectural design that largely depend on significant experience. As XKool AI design platform has been commercialized, establishing an AI knowledge graph will be XKool’s next research focus. Second, unsupervised learning is expected to become far more in the long term because human and animal learning is largely unsupervised [12, 13]. In the field of urban design and architectural design, there will be a possibility that if the most basic urban planning rules or architectural design rules are given to the machine, multiple different network models can continuously generate new design solutions according to “self-understanding” and constantly PK with each other to produce the optimal one. What should be particularly noticed is that applying unsupervised learning in the urban

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and architectural fields requires sorting and extracting the basic rules which are very complicated and irremediable once a project is constructed. Therefore, to simplify a set of basic logics is the critical step for successful application of this technology. Architecture is facing unprecedented challenges. The emergence of artificial intelligence architects is to better assist the architects and let design process return to thinking, thereby promoting innovations and progress in the discipline.

References 1. Koolhaas, R., Gianotten, D.: MTALKS. In: Rem Koolhaas and David Gianotten on countryside. https://msd.unimelb.edu.au/events/mtalks-rem-koolhaas-and-david-gianottenon-countryside (2017). Accessed 10 Mar 2019 2. Li, N., Mao, M.: Probing into the relationship between function and form in architectural design. Urban Constr. Theory Res. (14) (2014) 3. Chaslin, F.: Koolhaas Talks About Koolhaas: Two Conversations and Other. Lin, Y.X. translated. Garden city culture enterprise co. LTD, Taipei (2003) 4. Foucault, M.: Security, Territory and Population: French Academy Speech Series, 1977– 1978. Qian, H., Chen, X. translated. Shanghai People’s Publishing House, Shanghai (2010) 5. Tummer, P.: Associative Design1–6. Berlage Institute (2004–2010) 6. Gatys, L.A., Ecker, A.S., Bethge, M.: A neural algorithm of artistic style. Comput. Sci. (2015). https://arxiv.org/abs/1508.06576 7. Krizhevsky, A., Sutskever, I., Hinton, G.: Imagenet classification with deep convolutional neural networks. Adv. Neural. Inf. Process. Syst. 1, 1097–1105 (2012) 8. He, W.Y.: Rethink parametric design-its theory, research, summarization and practice. City Archit. 2012(10), 62–67 (2012) 9. Silver, D., Huang, A., Maddison, C.J., et al.: Mastering the game of go with deep neural networks and tree search. Nature 529, 484–489 (2016) 10. Goodfellow, I.J., Abadie, J., Mirza, M., et al.: Generative adversarial nets. In: Montreal: Advances in Neural Information Processing Systems, pp. 2672–2680 (2014) 11. Liu, Q., Li, Y., Duan, H., et al.: A survey of knowledge mapping construction techniques. Comput. Res. Dev. 3, 582–600 (2016) 12. Silver, D., Schrittwieser, J., et al.: Mastering the game of go without human knowledge. Nature 550, 354–359 (2017) 13. LeCun, Y., Bengio, Y., Hinton, G.L.: Deep learning. Nature 14539 (2015)

Comparison of BESO and SIMP to Do Structural Topology Optimization in Discrete Digital Design, and then Combine Them into a Hybrid Method Gefan Shao(&) Bartlett School of Architecture, University College London, London WC1H 0QB, UK [email protected] Abstract. On account of the high efficiency of discrete digital design when comparing with 3d-printing in the background of additive manufacture, this essay is going to introduce a hybrid high-efficiency method that is combined with BESO and SIMP for solving topology optimization in discrete digital design. The reason is that both BESO in Karamba3D and SIMP in Millipede have some disadvantages and cannot optimize the structure in an extremely efficient way in discrete design. Based on the project TRANSFOAMER (Chen Ran, Chen Zhilin, Shao Gefan, Wei Na, 2016–2017), RC4, Bartlett School of Architecture, loads of tests will be conducted to demonstrate how hybrid method is operated and why it is more efficient than each single method. Finally, the method will be applied to the project to design some productions. Keywords: Discrete design


Topology optimization
BESO
SIMP

1 Context of Discrete Design and Topology Optimization 1.1

Background of Digital Design and Discrete Assembly

According to philosopher Nelson Goodman, the digital computer is a theory of counting and transferring signals by a binary system (1968, pp. 159–160). Architect Gilles Retsin argues that digital discrete design which is a kind of additive manufacture method means that both the design process and the physical organization of material should be digital and discrete (2015, p. 144), not like the continuous way such as 3dprinting and CNC milling. Physicist Neil Gershenfeld, et al. claim that the implication of the use of digital materials should be defined as “reversibly assembled from a discrete set of parts with a discrete set of relative positions and orientations into large scale projects” (2015, p. 122). A construction can be regarded as an aggregation that combined by thousands of discrete elements like the “bits” in computer fields, and automatically develop by a sort of rules with limited positions and orientations. Unlike those projects such as The Programmed Wall (2006) by Gramazio Kohler (Kohler. G, 2006), whose project is to pile bricks with analogue orientation of increasingly freedom degrees, Architect Jose Sanchez (2014, pp. 91) argues that differentiated and complex © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 199–209, 2020. https://doi.org/10.1007/978-981-13-8153-9_18

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space can also be produces with serialized and serially repetitive elements. Retsin, Gracia and Soler (2017, pp. 180) demonstrate that discrete digital design aims to produce efficient heterogeneous space by same asymmetric pieces with several limited combinatorial design strategies. 1.2

Topology Optimization and Architecture Design

Actually, most problems that designers need to solve are what’s known as “wicked problems” (Rittel 1984). It contains incomplete, contradictory, and changing requirements that are often difficult to recognize (Australian Public Service Commission 2007, p. 3), so solutions to wicked problems cannot be easily regarded as true or false but better or worse. The concept of topology optimization was firstly raised by Bendsøe and Kikuchi in (1988, p. 197–198). They claim that topology optimization is conducted by giving some constraint conditions as well as satisfying other design requirements, and it is also related to modern manufacture techniques in augmented ages, in which computer will participate in the optimization process to calculate optimal distribution in space of an anisotropic material. This issue is also revealed in architecture that architectural design concerns numerous factors, such as structure, costs, material, appearance, scale, etc. Famous Architect Vitruvius claims that a building should follow 3 basic principles of strength, utility and beauty (firmitas, utilitas, venustas). (Marcus Vitruvius Pollioi, BC.14) However, there is usually a chasm between the vision of the architect and structure engineer in traditional process. Since Architects focus more on aesthetics and engineers focus more on techniques, the cooperation would be (at worst) a compromise or (ideally) a synergistic (Beghini et al. 2014, pp. 715–717) if they divide the work. Historically, there are architects whose aesthetic design also follows very creative structural design, for example, Antonio Gaudi, who uses physical models to calculate sophisticated structure, and Frei Ot-to, who tests membrane structure in long-span architecture by doing experiments with soap bubble. When it comes to the field of additive manufacture, it is reasonable to manufacture complex topologies. Theoretically, any shape that is improved by topology optimization is able to be built by digital design. The method allows designer to define constraint conditions such as loads, support points and joint types of the final shape and mass, and then by computing optimal distribution, the shape will be changed into a structure with less material but following the optimal structure strength. In this case, the advantages of topology optimization such as weight saving and material saving can be reflected in maximum. (Razvan 2014, p. 17). Since the biggest advantage of discrete digital design is its efficiency of producing loads of heterogeneous space by limited combination methods, topology optimization will further increase efficiency by regarding minimum weight of materials as the primary condition on this wicked problem.

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2 Existing Topology Optimization Methods-SIMP and BESO 2.1

Solid Isotropic Material with Penalisation (SIMP)

Before 1989, topology optimization has only been studied in integer value with only 0 and 1. By giving less influence to intermediate values of the structural analysis variables, Bendsøe (1989, p. 194) proposed a method to vary the design variables continuously which resulted in a non-discrete solution. This is the beginning of developing theme that is named Solid Isotropic Material with Penalization (SIMP) (Bendsøe 1989). Later, it has been optimizing by some engineers, such as Rietz (2001), Sigmund (2001), Martinez (2005), etc. SIMP is a topology optimization method in virtue of density. According to Aremu et al. (2010, p. 684), the process of SIMP is a kind of integral analysis, after times of density analysis, the density of the mass will be updated. The process will stop until more mass are converged in high-density part and emptier in less density part. Therefore, the result will look like a continuous mass with higher density volume remaining and lower density volume deleted when mass ratio dropping off. The whole process can be generalized into the chart below (Fig. 1), which shows the algorithm of this method. A grasshopper plugin called Millipede has similar theory of SIMP. 2.2

Bi-Directional Evolutionary Structural Optimization (BESO)

BESO is a method that combines with ESO (algorithm for removal) and AESO (algorithm for addition) (Querin et al. 1998, p. 1031). In 2006, Huang, et al. updated the existed BESO method by Querin, et al. to a new algorithm with only one parameter, i.e. the removal ratio of volume (weight) (Huang, Xie and Burry, 2006, pp. 1091–1092). BESO operates more similar as a discrete method. Although the finite elements are subdivided into quite tiny beams, the results are nothing but 1 (add) or 0 (remove). Aremu et al. (2010, p. 684) also give a flow chart of BESO algorithm for the minimization of strain energy(SE) for a given volume fraction constraint (V*) (Fig. 2). In this chart1, an evolution rate (ER), at which the volume is allowed to change per iteration, filter radius (FR), which is a distance limit, V* and design domain are supplied to the algorithm. So the volume will be optimized into a relatively more efficient shape after the setting times of iterations. There is a component called BESO analysis in the Grasshopper plugin Karamba3D in Rhinoceros, to optimize topology in structure grids and structure shapes (Moritz et al. 2017). For discrete digital design, analysis of loads of beams can be regarded as a kind of conversion of discrete elements, thus in this essay, most test will be done in BESO for Beams to optimize the structure of discrete digital architecture.

1

Nomenclature: FR = Filter radius; ER = Evolution rate; V* = Volume fraction constraint; ka = Sensitivity of element a; kth add = Element sensitivity threshold value (adding); kth del = Element sensitivity threshold value (deleting); DSE = change in strain energy; tol = Convergence tolerance, le-5; V* = Volume fraction constraint.

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Fig. 1. Flow chart of SIMP (Aremu et al. 2010, pp 684)

Fig. 2. Flow chart of BESO (Aremu et al. 2010, pp 681)

3 Project TRANSFOAMER Project TRANSFOAMER aims to cut mega blocks of high-density XPS foam pieces by hot-wire cutter and then pick and place them into large scale aggregation through a spatial design strategy (Fig. 3). Gilles Retsin argues discrete digital system as an efficient method to design, fabricate, automate and build on the scale of architecture (2016, pp. 144). Therefore, the main target of the research project is efficiency, of which not only in design process but also fabrication part Fig. 3. Robotic hot-wire cutting- project should be very fast. In the material thinking, TRANSFOAMER foam itself can be delivered and fabricated in very quick way; In fabrication aspect, each foam piece can be precisely manufactured by robotic hot-wire-cutter within only 18 min; In design aspect, the concept of efficiency should also be the main purpose. In the premise of foregone fabricating time of each discrete piece, the efficiency is embodied in the limited amount of digital materials, but it also meets strongest structural requirements. In other words, the meaning of topology optimization in discrete digital design is to find a most efficient organization of discrete pieces to build a construction. This discrete piece follows 2 grids of triangle and 1 grid of square, and it is also introduced a method of point-to-point connection in computational logic. Each piece will have a center point (red) and 8 serialized surrounding points (blue) (Fig. 4). Every

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time when aggregating, the second cloned piece will connect its red point to one of blue points on previous piece, and then rotate by a certain Euler angle (8 types) until finding a strong combination without colliding (Fig. 5). The line between center points of the first and the second pieces shows the direction of aggregating. In this way, the piece can be guided to propagate through a serial of structure lines after the structure analysis.

Fig. 4. Piece analysisTRANSFOAMER(left)

project

Fig. 5. Different rotations of pieces- project TRANSFOAMER(right)

In order to find the equivalent transformation between pieces and structure lines, there are also some structure tests between only 2 pieces by karamba3D. It shows the displacement (m) of each combination and also the orientation between their center points (Fig. 6). After loads of different combinatorial structural tests, the piece shows a kind of connection feature between center points: the force follows the direction between center points, for which the combination of pieces can be regarded as the structural line with 60-degree-angle in a special grid with 0.15 * 0.15 * 3√3/20 (Fig. 7). More than that, some properties such as the material and cross-sections need to be set to make the analysis closer to the reality. In this project, the material is high-density XPS foam, with the density of 0.3 kN/m3, the Young’s modulus of 15000 kN/cm2, the shear modulus of 6481 kN/cm2, the yield strength of 23.5 kN/cm2, and the Cross-Section is a trapezoid shape with upper width of 1 cm and lower width of 15 cm, which is the exact cross-section of the piece. So further research will be all based on this special gird with structural lines (beams), material, Cross-section shape. Since the main comparison between these 2 methods is the efficiency, which means to compare the amounts of pieces (beams) that are existing after optimization, and also staying a stable structure. Typically, the maximum deformation of beams is limited to the beam’s span length divided by 250, so those tests aims to find the minimum pieces and also allow the displacement to be less than around 1/250 of the beams span (Saddiqi 1997, pp. 90).

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Fig. 6. Structure analysis of different combinaFig. 7. Piece grid- project TRANSFOAMER tions- project TRANSFOAMER

4 BESO and SIMP Based on Project TRANSFOAMER No matter which type of method is going to be applied to optimal digital discrete building, the aim is to search for best constraint conditions to balance structure, material, form and aesthetics. This part is going to show loads of tests in some typical shapes (Fig. 8) by both BESO in karamba3D and SIMP in Millipede.

Fig. 8. (a) Cube with only 1 load surface and 1 support part of 3 m*3 m*3 m; (b) Truss with 1 load Surface and 2 supports of 6 m*1.5 m* 1.5 m; (c) Column with 4 load points and 1 support part of 3 m*3 m*4 m; (d) One-floor building with support point in 4 corners of 6 m*6 m*3 m; (e) Beam with 1 load surface and 2 supports with 12 m*1.5 m*1.5 m.

4.1

BESO in TRANSFOAMER

In the BESO method, the load is set as 1 KN/m3, the number of change iterations is 10 and the number of convergence iterations is 20. And the tension factor, the compression factor and the BESO factor are separately set as 1,2 and 0. In order to make a more intuitional result, all the pieces will be replaced by 60° structure lines to show the percentage of remaining volume (Fig. 9). And the most efficient result happens when the distortion meets 1/250 of the cantilever length. Some typical percentages are listed as follows.

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Fig. 9. Topology Optimization by Karamba3D with typical structures: (a) 55% (b) 63% (c) 3% (d) 45% (e) 87%.

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SIMP in TRANSFOAMER

In the SIMP method, the load is also set as 1 KN/m3. The cell size is 0.15 m, when the optimization iteration is set as 5. In order to get a relatively smooth result, the smooth factor is 0.2 with the target density of 0.05. Comparing with BESO in Karamba3D, SIMP in Millipede shows a relatively continuous result. But the criterion will be the same to approach the most efficient result (Fig. 10).

Fig. 10. Topology Optimization by Millipede with typical structures. (a) 29% (b) 14% (c) 5% (d) 10% (e) 59%.

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Hybrid Method of BESO and SIMP

In this part, a hybrid method is going to be introduced. The structure will be optimized by SIMP in step 1 (Fig. 11) to get a rough structure irregular shape, and after transforming into discrete grid, the inside structure will be optimized further by BESO into a more efficient stable structure. Some results in same structures are as follows (Fig. 12).

Fig. 11. Topology optimization by hybrid method-step 1: (a) 30% (b) 15% (c) 5% (d) 10% (e) 60%

Fig. 12. Topology optimization by hybrid method-step 2: (a) 1.5% (b) 8.55% (c) 1.35% (d) 1.6% (e) 45%

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Comparison of the Results

After precious tests, both these 2 methods show different advantages and optimization effects in different structure. From the tests and data that are shown in the chart (Table 1), some comparison results are as follows. Table 1. Comparison of 3 methods doing topology optimization in typical structures. BESO Ratio Displacement/m SIMP Ratio Displacement/m Hybrid Minimum ratio Displacement/m

Cube

Truss

Column

Floor

Beam

55% 0.0004 29% 2*10−6 1.5% 0.001349

63% 0.0036 14% 0.000235 8.55% 0.0047

5% 0.0036 5% 0.000244 1.35% 0.0064

45% 0.000096 10% 0.000027 1.6% 0.0021

87% 0.007 59% 0.0235 48% 0.0238

(1) In most cases, SIMP performs more efficient than BESO. Firstly, it is probably because BESO in Karamba3D analyses the structure by subdividing it into discrete grid at first, while SIMP in Millipede analyses the structure in a more precisely continuous way, and then divides it into discrete grids. Since discrete grids always lead to redundancy and less precise than continuous shape, SIMP will produce more precious optimization than BESO. It can also be seen that some structure lines that are optimized by Karamba3D appear in low density part of model that optimized by Millipede. Another reason may be the analysis mechanism of these two methods. Millipede is going to delete low density part and converge high density part together, which will make the high-density structure stronger. But BESO is to delete low-structural discrete lines in scatter way without converging, so in some extent, BESO attenuate the strong part of the structure gradually when target ratio decreasing; (2) The larger the span of structure is, the more efficient that SIMP is. Because for large-span structure, the key part of the structure is more important than small-span structure. As SIMP converges high-density structure and delete low-density part but BESO is to attenuate the volume, the disparity of effect will be enlarged; (3) Not only for BESO in Karamba3D, but also for SIMP in Millipede, sometimes, displacement plunges at a certain range of value. It probably because to a certain ratio, all load points can transmit the force to the support points by continuous structure lines; (4) As for the hybrid methods, on the basis of SIMP in Millipede, BESO in Karamba3D further optimize the structure by delete some redundant lines. And all of them show higher efficiency in topology optimization in different typical structure. And the longer the span of structure is, the less significant the effect is. In some structure like Cube and Column, only around 1%–2% undeleted lines can keep the structure stable.

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5 Applying to Project-TRANSFOAMER This kind of hybrid method is also applied to the project TRANSFOAMER to design some practical structure like table (Fig. 13) and Pavilion (Fig. 14).

Fig. 13. Structure test of table design-project Fig. 14. Pavilion in B-pro Show 2017, in TRANSFOAMER bartlett-project TRANSFOAMER

6 Conclusion Though SIMP and BESO attains topology optimization efficiently, the results are often local since it is constrained by the loads, supports, element sizes and other parametric values. So the redundant cannot be cleaned up before the displacement of structure deformation starts getting larger. Tests show that the hybrid method is more efficient than individual SIMP or BESO in additive manufacture. It perhaps because the local redundant has been avoided in the first step of SIMP, so that BESO can optimize integrally and get a more efficient result, which still needs further research. As for the digital design, the complexity of design makes it a problem without a clear standard answer (Buchanan 1992, p. 5). A variety of limiting factors also stop designers to solve the problem perfectly. For example, in the previous tests of topology optimization, the main factor that I focus on is the efficiency with reasonable structure strength, but on the other hand, some conditions such as aesthetic value are lost. When it comes to the second digital turn (Carpo 2014, pp. 168–173), many design factors can be digital, such as material weight, costs, time consumption, structure behaviour, etc. Although topology optimization is a quite cutting-edge technology to introduce to architecture field at the moment, hopefully, in the future, more methods can be produced to make the whole process fundamentally digital.

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References Aremu, A., Ashcroft, I., Hague, R., Wildman, R.: Suitability of SIMP and BESO Topology Optimization Algorithm for Additive Manufacture. PHD. Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University, pp. 679–692 (2010) Beghini, L., Beghini, A., Katz, N., Baker, W., Paulino, G.: Connecting architecture and engineering through structural topology optimization. Eng. Struct. 59, 716–726 (2014) Bendsøe, M., Kikuchi, N.: Generating optimal topologies in structural design using a homogenization method. Comput. Methods Appl. Mech. Eng. 71(2), 197–224 (1988) Bendsøe, M.: Optimal shape design as a material distribution problem. 1st ed. [Lyngby]: Danmarks Tekniske Højskole. Matematisk Institut (1989) Buchanan, R.: Wicked problems in design thinking. Des. Issues 8(2), 5 (1992) Carpo, M.: Breaking the curve. ArtForum 52(6), 168–173 (2014) Gershenfeld, N., Carney, M., Jenett, B., Calisch, S., Wilson, S.: Macro-fabrication with digital materials: robotic assembly. In: Architectural Design: Material Synthesis: Fusing the Physical and the Computational, vol. 85, no. 5, pp. 122–7 (2015) Goodman, N.: “Analogues and digits.” Languages of art: an approach to a theory of symbols, pp. 159–164. Hackett Publishing, Indianapolis, IN (1968) Huang, X., Xie, Y.M.: Convergent and mesh-independent solutions for the bidirectional evolutionary structural optimization method. Finite Elem. Anal. Des. 43, 11 (2007) Kohler, G.: ROK-Rippmann Oesterle Knauss GmbH|Projects|The Programmed Wall. Rokoffice.com. http://www.rok-office.com/projects/040-programmed-wall/ Marcus Vitruvius Pollio BC.14. The ten books on architecture. 1st edn. Martinez, J.: A note on the theoretical convergence properties of the SIMP method. Struct. Multidiscip. Optim. 29(4), 319–323 (2004) Moritz, H., Orlinski, A., Clemens, P., Matthew, T., Robert, V., Christoph, Z.: BESO for karamba. Clemens Preisinger, Vienna (2017) Querin, O., Steven, G., Xie, Y.: Evolutionary structural optimisation (ESO) using a bidirectional algorithm. Eng. Comput. 15(8), 1031–1048 (1998) Razvan, C.: Overview of Structural Topology Optimization Methods for Plane and Solid Structures. Annals of the Oradea University. Fascicle of Management and Technological Engineering, vol. XXIII (XIII), 2014/3(3) (2014) Retsin, G.: Discrete assembly and digital materials in architecture. In: Proceedings of ECAADE 34, FABRICATION|Robotics: Design & Assembling, Vol. 1 (Aug 2016), pp. 143–151 (2015) Retsin, G., Gracia, M., Soler, V.: Discrete computation for additive manufacturing. Fabricate 2017, 178–183 (2017) Rietz, A.: Sufficiency of a finite exponent in SIMP (power law) methods. Struct. Multidiscip. Optim. 21(2), 159–163 (2001) Rittel, H.: Second generation design methods. In: Interview in Design Methods Group, 5th Anniversary Report, DMG Occasional Paper 1, 1972, pp. 5–10. Reprinted in Cross, N. (ed.) Developments in Design Methodology, pp. 317–327. Wiley, Chichester (1984) Saddiqi, Z.A.: Concrete Structures, 2nd edn. Help Civil Engineering Publisher, Lahore (1997) Sanchez, J.: “polyomino-Reconsidering Serial Repetition in Combinatorics”. In: ACADIA 14: Design Agency, 23–25 Oct. 2014, Los Angeles, ACADIA/Riverside Architectural Press, p. 91–100 (2014) Sigmund, O.: A 99-line topology optimization code written in Matlab. Struct. Multidiscip. Optim. 21(2), 120–127 (2001)

Application of Algorithmic Generation to Kindergarten Design Shuqi Cao, Zilin Zhou, and Ziyu Tong(&) School of Architecture and Urban Planning, Nanjing University, Nanjing, China [email protected] Abstract. Previous automated building layout studies focus more on optimization than design diversity. However, designers constantly generate new goals in a design task owing to the complex constraints and ill-defined evaluation criteria, and then they have to repeat the optimization consequently. We consider that a more interactive human-machine cooperative design should rapidly create considerable design alternatives with performance analysis in preliminary design period for architects to select. Inspired by Monte Carlo Tree Search (MCTS), we propose an algorithm which can generate various acceptable solutions rapidly for building layout problem. In this article, this algorithm is applied to a kindergarten design project to investigate its efficacy, and to discuss its potential for universal building layout problems and machine learning. Keywords: Algorithmic generation
Automated building layout Monte Carlo Tree Search
Human-machine cooperative design




1 Background Architectural design generally involves complex problems. With incomplete information, architects have to repeat the stages of design (analysis, synthesis, and evaluation) iteratively [1] in order to find out a better solution among innumerable possibilities to achieve multi-objective under complex constraints. This work is time consuming but where the value of design lies. To improve the efficiency or quality of design, architects use computer-aided design tools which can reduce duplicate work, optimize performance, and explore possibilities. That is, these tools should be evaluated by speed, results qualities and creativity. The study of automatic building layout began with the researches of “Facility Layout” about fifty years ago [2]. After that, more disciplines are introduced to this field and some methods have already reached a satisfactory level of optimization or generation for a certain objective [3]. With regard to generation, Shape Grammar [4] and Cellular Automata [5] is used for sequential shape growth, and Expert Systems [6] generate solutions relying on an integrated set of rules. With regard to optimization, there are direct search methods such as Mathematical Optimization [7], widely popular metaheuristics methods, such as genetic algorithm [8], and younger global model-based methods using machine© Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 210–218, 2020. https://doi.org/10.1007/978-981-13-8153-9_19

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learning methods [9]. There are also some methods for creativity, such as Multi-agent system [10]. However, design is to satisfice rather than to optimize [11]. On the one hand, architectural problems have been defined as complex, ill-defined, incomplete and contradictory problems for long [12], thus, neither human nor computer can reach the optimum value. On the other hand, the goals and constraints will be redefined constantly in a design task, and there are normally many alternative solutions to meet the objectives [13]. Therefore, it would not only avoid repetition but also broaden design horizons if architects can overview various design alternatives and their performance at the very start of a project. The desire has brought forward requirements to a new computer-aided design method. First, the speed. Only with high productivity can architects interact with computer in real time. Second, the results qualities. Validity is elementary, and wellperforming results are premises of valuable design recommendations and less manual selection. Third, the creativity, which should be based on the diversity of results. The superiority of the new method over previous ones is the capacity of discover feasible solutions beyond expectations. Ideally, we want an efficient, effective and creative algorithm. However, limited by hardware, speed and accuracy are of an algorithm are always rivals in a computer task [14]. Therefore, the method to provide design recommendations should give consideration to speed, results qualities and creativity at the same time. We consider that Monte Carlo Tree Search (MCTS) might be an ideal algorithm because it can balance the exploitation of well-performing results with the exploration of unknown results [15]. In this article, we use pruning strategy and random sampling strategy from MCTS to write an algorithm for a kindergarten design. Taking it as an example, we will discuss how to generate various feasible solutions efficiently for automated building layout will and use the results to guide design.

2 Case Study The kindergarten design project selected to verify our method locates in Nanjing, China (Fig. 1). We clarified the objective constraints and subjective requirements in the initial analysis stage of design. The “objective constraints”: There are some restraints of function and performance due to external conditions and building norms. The site location (32°03′N, 118°46′E) belongs to the humid subtropical climate zone. The four seasons are distinct with high temperature in summer (28.1 °C / 82.6 °F in July) and cold temperature in winter (2.7 °C / 36.9 °F in January). Spring and autumn are of reasonable length. Because of on the specific geographical features, four forcible constraints are set: The first is boundary: The site is an irregular quadrilateral with an area of 7,200 sq. m, two sides facing the streets requiring 5 m road retreat distance. The second is function and area requirements: A total of 9 classes for three grades are set, each class has 25 children. All the classes need more than 3 h of sunlight in the coldest day. The kindergarten should include learning spaces such as a music room, a library and a science room, and service spaces are also required. The total construction area is 2,100 sq.m. and an

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Fig. 1. Site information.

outdoor public space requires sunlight (at least 450 sq.m.). The last is location requirement: The medical room and security office should be arranged at the entrance and the kitchen should be arranged downwind. The “subjective requirements”: In this case, the additional requirements with the architect’s intention and evaluation include “senior, middle and junior classes are grouped respectively for regulation”, “buildings for children should be away from road noise”, “more sunlight is required in the morning for children’s health”, “classes can have high accessibility and diverse sights”, “outdoor space is full of diversity”, etc. These requirements can be used as both constraints and evaluations in the program, which pose a great influence on the speed of search and the result presentation. The analysis of the kindergarten design is an illustrative example for the universal demands of diversity and efficiency in automated building layout. To be solved automatically, the problem of building layouts should be translated into a computer task, which is to locate building massing under constraints in a site. The generation system should produce a plenty of diverse solutions under the objective constraints in a short time to explore how each of these solutions satisfy the subjective requirements.

3 Method To quickly get diverse feasible solutions of designing the kindergarten’s plan, several existing methods have been attempted before we introduced MCTS. Based on MCTS, we proposed a new method different from the traditional ones. MCTS is an algorithm based on tree data structure, which combines the precision of tree search with the generality of random sampling. It is efficient even in enormous search space and can avoid falling into local optimal solutions thanks to an intelligent strategy [16]. The well-known AlphaGo also uses MCTS. In this project, the problem of setting building massing in a limited area with constraints is similar to the occupation and decision making of placing chess stones in the Go. What the stones to the chessboard is what the building massing to the site.

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All the positions that the building massing can be placed on the site is the potential child node of the previous placed one. Building massing is located sequentially for better final results, and a feasible solution is all the building massing having been located under constraints. The inherent advantages of using MCTS to solve building layout problems are as follow: 1. For the reason that each building massing will occupy or shadow some space, using pruning strategy in building layout problems can sharply reduce the breadth of the search. 2. As building massing’s small movement in the site impact little on its performance and feature, random sampling strategy can be more efficient to search various results. 3. Backpropagation of MCTS which uses the early results to updating the strategy in real time would lead to a higher value subtree. 4. The search tree built in search process can be preserved for future machine learning. Using appropriate methods such as Convolutional Neural Networks (CNN) to evaluate this tree can extract the features and optimization trends of different subtrees [17]. In summary, the pruning strategy and random sampling strategy bring high speed to the former search stage, and backpropagation bring high accuracy to the latter stage. The character caters to what design process requires coincidentally. This study focus on the former stage, so the method applied to the kindergarten design mainly uses pruning strategy and random sampling strategy.

4 Program The program is written in C#, adopts object-oriented programming method and is built with Grasshopper. All the objects in the program are abstracted to two classes: the site grid and the function unit, and the program process includes four modules of site analyst, unit definer, generator, and evaluator (Fig. 2). The MCTS algorithm is implemented in the “generator”.

Fig. 2. Four modules of the program process.

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Construction of Classes: Function unit class: A class used to define the function units. The basic properties include type, length, width, height of the unit, and whether it needs enough sunlight. When a function unit was placed in a site, the “site” property of it will be set, the feasible solution set will be calculated, and the trial times will be recorded. After being placed in the site, the “Location in the Site” is recorded in its property. This class contains two methods: “calculating occupancy” and “calculating shadows”, which can update site information in real time. Site Grid Class: A class used to define the site. The basic properties are boundary, base plane, number of rows and columns, and subdivision. When a function unit is placed in a site, the “unit in the site” property and the “group unit” property will be set. In this class, there are two methods of “available solution set for computing unit” and “attempt to place unit” for unit placement. The “delete unit” method adjusts or rolls back when no feasible solution is found. Program Process: Unit definer: Input the type and number of units to be placed, and instantiate the “functional unit” class as objects waiting to be placed. Site analyst: Input the boundary shape and subdivision to instantiate the “site grid” as a lattice with stored site attributes. Site attributes include: occupation, lighting, distance from the road, the location of entrance, etc. As the unit is placed, the site information updates in real time (Fig. 3).

Fig. 3. a. The site is transformed into a grid (a more subdivided grid is used in the program); b. The relationship with the road; c. The lighting on the coldest day; d. The lighting information updates in real time with the placement of the unit.

Generator: It is the core step of the program to place the unit objects in the instantiated site grid under constraints. A search tree is built according to the outcomes of search. Some constraints to prune the worthless nodes are expressed as methods of the site grid class. Figure 4 shows the process of one generation. First, to set the kitchen near the back gate, points within 14 m to the gate position are searched and 20 angles for each points are tested to judge whether it is able to be set. As the first placed unit, it can be placed at the first tested point, that is, the first child node is selected (Fig. 4a). Meanwhile, the daylight information is updated. Second, the outdoor square need to be set unlike other units, there is no wall for enclosure and no shadows to generate. So we utilize the shape feature to narrow the search range and the random test point is set successfully at the first time (Fig. 4b). Third, to place the first class, the shape feature is

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Fig. 4. Process of a generation.

still used to update the search range. One randomly selected test point is set successfully (Fig. 4c). Fourth, to place the second class, the requirements proposed by the architect for grouping each of the three classes are converted into a geometrical relationship, that is, the centers of the three classes can form an acute triangle. Therefore, the search scope of the second class is limited between 15 and 24 m from the first class. The point is successfully placed until the third times to place the third class (Fig. 4d). Fifth, to set the third class, it recalculates the points can be placed according to the geometric relationship as shown in Fig. 4e. Considering the quite small search range, it will return to the former step for new generations if there is no place for the third one within the preset times. If it still fails, the progress will keep back and it will restart for a new generation when it back to the first step. Sixth, the remaining units are placed in accordance with the above rules, which means the first valid subtree is achieved (Fig. 4f). The search tree is expanded as Fig. 5 shows. Evaluator: The constraints in the generation process cannot remove all the unsuitable solutions. So, after generating the plan, the evaluation of overall analysis (space richness, etc.) will be introduced. In one operation of the generator, the times for generation are set to 1000, and 109 alternatives are successfully generated within 5 min. Then, the updated lighting information is used to evaluate 18 selected plans (Fig. 6). First, the average lighting time of each wall in the coldest day for each unit is calculated, and then the average and variance for all the values of the units are

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computed. Figure 5 shows the difference between arrangements and performance in these plans. Although the score of option 4 in Fig. 6 was not the highest, the architect chose it relying on her own experience and continued the design (Fig. 7).

Fig. 5. Monte Carlo tree search in generator.

Fig. 6. 18 generation results and simple evaluations.

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Fig. 7. The design result.

5 Discussion Some people may query that the method is just throwing scraps of paper randomly. On the one hand, it is by no means easy to generate a viable result with numerous constraints and complex relationship between function and space. On the other hand, the search space is considerable even though in spite of so much constraints. Thus, we should search by selecting higher-value subtrees instead of random ones. Besides, at present, to quickly generate and record a massive amount of samples to train neural networks is a practical method in AI. That is to say, to achieve AI architectural design, the mothed can be a basis. Quick and massive production of feasible solutions can provide valuable reference for architects, can improve the efficiency of performance optimization, and also can be a prerequisite for machine learning and computer architectural creativity. In this kindergarten design, the method inspired by MCTS successfully produced plentiful viable results and calculated obviously faster than other algorithms. By evaluating and refining ample results, the computer can feedback the characteristics of different design strategies, according to which designers can select an appropriate one and develop it for further design. However, the MCTS used in this project is far from the level of state-of-the-art and still to be enhanced. Looking further ahead, the potential of MCTS to be combined with deep neural networks indicates that machine “consciousness” and “cognition” of architectural design will not only be an imagination. Acknowledgment. This research was supported by National Natural Science Foundation of China (51578277) and Major Program of National Natural Science Foundation of China (51538005).

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References 1. Eastman, C.N.: Spatial synthesis in computer-aided building design (1975) 2. Lobos, D., Donath, D.: The problem of space layout in architecture: a survey and reflections. Arquitetura Revista 6, 136–161 (2010) 3. Myszkowski, P., Nisztuk, M.: Usability of contemporary tools for the computational design of architectural objects: review, features evaluation and reflection (2017) 4. Mckay, A., Chase, S.C., Shea, K., Chau, H.H.: Spatial grammar implementation: From theory to useable software. Ai Edam Artif. Intell. Eng. Des. Anal. Manuf. 26, 143–159 (2011) 5. neo SUNGOD CITY / MOON GODDESS CITY. https://makoto-architect.com/ ALGODEX_e_neoSUNGOD_CITY.html 6. Del Río-Cidoncha, G., Martínez-Palacios, J., Eugenio Iglesias, J.: A multidisciplinary model for floorplan design, 3457–3476 (2007) 7. Lomker, T., Frazer, J., Tang, M.: Designing with Machines: Solving Architectural Layout Planning Problems by the Use of a Constraint Programming Language and Scheduling Algorithms. ASCAAD, Sharjah, United Arab Emirates (2006) 8. Merrell, P., Schkufza, E., Koltun, V.: Computer-generated residential building layouts. In: International Conference on Computer Graphics and Interactive Techniques, vol. 29, p. 181 (2010) 9. Wortmann, T., Waibel, C., Nannicini, G., Evins, R., Schroepfer, T., Carmeliet, J.: Are Genetic Algorithms Really the Best Choice in Building Energy Optimization? (2017) 10. Nourian, P.: Configraphics: graph theoretical methods for design and analysis of spatial configurations. A + BE: Archit. Built Environ. 6, 1–348 (2016) 11. Ball, L.J., Lambell, N.J., Reed, S.E., Reid, F.J.M.: The Exploration of Solution Options in Design: A ‘Naturalistic Decision Making’ Perspective, Context: Fifth Design Thinking Research Symposium—dtrs (2001) 12. Simon, H.A.: The Structure of Ill Structured Problems, pp. 181–201 (1973) 13. Akin, Ö.: Variants in Design Cognition. Design Knowing & Learning Cognition in Design Education, pp. 105–124 (2001) 14. Th, C., Leiserson, C., Rivest, Z.: Introduction to Algorithms (1990) 15. Browne, C.B., Powley, E., Whitehouse, D., Lucas, S.M., Cowling, P.I., Rohlfshagen, P., Tavener, S., Perez, D., Samothrakis, S., Colton, S.: A survey of Monte Carlo Tree Search methods. IEEE Trans. Comput. Intell. AI Games 4, 1–43 (2012) 16. Van Eyck, J., Ramon, J., Guiza, F., Meyfroidt, G., Bruynooghe, M., van den Berghe, G.: Guided Monte Carlo Tree Search for planning in learned environments, pp. 33–47 (2013) 17. Silver, D., Huang, A., Maddison, C.J., Guez, A., Sifre, L., Van, d.D.G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M.: Mastering the game of Go with deep neural networks and tree search. Nature 529, 484–489 (2016)

Computational Methods for Curved Surface Modeling Based on Muria-Ori Zhengtao Wang, Fulong Jia(&), Zhonggao Chen, and Guohua Ji School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China [email protected] Abstract. Origami is a “bottom-up” method for surface modeling which contributes to more possibility for the exploration of architectural forms. In this paper, we investigate the geometrical properties of rigid folding and Miura-ori pattern. The geometrical rules in the folding process of several variations of Miura-ori are obtained. Additionally, we present three new variations and describe the folding process in a 3D coordinate system which provides more possibilities for origami surface generation. The folding process is simulated by describing the path of the vertex. This method explores a unified approach to 3D folding model simulation in Rhinoceros/Grasshopper. Keywords: Origami


Folding pattern
Rigid folding
Surface modeling

1 Introduction Natural folding as light weight structure could be of high interest for engineering and architecture [8]. In consideration of the advantages of natural folding such as low production cost, mature technology, the convenience of transportation and storage, the effort to generate 3D surfaces directly by folding single-sheet planar materials (e.g. plywood, metal, plastic, cardboard) has been taken for years. Traditional paper folding mostly uses straight creases. We call this type of origami “prismatic origami”. Origami can form kinds of deformation without changing the properties of the original material. It is often used to transform 2D planar materials into 3D shape, and the reasonable design of creases provides the possibility for the generation of complex shapes. Miura-ori is a common rigid folding pattern. Many scientists and artists have been attracted to the development of the variations based on Miura-ori, such as the Huffman mesh, the Baro pattern, etc. We start our research with the basic origami patterns Miura-ori in order to find more patterns that we can use in the architectural context. Here are the main contributions of this paper: 1. We investigate the geometrical properties of rigid folding and Miura-ori pattern. 2. The folding process is simulated by describing the path of vertex, which could be a unified method for folding simulation in Rhinoceros/Grasshopper.

© Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 219–231, 2020. https://doi.org/10.1007/978-981-13-8153-9_20

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3. This paper summarizes the rules of combination in the folding process of Miura-ori and its variations and puts forward three new patterns. 4. This paper provides several architecturally as well as structurally interesting form possibilities.

2 Related Work Origami stems from the art of paper folding in Japan and now is commonly used in architecture and engineering. Over the years, many artists and scientists have interest in origami and have attempted to investigate its underlying principles. One of the most influential origami artists and theorists, the American physicist Robert Lang, has not only contributed many publications on folding strategies but has also made great advances in applying origami to real-world engineering problems [3]. In addition to the geometric characteristics of origami, scientists formulated several theorems and principles such as Huzita’s axioms, Maekawa’s fundamental theorems, Miura’s patterns, and Kawasaki’s theorem. These theorems and principles determine whether the form can be done by paper folding. Thereinto, Miura-ori was first proposed by K. Miura in 1972. Tachi. T and Joseph. Gattas and others have carried out further research on Miura-ori. Robert lang has designed a origami design tool called “treemaker” based on the “tree theory”, which can calculate the plane crease distribution according to the tree view of the desired shape, and fold along the crease to get the target shape. But this method can only get the shape of the plane two-dimensional. In order to obtain arbitrary space polyhedron, Tachi proposed a paper origami method named tucking molecules and made it into a software called Origamizer. Duncan and Fuchs further studied the geometric properties of curved origami. It was found that curved origami did not change the Gaussian curvature of curved surface, that is, cylindrical, conical and tangential surfaces can be achieved by bending folding. According to the basic principle of lattice paper-cut, Sussman et al. developed a tool to simulate any curved surface with paper-cut. Compared with the traditional origami method, the operation process is simpler than the traditional origami method. The impact of origami as a medium to generate different architectural forms is visible in the practice of architecture [6]. Helmut Hachul and Wilfried Führer built the Colourdome which was exclusively composed of profiled and folded metal sheets in 2002 [8]. The Art Tower Mito in Japan designed by the architect Arata Isozaki applied origami further. In addition, origami has also been applied in custom and interior areas (Fig. 1). (a) Trautz and Herkrath [8]. The application of folded plate principles on spatial structures with regular, irregular and free-form geometries. Symposium of the International Association for Shell and Spatial Structures. Editorial Universitat Politècnica de València. (b) https://www.pinterest.com/pin/614671049120425551/ (c) Francesco Gioia, David Dureisseix, Vinicius Raducanu, Bernard Maurin, René Motro. Conceptual design, realization and experimentation on a

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Fig. 1. (a) Colourdome, Aachen, Hachul, Führer, 2002; (b) Origami-inspired geometric dresses; (c) Art Tower Mito; (d) Interior view of the chapel in St Loup

foldable/unfoldable corrugated curved envelop. IASS-APCS Symposium 2012: From Spatial Structures to Space Structures, 2012, Seoul, South Korea. 7 p. on CD-ROM, 2012 (d) Andreas Falk, Peter von Buelow, Poul Henning Kirkegaard (2012) Folded Plate Structures as Building Envelopes, World Conference on Timber Engineering (WCTE 2012): The Future of Timber Engineering, 10:5, 155–164

3 Preliminaries 3.1

Origami

Origami is an art of paper, that is, to transform a complete sheet of paper into 3D form by flipping, turning, pulling and other techniques without shear and adhesion. Origami, as an ancient art form, has long been a common and practical means of industrial design. Architects have also drawn inspiration from this traditional handicraft. The Miura fold pattern is a flat-foldable origami tessellation which has been applied to the folding of deployable structures for various engineering and architectural applications. 3.2

Rigid Folding

Rigid folding is a three-dimensional structure which is built by folding planar materials while keeping all the elements planar after folding. In this case, the folding surfaces and creases can be replaced by rigid panels and hinges. This principle is commonly applied to many fields, such as industrial design, fashion, interior design, architecture and textile industry. Take 4-fold-mechanism as an example. 4-fold-mechanism is the case where four creases are intersected at one point. The parameters are as follows: four initial crease angles uA ; uB ; uC ; uD , and four folding angles hAB, hBC, hCD, hDA (Fig. 2). hCD is negative (mountain fold) and the rest are positive (valley fold). According to Hoffman’s study, the folding angle meets the following conditions1:

1

D. Huffman, Curvature and creases: a primer on paper, Washington, DC: IEEE Trans. Computers, 1976,10:1010–1019.

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Fig. 2. 4-fold-mechanism rigid

hCD ¼ hAB and hDA ¼ hBC hAB and hBC can be calculated to satisfy the following relationship2: cosðp  hAB Þ ¼ cosðp  hBC Þ 

sin2 ðp  hBC Þ sin uA sin uB 1e

ð1Þ

where e satisfies: cos e ¼  cos uA cos uB þ sin uA sin uB cosðp  hBC Þ

ð2Þ

According to the above conditions, it can be seen: cos hAB ¼ f ðcos hBC Þ ¼ K þ

1  K2 cos qBC  K

ð3Þ

cos hBC ¼ f 1 ðcos hAB Þ ¼ K þ

1  K2 cos qBC þ K

ð4Þ

Otherwise:

The conversion factor k is: K¼

1 þ cos uA cos huB sin uA sin uB

ð5Þ

When the folding angle around a crease intersection of 4-fold-mechanism satisfies the above-mentioned equivalent relation, then rigid folding can be realized. If each crease intersection point in the model satisfies the above-mentioned equivalent relationship, the whole folding model is rigid folding.

2

Thomas Hull, Project Origami, Boca Raton: CRC Press, 2012.

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4 Geometrical Principal of Miura-Ori and Variations 4.1

Miura-Ori

The Miura-ori is a form of rigid origami, meaning that the fold can be carried out by a continuous motion in which each parallelogram is completely flat. The Miura-ori has been applied to the folding of structures in various engineering and architectural works. This paper analyzes its geometric properties and describes its geometric rules in the folding process by mathematical formula. The basic element of Miura-ori is shown in Fig. 3, it can be determined by three parameters: crease length a and b, angle u between initial creases. During the folding process, four parameters are introduced to define a particular state. As shown in Fig. 3, the crease angles ηA and ηB, and folding angles hA and hB: ð1 þ cos gB Þð1  cos gA Þ ¼ 4cos2 u

ð6Þ

The relationship between crease angle η and folding angle h can be established as follows: cos gA ¼ sin2 ucoshA þ cos2 u

ð7Þ

cos gB ¼ sin2 ucoshB  cos2 u

ð8Þ

The variables w, h, and l represent width, height, and length. According to the rigid folding constraints, the following relationships would be satisfied in the folding process: w ¼ 2b
sinðgB =2Þ

ð9Þ

h ¼ a
sinðgA =2Þ

ð10Þ

l ¼ 2a
sinðgA =2Þ

ð11Þ

Then the position of arbitrary crease intersection in the folding process can be calculated. We assume that the number of vertical creases is m and the number of transverse creases is n. The intersection between the vertical creases of item m and the transverse creases of item n is recorded as Vi.j, in which i = 1, 2, 3,…, m; j = 1, 2, 3,…, n. The point Vi,j can be expressed as: x ¼ ði  1Þb sin
y¼

gA 2

ðj  1Þa sin g2B ðj  1Þa sin g2B þ b cos g2A
z¼

0 a cos g2B

ð12Þ i is odd i is even

i is odd i is even

ð13Þ ð14Þ

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In summary, x, y, z can be expressed as a function of hA. There are 12 parameters in the whole process: a, b, u, m, n, hA, hB, ηA, ηB, w, h, l. The first five parameters are constants, which are independent of the folding state and remain unchanged during the folding process. Therefore, five constants and an independent variable hA determine a unique Miura-ori model.

Fig. 3. Left: The unit of Miura-ori in unfolded state, Right: The unit of Miura-ori in folded state

The next step is to define the parametric models in Rhinoceros with the coordinate data we have calculated. Since the coordinate data change instantly with the parameter, we can obtain the instant 3D model (Fig. 4).

Fig. 4. Generation of Miura-ori pattern

4.2

Arc Pattern

The basic unit of an arc pattern can be seen as a union of two Miura-ori (Fig. 5). The basic unit of arc pattern is determined by six parameters: Crease length a1, a2, b1, b2, initial crease angle u1, u2, while a1 < a2, b1 < b2, u1 > u2. The relationship between b1, b2 and the remaining four parameters can be obtained: b1 ¼

ða2  a1 Þ sin u2 sinðu1  u2 Þ

ð15Þ

b2 ¼

ða2  a1 Þ sin u1 sinðu1  u2 Þ

ð16Þ

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Fig. 5. The basic unit of arc pattern

According to rigid folding constraints, the folding angles along vertical creases are denoted as hA, and the folding angles along the transverse creases are recorded as hMZ, hVZ. The crease angle is denoted as ηMA, ηVA, ηMZ, ηVA, according to the Eqs. (1)–(3) and the rigid folding constraints: hMZ ¼ K þ

1  K2 1 þ cos2 ðp  u1 Þ ;K ¼ sin2 u1 K þ cos hA

ð17Þ

hVZ ¼ K þ

1  K2 1 þ cos2 ðp  u2 Þ ;K ¼ sin2 u2 K þ cos hA

ð18Þ

From the section view of the folding process of the model (Fig. 6), we can see that the M-crease intersection point and the V-crease intersection point are located on two concentric circles with radius R1 and R2. Therefore, ha1, ha2, hb1, hb2 may be calculated. ha1 ¼ cos1

R21 þ R22  a22 2R1 R2

ð19Þ

ha2 ¼ cos1

R21 þ R22  a21 2R1 R2

ð20Þ

hb1 ¼ cos1

2R21  cos2 ðgMZ =2Þb21 2R21

ð21Þ

hb2 ¼ cos1

2R22  cos2 ðgVZ =2Þb22 2R22

ð22Þ

h1 ¼ ha1 þ ha2

ð23Þ

Based on the equivalent relation mentioned above, the position of arbitrary crease intersection in the folding process can be calculated. Then in the three-dimensional cylindrical coordinate system, the point Vi,j coordinates can be expressed as ðr cos h; y; r sin hÞ, where r, h, y are:

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Fig. 6. Arc pattern in folding state


r¼

h¼

8 > > >
þ hb2 > > : ðj1Þh02 þ hb2 þ ha1 2

j is even j is odd i is even, i is odd, i is odd, i is even,

ð24Þ j is odd j is even j is odd j is even

y ¼ ði  1Þb1 sinðgMZ =2Þ

ð25Þ

ð26Þ

Therefore, there are 22 parameters defined in the process of finding the crease intersection points of arc pattern. a1, a2, u1, u2, m, n are constants which control the initial plane shape, the folding angle hA is an independent variable. These seven parameters are required to determine the shape of a certain folded state of an arc pattern. With the same method in Sect. 4.1, we can simulate the real-time model of the arc pattern in Rhinoceros/Grasshopper (Fig. 7).

Fig. 7. Generation of arc pattern

4.3

Fan Pattern

A cylindrical surface can be obtained by changing the angle of the crease of the Miuraori, while the fan pattern can be obtained by changing the angle of these straight creases.

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The basic unit is shown in the following diagram. The fan pattern has four basic parameters: crease length, ac, b1, initial crease angle u1 ; u2 . The length of axial crease is recorded as b1, b2,…, bj (Fig. 8): bj ¼ b1 þ ðj  1Þac sin q= sin u2

ð27Þ

Fig. 8. Left: Unit of arc pattern in unfolded state, Right: Unit of arc pattern in folded state

According to the Eqs. (1)–(3) and the rigid folding restriction conditions: hMZ ðhVZ Þ ¼ K þ q1 ¼ cos1

1  K2 1 þ cos2 ðp  u2 Þ ;K ¼ sin2 u2 K þ cos hA

2ac2  2ac2 cos gCZ þ 2af 2  2af 2 cos gFZ  ac2 sin2 q=sin2 u2 pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffipffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 2ac2  2ac2 cosgCZ 2af 2  2af 2 cos gFZ

ð28Þ ð29Þ

Assuming that the number of axial creases is m and the number of radial creases is n, their intersection is recorded as Vi,j. For fan pattern, the crease intersection Vi,j is expressed in the three-dimensional cylindrical coordinate system:
r¼

Rc;j Rf ;j

i is odd i is even

ð31Þ

h ¼ ði  1Þq1
z¼

0 ac cosðgCA =2Þ

ð30Þ

j is odd j is even

ð32Þ

Above all, constant ac, b1, u1, u2, m, n and the folding angle ha determine the shape of a sector pattern in a folded state. With the same method in Sect. 4.1, we can simulate the real-time model of fan pattern in Rhinoceros/Grasshopper (Fig. 9).

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Fig. 9. Generation of fan pattern

4.4

Sphere Pattern

Spherical surfaces are formed while crease vertices move in both horizontal and vertical directions. The parameters in the spherical pattern are crease angle u1, u2, u3, crease length ac, af, b1, b and radial crease angle q. According to the trigonometric function (Fig. 10): b2 ¼ b 1 þ

ac*sinðu1  u3 Þ 2 sin u3

ð33Þ

sin u1 sin u3

ð34Þ

q ¼ u1  u3

ð35Þ

af ¼ a c

Fig. 10. The unit of sphere pattern

According to the rigid folding restriction condition and the Eqs. (1)–(3) (Fig. 11): cos gca ¼ sin2 u3 cos hA þ cos2 u3

ð36Þ

cos gda ¼ sin2 ðu2 þ u3  u1 Þ cos hA þ cos2 ðu2 þ u3  u1 Þ

ð37Þ

cos gcz ¼ sin2 u1 cos hCA  cos2 u1

ð38Þ

cos gfz ¼ sin2 u2 cos hFA  cos2 u2

ð39Þ

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cos gdz ¼ cos gcz

cos hFA cos hCA

ð40Þ

cos gez ¼ cos gfz

cos hCA cos hFA

ð41Þ

Fig. 11. The unit of arc pattern in folded state

Firstly, we consider the motion in the horizontal direction. The x and y coordinates of the crease intersection are expressed as (Fig. 12):
x¼
y¼

Rc;j cosðði  1Þq1 Þ i is odd Rf ;j cosðði  1Þq1 Þ i is even

ð42Þ

Rc;j sinðði  1Þq1 Þ i is odd Rf ;j sinðði  1Þq1 Þ i is even

ð43Þ

Fig. 12. Left: Crease graph, Right: Section of folding sphere pattern

Then calculate the motion in the vertical direction. Finally, the crease intersection Vi,j is expressed in the three-dimensional cylindrical coordinate system:

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zac ¼

Rc2 ð1  cosððj  1Þb=2ÞÞ j is odd Rc1 ð1  cosððj  1Þb=2ÞÞ j is even   zaf ¼ zac  bj sin gj ðj  1Þ=2

ð44Þ ð45Þ

It is important to note that because the axial creases are not parallel, the pattern cannot be extended indefinitely, otherwise, there will be two creases intersecting and unable to meet rigid folding conditions:

n\

2 sin u1

 b1 þ

af sinðu1 u3 Þ 2 sin u2



cos u2  b1 cos u1

af  sinðu1  u3 Þðcos u1  cos u2 Þ

 þ1

ð46Þ

With the same method in Sect. 4.1, we can simulate the real-time model of sphere pattern in Rhinoceros/Grasshopper (Fig. 13).

Fig. 13. Generation of sphere pattern

The spherical shape with different curvature can be obtained by changing the angle of the crease. Based on the geometric properties of spherical patterns and rigid folding constraints, the combination of spherical patterns with different crease angles must meet the following conditions: 1. The radial crease length ac, af of the different creases is the same; 2. The first axial crease length of the second pattern b1 is the same as that of the last axial crease length of the first pattern, bj1; 3. The initial crease angle u1 and u3 of different crease angles are the same; 4. The angle q between radial creases in different crease angles is the same.

5 Conclusion and Future Work This paper focuses on the generation of surface modeling based on Miura-ori and its variations, summarizes the rules between creases and model shapes, simulates the folding process by parametric modeling approaches, achieve surface modeling. Three new variations based on Miura-ori are proposed, and the relationship between crease angle and surface shape is identified.

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Firstly, the folding process is simulated by the method of describing the trajectory of the crease intersection. It is easy to implement in the Rhinoceros/Grasshopper platform, but it is different from the actual folding process. In addition, whether the method is correct depends on the validity of the calculation of the spatial geometric relationship, so we can not ensure the validity of the modeling process by observing the folding. Secondly, the results of 3D modeling are still limited. This paper focuses on surface wrinkling modeling based on Miura-ori. The results are limited to cylindrical and spherical surfaces. In order to generate surfaces with negative Gaussian curvature, nonrigid folding is required. This involves further complex mathematical relationships which would be studied in the future.

References 1. Falk, A., von Buelow, P., Kirkegaard, P.H.: Folded plate structures as building envelopes. In: World Conference on Timber Engineering (WCTE 2012): The Future of Timber Engineering, vol. 10:5, pp. 155–164 (2012) 2. Gioia, F., Dureisseix, D., Raducanu, V., Maurin, B., Motro, R.: Conceptual design, realization and experimentation on a foldable/unfoldable corrugated curved envelop. In: IASS-APCS Symposium 2012: From Spatial Structures to Space Structures, 2012, Seoul, South Korea. 7 p. on CD-ROM (2012) 3. Hemmerling, M.: Origamics: digital folding strategies in architecture. In: Proceedings of the 5th ASCAAD-Conference, National School of Architecture Fès, Morocco, pp. 89–95 (2010) 4. Joseph, M.: Gattas, Miura-base rigid origami: parameterizations of first-level derivative and piecewise geometries. New York J. Mech. Design 135(11), 111011 (2013) 5. Miura, K.: Zeta-core sandwich-its concept and realization, Institute of Space Aeronaut, Tokyo, pp. 137–164 (1972) 6. Megahed, Naglaa A.: Origami folding and its potential for architecture students. Design J. 20 (2), 279–297 (2017) 7. Tachi, T.: Generalization of rigid-foldable quadrilateral-mesh Origami, Tokyo. J. Int. Assoco. 50, 173–179 (2009) 8. Trautz, M., Herkrath, R.: The application of folded plate principles on spatial structures with regular, irregular and free-form geometries. In: Symposium of the International Association for Shell and Spatial Structures. Editorial Universitat Politècnica de València (2009)

A Computational Approach for Knitting 3D Composites Preforms Yige Liu, Li Li(&), and Philip F. Yuan(&) Tongji University, SiPing Rd. 1239, Shanghai 200092, China {yige.liu,Lixsh57,philipyuan007}@tongji.edu.cn

Abstract. This paper shows a computational approach for knitting net shape preforms with bespoke 3D shapes and patterns. The approach takes partial knitting as the major shaping technique and as the fabrication constraints to generate multi-coloured pixel-based knitting maps based on given 3D meshes. The generation process include 5 steps: 1 generation of wales, 2 generation of courses, 3 generation of 2D knitting maps, 4 stitch placement optimizations, and 5 pattern variations. At final stage, users can get a knittable 3D mesh with each face representing each stitch, as well as a 2D pixel-based knitting map. The knittable 3D mesh allows designers to further design pattern variations, the 2D knitting map can be directly used for generating knitting information in knitting software or easily followed by users. Keywords: 3D knitting
Machine knitting
Net-shape
Composites preform
Knittable 3D mesh

1 Introduction Knitting is one of the most ancient techniques in human civilization. With the development of knitting technology and advanced fibers, nowadays designers are increasingly thinking about the potential of knitted textiles. In architecture filed, multiple knitted textiles hybrid prototypes have been investigated [1–8]. “Listener” project can correspond to its surroundings, “Tower” and “Isoropia” projects feature light-weight systems made of bending-active load-carrying GFRP rods and CNC knitted non-homogenous textile membranes. Moreover, postforming knitted textile composites [9], pneumatic textile systems integrating silicon tubes and textiles have also been explored in architecture filed [10]. Some designers have tested bespoke knitted tubes to form complex architectural systems, such as in “MyThread” Pavilion [11], others look to the possibilities of using knitted technical textile as lightweight stay-in-place formwork for complex concrete shell [12–14]. In this research, knitted textiles are used as net-shape preforms for textile-reinforced composite structures. Knitted net shape preforms minimizes material wastage and is possible to customize material density, porosity and micro-structure locally. However, there still lacks a simple effective tool to transform designers’ 3D models into machine’s knitting data. In current textile industry, the transformation process from arbitrary 3D shapes or 3D patterns to knitting information is laborious and time consuming, and is highly relied on experienced technicians. © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 232–246, 2020. https://doi.org/10.1007/978-981-13-8153-9_21

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Therefore, this research aims to provide a computational approach allowing smooth transitions between designer’s 3D models and machine knitting information.

2 State of the Art In terms of generating knitting information from 3D models, multiple approaches have been proposed. Igarashi et al. introduces a system that generates hand knitting patterns for 3D rotund animal models. [15] Yuksel et al. proposes a yarn-level modeling technique for knitted garments [16] and Wu et al. further develops this technique into a fully automatic pipeline capable of converting arbitrary 3D meshes into knit models [17]. Yet, this pipeline doesn’t guarantee the result is knittable. Later, Wu et al. introduces knittable stitch meshes by introducing shift paths to connect neighboring knitting rows and short rows to create shape variations [18]. This method requires user to have certain knowledge of knitting thus to determine the knitting structure, and currently the input geometries are not arbitrary. McCann et al. represents a complier that automatically transforms shape primitives into low-level instructions of knitting machine [19]. The shape primitives are sheets and tubes with parameters of heights, circumferences, short rows, time, skew, spin. Desired 3D geometries are achieved through the combinations of primitives and manipulations of parameters. Yet, this complier cannot take arbitrary 3D geometry as direct input. Popescu et al. describes an approach that transforms undevelopable surfaces into 2D knitting patterns [13]. The 2D knitting patterns requires the yarns to be cut or replaced by a new yarn at the end or start of short rows, and manual transformations of the 2D knitting patterns are necessary for knitting software. Narayanan et al. provides a fully automated computational approach that transforms arbitrary 3D meshes directly to knitting instructions based on computer-controlled V-bed knitting machines [20]. They use time-field guided procedures to produce knitting graphs based on the input 3D surfaces, and such graphs is transformed into low-level knitting operations by a tracing algorithm. Our approach aims at generating 2D knitting maps from designers’ models with arbitrary shapes and textures. The features of our approach compared with previous researches could be summarized as followings: 1. The final 3D knit mesh generated by this approach can be knitted continuously using a single yarn. 2. The final 3D knit mesh shows the placement of each stitch on the 3D geometry, and allows designers to customize knit patterns at stitch level. 3. Partial knitting is the major shaping technique, so the final knitting map could be applied to both common domestic single-bed machines and industrial knitting machines to produce 3D preforms. 4. The 2D knitting map could be directly used for generating knitting information in knitting software without necessity of manual transformations. It allows quick production of large-scale preforms with hundreds and thousands of knitting wales and courses. There is also a layer of index numbers of wales and courses in the knitting map, easy for users to read and follow.

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3 Partial Knitting Similar to other knitted textiles, textiles using partial-knitting techniques is composed of repetitive stitches with course-wale structures. In our approach, such textile is abstracted to a network of quadrilaterals and a few triangles. Each quadrilateral represents a regular stitch and each triangular represents an end stitch of a short course (Fig. 1).

Fig. 1. Abstraction of a knitted fabric into a network of quadrilaterals and a few triangles

There are multiple knitting techniques to create 3D structures on a flat knitting machine, such as tubular knitting, transfer stitches, partial knitting and etc. [21]. Tubular knitting uses double-bed knitting machines to create seamless tubes. Transfer stitches locally increase or decrease the width of fabric. Yet, over certain amount of transfer stitches in a knitting course may lead to failure of knitting machines, since they cause yarn tension to increase. Partial knitting creates a raised or sunken area by adding short knitting courses, and a 3D surface could be achieved with the accumulations of short courses. Our approach adopt partial knitting as the major shaping technique due to ease of operation and less fabrication constraints. An ideal partial knitting structure can form a 3D geometry using a single continuous yarn. Major fabrication features of partial knitting include, knitting direction of each course is always the opposite to its previous and next course, every new course start knitting from the same wale where the end stitch of previous course lies (Fig. 2).

4 Description of the Approach Inputs of this approach include a 3D mesh, stitch parameters and reference points. The input mesh is should be a triangulated mesh. The input stitch parameters are measured from knitted textile samples, they are an average stitch’s width along course direction (W) and height along wale direction (H). Such parameters often change when machine parameters, knitting parameters, stitch structures or yarn types change. The input points could be either one point or multiple adjacent points. Multiple points are used as approximation of a curve (Fig. 3).

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Fig. 2. Fabrication process and features of partial knitting. a Knit a full-length course; b Knit only the stitches on the right side, creating a short course. Stitches on the left side don’t knit and are still held on needles; c Knit a new course from the end stitch of last knitting course. Stitches on the left side still don’t knit; d Stitches on left side later join knitting again and a raised area is formed by the short courses created in step b and c; Step a–d could be continuous knitted using a single yarn.

Fig. 3. a Input triangular mesh; b input stitch parameters include an average stitch’s width along course direction (W) and height along wale direction (H); c input points could be either one or multiple adjacent points

This approach is implemented in 3D modeling tools Rhinoceros 5.0 and Grasshopper, custom codes for generating knitting courses, 2D patterns and stitch placement optimization, are written in Python. The generation process include 5 Steps: 1. Generation of Wales. The surface is covered with iso-curves of constant distance W based on a geodesic distance field. Since fabric using partial-knitting technique have parallel wales, we take these iso-curves as wale edges. 2. Generation of Courses. Each wale edges is divided at constant intervals by points, and each point is connected to the closest point on neighboring curves. The connections constitute course edges. Course edges and wale edges together constitute the initial 3D knit mesh. 3. Generation of 2D Knitting Map. The initial 3D knit mesh is mapped onto 2D as a knitting map. Each stitch is marked as a square with a specific color representing its typology. 4. Stitch Placement Optimization. A 3-step optimization is developed to adjust stitch structures over the 3D knit mesh and 2D knit map, following fabrication constraints of partial knitting. 5. Pattern Variations. Based on the final 3D knit mesh, stitches for pattern variations are selected and represented on the 3D knit mesh and 2D knitting map.

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Generation of Wales

Wale edges are generated based on a geodesic distance field with equal intervals of loop width W. There are multiple ways of computing geodesic distance field on a given mesh [22, 23], and we use the geodesic algorithm proposed by Surazhsky and implemented by Laurent Delrieu in Rhinoceros 5.0 and Grasshopper. This algorithm uses a parameterization of distance function over edges to determine the geodesic distance fields of triangle meshes. Before generating knitting courses, sequence and curve direction of wale edges need to be adjusted. Wale edges should be arranged from near to far from the input points and aligned in the same curve direction. Since we assume the knitting direction of the first course starts from left, and the knitting maps are read from bottom up, the direction of first wale edge should be examined and the direction of rest wale edges should be aligned to that of the first wale edge. To be specific, we take the starting point of first wale edge (P0) and its closest point on second wale edge (P1) as sampling points. Those sampling points are mapped into a plane where P0 is the origin and curve tangent vector V0 at P0 is the positive direction of x axis. The curve direction is flipped if P2 is not located in first and second quadrants. Furthermore, when wale edges at a certain geodesic distance include two or more curves, curves are sorted following the curve direction. At last, since we don’t consider connections of first and last knitting course, wale edges should not be closed curves, otherwise, they will be cut with an opening about twice the width of an average stitch (Fig. 4).

Fig. 4. a Wale edges have aligned curve directions and are sorted from near to far from the input point; b A reference coordinate defined by P0, P1 and V0 is used to judge the curve direction of first wale edge; c When there are multiple curves at certain distance from the input points, they are arranged following the direction of wale edge; d Closed wale edges are not considered in this approach and should be cut with small openings.

4.2

Generation of Courses

To generate courses, each wale edges is divided with equal length around twice the H value. Why twice the H value will be later explained in stitch placement optimization step. Each dividing point is then visited and connected to the closest dividing point on next wale edge. During the connection, a maximum connection length is set to

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guarantee the accuracy of the model, and connections exceeding this length are eliminated. Yet, steps above cannot guarantee very points is connected to a point on its previous wale edge. So points without connections to its previous wale edge are revisited and connected. While generating courses, our tool is able to detect whether newly added lines cross existed lines, and if so, end point of the new line will be adjusted to the end point of its closest intersected line (Fig. 5).

Fig. 5. a Course edges and wale edges together constitute the initial 3D knit mesh; b Wale edges are divided by equal length; c Only connecting dividing points to their next wale edges may leave points without connections to their previous wale edges, those points will be revisited and connected to their previous wale edges; d connections over maximum length are eliminated; e Intersected connections are adjusted.

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Generation of 2D Knitting Map

Course edges and wale edges together constitute the initial 3D knit mesh, each intersecting point of a course edge and a wale edge is given a label (i, j) with i representing the index number of the course edge and j representing the index number of the wale edge (Fig. 6).

Fig. 6. The network of course edges and wale edges in a is translated into a 2D pattern in b.

In the 3D knit mesh, each stitch is represented as an area enclosed by four neighboring points, such as stitch(i, j) is an area defined by point (i, j), point(i + 1, j), point(i, j + 1) and point(i + 1, j + 1). Each stitch is assigned a type attribute based on

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the relationship between the four points. There are four possible relationships between those four points. When point (i, j), point(i + 1, j), point(i, j + 1) and point(i + 1, j + 1) don’t overlap each other, they form a quadrilateral area, representing a “Regular Stitch”. When only point (i, j) and (point i + 1, j) overlaps or only point (i, j + 1) and (point i + 1, j + 1) overlaps, the four points defines a triangular area, representing a short course’s “End Stitch”. When point (i, j) overlaps point (i + 1, j) and point (i, j + 1) overlaps (point i + 1, j + 1), no area is defined between the four points, and the stitch(i, j) belongs to “No Stitch” type. After labeling each stitch in the initial knit structure, stitches are mapped onto a 2D plane as 1 mm squares. The i value of each square serves as its y coordinate, representing the index number of a specific knitting course. The j value of each square is its x coordinate, representing the index number of a knitting wale. Type attributes are expressed in colors, such as dark gray for “Regular Stitch” “End Stitch” and white for ‘No Stitch’. 4.4

Stitch Placement Optimization

The initial knit mesh is usually not of an ideal partial knitting structure, and can not be knitted continuously using a single yarn, therefore we introduce a three-step optimization in our approach. To be specific, the optimization is to make sure last stitch of every course is in the same wale as the start stitch of next course. Step 1 deals with situations that neighboring courses don’t have common wales. Step 2 and 3 adjust even courses and odd courses respectively to make last stitch of every course in the same wale as the start stitch of its next course (Fig. 7).

Fig. 7. a Optimized 3D knit mesh could be knitted using a single yarn, a continuous yellow curve connects each stitch and represents the knitting sequence; b Double course edges; c Adjust stitches’ placement

In the final 3D mesh, a one-stroke curve representing the knitting sequence could be drawn through all the stitches. The optimization of 2D knitting map and 3D knit mesh are carried out simultaneously. During optimization, our approach assumes the knitting direction of every even course starts from knitter’s left to right and every odd

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course from right to left. Step 2 and 3 is inspired by the approach proposed by Narayanan et al. The major difference is that this approach directly adjust the knit structure while Narayanan’s approach deals with a tracing algorithm though existed knit graph. To get a correct knit mesh is important for further step of pattern design over the 3D mesh (Fig. 8).

Fig. 8. a In case of no common wales in adjacent courses, such as in course i and course i + 1, extra small stitches are added; b Adjust even courses by doubling the courses; c Adjust odd courses by varying the stitch structure of every odd course and its following two courses. Transformations is controlled within three courses

4.4.1 In Case of no Common Wales in Neighbouring Courses For every course i and course i + 1, if there are no stitches with common wales, extra stitches are added to course i until they share one stitch in the same wale. The size of those newly added stitches is half the height of regular stitches. This way of adding extra stitches sacrifices local accuracy to maintain the overall knit structure. 4.4.2 Adjusts Stitches in Even Courses Since the height of each stitch is of twice the regular stitch height, here we divide each stitch into two smaller units of regular height. By doing so, the end stitch of every even course and the start stitch of its next odd course are in the same wale, furthermore, the structure of every even course is now exactly the same as its next course. 4.4.3 Adjusts Stitches in Odd Courses The way of adjustment for odd courses depends on the comparison of stitches’ wale index numbers. To be specific, for an odd course i with last stitch in wale j0 and its next course i + 1 with start stitch in wale j1, we compares j0 and j1. If j0 not equals j1, stitches of course i and i + 2 in wale domain [j0, j1] exchange their stitch types. If j0 equals j1, then no adjustments is needed. This optimization starts from first odd course and proceeds to penultimate odd course. This way of adjustment could limit transformations within three courses and the

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outline of those three courses remain unchanged, minimizing the impact over global stitch structure. 4.5

Pattern Variations

Our approach allow users to knit textiles with customized patterns. The 3D knit mesh records the location of every single stitch on the 3D geometry, and when given designed 3D pattern models, stitches closed to those models are selected, and represented in a different color. For representation, stitches are modeled as beam systems based on the 3D knit mesh. Each stitch is an inverted triangle frame made of 3 beams and fits within a face of the 3D knit mesh. Each triangle frame has wide top and pinched bottom, and the 3 beams are of identical diameter. Since the knitted preforms later get sprayed by resin for composites structure, we assume all the connections between beams are fixed (Figs. 9 and 10).

Fig. 9. a Each stitches are presented as an inverted triangle frames made of 3 beams; b Each triangle frame is located within a face of the 3D knit mesh

Fig. 10. a Input 3D model and patterns; b Representation of 3D knit mesh and pattern variations; c 2D knitting map; d Knitted preform

5 File Conversion The final 2D knitting map contains 2 or more colors with each color representing a specific stitch type and a series of machine actions. Most stitches of “Regular Stitch” type or “End Stitch” type are mapped to 2D pattern as grey squares. Each grey square represents a series of basic loop-forming actions. All stitches of “No Stitch” type are mapped to 2D pattern as white squares and white squares represents no knitting actions. Orange and pink squares represents the knitting actions of decreasing a stitch to its right

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stitch and to its left stitch respectively. They cover “End Stitch” or “Regular Stitch” stitches at end of wales. The final 2D Pattern has a layer of numbers showing the wale index number and course index number of each stitch. User could follow the 2D pattern from bottom up to knit each course. If one wants to use automatic knitting machine, the layer of index number could be turned off and the pattern image could be possessed by Photoshop turning each square into a pixel. This pixel-based image could then be directly used for knitting software, such as M1 Plus for Stoll. Machine actions are represented by colors, they can be set in advance using software’s color arrangement function. After setting color arrangement and loading a default cast-on templates, knitting information could be immediately generated without manual transformations (Fig. 11).

Fig. 11. a 2D knitting map has a layer of course and wale index numbers for users to follow; b Knitting map in software M1 Plus is the same as the input 2D knitting map and need to be added a default cast-on template at the bottom; c Interface of M1 Plus software; d The machine actions corresponding to grey, pink and orange colors can be defined in color arrangements function.

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6 Results We tested our approach with different 3D meshes, such as helicoid, saddle, horn tube and twisted tube. The yarn is a heat-setting 100% polyester yarn, so that textile could maintain shape after mold removal (Fig. 12).

Fig. 12. Input 3D meshes, final knittable 3D meshes, knitted samples and 2D knitting maps of helicoid a, saddle b, horn tube c and twisted tube d.

Objects with customized patterns are also tested. We tried different stitch structures for texture variation, such as two-color jacquard and lace stitch. Different stitch structures are distributed following given design patterns, such as voronoi cells, arbitrary curves and points (Fig. 13).

Fig. 13. a Representation model; b Knitted preforms; c multi-colored 2D knitting map

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We also test to customize a full-scale 3D preform for a composites chair. The chair is developed from the typology of saddle surface with strengthen flanges on lateral and back edges. The final knitting pattern covers 5302 courses and 407 wales. It was knitted on Stoll CMS 502 HP+, and the whole knitting process took 3 h 22 min (Fig. 14).

Fig. 14. a Design model; b Knitted preform; c Knitted chair after curing with resin; d Knitting map

Physical tests mentioned above are made on different knitting machines. It proves this approach works for both high-end industrial knitting machines, such as Stoll CMS502+, and domestic knitting machines, such as Brother KH970/KR850, even toy knitting machines, such as Siver Reed LK100. The major difference is that Siver Reed LK100 could only produce basic 3D preforms without complex pattern variations. It only has 100 needles, and the width of preforms is limited. Brother KH970/KR850 could produce 3D performs with more texture variation choices. Since it is semiautomated, the knitting process is time consuming, such as taking 2-3 h to knit a 3D preform around 200 courses. Stoll CMS 502 HP+ machine allows the production of larger and more accurate 3D preforms as well as more complex patterns. Yet not every school is equipped with industrial knitting machine (Fig. 15).

Fig. 15. a Silver Reed LK100 single-bed knitting machine; b Brother KH970/KR850 v-bed knitting machine; c Stoll CMS 502 HP+ automated knitting machine.

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7 Discussion and Outlook Shape Limitation. Currently our approach is mainly suitable for 3D meshes with open edges. For tube-like shapes, our approach leaves one or more seams and those seams need to be processed after knitting. Our approach cannot directly work for 3D meshes with holes or 3D meshes with more than one significantly raised/sunken area. Those geometries could be achieved by segmenting the original geometry into small patches (Fig. 16).

Fig. 16. a Bar graphs showing the length variations of stitches edges compared with the input stitch parameters; b Stitches’ edges with larger deformation appears more frequently at the boundary of given meshes.

Accuracy. Knitting results fit the input mesh in general. Our approach allow 85% of edges to be within the length variation of 20%. Large deformations appear mostly at the boundary of given meshes. In addition, the resolution of input mesh, the accuracy of input stitch parameters, stitch variations, tension distribution during knitting process, molding technique also affect the knitting result. Nice mesh structure, higher resolution of input mesh and more accurate knitting parameter may increase the accuracy. Stitch structure variations may result in uneven stitch sizes, and it could be improved by setting different knitting densities for different stitch type. In terms of tension distribution, partial knitting may cause uneven distribution of knitting tension within textile, affecting stitches’ actual sizes as well as success rate of loop forming process. One of the solutions to this problem is to introduce special sinkers and roller systems. In terms of molding techniques, molds composed of flat plates may create bumps in a surface, this could be improved by increasing densities of plates or replacing plate molds with 3D printed or CNC milled molds with smooth surface. Size Limitation. Width of knitted preforms is restricted by width of the needle bed, in other words, number of wales should not exceed the needle numbers in one machine. While width is limited by knitting beds, length of a knitted preform is relatively less limited. Further, size of a 3D preform is also limited by computing power, computing time and storage size during the generation process of 3D knit mesh and 2D knitting

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map. Patches, larger stitches, computers with stronger computing and storage power are helpful to produce large-scale preforms for architectural applications. Comparison with 3D Printing. 3D knitting offers an alternative way to produce 3D composites objects. Yet, knitted 3D textiles are too flexible to stand under its selfweight and they need extra molds or supporting frames to form desired shape. So design of molding systems is part of the design of the overall composites preforms. Future works will focus on knitted composites structures for architecture. Main focus include how to design a light-weight mold system and integrate the mold system with knitted textile to form a structural whole. Apart from this, form finding and structural simulation for heterogeneous textile-reinforced composites will also be explored. Acknowledgements. This research is supported by Supported by Open Projects Fund of Key Laboratory of Ecology and Energy-saving Study of Dense Habitat (Tongji University), Ministry of Education 201810102. Machine knitting experiments have been done in collaboration with Stoll and Chemtax Industrial Co Ltd.

References 1. La Magna, R., et al.: Isoropia: an encompassing approach for the design, analysis and formfinding of bending-active textile hybrids. In: Proceedings of IASS Annual Symposia. 2018, International Association for Shell and Spatial Structures (IASS). pp. 1–8 (2018) 2. Tamke, M.: Designing CNC knit for hybrid membrane and bending active structures. In: Textiles Composites and Inflatable Structures VII: Proceedings of the VII International Conference on Textile Composites and Inflatable Structures. CIMNE, Barcelona (2015) 3. Tamke, M., et al.: Bespoke materials for bespoke textile architecture. In: Proceedings of IASS Annual Symposia. 2016, International Association for Shell and Spatial Structures (IASS). pp. 1–10 (2016) 4. Thomsen, M.R., et al.: Knit as bespoke material practice for architecture. In: ACADIA 2016: POSTHUMAN FRONTIERS: Data, Designers, and Cognitive Machines - Proceedings of the 36th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), Ann Arbor, pp. 280–289 5. Ahlquist, S., Menges, A.: Frameworks for computational design of textile microarchitectures and material behavior in forming complex force-active structures. In: ACADIA 2013: Adaptive Architecture - Proceedings of the 33rd Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) 2013, Cambridge, pp. 281–292 (2013) 6. Ahlquist, S., et al.: Exploring materials reciprocities for textile-hybrid systems as spatial structures. In: Stacey, M. (ed.) Prototyping Architecture: The Conference Papers, London, pp. 187–210 (2013) 7. Ahlquist, S., et al.: Physical and numerical prototyping for integrated bending and formactive textile hybrid structures. In: Rethinking Prototyping: Proceedings of the Design Modelling Symposium, Berlin, pp. 1–14 (2013) 8. Ahlquist, S.: Integrating differentiated knit logics and pre-stress in textile hybrid structures. In: Modelling Behaviour, pp. 101–111. Springer, Cham (2015)

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9. Ahlquist, S.: Post-forming composite morphologies: materialization and design methods for inducing form through textile material behavior. In: ACADIA 14: Design Agency Proceedings of the 34th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) 2014, Los Angeles, pp. 267–276 (2014) 10. Ahlquist, S., McGee, W., Sharmin, S.: PneumaKnit: actuated architectures through wale-and course-wise tubular knit-constrained pneumatic systems. In: ACADIA 2017: DISCIPLINES & DISRUPTION - Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), Cambridge, pp. 38–51 (2017) 11. Sabin, J.E.: myThread pavilion: generative fabrication in knitting processes. In: ACADIA 13: Adaptive Architecture - Proceedings of the 33rd Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) 2013, Association for ComputerAided Design in Architecture, Cambridge, pp. 347–354 (2013) 12. Popescu, M., et al.: Building in concrete with an ultra-lightweight knitted stay-in-place formwork: prototype of a concrete shell bridge. In: Structures. Elsevier (2018) 13. Popescu, M., et al.: Automated generation of knit patterns for non-developable surfaces. In: de Rycke, K., et al. (eds.) Humanizing Digital Reality - Design Modelling Symposium, 2017, pp. 271–284. Springer, Paris (2017) 14. Popescu, M., et al.: Complex concrete casting: knitting stay-in-place fabric formwork. In: Proceedings of IASS Annual Symposia. International Association for Shell and Spatial Structures (IASS) (2016) 15. Igarashi, Y., Igarashi, T., Suzuki, H.: Knitting a 3D model. Comput. Graph. Forum 27(7), 1737–1743 (2008) 16. Yuksel, C., et al.: Stitch meshes for modeling knitted clothing with yarn-level detail. ACM Trans. Graph. (TOG) 31(4), 37 (2012) 17. Wu, K., et al.: Stitch meshing. ACM Trans. Graph. (TOG) 37(4), 130 (2018) 18. Wu, K., Swan, H., Yuksel, C.: Knittable stitch meshes. ACM Trans. Graph. (TOG) 38(1), 10 (2019) 19. McCann, J., et al.: A compiler for 3D machine knitting. ACM Trans. Graph. (TOG) 35(4), 49 (2016) 20. Narayanan, V., et al.: Automatic machine knitting of 3D meshes. ACM Trans. Graph. (TOG) 37(3), 35 (2018) 21. Underwood, J.: The Design of 3D Shape Knitted Preforms. RMIT (2009) 22. Surazhsky, V., et al.: Fast exact and approximate geodesics on meshes. ACM Trans. Graph. (TOG) 24(3), 553–560 (2005) 23. Crane, K., Weischedel, C., Wardetzky, M.: Geodesics in heat: a new approach to computing distance based on heat flow. ACM Trans. Graph. (TOG) 32(5), 152 (2013)

Data-Optimizing on Minimal Surface Pavillions: Analysis of the Whole Process of Design and Optimization of the Minimal Surface Pavillion Series “Flora” Jiong Xu1, Ying Zhang1(&), Yangchen Zhao1(&), and Xiao Zhang2(&) 1

Nanjing University of the Arts, Nanjing, China [email protected], {1403110814,1097644254}@qq.com 2 CAUP, Tongji University, Shanghai 200092, China [email protected] Abstract. Based on the minimal surface shape pavillion “FLORA” series as an example, this paper analyzes four key techniques in data intelligence in the construction: 1. Form finding method, 2. Main structure optimization, 3. Cell membrane and node optimization. By sorting out a series of key problems in the whole design and construction process, such as grid optimization, curve fitting, node assembly, material selection and so on, this paper provides a construction approach for the double-curved surface geometry. Keywords: Minimal surface


Spacial pavilion
Design optimization

1 Introduction Under the background of digital researches, the physical simulation of minimal curved surface [1], multiple geometric modeling, multi-field application and other characteristics are gradually highlighted, and therefore become an important object of design practice and academic research [2]. Under the digital technology, the minimal surface innovates the design method, breaks through the existing shape and form, and brings new form, new construction and new space [3]. As a nonlinear complex hyperbola, the minimal surface can be visually and transparently presented in various forms in the current environment, and the data representation under simulation optimization can be guaranteed, which is of great significance for the form and method expansion of pavillion design [4]. In recent years, we have been exploring the material representation strategy and the way of the integration of digital technology and art in the pavillion design on the basis of minimal surface. Through the process of form finding, mechanical simulation, structural optimization, node design, and full scale construction, the minimal surface study get great advantage and applied in pavillion, “FLORA” series is one of them (Fig. 1).

© Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 247–256, 2020. https://doi.org/10.1007/978-981-13-8153-9_22

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Fig. 1. One pavilion of “FLORA” series

In the design process, from the topological formation method with t-splines as the main method, to the kangaroo physical simulation biomimetic method, different biomimetic methods have been tried to be applied in the actual design. In addition to the computer biology research, how to implement the design into the full scale construction is also the research focus. In the whole construction process of the series, from the simple low-tech construction method, to the 3d-printed joint node, and finally to the self-supporting pavillion in the tension skin unit, the rain particle path simulation of the built structure and the structural deformation simulation under the wind environment were conducted [5]. From “FLORA 1.0” to “FLORA 3.0” (Fig. 2), the works are constantly exploring more possibilities in terms of form and construction, continuously improving the level of data intelligence, and obtaining more invisible parameters beyond modeling.

Fig. 2. FLORA 3.0

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2 Form Design Method Because of the double definition in mathematics and physics definition in minimal surface, it has various shapes. Since its development, some basic prototypes have been generated from formula, from which designers can attempt to carry out correspondingly more diversified and subjective extension designs. Now the mature tools on the digital platform can directly assist the designer to do physical simulation of minimal surface in physics definition. The generation methods can be roughly divided into three categories: formula method, topological generation based on t-splines, and kangaroo physical simulation generation. In the design of “FLORA” pavilion, topological and physical simulation methods for finding shapes have been used. 2.1

Form Finding Stratagem in FLORA 1.0 and FLORA 2.0

Topological modeling method is the a basic minimal surface modeling method. FLORA 1.0 USES T-splines in Rhino to finish the basic plane modeling by manual wiring, and then gives the basic mesh to the kangaroo to do physical form finding. The design process of “FLORA 2.0” (Fig. 3 left) was also started from a subdivided mesh, and do the form finding process with the help of kangaroo to generate a complex curved surface and structure. However, due to different parameter settings, the hyperbolic shell does not necessarily form a minimal surface, and its average curvature cannot guarantee zero everywhere (Fig. 4 left). FLORA 3.0 (Fig. 3 right) improves on this by using a defined contour to produce a minimal surface that is closer to the physical definition (Fig. 4 right).

Fig. 3. Flora 2.0 in grid iron structure (left); Flora 3.0 in self-supporting structure (right)

Fig. 4. Kangaroo found minimal surface (left); Math definition of minimal surface (right)

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Spatial Contour Form Finding Method in “FLORA 3.0”

In general, the generated results from this physical generation method have strict boundary conditions to preset the shape of the contour. In the topological generation process mentioned above, this point has been used in the optimization of the minimal surface. Kangaroo will perform force simulation for the target mesh. By giving the mesh tension and anchor points, the form can be self-stretched to stabilize the structure. Meanwhile, Kangaroo can also give gravity, wind and other forces to simulate the multi-target shape. What the designer needs to complete is the design of the boundary contour and the internal network generation.In the design of “FLORA 3.0” (Fig. 5), the form of minimal surface was continued, and the multi-dimensional and complex spatial form was further explored based on the previous version. Compared with the “FLORA 2.0” topological generation, the design of 3.0 avoids the limitations of the torsion surface fitting in topological modeling and creates a more multi-dimensional and complex minimal surface space (Fig. 6).

Fig. 5. Generation of FLORA 3.0

Fig. 6. Optimization in curvature of FLORA 3.0 (left to right)

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3 Main Structure Optimization Because of the complexity and multidimensionality of the minimal surface, it is difficult to construct it. In the process of surface splitting, there are not exactly the same combination of elements, and there are certain parameter relations between elements, which will require high-precision production. How to ensure the shape of the design, and to overcome many objective factors in reality, the completion of the optimization of the main structure of the device is also a major problem. Therefore, in the design and construction of “FLORA” series devices, corresponding optimization was made for the complex design and construction of minimal curved devices to varying degrees. 3.1

Preliminary Optimization of Mesh Framework

In the “FLORA” series pavillion, from the initial triangular grid structure to the selfsupporting structure under the membrane tension afterwards, the structural form has been constantly optimized to try more structural possibilities. At the beginning of the research and design of “FLORA 1.0”, the curved surface structure was optimized by triangle meshes, and the shape was self-stretched to simulate the optimal structural form by giving the grid tension and anchor points, and then the grid was split into a triangular structure skeleton, so as to improve the overall stability. However, in actual construction, limited by economic benefits and construction efficiency, the stainless steel tube was selected as the triangular structure skeleton to complete the construction in a relatively low-tech way. “FLORA 2.0” was basically consistent with 1.0 in terms of structural optimization. It used topological surface generation and physical simulation technology to subdivide and optimize the surface structure system. However, in terms of practical construction details, the application of 3D printing technology to the unit components improves the precision of the overall structure and makes the structure more flexible (Fig. 7). But neither of them was a true simulation of the principle of minimal surface generation until ‘FLORA 3.0’, when cross-bearing structures were introduced and overall forces were applied.

Fig. 7. 3D print joints in FLORA 2.0

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Curved Contour Fitting Optimization

“FLORA 3.0” is different from the previous two works in terms of the design of biology and structural optimization. This design work is integrated into a selfsupporting structure, using the physical simulation of the biological method. In version 3.0, only three curves are retained as rigid outline skeleton for the boundary, and the internal surface is guaranteed by the tension between membrane elements to ensure the integrity of the surface structure. It is difficult to construct three boundary curves because they are three dimensional curves. Therefore, the team optimized the contour skeleton and divided the 3d curve into multiple 2d curves for manufacturing. Every 3-d curve after optimization into nine section of two-dimensional circular arc (Fig. 8), calculate the detailed data of ids, and require auxiliary to structure of all nodes in the three-dimensional space x, y, z coordinate data, and ensure that all data intelligent precision, get precise results of structure optimization of implementation and the actual construction (Fig. 9).

Fig. 8. 2-D arc optimized from 3-D contours

Fig. 9. The assembly of 2-D arc

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In the “FLORA” series pavillion, visual effects have been getting good reviews since the 1.0 version, thanks to the formal expression of the epidermal membrane unit and the selection of materials. After the structure is optimized into a triangular grid, the membrane element is defined as a triangular element with independent ID. In the design generation, the computer optimizes each membrane element and writes the output data of each element. In “FLORA 1.0” and “FLORA 2.0”, the membrane unit is independent of the structure. The membrane unit is connected to the structure node by rolling belt, which involves the size limitation of the finished product sample in the construction. After the actual experiment, necessary concessions should be made to the structure data and the membrane unit data to ensure the possibility of the actual installation. The data of the membrane unit is intelligently derived from the computer data after the optimization in the front row. Due to the limitation of objective conditions, manual comparison is used in the actual construction of data clipping membrane unit, resulting in the imprecision of data implementation. Therefore, in the later “FLORA 3.0”, the objective conditions were improved and the precise CNC cutting technology was used to ensure the accuracy of the data. In this unit optimization, the triangle was split into three sides to draw multiple circles connected by data. After tangential optimization, it was ensured that each triangle had the same set of rounded corners at different angles (Fig. 10). Under the skin optimization, each unit is independent, but there is a certain data connection between each other, and more than 360 film unit shapes are generated, and the accuracy of data is guaranteed by CNC cutting. The PVC laser film was vulnerable to damage in the wind environment. Therefore, after the wind load finite element analysis (Fig. 11), the damage degree data of different parts of FLORA 3.0 were also extracted. Based on the data, the team adjusted the size of the film in different positions and the area of each film (Fig. 12) and also each joint was different (Figs. 13 and 14).

Fig. 10. Generation of each film piece

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Fig. 11. Finite element analysis under wind load of FLORA 3.0

Fig. 12. Each film piece on FLORA 3.0

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Fig. 13. Generation of each joint piece

Fig. 14. Each joint piece on FLORA 3.0

4 Conclusion In the research and design of minimal surface, form finding, mechanical simulation and detail optimization not only stay on the computer virtual level, but also serve the real needs of the present era by combining the actual construction method. The entire design process, through the internalization data link reality construction, enables the extremely minimal surface to complete the materialization transformation from the

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computer model. In addition, the uniqueness of non-standard modules under parameterized aided design has become an advantage over other design forms. This is also the result of repeated experimental optimization of “FLORA” series pavilions (Fig. 15), which continuously plays a role in promoting the intelligence of data and the perfection of forms.

Fig. 15. The final effect of FLORA 3.0

References 1. Giusti, E., Williams, G.H.: Minimal Surfaces and Functions of Bounded Variation. Birkhäuser and Springer, Boston (1984) 2. Adriaenssens, S., Block, P., Veenendaal, D., Williams, C. (eds.) Shell Structures for Architecture: Form Finding and Optimization. Routledge (2014) 3. Pan, Qing, Guoliang, Xu: Construction of minimal subdivision surface with a given boundary. Comput. Aided Des. 43(4), 374–380 (2011) 4. Velimirović, L.S., et al.: Minimal surfaces for architectural constructions. Facta Univ. Ser. Arch. Civ. Eng. 6(1), 89–96 (2008) 5. Lavassas, I., Nikolaidis, G., Zervas, P., Efthimiou, E., Doudoumis, I.N., Baniotopoulos, C.C.: Analysis and design of the prototype of a steel 1-MW wind turbine tower. Eng. Struct. 25(8), 1097–1106 (2003)

Why Processing is Not Swarm Intelligence Bing Zhao(&) Tongji University, No. 1239 Siping Road, Shanghai 200092, China [email protected] Abstract. Swarm intelligence has been applied to form-finding methodologies in architectural design, with Processing as one of the most important working platforms deployed. With swarm intelligence feedback is one of the core issues to deal with as this is where complexity emerges and the potential of this methodology becomes manifest. However, with Processing only limited feedback can be achieved as true swarm intelligence involves other incalculable and nonlinear factors, such as stigmergy, that requires a deep relationship not only with other agents but also with the broad background condition. As such, we need to draw a distinction between computational and non-computational complexity, and to recognise the limitations of computational complexity. Processing therefore offers us only a computational and therefore a limited model for understanding swarm intelligence. Keywords: Feedback


Generative design
Stigmergy
Emergence

1 Introduction: Processing and Swarm Intelligence Swarm intelligence refers to the non-empirically classified disciplines of collective behaviors that have higher complexity emerging from simple components or agents. We can see examples of it in nature in bee behavior, termite foraging, flocks of birds and the collective behaviors of other social species. It came into focus in the ‘time of belief in the infinite possibility in mathematics and science’, according to Melanie Mitchell’s description of nineteenth century.1 Swarm intelligence have been applied to economics, medical science, architecture, robotics and other areas, mostly referring to decision making or optimization problems on the basis of the development of digital computation. It was introduced into architecture as a methodology of generative design by architectural practices such as Kokkugia.2 Processing3 is the software platform bridging swarm intelligence and architecture. It is based on JAVA and Python language. And the most commonly used model are multi-agent systems (MAS). Multi-agent systems are driven by forces that are set

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Mitchell [1]. Kokkugia was an experimental architecture research practice led by Roland Snooks and Robert Stuart-Smith, mainly exploring generative design methodologies developed from the complex selforganising behavior of biological, social and material systems. Available at: https://www.kokkugia. com/about. Processing is a software initiated by CEB Reas and Ben Fry.

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uniformly on agents. The process iterates towards dynamic equilibrium. Non-set patterns will emerge from it. But different original conditions will lead to different equilibrium states and different complexities. The unpredictable part of the process is where the huge potential lies. In a multi-agent system, a line is not a mathematical description of connectivity between two points but the linear accumulation of points. And a surface is the matting together of lines or fibres in a manifold topology, rather than the description of u and v isoparameters.4 Geometry topologies are generated based on that. In an interview conducted by Leopold Lambert, François Roche mentions that understanding swarm intelligence requires understanding the difference between Newtonian and entropy scientific approaches. The behavioral trajectories of particles in the Newtonian approach can be calculated and predicted, but from the perspective of entropy, the system is a never-ending exploration between equilibrium and nonequilibrium states, where behaviors cannot be predicted. Any undergo physical process will cause a change of entropy, then a change of state. In swarm intelligence, neighborhood protocols are believed to be one aspect to cause changes to the system, but external influences are another aspect to affect the dynamic process of swarm intelligence.5 In an artificial swarm intelligence system, the focus has been on feedbacks as they show the changes of entropy, that cause emergence. An artificial termite model has been built by Justin Werfel, but the result of it is not a manifestation of emergence but a priori. Kevin Kelly described a decentralized robotic system which is used in car painting. It shows the great potential of swarm intelligence, but does not display enough complexity. Roland Snooks tried to approach a macro scale surface through micro scale agents in his works but found out the logic he applied to geometry does not match the logic of architecture in that multi-agent systems leave linear traces, but architectural forms are composed of planes. Swarm intelligence is therefore not such an effective method of generating form. Direct design approaches usually need to be taken to meet architecture criteria.6 Pheromones are found especially in ant colonies. Stigmergy- the mechanism between ants and their pheromones is so important as it is just here that Processing is somewhat limited - the mutual feedback between an agent and its environment. In all artificial swarm intelligence systems, the agents or components are blind or stupid. They are not aware of the global condition. Even though ant observer Deborah Gordon argues she doesn’t think the ants are accessing the size of the colony, but she does think the colony size affects what an ant experiences.7 Stigmergy is one of the unsolved parts of swarm intelligence, especially in computing. Pheromones also exist in human society. They are described as the vectors of sharing knowledge by Francois Roche. It could be an interface through which people analyze and understand others people’s information, so that it creates more chances for

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Snooks [2, p. 16]. Leach and Snooks [3, pp. 91–92]. Snooks [2, p. 101]. Johnson [4].

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new forms of emergence.8 But pattern is the code according to Steven Johnson. He compares pheromones and patterns, and believes humans are more sensitive to visual effects and patterns. That’s the reason why we build our computing system based on patterns, not on stigmergy.9 The principles behind patterns in swarm intelligence are therefore significant. Where Processing is weak in terms of swarm intelligence is in the area of stigmergy, in other words, mutual real-time feedback. It is not only a limitation of Processing, but also a limitation of digital computing as a whole. Although it is challenging as a computational problem, it indicates a promising research area relating to the sociology of human beings.

2 Exploring Feedbacks Justin Werfel, a researcher at Harvard University’s Wyss Institute, placed termites into a petri dish covered with soil and observed that termites are not only affected by the terrain but also by each other. They clearly know that the holes in the nest should be excavated in low-lying areas, and the places where more termites gather are more likely to attract other termites. He then made a simulation and built an artificial robotic system based on his observation. The artificial termites determine the next step by judging the properties of the material or the location of the module. But this autonomous system is more like a cellular automaton system, in which the next step is determined in advance in accordance with the pre-defined rules. Since the previous step is the input for the next step, the entire system is still set to be centrally controlled in order to avoid system defects. As a result this is not an example of emergence despite the feedback among the component robots. The result is pre-determined.10 Kevin Kelly describes a model that focuses more on feedback between the component and the global condition. But the global condition is one goal for which components only need to make “yes” or “no” decisions. One application is in the car painting industry. Mass-produced cars need to be painted one by one. When a different color is selected, the paint also needs to be changed, thereby wasting time and increasing costs. The factory therefore redesigned the system. Each painting machine is arranged to spray only one color. When the car enters the painting system, the machine that meets the requirements of the task will autonomously send out the signal required for painting, and the car is led to its work place. The system thereby removed central control, but the overall efficiency has been greatly improved.11 This is an example of the potential of swarm intelligence as Kelly hs noted. It is based on a feedback loop between the local and the global. But what is missing is the feedback among the components. All feedback happens in a linear sequence. It is rather a task-oriented loop than a swarm intelligence system. Feedback among homogenous components and

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Leach and Snooks [3, pp. 95–96]. Johnson [4, p. 206]. Werfel et al. [5]. Kelly [6].

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feedback between the local and the global seem to be incompatible. Unlike in a hierarchical system where information can be passed down in order, it is hard to contain the two kinds of feedbacks in one system as they are based on different technological logics. Roland Snooks has explored multi-agent behavior at a micro scale and used it to explore generative design. Using agent-based systems, he embedded design intent in the process, but generative design itself can hardly get an efficient result. Snooks worked on it by combining the manipulation of known topologies and the generating of agents.12 But even though agents form topologies, they are still not aware of the global condition. It is a significant problem for architecture, as analyzing problems such as structural load at a given point and the load paths requires an understanding of the connectivities of the entire system.13 Snooks made another attempt to get the local to be aware of the global, inspired by the mechanism of stigmergy. In an ant colony, pheromones are produced with social behaviors and contain readable information about their behaviors. In the agent-based system, he set feedback between the agents and the lines that are recording the history of agents’ motions. By involving real-time feedback, it formed a self-organizing system.

3 Strange Feedback In the process of form-finding, Snooks often improves the efficiency and controllability of form generation by adding preset conditions, such as directly inputting strands as one of the constraints of agent motion. He calls the interaction between generative design and direct design ‘strange feedback’.14 Cecil Balmond also switches between hand drawing and computation while designing. And he enjoys the unexpected possibilities generated from the process. But he still chooses the appropriate results according to the old Vitruvian triad of firmness, commodity and delight.15 Tom Wiscombe uses messy computation to describe his switch back and forth between direct modeling and algorithmic strategies.16 Strange feedback is the missing part in architecture when compared to the process of termite nesting. What is happening during strange feedback is usually about mapping, even though Snooks argues that generative design is different from mapping as it embeds design intent in the process, Balmond still think the way of transforming design intent and embedding it into the process can hardly escape mapping. He uses his early work on blob design as an example. First he extracts thermodynamic equations or viscosity equations, then visualizes them in the computer through a non-linear process, and finally maps or integrates them into the building. He believes that the essence expressed

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Leach and Snooks [3, p. 127]. Snooks [2, p. 57]. lbid, p. 101. Leach and Snooks [3, p. 124]. Op. Cit, p. 127.

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by this equation has nothing to do with the essence of architecture. Hence this mapping is meaningless.17 The process of termite nesting is always influenced by the external environment, such as wind, rain, sunshine, etc.. The journal Nature recently published a paper on a collective robostic system within which components are circular devices with contractive radius. Components are meshed with each other. When the system vibrates, the robotic system produces collective locomotion. The significant contribution of this research is that it introduces obstacles and light sources as external influence factors. It is found that when the random motion of the component is related to the light source, the overall exhibits a collective locomotion towards the light source.18 This draws the attention to external influences. To some extent, it proves srange feedback is not the incompetence of the autonomous system but a necessary one. Kevin Kelly mentions the importance of top-down interventions in his paper The Bottom is Not Enough.19 He gives the example of Wikipedia, pointing out that Wikipedia’s boss, Jimmy Wales’s strategy of using elite editors to unilaterally prohibit vandals from messing up articles is more efficient than devising bottom-up legalistic rules. He believes that appropriate top-down interventions can make the dumb bottom smarter.20 Back to the concept of entropy, external influence is a way to increase entropy. The messing up of physical processes or breakdown of system is a signal of the end of the loop. Strange feedback is inevitable.

4 Stigmergy The concept of stigmergy was first explained by French biologist Pierre-Paul Grassé in 1958. It refers to the mechanism of ants laying pheromone trails with which each ant can act right feedbacks to accomplish the whole process. In the ants’ building process, as each worker performs a building action, the shape of the local configuration that triggers this action is changed. The new configuration will then influence other specific actions from the worker or potentially from any other workers in the colony. This process leads to an almost perfect coordination of the collective work and may give us the impression that the colony is following a well-defined plan.21 Although in Processing, the logic of stigmergy can provide a concept for selforganized fabrication, what Snooks did was to record the historical trajectory of the agents, which are strands, then set feedbacks between the agent and those strands, thereby establishing a self-organizing system. This generative process works well with materials with volatile behaviors.22 But the general supporting point and gravity load could not be calculated based on the process. The process has its limits when facing

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lbid. Sitti [7]. Leach and Snooks [3, pp. 101–105]. lbid, p. 103. Garnier et al. [8]. Snooks [2, p. 191].

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larger scale problems. To approach the global, the pheromones (the strands) should include more information besides of the motion history of the agents. The agents need to analyze the global condition whenever they are in motion, compare it with their local conditions and make decisions for the next step. It requires a mutual real-time algorithm, which is not only the limitation of Processing, but also the limitation of computation.

5 Beyond Processing Swarm intelligence is not only a concept for the use of generative methodologies for form-finding, but is also manifest in systems from cellular scale to cultural structures.23 Steven Johnson explains the similarities between streets and ant paths in his book Emergence: The Connected Lives of Ants, Brains, Cities, and Software. For example, ants will adjust their behaviors by evaluating the number of ants they encounter during a day, as well as the frequency with which they meet other ants. It is similar to people making choices of routes according to the broadcasts about the road conditions.24 Besides, spaces are seldom used as they were designed to be used. New spatial organizations and new functions always emerge as time and circumstances change. Johnson compares a human being’s visual skill to the pheromones of ants. He uses a very interesting hypothesis to explain this point - if ants can invent personal computers, they will make computers based on pheromone interfaces, while human computer systems are spatial metaphors based on their visual techniques. The human brain has obtained a sensitive cognition of patterns through the complex feedbacks of neurons over thousands of years of evolution. Compared with texts, it is always easier to capture graphics.25 It provides a new perspective to understand stigmergy. The mechanisms of stigmergy vary according to different social groups. This could explain why it is inefficient when applying the logic of ant stigmergy to architectural formfinding. Materials have their own way to operate at a larger scale. The parallel use of stigmergy provides a perspective but nothing else. Francois Roche provides a model of Nanoreceptor Interface to imitate the function of pheromones as he believes human pheromones are absent and weak. Based on a neurobiological concept, Nanoreceptor Interface can analyze the composition of exhaled gases and reinterpret the chemical properties of the body.26 It offers more possibilities for establishing neighborhood relationships on more layers. From another point of view, Johnson explains that feedback is not necessarily admirable; it can also be destructive. Tornadoes and hurricanes are results of feedbacks from the airstream, but they caus damage and that is not the kind of feedback we want to learn from.27 A report on BBC News by the writer Thomas McMullan also mentions

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Leach and Snooks [3, p. 19]. Johnson [4, p. 77]. Op. Cit, p. 206. Leach and Snooks [3, p. 96]. Johnson [4, p. 137].

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swarming drones and warfare, and notes that swarm robots will change the way that wars are fought. Both British and Amercian armed forces are planning to be equipped with them. This brings challenges to everything in society- peace protocols, boundaries of battlefields, defensive system and even lifestyle. Swarm drones can spread out over large areas and operate through self-organization. They can figure out what to do based on their targets and main mission. They can destroy targets but can also make rescue missions.28 The point is that the negative side of swarm intelligence needs to be taken into account while the advantage of the power is being taken. There are always two sides for a self-organized system. Great neighborhoods emerge from the interactions of social behaviors, but poor-living-condition neighborhoods such as slums are also produced from that. It should be noted that swarm intelligence is not a closed loop even though it is usually seen as an entity with its own internal dynamic equilibrium. Solids are composed of nonstop moving particles on a micro scale but are a closed system (at a macro scale?). Swarm intelligence is more unstable as an entity but more adaptive. Any changes of entropy in the universe will activate synchronous changes within the system. Roche compared it with L-system. The later can simulate the shape of branches, but not the re-adaptation in the growth process or photosynthesis.29 For sociology and culture which is an aggregation of discrete systems of different scales, the implication of swarm intelligence should be significant.

6 Conclusion: The Computable and the Incomputable It seems as though what Processing can do in terms of swarm intelligence is the computable part of it, and what it cannot do is the incomputable part. It is all about the handling of feedbacks. For the computable part, feedback happens between agents and agents, and agents and topologies. The latter is problematic as the use of topology is on the contrary to generative process, meaning that it is not a pure swarm mechanism. For the incomputable part, stigmergy is an important concept. The mechanisms of stigmergy are different in different social groups. Making comparisons between biological systems and human society or morphogenesis is full of possibilities, but to solve problems needs to look into the system itself. In terms of building, material particles matter on a micro scale. But on the macro scale, what matters is social behavior. To fill the gap between the computable and the incomputable, a mutual real-time feedback is needed. It must provide chances for agents to estimate the entire system every time they make an action. But it is impossible for now, either for Processing or for computation science. The best way is to shift our attention while the basic disciplines working on it.

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Available at BBC News, https://www.bbc.com/news/technology-47555588 How swarming drones will change warfare. Cited 31 Mar 2019. Leach and Snooks [3, p. 96].

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References 1. Mitchell, M.: Complexity: A Guided Tour. Oxford University Press, New York (2009) 2. Snooks, R.: Behavioral Formation: Multi-agent Algorithmic Design Strategies, p. 16. RMIT University, Australia (2014) 3. Leach, N., Snooks, R.: Swarm Intelligence: Architectures of Multi-agent Systems, pp. 91–92. Tongji University Press, Shanghai (2017) 4. Johnson, S.: Emergence: The Connected Lives of Ants, Brains, Cities, and Software. Simon and Schuster, p. 76 (2002) 5. Werfel, J., Petersen, K., Nagpal, R.: Designing collective behavior in a termite-inspired robot construction team. Science 343(6172), 754–758 (2014) 6. Kelly, K.: New Rules for the New Economy: 10 Radical Strategies for a Connected World. Penguin, p. 15 (1999) 7. Sitti, M.: Robotic collectives inspired by biological cells. Nature 567(7748), 314 (2019) 8. Garnier, S., Gautrais, J., Theraulaz, G.: The biological principles of swarm intelligence. Swarm Intell. 1(1), 3–31 (2007)

Theories and Algorithms of Complexity Science Used in Digital Design Pengyu Zhang and Weiguo Xu(&) School of Architecture, Tsinghua University, Beijing, China [email protected], [email protected] Abstract. Complexity Science with a lot of theories on complexity, can be used for diversified complexity issues in digital design. And taking use of the models and algorithms in Complexity Science, multiple novel forms can be generated efficiently for architectural design, along with the use of computer tools. Complexity Science not only serves as the inspiration for the ideas and methods in digital design, but also provides methods for complex problems and the increased complexity. And some possible applications are discussed in the paper. Keywords: Digital design
Complexity Science Form generation
Algorithms


Complexity


1 Introduction Complexity Science theories are a series of theoretical studies on complexity, and are devoted to simulating, reproducing complex natural phenomena or solving complex problems. There are also diversified complexity issues in digital design, as it facing more complex problems in form generation, function layout and streamline organization. The Complexity Science researches complex problems in all aspects of the natural sciences and the humanities, and it includes related theories that are applicable to digital design. Using Complexity Science theories as well as computer tools, can help understand and deal with the complexity in digital design. And taking use of the models and algorithms in Complexity Science, multiple novel forms can be generated efficiently, serving for architectural design.

2 Complexity Science Theories and Complexity Complexity Science is developed from Systems Science, and focuses on complexity and complex systems. The development of Systems Science can be roughly divided into three stages: in 1940s, Systems Science was mainly composed of System Theory, Cybernetics, Information Theory; in 1970s, Self-Organization theories were proposed, such as Dissipative Structure Theory, Synergy Theory, and Catastrophe Theory; in 1980s, Complexity Science theories emerged, such as Chaotic Dynamics, Fractal Theory and Complex Adaptive System Theory. In addition, there are Complex Network Theory, Combination System Theory, Optimization Theory and some © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 265–274, 2020. https://doi.org/10.1007/978-981-13-8153-9_24

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mathematical theories, enriching the content of Complexity Science. The development process shows the attempt of human to understand complex phenomena in nature and solve complex problems (Jinpei and Xuewei 2010; Huang 2006; Auyang et al. 2002). In daily life, simplicity and complexity are opposite and derived by comparing things on the system and hierarchy, while the criteria and results vary from person to person and from time to time. “What is complexity?” has always been a problem that many scholars are constantly studying. And “Complexity” appears widely in many disciplines, such as Biology, Social Systems, Computer Science, and Architecture as Robert Venturi proposed in his book (Venturi 1966). The interpretation of “Complexity” in Oxford English Dictionary is based on “Complex”, which means “consisting of or comprehending various parts united or connected together, formed by combination of different elements, consisting of parts or elements that involved in various degrees of subordination”. It is thought that complexity can only be the result of composition (Auyang et al. 2002); complexity is dialectical to and developed from simplicity, and it is the key characteristics of a system (Jinpei and Xuewei 2010). As Warren Weaver thinks that complexity is closely related to the organized complex problems which showing some characteristics that the individuals do not have (Weaver 1948). Langton interprets complexity as “Chaotic Edge”; Holland considers complexity as a hidden order created by adaptability; Qian Xuesen summarized the feature of complexity as between subsystems, subsystems of various types, various communication ways, different knowledge representation and the evolving structure (Huang 2006). There are more kinds of complexity, such as Computational Complexity, Kolmogorov Complexity, Algebraic Complexity, Grammatical Complexity, Layered Complexity and so on. Wu Tong proposed a classification of complexity with 9 categories and 54 species, making a summary for the concept of complexity (Tong 2004).

3 Complexity in Digital Design In digital design, Complexity Science inspired the development of digital design theories to some degree. Complexity Science explains the complex phenomena and laws in nature, and holds the opinion that there must be simple rules behind all complex things. This idea has great enlightenment for digital design. The complex phenomena and forms of nature have been the source of inspiration for architects and craftsmen since ancient times. And the interpretation of natural forms in Complexity Science now becomes the new theoretical basis for architects to explore new forms and to comprehend digital design. Complexity is significant in digital design. Some academic pioneers, such as Kas Oosterhuis, learned Complexity Science theories and proposed their own research theories in digital design; Kas Oosterhuis pointed out that the complexity in architecture is based on simple rules; he regards the building components as active Actors, which is relevant to the opinions in Complex Adaptive Systems Theory; and he proposed that each component contains the information of its own and others, and that components are associated with each other to transform their states (Oosterhuis 2002,

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2005, 2012). Jesse Reiser and Nanako Umemoto proposed a new architectural design methodology with Emergence, stressing that the whole can no longer be reduced to the sum of the individuals (Reiser+Umemoto 2006). Cecil Balmond’s series of studies include the study of Fractal Theory and some design experiments, such as Penrose puzzle used in the skin design of Battersea Power Station (Balmond et al. 2002; Ma Weidong, 2008). Neil Leach has studied the complexity of architecture, pointing out swarm and emerging features in architectural forms (Leach 2009). The American writer Steven Berlin Johnson used the swarm intelligence behaviour and group phenomenon of ant colonies to describe and understand the current cities (Johnson 2002). Above all, the complexity in digital design is manifested in three main areas. First, from the appearance, the architectural form in digital design shows a higher complexity than the general. This complexity may appear as complex geometric relations, or as complex combinations of a large number of simple elements. Second, the process of its generation has certain difficulties. The difficulties exist in the design process, such as the functional layout, streamline organization, structure realization and cost control of complex forms, involving Geometry, Computer Graphics or Computer Programming, and requiring more design and programming skills. Finally, and most critically, in digital design, the building behaves as a complex system, with its internal components (such as building components, space units, equipment systems, etc.) collectively organized. That makes the digital design process closely relate to the study of Complexity Science. Only by applying relevant theoretical methods in Complexity Science can we handle and solve all aspects of the complexity in digital design.

4 Complexity Science Theories Used in Digital Design Complexity Science theories influences and inspires the digital design ideas and methods. There are some possible applications proposed as follows. Self-Organization phenomenon exists in a large number of complex phenomena in nature. The Self-Organizing System can organize itself, create itself, evolve on its own without external specific instructions, and can form an orderly and structured system independently (Weidong 2008). Using the Self-Organization theories can generate orderly and complex forms of certain systemicity in digital design, by simulating natural phenomenon such as the Bird Flock, the Reaction Diffusion System, the Vortex and so on. These models are based on Self-Organization, including the communication, decision-making and multiple iterations; and these models inherit the characteristics of Self-Organizing Systems, and present a new, orderly and adaptive state in the repeated interaction among a large number of subsystems (Bonabeau et al. 1999; Witzany 2014; Ashby 1947; Tong 2001; Auyang et al. 2002). Thus, based on the models, new and adaptive spatial structures can be built and then used for generating architectural forms. When a whole or system reaches a certain level of complexity, it will exhibit certain characteristics that its components do not have, that is, Emergence (Vintiadis 2018). In Emergence, the form features of the unit itself are ignored, and the new special properties of the system are emphasized. With the aid of computer tools, the models of Emergence can be used in generating forms, such as Cellular Automaton and Diffusion-Limited Aggregation. By setting the rules and the initial state, the model of

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Cellular Automaton is possible to evolve from a simple initial shape to a complex form, and shows the properties that are not appeared in the initial state, such as random, discreteness, union and variety. In the model of Diffusion-Limited Aggregation, plenty of random and irregular particles aggregate while moving, forming a special appearance totally different from a single particle. Swarm Intelligence emphasizes the collective intelligence of self-organizing systems to cope with certain problems without central control. This is applied to algorithms such as Ant Colony Algorithm to solve practical problems (Beni 2012). But in digital design, swarm intelligence does not aim at pursuing optimal results. Instead, it uses this idea to make building models with certain optimized properties, such as coherent to the surroundings or facilitated to regional transportations. In digital design, swarm intelligence is demonstrated by two main modes: the interaction of polyhedrons and the agents without specific forms. In the first mode, the interaction results in the form transformations of polyhedrons, such as changing the positions of vertices, and the aim is to make a spatial tessellation or something else; in the second mode, the agents follow some common simple rules and change states while time goes on, and the states of agents on different time make up a data collection, which can be used for generating forms. In digital design, swarm intelligence is not used for achieving the most optimized result, but to obtain a number of consistent and coordinated forms or a complex form composed of a series of units. Complex Network Theory provides an abstract solution to complex problems (Lei 2006). According to the organizational principles, complex networks can be divided into Regular Network, Random Network and Small-World Network (Fig. 1) (Watts and Steven 1998). Complex relations among the components of a complex form can be described by complex networks, such as the complex associations of various components of a city, and the high-speed rail network (Fig. 2). Complex networks are implicit in digital design. In digital design, components are closely related. And their connections and affiliations may form a complex network, which can be quickly and conveniently analysed and represented by graphs, and then form complex networks or solve complex problems intuitively. Using this method, appropriate architectural or urban regional forms can be established considering design conditions.

Fig. 1. Regular Network, Random Network and Small-World Network (Extracted from: Duncan et al. 1998)

Fig. 2. Part of the high-speed rail network in China (http://crh.gaotie.cn/CRHMAP.html)

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Chaotic Dynamic Theories tend to be disordered, sensitive to the initials and difficult for predicting (Lorenz 1997; Boeing Geoff 2016; Danforth 2019; Hasselblatt et al. 2009). Based on the theories, designers can easily and conveniently establish special forms that seem random, chaotic, but have certain dynamic characteristics. One of these models is the Strange Attractor. It contains infinite curves, surfaces, or higherdimensional manifolds (Lorenz 1997), and has many types. It shows a clear spatial form and can be directly used as a prototype in digital design. Optimization Theories include a variety of optimization algorithms and intelligent optimization methods, using artificial intelligence for the optimization of systems by simulating or interpreting certain natural phenomena or processes (Jinpei and Xuewei 2010). Optimization algorithms are those that satisfy a series of constraints and/or systematically assign a value to their variables to optimize (Beni 2012). They are valuable in digital design, and provide new ways for generating forms by evolving objects or collecting data. In addition, in the optimization theories, the “satisfaction” principle with the characteristics of universality, ambiguity, intelligence and relativity, replaces the “optimal” principle (Jinpei and Xuewei 2010). This principle also profoundly affects digital design, especially in the early stages for selecting generated forms.

5 Complexity Science Algorithms Used in Digital Design In digital design, using computer programming and other methods, forms can be generated on the basis of the models and algorithms of Complexity Science. In this process, the computer is the tool for model calculation and performance, and the basic platform; the theories of Complexity Science can be demonstrated by some models, and then translated into algorithms for generating forms. There are the illustrations of the above-mentioned Complexity Science theories as follows. Each illustration is shown with its model, algorithms and possible forms, by simulating some complex natural phenomena or finding solutions for the complex problems. The Bird Flock model demonstrates a swarm behaviour and the characteristics of Self-Organization by simulating the interaction of bird populations during migration (Reynolds 1987). During the process, in addition to the constant interaction between adjacent individuals, each bird receives a “Self-Propelled” force, which is constantly waving its wings toward a certain direction. The simulation algorithm mainly includes five parts: initial bird group formation, separation, aligning direction, moving toward the centre, and flying forward (Fig. 3). The model contains a large amount of data with diverse dimensions, thus, various analysis results and forms can be obtained (Fig. 4).

Fig. 3. Diagram for the algorithms of Bird Flock model

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Fig. 4. Forms generated from the flying path in the Bird Flock model

The Cellular Automaton is an example of Emergence using one kind of square unit (von Neumann 1963, 1966; Wolfram 1983; Gardner 1970). General design cases are often similar in final forms. Taking Hufang Bridge Urban Complex Design as an example, with the consideration of the surrounding buildings of obviously different sizes in north and south, two grids of different sizes are used as units in the algorithm (Fig. 5). By evolving the whole model, several satisfactory forms can be obtained, with significantly changes from south to north (Fig. 6).

Fig. 5. Diagram for form generation using Cellular Automaton (Credit to Cui Wanyi)

Fig. 6. Forms generated using Cellular Automaton (Credit to Cui Wanyi)

The Bee Collecting Algorithm is used for simulating the process of the bee colony collecting honey in nature, showing the superior organization and swarm intelligence of the bee colony in exploring the surroundings and occupying resources. The algorithm of the model is different from the Ant Colony Algorithm in the contents and methods of communication. The simulation is completed with a large amount of spatial information data about bees and flowers, and based on these data can generate different kinds of forms (Figs. 7 and 8).

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Fig. 7. Simulation of bee collecting honey in flowers

Fig. 8. Possible forms generated using Bee Collecting Algorithm

Generally composed of lines and points, the graph is used to show complex networks and analyse the relations of the complex networks. It is a structure that represents the relationship between elements within a collection, widely used in Parametric Design and used to build polyhedrons or more complex spatial networks. There are various kinds of graphs corresponding to different network relations (Fig. 9). Based on the graph, the shortest path between the two nodes of the grid can be solved quickly in Mathematica, as well as the shortest tour for several points (Figs. 10 and 11).

Fig. 9. Kinds of Graphs Generated from the Fig. 10. The shortest path (the red one) data in Mathematica between the two nodes of the grid using graph

Fig. 11. The shortest tour for several points comparing to the Brain coral (The photo on the right extracted from: http://www.messersmith.name/wordpress/tag/acropora/)

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Strange Attractor is a core concept in Chaotic Dynamics Theories. It is sensitive to the initial states with different orbital shapes (Lorenz 1997; Boeing 2016; Hasselblatt et al. 2009), and based on these shapes a series of forms can be generated. According to the function formula, 3D curve shapes can be generated in Mathematica or Chaoscope (Fig. 12). Taking the design project of “Chaotic” as an example, the principle of attractors is used for generating building forms (Fig. 13).

Fig. 12. 3D Orbital shapes of different types of Strange Attractors (Generated using the program named as A Collection of Chaotic Attractors, written by Enrique Zeleny, http://demonstrations. wolfram.com/ACollectionOfChaoticAttractors/)

Fig. 13. forms generated on the basis of different strange attractor orbits (Credit to Du Guangyu, Wang Jiayi)

The Shortest Path Algorithm builds a model of optimization theories, with the goal of finding the shortest solution among multiple paths, such as Ant Colony Model. In the primitive Ant Colony Model, most ants will consciously select the shortest path influenced by pheromone after a period of time, completing the self-organizing process (Fig. 14) (Waldner 2008). Forms can be generated by utilizing and developing the Ant Colony Model. By simulating the attraction of food to ants to generate paths as a basic form in both 2D plane and 3D space, clustered tubular channels are generated (Fig. 15).

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Fig. 14. Diagram for the primitive ant colony model (https://en.wikipedia.org/ wiki/File:Artificial_ants.jpg)

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Fig. 15. Forms generated from the paths of ants (Credit to Wang Jingsong, Sun Pengcheng)

6 Conclusions and Future Works Diverse theories and algorithms in Complexity Science can be used for architectural form generation along with the use of computer tools. They not only serve as the inspiration for designers, but also provide methods for solving complex problems facing the increased complexity in architecture. The theories, such as SelfOrganization, Emergence, Swarm Intelligence, Complex Network Theory, Chaotic Dynamic Theory and Optimization Theory, and the algorithms such as Bird Flock, Cellular Automaton, Bee Collecting Algorithm, Graph, Strange Attractor and Shortest Path, are the possible applications as discussed in the paper. In the future, it is no doubt that the architecture will become more and more complex while serving multiple and delicate functions and requirements. The theories and algorithms in Complexity Science can not only be used for generating forms, but also other aspects and stages of design, such as the simulation for built environment, the accuracy control of construction, and so on. Acknowledgement. Some design cases mentioned in this paper is derived from the design studios that are tutored by Professor Xu Weiguo at School of Architecture, Tsinghua University. These cases are the Hufang Bridge Urban Complex Design Project by Cui Wanyi, the Chaotic Design Project by Du Guangyu and Wang Jiayi, and the project mentioned in Shortest Path by Wang Jingsong and Sun Pengcheng. This research is supported by National Natural Science Fund of China (NO. 51538006).

References Ashby, W.R.: Principles of the self-organizing dynamic system. J. Gen. Psychol. 37(2), 125–128 (1947) Auyang, S.Y., et al.: Foundations of Complex System Theories (In Chinese). Shanghai Science and Technology Education Press, Shanghai (2002) Balmond, C., Smith, J., Brensing, C.: Informal. Prestel, Munich, New York (2002) Beni, G.: Swarm intelligence. In: Meyers, R.A. (Ed.), Computational Complexity: Theory, Techniques, and Applications. Springer, New York, pp. 3150–3169 (2012)

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Boeing, G.: Visual analysis of nonlinear dynamical systems: chaos, fractals, self-similarity and the limits of prediction. Systems 4(37), 1–18 (2016) Hasselblatt, B., Katok, A.: Translated by Yujun, Z. et al. Introduction to Power System Tutorials and Recent Developments (In Chinese). Science Press, Beijing (2009) Danforth, C.M.: Chaos in an Atmosphere Hanging on a Wall. Mathematics of Planet Earth (2019). http://mpe.dimacs.rutgers.edu/2013/03/17/chaos-in-an-atmosphere-hanging-on-a-wall/. Accessed 2 Feb 2019 Reynolds, C.W.: Flocks, herds, and schools: a distributed behaviorial model. Comput. Graphics 21(4), 25–34 (1987) Watts, D.J., Steven, H.: Strogatz. Collective Dynamics of ‘small-world’ networks. Nature 393 (6684), 440–442 (1998) Vintiadis, E.: Emergence. Internet Encyclopedia of Philosophy (2018). https://www.iep.utm.edu/ emergenc/. Accessed 19 Oct 2018 Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press (1999) Gardner, M.: Mathematical games: the fantastic combinations of john Conway’s new solitaire game “life”. Sci. Am. 223, 120–123 (1970) Lei, G.: Complex Network (In Chinese). Shanghai Science and Technology Education Press (2006) Witzany, G.: Biological self-organization. Int. J. Signs Semiot. Syst. 3(2), 1–11 (2014) Huang, X.: Complexity Science and Philosophy (In Chinese). Central Compilation & Translation Press, Beijing (2006) Johnson, S.: Emergence: the connected lives of ants, brains, cities, and software. Simon Schuster (2002) Leach, N.: Swarm urbanism. Architect. Design 79(4), 56–63 (2009) Lorenz. Translated by Liu Shida. (1997) The Nature of Chaos (In Chinese). Meteorological Press Weidong, Ma.: Cecil Balmond (In Chinese). China Electric Power Press, Beijing (2008) Oosterhuis, K.: Simply complex, toward a new kind of building. Front. Archit. Res. 1(4), 411– 420 (2012) Oosterhuis, K.: Programmable architecture. Roma: l’Arca Edizioni (2002) Oosterhuis, K.: A new kind of building. In: Disappearing Architecture, 90–115 (2005) Reiser + Umemoto: Atlas of Novel Tectonics. New York: Princeton Architectural Press (2006) Venturi, R.: Complexity and Contradiction in Architecture. The Museum of Modern Art Press, New York (1966) von Neumann, J.: The general and logical theory of automata// von Neumann. J. Collect. Works 5, 288 (1963) von Neumann, J.: Theory of Self-Reproducing Automata. University of Illinois Press, Urbana (1966) Waldner, J.-B.: Nanocomputers and Swarm Intelligence. ISTE John Wiley & Sons, London (2008) Weaver, W.: Science and complexity. Am. Sci. 36(4), 536–544 (1948) Wolfram, S.: Statistical mechanics of cellular automata. Rev. Modern Phys. 55(3), 601–644 (1983) Jinpei, W., Xuewei, L.: Introduction to System Science Development (In Chinese). Tsinghua University Press, Beijing (2010) Tong, W.: Research on Self-Organization Methodology (In Chinese). Tsinghua University Press, Beijing (2001) Tong, W.: Research on the Concept of Complexity and Its Significance (In Chinese). J. Renmin Univ. China 5, 2–9 (2004)

The Age of Intelligence: Urban Design Thinking, Method Turning and Exploration Xi Peng1, Pengkun Liu2, and Yunfeng Jin1(&) 1

2

College of Architecture and Urban Planning, Tongji University, Shanghai, China [email protected], [email protected] School of Civil Engineering, Chongqing University, Chongqing, China [email protected]

Abstract. This paper puts forward some reflections on the great change of thoughts and mythologies in urban design by technological breakthrough an presents the application of artificial intelligence in urban design. Firstly, it reviews and rethinks on the traditional philosophical bases and original thinking paradigms in urban design, facing up to the limitations and problems of existing design methods. Then by using philosophy of new materialism, new technologies such as machine learning and new data represented by multi-source urban data those having emerged in recent years in order to clarify the possibility of new technologies for urban analysis and design simulation. In particular, convolution neural network has been used to make a large-scale and fine discriminant on the style of urban texture and land use classification. Finally, based on discussions, the paper further clarifies the main direction of current research, which is the possibility of artificial intelligence intervening in urban complex systems and new technologies for urban analysis, designs and simulations. The authors believe that these explorations not only provide more accurate and intuitive analysis in research methods, but also provide the possibility to innovate existing design thoughts and methods by applying artificial intelligence technology to serve urban design research. Keywords: Urban design method
Artificial intelligence
Mode of thinking
Urban fabric
Urban vitality
Convolutional neural networks

1 Introduction: Urban Environment in the Age of Intelligence 1.1

Technological Changes

In the second decade of the 21st century, highly accelerated computing and information processing capabilities made it possible to implement machine learning and pattern recognition algorithms that were previously unimaginable [1]. At the same time, the arrival of the intelligent age has also made urban design research unprecedented impact [2]. On the one hand, these shocks challenge traditional urban design thinking and

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methods; on the other hand, the advancement of technology, the transformation of the overall attitude towards computer science, the emergence of big data and data analysis have also promoted the development of artificial intelligence-assisted urban design methods. 1.2

Accelerated Urbanization Process

The Population Division of the United Nations Department of Economic and Social Affairs, in its revised “World Urbanization Prospects: The 2018 Revision”, pointed out that, on a global scale, the current urban areas have more people than rural areas. In 2018, 55.3% of the world’s population live in urban areas. It is estimated that by 2030, urban populations will account for 60.4% of the global population. What’s more, it will reach 68.4% by 2050. At the same time, urban environmental construction is also facing a new situation from “speed priority” to “quality pursuit”. In this unprecedented process of urbanization, in view of the sustainable development problems of society, economy and ecology in cities, technological drive of innovation is the key to urban sustainable development. Proper urban planning management and successful urban design can help maximize the benefits of agglomeration while minimizing environmental degradation and other potential adverse effects of the growing urban population. Therefore, the traditional urban design urgently needs to realize the needs of the new era under the new historical conditions.

2 Traditional Philosophical Bases and Thinking ParadigmReflections on the Original Urban Design Methods The term Urban Design appeared in North America in the late 1950s. It focuses on the inner and transcendental aesthetics, focusing on the space enclosed by the building entity and its adjacent buildings, and its field of work is usually considered to be between planning and architecture [5]. As a supplement to urban planning, it is a crossintegration and linkage infiltration of multiple elements, plots and systems based on urban planning. It is an integrated system design that can better deal with the relationship between urban population growth and the three closely related dimensions of economy, society and environment in sustainable development. In previous studies, Geoffrey Broadbent classified the philosophical bases of most urban design theories into two categories: Empiricism and Rationalism. At the same time, he pointed out the wide influence of Pragmatism philosophy on urban design [6]. The author believes that Empiricism, Rationalism and Pragmatism represent the main schools of urban design theory philosophy, which covers the main contents of contemporary urban design theory philosophy from three aspects: the cognitive system, the value system and the method system of urban design. Furthermore, under the influence of these three mainstream philosophical schools, the Formalist design method, the Functionalist Stance design method, the Systemic Stance design method and the Humanist Stance design method have been developed respectively. Its design thinking, concrete manifestation specific performance and deficiencies are shown in the Table 1.

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Table 1. Traditional philosophical thinking and typical urban design methods Traditional urban design philosophical bases Empiricism

Rationalism

Pragmatism

Philosophizing

Urban design method

Specific performance

Inadequacies

Through perceptual and intuitive feelings, it summarizes the past and existing empirical facts, laws and characteristics of urban physical environment [7] Based on rational judgment or subjective analysis, reasoning and evaluation of future cities [9], it advocates logical judgment and recognition of the objective world Research is closely related to people’s life, so that the philosophy of life, to improve and enrich people’s life service [10]

Formalism

Emphasize the absolute dominance of spatial form and visual aesthetics [8]

Neglecting social, cultural, economic, technological and practical needs

The functionalist stance

Use functional partitions to rationalize the design city

The sense of encirclement is seriously lacking, and the urban space lacks a center

The humanist stance

The shaping of the senses of various elements, including social factors

Ignore the largescale problems of the city and the overall needs

In summary, under the traditional urban design philosophy methodology, urban design methods are often carried out in the single logical context of prioritizing visual aesthetics, functional layout, transportation system, and public demand, etc. However, this design method is directly effective in the traditional society with less prominent urban population size and slower urban rhythm. However, facing the rapid global urbanization process in the new era, it is difficult to meet people’s diverse changing needs and complex urban environment requirements.

3 The Emergence of New Technologies and New Data—Exploration of New Urban Design Methods 3.1

New Materialism Philosophy and Urban Design

In “Theses On Feuerbach”, Marx created a new materialistic worldview which is different from old materialism. He pointed out that all relevant philosophical issues, such as “things, reality, sensibility”, must be understood as the activities of perceptual

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people and scientific practices, because the standpoint of new materialism is the social nature of human beings. The former philosophers only explained the world in different ways, and the problem was to change the world [11]. In terms of material concepts, Manuel De Landa proposed the philosophical thought of new materialism in the 1990s based on a long-term study of Gilles Deleuze’s philosophy. Different from traditional materialist philosophy, the material form of the objective world is the eternal real existence. The new materialism believes that the emergence of the material form is influenced by the inherent invisible rules, and it is an evolutionary process of continuous iteration. This kind of logic of Delanda Expresses the potential “intelligence” within the substance [12]. In urban design studies, Nigel Taylor foresees that “all these changes mean that if planners try to control and guide complex urban systems, the technical methods of urban planning will change. This seems to require a particularly rigorous scientific analysis method [13]. Compared with the traditional urban design philosophy methodology, the new materialist philosophy reveals that in the process of changing the world, it emphasizes that the material elements themselves have some kind of virtual intelligence, which transforms the inherent “virtual” characteristics of urban elements into “real” intelligent generation (Table 2). Table 2. Comparison between traditional philosophical thinking of urban design and new materialist philosophy Philosophy thinking city environment

Traditional

New materialism

The pace of life is slow, the urban population is small, and the problem of people and land is not prominent

Logical context Material view Methodology

Single, isolated, stereotyped

The characteristics of urbanization are remarkable, the relationship between man and land is complex, and the natural environment is deteriorating Complex, diverse, abundant

Explain the world

Change the world

Solving urban problems in isolation from a single context

Iterative generation process with inherent intelligence

3.2

The Shift of Thinking Mode of Urban Design Research

If we think deeply about the original design method, and agree that design is not only about the binary relationship between function and form, but more about the “Milieu” [14]. It is to deal with the structure erection, system design and the form expression based on its complex background, even the expression is no longer “Hard-coding” which is difficult to adapt to the changes of end-to-end, so the traditional design methods, design approaches and design tools can no longer meet these needs [15]. From the methodological point of view, urban design has always been to solve the urban space environment problem as its own responsibility. As a discipline emphasizing the application of technology, along with the discipline transformation brought

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by digital technology, its development cannot be separated from the close connection with other related fields [16]. Furthermore, the task of urban designers is to visualize the material world and its ever-changing “ virtuality” through some specific tools and media, and to explore the possibility of different urban design schemes. In this process, Antoine Picon’s so-called new materiality came into being. He believed that materiality was not unchanged, but depended on our relationship with the matter, and on our scientific, technological and belief systems. Materiality in the perspective of New Materialism Philosophy is that “materials, objects and phenomena become real participants, not passive elements manipulated arbitrarily” [17]. Therefore, as a practical process of integrating various contradictions in the three-dimensional urban spatial coordinate system, the research thinking of urban design should be to establish on a basis of a new materiality. 3.3

Method “Intelligent” Driven Urban Design- the Style Discrimination of Urban Texture

The innovation-driven intelligent urban design method becomes possible with the change of thinking mode of urban design research and the rise of new data and technological environment. This paper attempts to explore the application of deep learning tools in the large-scale and refined style discrimination research of urban texture, so as to provide data basis for urban spatial structure design and planning. The Experimental Principle. Urban texture means some kind of structured material environment, involving building type, street form, block pattern, open space, regional interface and other contents [18], which contains complex and profound social and economic relations. In previous studies, many urban studies have conducted in-depth studies on urban road network, trying to analyze the characteristics of urban texture from the perspectives of road grid spacing, street accessibility or building density, building form, volume ratio and building facade. However, this kind of research either comes from a simple summary of several cases, or from the basic knowledge of traffic layout. The research scope is relatively macro, but the operation method is relatively rigid. With the advent of the era of intelligence, Deep Learning, as a branch of machine Learning, attempts to use complex structure or multiple processing layers composed of multiple nonlinear transformations to abstract the high-level algorithm of data [19]. In other words, machines can bypass the classification management steps and rely on the “neural network” modeled after the form of human brain to carry out self-learning for a specific subject and continuously absorb and produce massive new data [20]. Data analysis technology represented by deep learning has become a tool for urban design research, among which convolutional neural network (CNN) is widely used in the field of image discrimination nowadays (Fig. 1) Therefore, it is the direction of this experiment to establish a reasonable correlation structure between urban texture and urban land use classification, and to find out the order principle between urban texture and urban land use by means of style discrimination and model algorithm, which can be understood and mastered.

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Fig. 1. Application of convolutional neural network to urban texture structure

The Experiment Design. This experiment is based on seven specific elements (park, high density area, medium density area, low density area, public buildings, transportation, old city) which can reflect the land use classification of cities and the regional cultural environment characteristics created by human activities in the plane layout as the discriminant types of urban texture. The convolutional neural network (CNN) is used to quickly distinguish the texture from the large-scale urban satellite map. Seven types of land use and the proportion of different regions are calculated. The training data of the experiment are all from two-dimensional satellite images of Baidu (processed by color). The satellite images of ten cities in Beijing, Guangzhou, Jilin, Jinhua, Linyi, Luoyang, Shanghai, Shenzhen, Taizhou and Xi’an were sliced into 1 km *1 km images, totaling 5458 images. Seven kinds of urban texture were classified as the data set for evaluation and classification (Fig. 2). [Computer configuration: processor Core I7 7700 k, graphics card NVIDA GTX1070, memory 32.0 GB].

Fig. 2. Seven specific element evaluation classification data sets

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The input layer of convolution neural network can process multi-dimensional data. Generally, the input layer of one-dimensional convolution neural network receives onedimensional or two-dimensional arrays, in which one-dimensional arrays are usually time or spectrum sampling; two-dimensional arrays may contain multiple channels; the input layer of two-dimensional convolution neural network receives two-dimensional or threedimensional arrays; and the input layer of three-dimensional convolution neural network receives four-dimensional arrays. The hidden layer of convolution neural network includes convolution layer, pooling layer and full connection layer. In convolution neural network (CNN), the data set is first read through the input layer and entered into the first convolution layer. The nature of convolution preserves the relationship between the pixels in the original image. The convolution layer extracts the features of urban texture data at different scales through convolution kernels of different sizes. With convolution kernels of different sizes, it achieves a variety of operations on the image, such as edge detection, dimension enhancement, dimension reduction and non-linear transformation. In order to recognize texture images from different sizes, after many convolutions and pooling operations, the data reaches the final full connection layer. Taking traffic texture as an example, as shown in Fig. 3, the first layer feature extraction of convolution neural network is the overall contour information of the image, and the second layer and the third layer extract the local feature information of the image layer by layer.

Fig. 3. Visualization of convolution layer for feature extraction of urban texture in convolution neural network (taking traffic as an example)

The Experimental Results. The upstream of the output layer in the convolutional neural network is usually a fully connected layer, so its structure and working principle are the same as those in the traditional feedforward neural network. For image classification problems, the output layer outputs a classification label using a logic function or a softmax function and maps it to a three-dimensional space. As shown in Fig. 4, it can be seen that in threedimensional space, the convolutional neural network can clearly and subtly recognize seven urban textures. After the completion of the Convolutional Neural Network (CNN) training, some satellite images of Huangpu District of Shanghai were used as test cases. Some of the results are shown in Fig. 5. Firstly, some satellite images of Huangpu District are sliced according to the size of the training set of 1 km×1 km, and the image data of the slice is used as the test data of the convolutional neural network for urban texture discrimination, and the urban texture corresponding to each image data can be output. Use one-

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hot encoding, such as [1,0,0,0,0,0,0] to indicate the first classification high-density area, [0,1,0,0,0,0,0] The second classification is the medium density zone. Finally, according to the classification structure, the proportion of all kinds of urban texture in this area was calculated, and the slice image data was merged into the original satellite image, and the discrimination result was visualized.

Fig. 4. Three-dimensional map of data distribution of image discrimination model of seven urban textures

Experimental results show that the discriminant results of convolutional neural network are consistent with the actual urban texture zoning. Convolutional neural network can be used to realize the large-scale and re-fined discrimination of urban texture. In other words, this method relies on in-depth quantitative analysis and data calculation to study the urban spatial form, which provides technical support for the urban design transformation from the new city development to the old city renewal.

Fig. 5. Classification results of urban texture discriminant model in Shanghai

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4 Conclusion and Prospect Nowadays, urbanization in the world has entered a critical stage of development. Promoting the ability of independent innovation is the most critical factor to promote urbanization from a quantity-oriented “physical” to a quality-oriented and innovationdriven “intellectual”. Today, China’s urbanization is facing a historic moment: which region can be transformed from “physical urbanization” to “intellectual urbanization” which is quality-oriented and innovation-driven in the second stage, and which region will become an innovative region [21]. Emerging network media and social tools make every individual produce a large amount of data accumulation and use imprint every moment. Data utilization is increasingly closely related to all aspects of social life. People can rely more on data and statistical means to discover the underlying logic behind things, rather than just interpreting reality based on past experience and prior assumptions. Urban researchers can combine new tools, methods and data in the field of computer and statistics to expand new ideas on complex scientific issues in urban design, so as to deliberate and find more effective urban design methods to adapt to the development trend of the new era. Obviously, new data and new technology environment are stimulating the transformation of urban design thinking and methods in urban research.

References 1. Schmmitt, G., Shuchen, X., Miao Y., et al.: The second chance for artificial intelligence in architecture and urban design. Time Archit. (2018) 2. Pan, Y.: Heading toward artificial intelligence 2.0. Engineering (2), 409–413 (2016) 3. World Urbanization Prospects: The 2018 Revision—Annual Percentage of Population at Mid-Year Residing in Urban Areas by Region, Subregion, Country and Area, 1950–2050. United Nations, Department of Economic and Social Affairs 4. Jiwei, Lu: Development trend of urban design in the new period. Shanghai Urban Plann. 01, 3–4 (2015) 5. Carmona, M., Heath, T., Tiesdell, S., Taner, O.C.: Dimensions of urban design: public places - urban space. Translated by Jiang, F., Yue, Y., Qian, W., etc. Jiangsu Science & Technology Press (2005) 6. Broadbent, Geoffrey: Emerging Concept in Urban Space Design. E&FN Spon, London (1990) 7. Shengjun, L.: Interpretation of Urban Design. Harbin University of Technology (2008) 8. Yan, T.: Urban design under the influence of “Pragmatism” philosophy. China Urban Planning Society. Harmony City Planning - Proceedings of the 2007 China Urban Planning Annual Conference. China Urban Planning Society (2007) 4 9. Lang, J.: Urban Design: The American Experience. Van Nostrand Reinhold, New York (1994) 10. Na, Liu, Wei, Wang: American pragmatism philosophy and community college. J. Shijiazhuang Univ. Econ. 06, 141–144 (2007) 11. Selected Works of Marx and Engels: Volume 1. People’s Publishing House, Beijing, p. 54 (1995)

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12. Yuan, P.F., Chai H.: Digital twin on visualization and materialization of 2017 “Digital Future” in Shanghai. Times Archit. (01), 17–23 (2018) 13. Taylor, N.: The Evolution of Western Urban Planning Theory after 1945. Baiyu, L., Yu, C. translation. Beijing: China Building Industry Press (2006) 14. Foucault, M.: Security, Territory and Population: Lecture Series, 1977–1978. Han, Q., Chen Xiaojing Translated. Shanghai People’s Publishing House, Shanghai (2010) 15. Wanyu, He, Xiaodi, Yang: Artificial intelligence design, from research to practice. Times Archit. 01, 38–43 (2018) 16. Yunfeng, J., Yi, D.: A study of landscape archetype design method—the landscape architecture approach for urban design. Chinese Garden 33(06), 48–52 (2017) 17. Antoine, P.K.: Architectural illustration. From abstraction to materiality. Zhou Minghao translation. Times Archi. (5), 14–21 (2016) 18. Wikipedia Dictionary. http://en.wiktionary.org/wiki/urban_fabric 19. Deng, L., Yu, D.: Deep learning: methods and application. Found. Trends in Signal Process. 7, 3–4 (2014) 20. Lynch, N.: The design of artificial intelligence age. Landscape Design, 4 (2012) 21. Zhiqiang, W.: On the new age urban planning and its ecological rational core. J. Urban Plann., 3 (2018)

Robotic Intelligence

Designing an Architectural Robot: An Actuated Active Transforming Structure Using Face Detection Ji Shi1, Yujie Wang2(&), and Shang Liu3 1

2

PILLS, Chaoyang, Beijing 100018, China [email protected] Massachusetts Institute of Technology, Cambridge, MA 02139, USA [email protected] 3 Carnegie Mellon University, Pittsburgh, PA 15213, USA [email protected]

Abstract. Although the advances of autonomous control in robotics broke new ground in the realization of architecture, they have hardly been integrated with architectural design intention. Very few examples of architecture-specific robot exist. This results from multiple realistic factors including the scalability and cost. However, the fundamental incentive lies in the stereotypical design ideology that fails to develop new spatial agendas to stimulate the integration. This paper presents a design workflow that revolves around designing an architectural robot. An operational full-scale architectural robot of an actuated active transforming structure was prototyped and tested to demonstrate the workflow. The design is based on a prototyping model with pneumatic actuation system and sensing using computer vision. The structure interacts with human by detecting face features and actively transforming its gesture to prevent human from approaching. The communication is based on a simulation-model-free host program that constantly reads sensor feedbacks and sends actuation values. Keywords: Architectural robot
Human-computer interaction
McKibben pneumatic artificial muscle
Face detection
Design and cultures

1 Introduction With the infiltration of digital technology into nearly all aspects of our life, we are now living with increasingly autonomous objects that are hybrids of digital and physical. However, architecture, as the most frequently used “object” we encounter in everyday life, is still understood as purely physical and non-computational construct. In fact, the contemporary architectural practice has developed a complex workflow that waves digital and physical. The architectural process has been divided into multiple standardized and specialized stages. Digital technology and autonomous features are

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introduced into each stage ranging from generative design of geometry to specialized fabrication technique. The reason people stereotypically consider architecture as noncomputational construct is that neither human design intention nor design outcome is included in any computational or autonomous processes. The advances of autonomous control are still confined in the realization of architecture. Thus, designers often encounter difficulties working with computation since the original intents are not initiated within such context. Likewise, the users may also have trouble interpreting the computational aspects after their inhabitation since most of them are only shown in the creation process not after the completion. Thus, it is productive to extend the meaning of computational design toward both ends simultaneously. It’s critical for designers not to isolate their design intentions from computational processes in realization, rather they should be constructed in one holistic setup that combines the creation, realization and the inhabitation of architecture. This calls for a new design model in which the conventional interaction between human and architecture should be rethought. This new model asks the fundamental question that how autonomous features can benefit architectural design intention and to what extent do the autonomous features last in the whole process.

Fig. 1. A. Multiple humans interacting with the architectural robot simultaneously. Interaction scenarios processed by a host program and presented to the public; B. Architectural robot constantly “observing” human using face detection method while the human looking at the robot; C. Module of the architectural robot in design prototyping iterations. D. Holistic setup of thearchitectural robot. The system combines actuation,sensing and programming in an integral installation.

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2 Related Work The development of human autonomous process in architecture has focused primarily on object-scale robots or machines. The practice within this thread has a conceptual link with design of interactive installations. Two inspiring precedents are the Table by Max Dean and Raffaello D’Andrea in 20011 and the Robotic Chair by Max Dean, Raffaello D’Andrea and Matt Donovan in 20062. These two art installations were modeled on the basis of generic furniture pieces, but they were designed with robotic hardware and program which allowed them to interact with human. The installations were designed for gallery performance and collection, however it presented strong architectural relevance by introducing autonomous process into daily living scenarios in the confinements of a room. Within the field of architecture, the research of object-scale robot also strongly connected with the concept of assembly. Smaller objects are designed as modules for a larger system, i.e. buildings in most cases, and have the physical and programmable capability of being assembled. Typical precedents can be found in research projects of Theodore Spyropoulos and his teaching at AADRL. Project Hexy by Yuan Yao, Yuhan Li and Yang Hong in 20173 developed a transformable hexagonal robot that autonomously assembled into reconfigurable room layouts. Similar studies around collective behavior and self-assembly have also been done in the field of biologically inspired engineering, for example, the Termite-inspired Robot Construction Team [1] and the Thousand-bot Swarm [2]. Another thread focuses on applying the autonomous concept directly to a full-scale architectural setup. The precedents include the Actuated Bending Tower Project (also known as the Bow-tower Project) which developed a simulation-model-free approach for combining the abstract computational and material artifact as a method for exploration in the design process [3], and the Flexing Room Project which developed a room size architecture prototype that communicates to its human inhabitants [4]. This paper is largely inspired by the research within this thread.

3 Architectural Robot with Lifelong Autonomous Agenda The motivation of this research is to rethink architecture as architectural robot which contains certain extent of autonomy that expands the concept of material computation into the realm of embodied computation [5]. The meaning of embodiment refers to a

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Raffaello D’Andrea and Max Dean, Table. Accessed: 14 January, 2019. https://raffaello.name/ projects/table/. Raffaello D’Andrea, Max Dean and Matt Donovan, Robotic Chair. Accessed: 14 January, 2019. https://raffaello.name/projects/robotic-chair/. Yuan Yao, Yang Hong, and Yuhan Li. Hexy_AADRL Research Book 2016-2017. Accessed: 14 January, 2019. https://issuu.com/yuanyao2014/docs/finalupload_small/.

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holistic understanding of architecture as computational spatial construct. Architectural robots should not be understood as machines or technical procedures used in isolated stages in architectural realization, rather it is a robust mechanism that intrigues the complex process of design, realization and inhabitation in the lifelong development of an autonomous agenda. The current practice has developed divergent interpretations toward the meaning of architectural robot. What this paper presents should not be confused with following perspectives. Firstly, the concept doesn’t refer to what is known as Smart Room. Architectural robot is nothing like a room drowned in all kinds of autonomous appliances and objects. Architectural robot uses interactions generated directly from its spatial setup instead of the appliances or objects it contains. Humans live with the architectural robot not only within it. Also, architectural robot isn’t merely automated process. The automated processes are all defined within the realm of the creation of architecture. However, the intervention of designer should not come to a stop at the completion of creation since the stages after are also important. In addition, architectural robot isn’t about designing anthropomorphic robots. Human has a long obsession with anthropomorphic robots. Architectural practice has also developed projects that encompassed the design of human-like robots, for example, the Robot DEKU and DEME [6] by Japanese architect Arata Isozaki for 70’ Expo at Osaka. The autonomous agenda doesn’t necessarily lead to a formal imitation, rather it addresses the autonomous interactions. The central task is to define an architecture-specific interpretation of “autonomous agenda” in contemporary digital culture and apply it to architectural processes in practice. The types of exchange between human and architecture is different from the established paradigm of human-machine interaction presented in object-scale computer devices [4]. The key of architectural robot is to combine these previously established features with architectural qualities. Architecture robot must be inhabitable which by nature brings more interaction scenarios to the system. From the perspective of designer, it’s critical to establish a new design method that organizes all design parameters within this setting. The parameters should not be limited in the material realm, rather it should be extended to prototyping systems through a combination of sensing, actuation and feedback programming. Architecture robotics is largely based on such prototyping model (Fig. 1).

4 Method: Design Through Prototyping Systems The method of designing architectural robot includes an autonomous-agenda-centric design workflow in which designers start simultaneously from prototyping, sensing and actuation (Fig. 2). Agenda is critical in this method and indicates the fundamental meanings of the design. However, it is not only the start point of a linear process, rather it unifies the design intents from all aspects and exists in the entire cycle. Prototyping. Prototyping approaches the agenda through making 1:1 prototype. Prototyping allows the designer to understand the design intention through physical impressions. Prototyping requires 1:1 models not scaled models, and it contains continuous iterations of hands-on experiment. This is also different from what is known as

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mock up. Prototyping requires a functional construct as a whole instead of a selected study fragment. Prototyping is critical in the proposed workflow. It informs the designer of the potential parameters in sensing and proper mechanism in actuation. Sensing. Sensing approaches the agenda by reading specific parameters and writing it into a feedback loop. The concept of sensing and feedback is borrowed from the field of automated control systems. The parameters to be sensed may come from the designer’s initial intents, the human interactions after the inhabitation, the environmental factors of the design, etc. Specific sensing instruments or devices need to be studied and this requires designer to implement research in areas which were not conventionally considered within the field of architecture. Actuation. Actuation approaches the agenda by constructing schemes. Actuation should not be simplified as a series of mechanical motions, rather it stands for iterations of design schemes in the agenda. Actuation is the material realm of the agenda and is the front end of the spatial construct which is developed by multiple iterations of prototyping and sensing.

Fig. 2. Stereotypical design workflow (top) vs. Proposed autonomous-agenda-centric design workflow (bottom).

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5 Case Study: An Actuated Active Transforming Structure The proposed workflow was tested in a design workshop4 the author instructed in Tsinghua University in 2017. The objective of the workshop is to familiarize students with the concept of architectural robot and the autonomous-agenda-centric workflow. Students were required to participate in multiple hands-on sessions of prototyping, sensing and actuation. One project is presented in this paper showcasing the design methodology (Fig. 3). The students designed an autonomous gallery installation for displaying artworks. The installation autonomously responds to surrounding environment and incoming visitors by constantly changing its geometry. On the one hand, the project itself was well developed following the proposed workflow and the students showed a thorough understanding of the notion of autonomous agenda in architecture; On the other hand, the selected topic, i.e. temporary gallery installation, is a good vehicle for the test run – the students, with architectural training, are experienced in making 1:1 prototype of objects in such scale and are skilled in comprehending and developing autonomous agenda for such topic. Here, the steps within the development of the project are presented in the sequence of agenda, prototyping, actuation and interaction, however in reality the developments in those aspects happened simultaneously and the parameters in each aspect affected each other. Additionally, the paper focuses on showcasing the overall workflow and how it could potentially benefit the field of architecture design. Thus, the technical procedures and setups are presented but the raw data and measurement might be partially omitted in the following discussion. 5.1

Autonomous Agenda

Visitor circulation in conventional galleries follows the curatorial arrangement of the artworks. Thus, the location of specific artwork may influence the distribution of the crowd, for example, the spot of Mona Lisa being presented in Louvre Museum always forms a tremendous gathering of people. It’s interesting that in this model architecture itself, though contains the human crowd, has no authorities in deciding how to distribute them. The project presented below questioned this stereotypical setup by proposing a new gallery installation for displaying artworks that constantly observes the crowd and responds to them through a series of geometrical transformation. This project showed a promising agenda. The transformability and reconfigurability is not exclusively based on designers’ intents, however it is generated from an autonomous program. Also, the project questioned conventional architectural concept, specifically, the definition of a wall, from very fundamental level. Additionally, the

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Parametric Design Workshop, School of Architecture, Tsinghua University, Beijing, 2017. Instructor: Ji Shi, Zigeng Wang. Teaching Assistant: Dinglu Wang, Pengcheng Sun, Jingsong Wang. Student: Xiangfan Chen, Ziyao Geng, Yao Jiang, Zhan Zhang, Wen Si, Shang Liu, Yujie Wang. The workshop was organized by Prof. Weiguo Xu.

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Fig. 3. Experiment setup in axonometric view and workflow diagram.

notion that walls looking back at human is fascinating by proposing a counter intuitive metaphor which motivates human to rethink their everyday behavior and relationship with architecture.

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This project is based on case studies of multiple precedents among which the studio project by Francois Sabourin5 was found mostly inspiring. The proposal was initially inspired by similar concept and has developed unique, innovative and complex features during the workshop. 5.2

Modular Transformation

A cubic geometry of 1 m  1 m  1 m was physically modeled to represent the installation unit (Fig. 4). Here, the dimension is a reductive abstraction that represents a generic exhibit wall which isn’t associated with any artwork or venue. The dimension was chosen based on the operationality of the actuation system and the prototyping feasibility. In reality, the actual dimension may change depending on the site. The cube geometry was fabricated with wood frames and fabric. The vertical faces represent the surfaces on which artworks will be mounted and the horizontal face at bottom represents the base of the unit. The rest faces of the cube were omitted from this prototype for operational and representational reasons. The joining vertical edges and base corner connections are designed to be flexible. The assembly details were designed for a modular transformation in which the base can shear from a square to a rhombus which in 3D transforms the cube into a uniform rhombic prism. The geometrical transformation of the module represents the change of orientation of each artwork on that face, which directly changes the relationship between the human visitor and the artwork. This describes the fundamental interaction scenario. The system may also go more complex if more modules are involved and connected to each other. Here, the project included three modules connected to each other side by side as a research prototype.

Fig. 4. Modular transformation from a cube (left) to a uniform rhombic prism (right).

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Actuation System: Pneumatic Artificial Muscle and Bow Connection

To realize such transformation, the system requires a contraction force that pushes the two opposite corners at the base toward each other; meanwhile, it also requires a corresponding spring action which pushes back and reset the system to its initial state. 5

Project for Studio ARC505B Architectural Robotics – Embodied Computation, Fall 2016 taught by Prof. Axel Kilian and Ji Shi, Princeton University.

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The actuation system developed for this project is inspired by the Bowtower experiment [3] and the Flexing Room Architectural Robot [4]. The contraction forced was realized by McKibben Pneumatic Artificial Muscle (hereinafter referred to as “the PAM actuator”), and the spring counteraction that reset the system was provided by a bow connection made with prestressed 15 mm diameter nylon rod. At the base of each module, two opposite corners were connected by one PAM actuator while the other two corners were prestressed by two bow connections (Fig. 5). During actuating phase, the contraction of PAM dominates the transformation and pulls the two opposite corners moving toward each other. This shears the geometry from a cube into a rhombus cube. During releasing phase, the prestress in the bent nylon bow connection counteracts the transformation and the system springs back to its initial state. The combination of the PAM actuator and the bow connection collectively works for a robust actuation cycle.

Fig. 5. Module (indicated with red dashed line) with PAM actuator and bow connections. (1). PAM actuator; (2). Bow connections.

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Fabrication, Experiment and Measurement of the PAM Actuator

The key of this actuation cycle is to design and make a robust PAM actuator. The PAM actuator, firstly developed in the 1950’s [7], contains an elastomer inner tube surrounded by double-helix-braided sheath. When an internal pressure is generated inside the inner tube, the free tip of the artificial muscle contracts while the external sheath maintains its cylindrical shape. The circumferential stress of a pressurized inner tube is transformed into an axial contraction force by means of a double-helix braided sheath whose geometry corresponds to a network of identical pantographs [8]. The reason of selecting PAM actuator is primarily based on its flexibility in prototyping. The actuator can be assembled from ready-made and easy-to-get materials and accessories. The properties, i.e. length, diameter, actuation speed, etc., can be customized and iterated through a series of modification in material and code. Compared to other actuators, for example, linear actuator, the PAM actuator works better as a tool for design. The PAM actuator used in this project (Fig. 6) was fabricated in-

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house with a combination of bicycle inner tube, braided cable sleeve and customized hose fittings6.

Fig. 6. A. (left) Schematic illustration of custom-made PAM actuator; B. (right) Sectional illustration of design details: (1). Standard silicone tubing connecting to pneumatic circuit. (2). Standard barbed fitting. (3). CNC fabricated fitting for PAM actuator made from hard nylon round rod. (4). Worm-drive hose clamp bundling all layers into a sealed system. (5). Outside layer of PAM made with braided sheath. (6). Inside layer of the PAM made with elastomer tubing.

During the design exploration and experiments, the team tested with different dimensions of the PAM with different internal pressure. The contraction showed the consistency of reaching approximately 75% to 80% of the PAM’s initial length (Fig. 7). This result was not ideal in terms of producing dramatic geometrical change, but it is good enough for the selected module in this design project. In addition, the rapidity and firmness reached the anticipation, and the system performed robustly when the module continuously transforming in multiple cycles over time.

Fig. 7. Experiment results of the PAM actuator contraction showing a consistent maximum contraction of 80% of initial length. 6

Hardware details: Inner tube of the PAM actuator: KENDA bicycle inner tube 700*23/25 C 60L; Sheath of the PAM actuator: LEIXINTE Terminal 35 mm diameter PETE braided cable sleeve; Custom made PAM fittings at two end: CNC fabricated 35 mm diameter nylon rod.

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Pressure Control Unit (PCU)

The pneumatic setup (Fig. 8) for controlling PAM actuators contains a combination of standard pneumatic appliances and custom-made pressure control units (hereinafter referred to as “PCU”).

Fig. 8. Air logic diagram and pneumatic circuit schematics of the PCU (left); Operational diagram showing valve state in relation to system state using dual-valve setup (right).

A single stage air compressor (800 W, 60L/min, 220 V) with air tank and regulator gauge was used as the exclusive pressure source for all actuators. The air was then divided into 3 streams by standard manifolds and tee fittings. Each stream was channeled into a PCU in which the designer has full control of the timing and on/off states of the air stream. Lastly, the programmed air stream was directed to 3 PAMs performing desired features. The air compressor unit has its own feedback to maintain desired pressure at the output port. The PCU in each stream uses valves to control the volume of air being directed into the actuator. Each PCU is based on a pair of simple open-close solenoid valves (2-way/2-position valve, 2V025-08 G1/4 N.C. DC12 V). Design schemes involving dual valves are popular in similar research [3, 4, 9]. In the pneumatic circuit, two valves are connected in series and the actuator is connected in between the two valves. This dual-valve setup allows three control states, respectively inflating, holding and deflating. When inflating, Valve-1 is switched on while Valve-2 is off. The air is constantly directed into the actuator; When holding, both Valve-1 and Valve-2 is switched off. The air is being held in the actuator; When deflating, Valve-1 is switched off and Valve-2 is on. The air is released out of the system. The pressure inside the actuator is controlled by setting up timing and on/off state of the PCU, and a pressure sensor is connected in parallel with the actuator to monitor the internal pressure changes. An alternative solution is to use proportional valves to control the flow/speed. Appliance of such category can be found from more complex pneumatic control company such as FESTO. These solutions are normally expensive and not very much feasible for prototyping in a design studio project.

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Electronics and Integral Prototype of PCU

All 6 valves for 3 PAM actuators were controlled digitally. The power for the DC12 V solenoid valves came from AC220 V outlet and was adapted with a 12 V/10A (max) DC adaptor. All valves were connected in the form of an Arduino UNO board with high power control setup using transistors and diodes (Fig. 9). The prototyping of the electronics was based on standard breadboard and jump-wires (Fig. 10).

Fig. 9. Electronic circuit schematics using transistor to control high current load in solenoid valves with ASDX amplified board-mount pressure sensor.

Fig. 10. Integral prototype of the PCU showing a combination of pneumatic circuits and electronic circuits.

Three web-cams, anchored at the top of each module, was oriented to the front, i.e. perpendicular with the vertical face, representing the artwork in search of the incoming human visitors. The web-cams were connected to a PC laptop through USB cables. The live video footages were constantly downloaded and processed in a program in the

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software Processing. In the workflow, the Processing sketch works as a host program and constantly uploads signals to the Arduino. The Processing sketch captures human faces in each frame of the footage in real time. The face detection sketch in the program is based on the OpenCV library for Processing7. The communication between the Arduino UNO board and the Processing host program was done using the Arduino Firmata Library for Processing8. As a result, the control of vales was associated with the detection of faces, and all coordination were done in the master host program on Processing without any stand-alone code stored in the Arduino board. The workflow of controlling Arduino through Processing was proved to be a very effective method since the human designer can visually observe, control and iterate the design through the interface of a PC laptop. A user-friendly interface was developed for the Processing program with the intent of making the program not only a control firmware but also a visual demonstration for people to observe the system from a global perspective and understand the interactions better. 5.7

Interactions: Wandering and Teasing

The interaction is divided into two typical scenarios, respectively named Wandering and Teasing (Fig. 11). Wandering scenario will be triggered if no faces are detected by the web-cam. This represents the situation that no one is looking at the artwork. In this situation, wandering state will be activated and the module will perform random transformations within its two typical states (the cube and the uniform rhombic prism). In this phase, orientation of each vertical face constantly changes as if the artwork is in search of human visitors. Since the pressure of each PAM actuator is controllable, the Wandering transformation presents a random pattern with various gestures and speed which resembles the behavior of human wandering. Teasing scenario will be triggered when the program detects faces. This stands for the situation that someone is directly looking at the artwork. Under this circumstance, the module immediately dodges people by a fast orientation change of its physical state. Similar interactions will continue if the visitor tries to approach the artwork from an alternative direction. Thus, every time the human visitor tries to approach the artwork, they will be rejected by the system. This human-like behavior is understood as a metaphor that the installation teases human visitors by not letting them see the artwork. This interaction supports our initial argument that spatial construct works as active agent that bring new living scenarios. The interaction is also interesting since it provided counterintuitive perceptions. In most cases the autonomous objects are programmed to assist human in achieving specific goals. However, autonomous agenda should also include the opposite scenario in which human’s initial intents are obstructed.

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The face detection Processing sketch used in this case is based on Greg Borenstein’s OpenCV Computer vision library for processing. Greg Borenstein, Open CV. Accessed: 14 January, 2019. https://github.com/atduskgreg/opencv-processing. Jeff Hoefs. Firmata Firmware for Arduino. Accessed: 14 January, 2019. https://github.com/firmata/ arduino.

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Fig. 11. The architectural robot shifted between Wandering and Teasing states based on the result of face detection. The program was designed to challenge human’s established conviction of human-robot interaction scenarios.

5.8

Results and Future Work

The public test-run was held during the workshop final review and it was intriguing to see people being confused by the behavior of the system. It seemed that no one has assumed that the robot would disobey human’s intention. The project performed a robust actuation in which the digital control of PAMs and the physical prototype all showed desirable features. However, the experiment didn’t reach a more complex stage in terms of behavior and interaction. The limitations primarily stay in following areas. Firstly, the actuation of PAMs, though fast enough, may still fail to keep up with human’s movements. This is due to the delay in the actuation and reset process. The speed in actuation is directly related to the inflation of the PAM actuators. To speed up this process, more tests with the valves need to be done. In the experiment, pressure sensors were not yet successfully integrated into the PCUs and need more detailed research. The pressure was exclusively controlled by setting the timing and on/off states of the valves. Thus, the initial pressure of the air compressor cannot be set too high since upon doing so, the timing will become very short and hard to be precisely controlled. However, when pressure sensor is applied, the speed of inflation may potentially go higher without concerning the controllability and safety. The speed of the reset process is associated with the prestressed bow connections. In the experiment, we used nylon rod and prestressed it by bending it into an arc. A stiffer material can be applied to the same design schematics and may result in a faster reaction. Also, the programming was largely based on the single module. The prototype connected 3 modules together and the behavior of each module interfered with its neighbors. This is the primary area to be focused in future works. On the one hand, more experiments need to be implemented to study the collective behavior and more composition typologies need to be tested, for example, the modules can also be connected in a rectangle or hexagonal grid instead of linear connection as it is in current stage; On the other hand, the interactions programmed in the Processing sketch were based on a chart which contains all possible events. The program needs to be improved and future work includes developing a better sketch that runs the system in a more advanced autonomous manner. Additionally, the feasibility to larger sale or permanent structure remains unsolved. The system, as noted earlier in the paper, contains an external package of valves,

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electronics, PC laptop, etc. The prototype was designed primarily for pedagogical demonstration of the workflow not for a fully autonomously-operated permanent structure.

6 Discussion The development of this architectural robot and its design workflow should be considered as a long process than any single project or research can cover. The workflow requires a holistic understanding of the meaning of autonomous agenda within the field of architectural design which can only be developed through continuous tests and experiments. Thus, the result of this experiment is not an answer to specific question, rather it is the question itself. The experiment proposed a question to the field and aimed to potentially inspire peer designers, as well as design students and teachers. It’s critical for designers to establish a design thinking ideology which includes the participation of autonomous technology in the core area of the discipline. Autonomous features should no longer stay as mediated steps in the realization of a conventional architectural concept, rather they should bring novelty to the concept itself. Also, this paper calls for attention that designers should establish a robust workflow in which prototyping system is considered as the fundamental tooling when iterating the design. The digital technologies used in the workflow, know-how of electronics, programming, coding, etc., are introduced to solve design questions form higher level of thinking, specifically the autonomous design agenda for architecture. Thus, the acquisition of these abilities is part of the designers’ responsibility, not the responsibility of the consultants or manufactures. The research also addressed the cultural driven force in contemporary digital practice. The manipulation of the digital should not be restrained in the form of material or automated process, neither should it be limited within the applications of optimization or simulation. The manipulation should also include unpredictable behaviors in which the computational spatial construct participates in social interactions as an active agent with equal importance as human participators. The very essential concept of architectural design, as the way it relates to our everyday social life, is by nature open-ended. The introduction of digital technology, no matter as mediated processes as is or as a central agenda and workflow as proposed in this paper, should obviously be prepared toward open-ended results, covering all aspects of design, from intent to outcome, and in a lifelong timeframe, from concept to inhabitation. Acknowledgements. This research was supported by Tsinghua University School of Architecture. The author would like to express great appreciation to the instructors and teaching assistants of the workshop, specifically, Zigeng Wang, Pengcheng Sun, Dinglu Wang, Jingsong Wang for their contributions in teaching. The author would also like to express deep gratitude to Yujie Wang for the post-workshop work and continuous insightful inputs to the research. The author would also like to extend grateful thanks to Prof. Axel Kilian, whose work has greatly inspired and motivated the author to do the research.

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References 1. Werfel, J., Petersen, K., Nagpal, R.: Designing collective behavior in a termite-inspired robot construction team. Science 343(6172), 754–758 (2014) 2. Rubenstein, M., Cornejo, A., Nagpal, R.: Programmable self-assembly in a thousand-robot swarm. Science 345(6198), 795–799 (2014) 3. Kilian, A., Sabourin, F.: Embodied computation–an actuated active bending tower: using simulation-model-free sensor guided search to reach posture goals. In: Nagakura, T., Tibbits, S., Ibañez, M., Mueller, C. (eds.) Disciplines & Disruption: Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture, pp. 324–329. ACADIA Publishing Company, Cambridge (2017) 4. Kilian, A.: The flexing room architectural robot: an actuated active-bending robotic structure using human feedback. In: Anzalone, P., Signore, M.D., Wit, A.J. (eds.) Recalibration: On Imprecision and Infidelity: Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture, pp. 232–141. ACADIA Publishing Company, Mexico City (2018) 5. Kilian, A.: Prototypes as embodied computation. In: Gengnagel, C., Nagy, E., Stark, R. (eds.) Rethink! Prototyping: Transdisciplinary Concepts of Prototyping, pp. 37–48. Springer International Publishing Switzerland, Cham (2016) 6. Daniell, T.: Bug eyes and blockhead. Log 36, 34–47 (2016) 7. Chou, C.P., Hannaford, B.: Measurement and modeling of McKibben pneumatic artificial muscles. IEEE Trans. Robot. Autom. 12, 90–102 (1996) 8. Tondu, B.: Modelling of the McKibben artificial muscle: a review. J. Intell. Mater. Syst. Struct. 23, 225–253 (2012) 9. Yao, L., Niiyama, R., Ou, J., Follmer, S., Silva, C.D., Ishii, H.: PneUI: pneumatically actuated soft composite materials for shape changing interfaces. In: Proceedings of the 26th Annual ACM Symposium on User Interface Software and Technology, pp. 13–22. ACM, New York City (2013)

Advanced Timber Construction Platform: Multi-robot System for Timber Structure Design and Prefabrication Hua Chai, Liming Zhang, and Philip F. Yuan(&) College of Architecture and Urban Planning, Tongji University, 1239 Siping Rd., Shanghai, China [email protected]

Abstract. Robotic Timber Construction has been widely researched in the last decade with remarkable advancements. While existing robotic timber construction technologies were mostly developed for specific tasks, integrated platforms aiming for industrialization has become a new trend. Through the integration of timber machining centre and advanced robotics, this research tries to develop an advanced timber construction platform with multi-robot system. The Timber Construction Platform is designed as a combination of three parts: multi-robot system, sensing system, control system. While equipped with basic functions of machining centers that allows multi-scale multi-functional timber components prefabrication, the platform also served as an experimental facility for innovative robotic timber construction techniques, and a service platform that integrating timber structure design and construction through real-time information collection and feedback. This platform has the potential to be directly integrated into timber construction industry, and contribute to a masscustomized mode of timber structures design and construction. Keywords: Timber construction platform system
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Sensing

1 Introduction Technology development has always been a source of driving forces in the transformation of the construction industry. The last two decades have witnessed unprecedented development in material sciences, digital design methods and fabrication techniques, which not only contributed to the increasing complexity of architectural practices, but also gradually led to the new interdisciplinary way of handing complexity. By introducing multidisciplinary fields such as mechanics, computer science, and material science into architecture, robotic fabrication researches manage to integrate material properties, structural performance, fabrication constraints and construction methods through computational design process, which shows an integrated approach for architectural design and construction. Timber has gained extensive attention in this process because of its great advantages in terms of sustainability, and the enormous potential in the new technological context (Menges et al. 2016). With the increase in practices, complexity in timber © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 303–311, 2020. https://doi.org/10.1007/978-981-13-8153-9_27

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structures are gradually becoming more prominent, posing new challenges for design and construction (Scheurer 2010). Complexity lays not only in the design and simulation, but also in the fabrication and construction of complex structures, components and Joints, which calls for innovative technologies with high accuracy and efficiency. 1.1

Timber Machining Center

At present, large-scale timber machining centers, which constitute the core equipment of the timber structure contractor such as Hess-timber, Simonin, and Blumer-Lehmann AG, are the main platform for complex timber structures production. Timber machining centers are developed on the basis of five-axis CNC with milling as the core function, as well as other auxiliary features including cutting, drilling. As light wood structures such as small houses dominates the early timber building market, timber machining center such as Hundegger in Germany were mostly developed for light wood structures production (Hundegger 2019). There are also machining centers such as Technowood, Switzerland, which are mainly developed for heavy wood structures and large panels (Technowood 2019). The advantage of the wood processing center lies in the extremely high processing efficiency in handling all kinds of geometric complexity. While timber machining centre and other task-specific computer-aided manufacturing machines manage to handle some of the challenges, they often overlook the material efficiency in the milling process and causing a lot of material waste. Computer-aided manufacturing, also leads to difficulties in data transmission between design model and machines, Impeding integration of architectural process. For example, the Hundegger K2I machining center, which is quite popular among Chinese timber contractors, can only receive special format files made by limit software such as CADWORK. 1.2

Robotic Timber Construction

In contrast, robotic fabrication technology has demonstrated the ability to handle these complexities with their strengths in terms of flexibility, multifunction, large workspace and accuracy. More importantly, with parametric robot control tools, architects can simulate the fabrication process directly from the design process, blurring the boundaries of design and construction. Robotic Timber Construction has been widely researched in the last decade and achieved remarkable advancements. Both additive and subtractive construction technology have been studied by a large range of research institutions such as Gramazio and Kohler research, ICD, AA School, EPFL (Menges et al. 2016). The researches show a wide range of concerns. Different robotic techniques, including milling, sewing, saw-cutting, have been developed in the construction of different timber materials, from logs to all kinds of engineered wood like Glulam and plywood boards. Despite this, it should be noted that, existing technologies in robotic timber construction were mostly developed to meet the needs of specific tasks.

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With the maturity of the robotic techniques for timber construction, large platforms for timber structure prefabrication start to emerge, introducing researches into the industrial field. The gantry robot in ERNE AG show great potentials, especially in robotic additive timber construction for large scale platform in timber industry (Willmann et al. 2016). The gantry robot set-up in ETH also conducts a lot of researches in of bespoke timber structure (Thoma et al. 2018). TIM – a mobile robotic timber construction platform was built by ICD mainly for timber plates structures (Wagner 2018). The introduction of advanced robot technology has made it possible to develop multifunctional robotic technology and introduce material properties in the fabrication process. As Prof. Menges said in his description of Cyber-Physical Making: “As production machines and fabrication robots no longer remain dependent on a clear set of instructions…… and are increasingly capable of sensing, processing and interacting with each other and with the physical world in real time, a novel point of convergence of design and materialization is on the horizon” (Menges 2015). Recently, advanced robotics research including machine vision-in Robot localization (Brugnaro et al. 2016)/Material monitoring (Bard et al. 2018)/Human-Robot collaboration (Vasey et al. 2016), Autonomous path planning (Dubor et al. 2016, Huang et al. 2018) and Realtime Robot Control (Munz et al. 2016) has emerged in the construction field. In this context, this article describes a multi-robot platform being built, which try to cope with the challenges in timber construction by taking use of the opportunity in advanced robotics. The platform consists of multi-robot set-up, sensing system, control system and fabrication tools. Instead of being a simple construction machine, this platform will allow for timber structures innovation by integrating multi-source information into the interactions between design and construction process.

2 Development of Advanced Timber Construction Platform 2.1

Purpose and Scenario

The design and development of Advanced Timber Construction Platform was initiated in 2015, and was mainly developed by Fab-Union, together with Tongji University (Yuan and Meng 2016) (Fig. 1). The initial purpose of the platform is a Multifunctional research laboratory for digital design and robotic construction. Therefore, the platform was developed as a compact physical facility which integrated a gantry robot system with tools for different fabrication processes. Served as a general platform, the initial configuration focuses on the physical system, leaving the content of the virtual processes such as perception, location, and communication to each specific experiment. The timber construction platform is developed on the basis of the existing facility, which needed to be upgraded and refined to meet the demands and vision of timber construction. The platform will serve as: first, a machining center that allows multi-

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Fig. 1. The initial infrastructure of timber construction platform

functional multi-scale timber components prefabrication. Therefore, the platform needs to serve the general function of a normal machining center. Second, an experimental facility for innovative robotic timber construction techniques, thus should provide basic function and allow for flexible expansion of effector set. Third, a service platform integrating design and construction, which require an interface that allow the connection and interaction between design and fabrication process. Through real-time information interaction, the platform will contribute to a mass-customized design and construction mode for timber structures. 2.2

Structure

In order to achieve the vision, the Timber Construction Platform will consist of three parts: multi-robot system, sensing system, control system and interfaces (Fig. 2). The multi-robot system is developed by integrating the current multi-robot system with multifunctional Plug-and-Use robotic timber fabrication tools. The sensing system is to achieve material and process monitoring by implanting sensors and machine vision technology. In order to realize integrated design and fabrication, the robotic control system include a grasshopper based robotic simulation software called FURobot, and a “digital twin” system for real-time control and feed-back through system modeling and real-time communication; The connection between design and fabrication by establishing integrated process from path planning, robotic simulation, path to robot control.

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Fig. 2. The structure of the timber construction platform

2.3

Infrastructure and Tools

The main manufacturing resources of the platform are comprised of: The gantry robot system includes a 3 axis gantry system with 12 m long, 8 m wide and 4 m high. Two KUKA KR120 robots are hanged on the two z-axis of the gantry, which is installed on the same y-axis (Fig. 3). The two robot is equipped with multitool rapid transfer system that integrates electrical, gas, liquid, signal and other modules that may be required by different tools, laying the foundation for flexible combination and expansion of tools. The gantry and two robots are integrated and coordinated with the same control system. Using the KUKA Roboteam software, the two robots can be used to fabricate collaboratively. The machining table includes several mobile modules for material supporting and fixing. The distribution of the supporting modules on linear ground rail can be flexibly adapted according to the specific form of the material. The material is fixed by vacuum at the support point. The material handling tools are comprised of a set of robotic effectors for timber additive fabrication and subtractive fabrication (Fig. 4). For additive fabrication, a gripper and a vacuum chuck, all integrated with nail guns, are equipped respectively for timber beams and boards assembling. The core components of subtractive fabrication are two universal milling modules with a set of milling bits and circular saw; a chain saw module for fast slotting on wood components; a band saw module for curved beam cutting. A Surface polishing device is also designed. The laser marking tool is integrated as an important part in mass customization. In order to meet the requirements of green production, auxiliary systems such as dust removal, chips cleaning, noise reduction and safety protection are also included.

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Fig. 3. The model of the multi-gantry robot system

Fig. 4. The main tools library

2.4

Multi-heterogeneous Sensors

To ensure process transparency and interaction between control system and fabrication process, a multi-heterogeneous sensors system is designed to monitor machine condition, material condition and power consumption. In terms of vision system, depth camera is used for fast and real-time positioning the material in the fabrication process; 3D laser scanning sensor are used for precise scanning of finished products and others. Motion capture device and 2D tags are used to localisation the tools and collision avoidance. Because timber is an anisotropic material, it is sensitive to environmental condition. Therefore, thermal sensors such as infrared thermal imagers, and humidity sensors are

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designed to be used to detect environmental information like temperature and humidity, which can be used to stabilize environmental conditions to optimize the accuracy of the finished product. In addition to system sensors, most tool will be equipped with sensors to optimize the machining process. The motor current is monitored with current transformer, which is connected with the robot through PLC, and used to optimize the energy consumption and material feed rate (or robot processing speed). Three-axis force sensor was mounted either on the tools or on the saw table to monitor excessive force or speed. In addition to their respective functions, all the information from the sensors are also designed to form a multi-heterogeneous information database altogether. According to different analysis requirements, such as error analysis, deformation and temperature correlation analysis, specific data can be extracted from the database, and fused to establish different analytical models. 2.5

Control System

The core of the control system is FURobot, an online and offline programming software developed by Fab-Union (Fig. 5). The software is developed based on the parametric design platform grasshopper. A virtual model of a robotic platform and tools has been built in the FURobot, and different sensors will be introduced later, to form a complete “digital twin” system. As for the connectivity of the robot system, the PLCs of the robot system and tools are inter-connected, through which a host computer can control the whole system in real-time. The real-time interaction between design and the fabrication process is now under development. At current state, the parametric design model on personal computers can communicate with the platform through KUKA software RSI (Robot Sensor Interface) or mxAutomation. Another core part of FURobot is a robotic timber construction programming toolkit, which is used for path generation of basic robotic timber fabrication process. Robotic milling is still the dominate method for timber fabrication. Some basic path planning algorithm for 2d contour, 3d contour and 3d surface milling are packed in batteries in grasshopper. Robotic cutting processes for band saw and chain saw are also preparing. Further, some basic path generation tools are also being developed for different timber components and joint types.

Fig. 5. The interface of FURobot

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3 Discussion and Outlook The target of the platform development is not for timber construction automation, but for a degree of automation that enables the combination of timber properties and advanced robotics. Based on the platform, robotic timber construction techniques need to be developed through process organization, parameter adjustment, quality control, etc. to meet the mass customization requirements of timber structures. For the development of integrated timber design method, this platform will be used for establishing an integrated design workflow that synthesize material properties, structural performance, fabrication constraints, which could adjust in real time according to the fabrication information. There are still several key technical issues need to be addressed in the development process. The integration and coordination of multi-robot platform, sensing system and tools is still great challenge for platform stability; Autonomous path planning techniques are still an important but difficult problem to be further studied.

4 Conclusion This paper describes a systematic design of robotic timber construction platform. The platform integrates the advantages of timber machining center and robotic fabrication technologies to form an advanced platform for timber structure innovation. The development, which is still in progress, is largely guided by the principle of cyberphysical system, in which the information acquisition and feedback stand at the core of the platform. The hardware, software and techniques are all interrelated with information. In this case, the platform has the potential to be directly integrated into the future timber construction industry.

References Bard, J., BIdgoli, A., Chi, W.W.: Image classification for robotic plastering with convolutional neural network. In: Robotic Fabrication in Architecture, Art and Design, pp. 3–15. Springer (2018) Brugnaro, G., Baharlou, E., Vasey, L., Menges, A.: Robotic softness: an adaptive robotic fabrication process for woven structures. In: Posthuman Frontiers: Data, Designers, and Cognitive Machines, Proceedings of the 36th Conference of the Association for Computer Aided Design in Architecture (ACADIA). Ann Arbor (2016) Dubor, A., Camprodom, G., Diaz, G. B., Reinhardt, D., Saunders, R., Dunn, K., Niemelä, M., Horlyck, S., Alarcon-Licona, S., Wozniak-O’connor, D.: Sensors and workflow evolutions: developing a framework for instant robotic toolpath revision. In: Robotic Fabrication in Architecture, Art and Design. Springer (2016) Huang, Y., Carstensen, J., Tessmer, L., Mueller, C.: Robotic extrusion of architectural structures with nonstandard topology. In: Robotic Fabrication in Architecture, Art and Design, pp. 377– 389. Springer (2018) Hundegger. Product overview (2019). https://www.hundegger.de/en/machine-building/company. html. Accessed 9 Mar 2019

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Menges, A.: The new cyber-physical making in architecture: computational construction. Arch. Des. 85, 28–33 (2015) Menges, A., Schwinn, T., Krieg, O.D.: Advancing Wood Architecture: A Computational Approach. Routledge (2016) Munz, H., Braumann, J., Brell-Cokcan, S.: Direct robot control with mxautomation: a new approach to simple software integration of robots in production machinery, automation systems, and new parametric environments. In: Robotic Fabrication in Architecture, Art and Design. Springer (2016) Scheurer, F.: Materialising complexity. Arch. Des. 80, 86–93 (2010) Technowood. TW solutions (2019). https://www.technowood.ch/de/solutions. Accessed 29 Mar 2019 Thoma, A., Adel, A., Helmreich, M., Wehrle, T., Gramazio, F., Kohler, M.: Robotic fabrication of Bespoke timber frame modules. In: Robotic Fabrication in Architecture, Art and Design, pp. 447–458. Springer (2018) Vasey, L., Nguyen, L., Grossman, T., Kerrick, H., Schwinn, T., Benjamin, D., Conti, M., Menges, A.: Human and robot collaboration enabling the fabrication and assembly of a filament-wound structure. In: ACADIA//2016: Posthuman Frontiers: Data, Designers, and Cognitive Machines, Proceedings of the 36th Annual Conference of the Association for Computer Aided Design in Architecture, pp. 184–195 (2016) Wagner, H.J.: Introducing TIM – a mobile robotic timber construction platform (2018). https:// icd.uni-stuttgart.de/?p=23427. Accessed 29 Mar 2019 Willmann, J., Knauss, M., Apolinarska, A.A., Gramazio, F., Kohler, M.: Robotic timber construction—expanding additive fabrication to new dimensions. Autom. Constr. 61, 16–23 (2016) Yuan, P., Meng, H.: Fab-Union: a collective online to offline robotic design platform. Arch. Des. 86, 52–59 (2016)

Developing an Interactive Fabrication Process of Maker Based on “Seeing-Moving-Seeing” Model Chun-Yen Chen1,2(&), Teng-Wen Chang1,2, Chi-Fu Hsiao1,2, and Hsin-Yi Huang1,2 1 National Yunlin University of Science and Technology, Douliou, Taiwan [email protected], [email protected], [email protected] http://idfactory.tw/ 2 Tamkang University, New Taipei City, Taiwan

Abstract. In generally situation, maker will using the prototyping to solve their problem and mistake. However, if they need to try the digital fabrication to complete their deign, it will be embarrassment. Because they need to spend more time to communicate with the manufacturing how to complete the design. In this paper we use the “seeing-moving-seeing” model to combine the design tools and reduce the problem of communicate with other people. By using this method we can more easier to understand the different of the finish product and prototyping. Using the robot arm to combine the design, manufacturing and fabrication tool it can increase the digital fabrication’s special value. Finally, our research will using design computing connecting the digital interface and the machine to communicate. Keywords: Robot arm


Digital fabrication
Mixed reality
Design process

1 Introduction In architecture design it has large information behind the process, when we need to understand this context it need some tools and technical to support it. Using the tool to support understand the context and relationship. Robot arm is a manufacturing tool that between the computing and physical digital tools. It is hard to use robot arm when you do not have the professional knowledge by yourself. Thus, if the robot arm can be liberate on the operate method and immediately to have the respond, it can reduce most of problems for maker. In 2005 the hands-made become the most popular things in the world. However, the prototyping design are similar the hands-made, if you do not have enough knowledge you will need to face many mistake and problem. Thus, how to reduce the

© Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 312–321, 2020. https://doi.org/10.1007/978-981-13-8153-9_28

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errors and increase the prototyping usage is the most important things for maker. Using the digital fabrication is the way to approaching this problems but if you do not have the great communicate skills it will be the complex and cumbersome things. In this paper we will used the “Seeing-Moving-Seeing” model and observation to represent the design process. When the design thinking can be logical represent on the media, the maker can be easier to understand the prototyping and the final product communicate different. When the robot arm combine the design, manufacturing and the fabrication tools, maker can through the digital media to communicate each other and a new interactive fabrication process. In this interactive fabrication process, maker can change design, fabrication, finding the best computing mode and the technology skills. The Cyber-Physical Interactive System (CPIS) forms an interactive manufacturing process that allows for real-time modification and manufacturing in the manufacturing process, and analyzes each process and fits into the computing system model to control the prototype manufacturing machine, lowering its technical threshold (Fig. 1). 1.1

Human: The Technical Threshold for Digital Manufacturing

In 1992, Schon and Wiggins proposed a design model it called “seeing-moving-seeing” [1]. This model was focus in the designers observation and iterative design via this process can let the design more complete. In the designs field designer almost used the hands-made and design thinking to approach their products. In the digital fabrication design, designer need to via the design thinking and observation to present on the agent. After their thinking show on the agent they can more easier to explain the process and thinking. Thus, how to reduce the complex process between the maker and the manufacturing is the key of the problem in this paper. We need to integration the fabrication and the final design by using the cyberphysical system generated by combining digital and entity information through the process of embedded computer, network monitoring and control entity calculates the feedback through the influence of entity information [2]. This design produce the coexiting space, this space include the physical and the virtual system. In this space it will record the maker’s behavior via the virtual system to communicate with the physical machine feedback to maker. 1.2

Digital: Digital Interface into the Reality

Designer tends to used CAD/CAM to present their ideas but the transfers process always have large problem. Cause, in the transfers stages, the maker can’t have the realtime feedback to understand the situation of the fabrication. In order to have an intuitively way to programming and using the fabrication tools, it almost need an easier interactive interface between each others. The mixed reality(MR) is the popular machine in the digital interface field. because it not only combine the virtual and physical information but also visualization and create a new environment for the user. Thus, using the MR its has the different experience include augmented reality and enhanced virtual immersive technology.

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Fig. 1. CPIS system

1.3

Physical: Manufacturing Tools into the Digital

The convenience and rapid prototyping of “digital manufacturing” has become a trend in manufacturing tools. Lavallee’s 2011 study mentioned that manual assembly of parts is as complex as manufacturing tool construction. in the fabrication process we need to consider a holistic approach to building manufacturing methods that successfully incorporate manufacturing tools, humans, and materials organizations into the field [3]. Most of the traditional industry in the fabrication process still rely on control by professional, such as metal bending, table saws and other fabrication tools. in the fabrication process using the machine is dangerous when you don’t have enough technology. However, the robot arms are the manufacture new favorite machine, it integrates the virtual and physical object and expands multiple possibilities tools. Thus, If the robot arm can help the maker to have precision prototyping or budget sample, it can reduce much of the assembly problem and complex process. Thus, if we need to develop a more convenience system there are three element need to consider (1) fabrication tools, (2) humans and (3) the materials. The three element will affect the process and the user experience.

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2 Related Work Since 2005, the maker movement grown up people’s habits change, the transition from the original regularization to customized. In the traditional manufacturing prototyping process, the technology is too dangerous and difficult. Thus, the digital fabrication become more popular way to solve this problem. By using the digital fabrication, it will via the computing system to control the machine. Using this method its not only can increase the produce rescission but also have the quickly prototyping. However, in the current digital manufacturing process, the maker can’t in real-time to control their design. They still need to communicate with the manufacturing to complete their design. Thus, this paper will via the three problem to approach our problem: (1) Human: Threshold and limit for Digital Manufacturing, (2) Physical: Application and status for robot arm, (3) Digital: Application and status for Mixed Reality. The robot arm as a tool for physical operation because it has the characteristics of a threedimensional moving path. By combining such techniques with a mixed reality for remote control, the complexity of operating the robot arm can be reduced, and the user can be more intuitive to operate the robot arm, to solve problems in the digital manufacturing process. 2.1

Human: Threshold for Digital Manufacturing

Digital manufacturing is changing the way people design, produce, and interact with objects and devices. The diversity of current manufacturing processes includes laser cutting, 3D printing, CNC milling, and printed circuit board (PCB) manufacturing, enabling them to produce parts in a variety of forms and materials. Because of the rise of digital manufacturing technology, it redefines and integrates industrial manufacturing logic. Designers must have abstract thinking design description capabilities and the ability to control design results. With the advent of a series of rapid prototyping (RP) technologies and their absorption into implementation, designers are able to see design results more quickly. As a result, design and design colleges began to incorporate rapid prototyping equipment into the design process. The problem of this intermediary relationship began to unforced less on the characteristics of the machine and more on the nature of the design process. The evolution of digital technologies is inseparable from the transformation of conventional building techniques. The use of digital fabrication in architecture allows mass-production of customized complex structures, Therefore, they began committed to work on-site, but it still can’t solve the problem of immediate correction on-site. Schon and Wiggins in 1992 proposed a theoretical model of design thinking and considers design to be a “process of dialogue between designers and design media,” and this view relies heavily on “observation” activities [1]. Through observation, and then refined by the designer’s ideas, and then presented on the design media, such loop thinking, making the design more complete, as shown in Fig. 2. The designer draws on the paper, observes that the finished product is gradually forming, and uses different “seeing methods”, example: visual apprehension and literal seeing, and then through the refined behavior of the drawing, the design features and associations can be defined, and accumulated more in-depth thoughts.

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Fig. 2. Seeing-moving-seeing model

2.2

Physical: Robot Arm Application

Ever since 1980s, the six-axis robot arm has been widely applied in automobile and aerospace industries, since it can operate and process the objects intuitively which will help the construction of the shape produced by the design process. At present, the manufacturing countries of robotic arms are mostly countries with heavy industry technology, such as Germany, the United States, and Japan. In [4, 5]. can see the research and development of many robotic arms, such as 3D printing [6], concrete printing [7], cutting [8], etc. There are various processing methods in various materials, and there are various processing processes on the production line. Robot arm can save a lot of complicated manual processing. The end effector is just like the palm of our hand. It can learn different ways of processing according to learning. Robot arm unlocks the limitations of the palm joint and the fatigue of the muscles. The different processing methods developed by the design. Both promote the efficiency of the manufacturing process and the automation of manufacturing. In the 2015 “Extrusion Structure” course, the designer initially starting with conventional triangulated space frame structures, they expanded their research towards combined multi-sided polygons like rectangles and hexagons, and developed custom printing sequences for nonStandard spatial frames [9] (Fig. 3).

Fig. 3. The process of applying the robot arm to 3D printing (left) and results (right)

2.3

Digital: Mixed Reality Applications

Mixed Reality is the integration of both real world and virtual world to create new environments and visualizations where physical and digital objects coexist and interact in real time. Mixed reality occurs not only in the physical world or in the virtual world, but also in the combination of reality and virtual reality, including augmented reality

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and enhanced virtual immersive technology. At present, the range of mixed reality technology and applications has expanded to include entertainment and interactive arts as well as engineering and medical applications. In 2014, Weichel, et al. proposed a mixed-reality environment for personal fabrication that lowers the barrier for users to engage in personal fabrication. Users design objects in an immersive augmented reality environment, interact with virtual objects in a direct gestural manner and can introduce existing physical objects effortlessly into their designs [10].

Fig. 4. MixFab’s user interface.

2.4

Case Learning

Through the analysis of the above literature, the concept of the “seeing- movingseeing” design thinking model is introduced into the digital manufacturing process. Under the operating conditions of rapid prototyping and virtual reality blending, the designer can use different “look and see” methods to observe the finished product. Gradually, the design media has also evolved from a pure passive assist role to an active support role that may interact with the designer. Generally, the devices in a mixed reality are limited in their own resolution and inter-activity in the display of the interface. The HoloLens developed by Microsoft not only provides a wireless headmounted display, but also provides the ability to assemble AR commands and the opportunity for users to face the appearance of such applications. It has the unique ability to integrate virtual 3D content with the real world. Optimized for interactivity with a simple gesture recognition input system, allowing users to easily manipulate 3D reconstructions and create 3D models in space. Therefore, this paper will use HoloLens as a mixed reality interface device for the system (Figs. 4 and 5).

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3 Materials and Methods Maker are inextricably linked with digital manufacturing. This paper explores through participatory behavioral observations. Therefore, makers with cross-domain integration are the main targets, and various manufacturing methods capable of rapid prototyping are analyzed to obtain thermoforming. Manufacturing methods such as metal bending, metal printing, hot wire cutting, incremental sheet forming, CNC engraving, and panel striking, in which the metal printing material has a large difference in plasticity, strength, and hardness, so we will use Metal printing as a research test. Arc welding uses a welding power source to create and maintain an arc between the electrode and the solder material, causing the metal on the solder joint to melt to form a molten pool. They can use either direct current or alternating current, using consumable or nonconsumable electrodes. Sometimes an inert or semi-inert gas, that is, a protective gas, is introduced near the molten pool, and sometimes a weld repair material is added. The molten pool is formed by heating the workpiece to be joined to form a molten pool, and the molten pool is solidified and then joined. We divide the manufacturing process of metal printing into four steps: (1) Preparation, (2) Warm-up, (3) Processing, and (4) Finish, but in each step, the manufacturer All need to have different technical knowledge, including the assembly of the tool head, the adjustment of parameters and the setting of safety equipment (Fig. 6).

Fig. 5. Traditional manufacturing process for metal printing

This paper hopes to extend the rapid prototyping application to other manufacturing processes through the use of the network entity interaction system. After the analysis, metal printing is selected as the main research, because the material printed by metal has great plasticity, strength, and hardness. Therefore, we decompose the metal printing steps into different tasks, and systematically modularize each step by designing the operation. In the process, it is mainly through the Cyber-Physical Interactive System, which combines the mixed reality and the machine. The basic design flow is set by the mixed reality interface, and the value is transmitted to the machine through the system. Finally, the material is heated and moved and processed (Fig. 7). Therefore, when the maker starts manufacturing, the basic settings of the machine are first performed through the mixed reality interface, such as the work area, the initial model and the tool head, the positioning of the starting work, the initial position and the tool. The point of

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contact of the head. After setting the basic values in the early stage, it will enter the heating stage. This stage is also the parameters of power supply adjustment, heat concentration and deposition speed from the interface of the mixed reality. In the stage of mobile processing, the maker through the gesture operation, the path of the printing is input, and through the system automatic calculation to generate the moving path, angle and switching points of the feeding, to control the movement path printed by the machine. In the final stage of the completion, we will display the progress of the physical printing on the mixed reality interface through the system operation. Through the virtual interface and the reality scene, we observe each other and gradually form the finished product, and use different “seeing methods” to modify the finished product.

Fig. 6. CPIS system process

In order to render the model and generate the model interface, in this installation program, an MR mobile device and a computer must be used the mobile device is used for the control interface and the computer is used for robot manufacturing. First, set up the mobile device through Unity. In Unity, set up a pre-fabricated message to connect the IP address of the local server to the IP address of the mobile device to obtain the IP of both parties and connect to the correct port. The mobile device can communicate with the localhost the virtual model in the mobile device can generate a data string the data is transmitted back to the localhost and the data in the server is read through the computer. Then, using the GHowl plug-in (Fraguada) for Grasshopper, the data string transmitted by the mobile device is converted into a 3D model and the variables positions and sizes of the arm and the model are displayed in Rhinoceros. Finally, the TACO ABB plug-in is used to convert the points at the edge of the model to form the moving path of the robot arm which is evaluated and adjusted. This allows the designer to eliminate the complexity of robot programming while operating the mobile device creating a more direct link between the designer and the manufacturing process. Such technology allows robots to create unlimited design variants each of which is the result of immediate feedback from the designer during construction.

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4 Results and Discussion Generally, when the prototype is tested the 3D printing is the most basic mode. However, the 3D printing materials are mainly ABS and PBL but the two materials are used and in terms of results. They are all relatively fragile and not strong and the machines that are printed in 3D are generally limited in size. Therefore, when the maker is prototyping used the strong material the large-scale machine is the primary consideration. Taking metal printing as an example under the condition of general metal printing the heat concentration of the positive electrode reaches 60%, so that the metal material melts at a high temperature and a strong spot is generated at a melting point, the surrounding is also protected by a helium gas layer, and the high temperature metal material is sprayed. In such a dangerous working environment the professionalism of the metal printing machine is high and it is impossible to achieve it if the maker wants to use it by himself. Therefore, it is necessary to hand over the design draft to the builder, and after a long period of communication with the manufacturer the two sides must reach a consensus before manufacturing, but the defects appearing in the design draft will be discovered after the finished product is finished. If we can develop a system that combines the environment with the hybrid environment the maker can reduce the technical threshold by mixing the real interface and remotely manipulating the ma-chine for metal printing. Through the virtual interface and the actual scene, we observe each other’s finished products and use different “seeing methods” to modify the finished products. This reduces the time it takes for the maker to communicate with the builder and wait for the finished product, and reduces the number of revisions after the finished product is completed. In the usage ow used it can be seen that the steps of setting the initial working area and positioning the tool head are too cumbersome, and the maker is confused by the difference between the virtual and the physical. Therefore, in the preparation stage the positioning point needs to be attached with the function of the point to reduce the trouble of the maker in positioning. However in the process of adjusting each parameter and starting to move the printing path, the maker can customize the manufacturing according to his own preferences. After the progress is displayed the subsequent printed paths can be changed. In these steps, the maker is able to get a simpler operation and can delay the design model phase in the entire manufacturing process.

Fig. 7. User journey map

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5 Conclusion In order to reduce the threshold for makers to use different manufacturing processes, this paper is roughly divided into three categories according to common manufacturing processes, namely (1) forming method, (2) cutting method, and (3) joining method. Through these three types of manufacturing processes, the types of manufacturing processes that can exhibit rapid prototyping include thermoforming, incremental sheet forming, metal bending, hot wire cutting, laser cutting, arc welding. Among them, metal printing materials have different plasticity, strength, and hardness, so metal printing is selected as a research test. Through “seeing- moving- seeing” design concept, the concept of the design model is introduced into the digital manufacturing process. Under the operating conditions of rapid prototyping and virtual reality blending, designers can use different “seeing methods” to observe the finished product. Therefore, belong maker’s Cyber-Physical Interactive System (CPIS) process will be developed to form an interactive manufacturing process of virtual and real coexistence, so that the manufacturing process can be modified and manufactured in real time, so that the designer can at the same time as the model is built, the manufacturing process of the robot arm in reality can be seen to form a remote wireless virtual reality integration system. Through such human-machine collaboration, the time to manufacture complex building combinations can be reduced, the structure of buildings can be quickly formed, and the fabrication of complex space structures can be realized, while reducing costs, risks and complexity, eliminating the traditional dependence on 2D documents.

References 1. Schon, D.A., Wiggins, G.: Kinds of seeing and their functions in designing. Des. Stud. 13 (2), 135–156 (1992) 2. Lee, E.A.: Cyber physical systems: design challenges. In: 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing (ISORC). IEEE (2008) 3. Lavallee, J., Vroman, R., Keshet, Y.: Automated Folding of Sheet Metal Components with a Six-axis Industrial Robot (2011) 4. Willette, A., Brell-Cokcan, S., Braumann, J.: Robotic Fabrication in Architecture, Art and Design 2014. Springer (2014) 5. Reinhardt, D., Saunders, R., Burry, J.: Robotic Fabrication in Architecture, Art and Design 2016. Springer (2016) 6. Yuan, P.F., et al.: Robotic Multi-dimensional Printing Based on Structural Performance, in Robotic Fabrication in Architecture, Art and Design 2016, p. 92–105. Springer (2016) 7. Culver, R., Koerner, J., Sarafian, J.: Fabric Forms: The Robotic Positioning of Fabric Formwork, in Robotic Fabrication in Architecture, Art and Design 2016, p. 106–121. Springer (2016) 8. Søndergaard, A., et al.: Robotic hot-blade cutting. In: Robotic Fabrication in Architecture, Art and Design 2016, p. 150–164. Springer (2016) 9. Helm, V., et al.: Iridescence print: robotically printed lightweight mesh structures. 3D Print. Addit. Manuf. 2(3), 117–122 (2015) 10. Weichel, C., et al.: MixFab: a mixed-reality environment for personal fabrication. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM (2014)

Design Optimum Robotic Toolpath Layout for 3-D Printed Spatial Structures Philip F. Yuan(&), Zhewen Chen, and Liming Zhang Tongji University, 1239 Siping Road, Shanghai, China [email protected]

Abstract. This paper presents an improved method for designing robotic toolpath of 3-D printed spatial structures to enhance the overall structural performance. This research includes a practical case of the Cloud Pavilion 2.0, an upgrade version of Cloud Pavilion 1.0 which was conducted in the IASS 2018 conference. Traditionally, the computational and structural design phases for robotic printed structures were considered as independent. However, since the printed lattice structure itself can be recognized as a space frame system in a smaller scale, there is the potential to improve its structural efficiency by modify the toolpath geometry and layout at the early design stage. This paper discusses the design parameters in robotic toolpath that influence the structural stiffness, and also a numerical method is applied on the testing specimens consisting of an amount of discrete toolpath elements. The structural topological optimization is used to define the toolpath prototype and relocate the mesh vertices. Keywords: 3D-Printing
Robotic fabrication Discrete system
Toolpath design




Structural optimization




1 Introduction With the rapid development and extension application in additive manufacturing, architects have proposed a variety of large-scale spatial structures from robotic fabrication to meet the requirements in light weight, high productivity, and flexible customization. The method for creating lattice structure using robotic 3D-printing technique has been widely adopted in many projects, such as the Mesh Mould by ETH Zurich, Daedalus Pavilion in Amsterdam by Ai Build, Flotsam & Jetsam in Miami by Oak Ridge National Laboratory (ORNL), SHoP Architects, and Branch Technology. Different printing toolpath logic in the design phase results a unique appearance texture, and this kind of uniform spatial lattice structure formed by robotic extrusion usually plays a role of space filling. However, due to the lack of structural optimization processes involved in the early design phase, these projects have varying degrees of structural inefficiency. Researchers began to integrate robotic extrusion with structural optimization methods. One City Pavilion is Branch Technology’s newest project aims to create a compressed form by eliminating the parts with low structural efficiency. MIT also starts a research on topology optimization framework allows robotic extrusion to follow a toolpath to materialize a 3D topology-optimized truss, but up to date this framework can only apply for small physical scale work. © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 322–330, 2020. https://doi.org/10.1007/978-981-13-8153-9_29

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2 Challenges The spatial printing structure is more complicated than the geometric form of the common truss structure, and it will encounter relatively large difficulties in the structural calculation. Since a spatial printed structure usually extruded from a single material, the bars and joints in the system are composed of the same material, and the joints strength are also dependent on the bond strength from two adjacent bars. It is difficult to quickly determine the optimal toolpath layout by using the FEM (Finite Element Method) analysis. Therefore, in order to simplify the robotic toolpath design process, the common method is filling the space with uniform cellular structures, and then the filling structure will be analyzed in FEM software. However, it is a passive optimization process with low efficiency and often requires the intervention of professionals. In response to this question, it is important to transform the original passive structural analysis into an active optimization process in the early design stage. In our early research, a pavilion exhibited in DigitalFUTUREs2016 workshop aimed to improve the structural performance by relocating the mesh vertices based on the stress behavior for a shell structure (Fig. 1). Although the structural performance has been improved, the effect is not significant and it is difficult to quantify the improvements in mechanical properties. Another practical case, the Cloud Pavilion 1.0 project in Shanghai, China, uses the concept of topology optimization to divide the surface into five regions, representing different levels of structural stiffness and filling the corresponding unit toolpaths (Fig. 2). The research on Cloud Pavilion 1.0 shows that treating the printed spatial structure as a discrete system can bring additional strength to areas of the structure that need to be reinforced, however, there are still limits on the structural stiffness values that cannot be adjusted by parameters.

Fig. 1. Robotic spatial printing pavilion in DigitalFUTUREs2016 workshop

This research will further study the optimization process on robotic toolpath layout to enhance its structural stiffness with light structure weight, the parameters used to adjust the overall stiffness are structure thickness and unit toolpath types. The goal of this paper is to present an innovative design method to optimize the layout of robotic toolpath for a spatial printing structure in order to increase the stiffness significantly.

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Fig. 2. Structural optimization in cloud pavilion project

3 Methodology In order to generate a structurally optimized toolpath layout for a shell structure more efficiently, a workflow of toolpath design process is presented in this research (Fig. 3). The input geometry is a shell structure modelled in Rhinoceros3D and analyzed in Millipede, a structural finite element analysis plugin in Grasshopper. The main steps include: (1) convert the structural performance into geometric forms; (2) parameterize the overall robotic toolpath; (3) find the optimal robotic toolpath layout from feasible outputs.

Fig. 3. Robotic toolpath design workflow

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Convert Structural Performance into Geometric Forms

The initial 3D-model of a shell structure is simplified to a mesh surface, the sizing in U and V directions also indicate the maximum printing length during the fabrication process. The input structure is analyzed by using FEM in Millipede with the applied boundary conditions, after the iterative optimization process, the result shows a stiffness factor model of the mesh surface according to calculated stresses. The output is the thickness reflecting the assigned thickness plus the effect of sizing optimization, however, since the optimal thickness is generated based on a solid material with uniform mechanical properties, the specific value of the optimized thickness cannot be used as the thickness for a printed lattice structure directly. To adopt this method in robotic toolpath design, the stiffness distribution is transformed into another format, which has a unique stiffness multiplier on every mesh vertex. Figure 4 illustrates a comparison of the optimized stiffness distribution over the cells and the vertices of the target mesh.

Fig. 4. Optimized stiffness distribution on mesh elements and vertices

The value of stiffness factor (K) has a range of 0.0–1.0, the number designating the relative “importance” of the member for structural stability. Elements that have a near 0.0 value are not needed while elements with a value of 1.0 should be considered for reinforcement. Base on the calculated stiffness factor on each vertex, given the initial thickness, t0, representing the minimum thickness existed in the designed shell structure, and the maximum designed thickness of t1, the actual thickness, tactual, on each vertex can be described as: tactual ¼ t0 þ K  ðt1  t0 Þ

ð1Þ

With the applied thickness, the original mesh surface is now change into a twisted mesh box with different length on four vertical edges, it is also the space that need to be filled with the discrete toolpath element.

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Quantify the Stiffness Improvement of Overall Robotic Toolpath

In practical engineering, the overall stiffness performance of a space truss is controlled by the diameter of the rods, the size of the truss, and the joist spacing. A truss structure is a discrete system consists of a number of joints and connected by bars, the structural system of space truss has strong similarity to the geometry formed by robotic spatial printing, which is a truss-like system in much smaller scale and usually contains a massive number of members that far exceeds the number of bars in traditional truss structure. The length of the bars printed in space is often limited by the setting time of the thermoplastic printing consumables in the air, and the length generally does not exceed 20 cm for a printed bar with diameter of 7 mm. However, as the number of bars rising, the calculation time of FEM process could increase rapidly and brings great difficulties in analyzing the stress behavior for robotic printed spatial structures. In order to solve this problem, at the early design stage, the printed shell structure should be considered as a combination of mesh boxes with various mechanical properties, meaning that the correct type of toolpath is filled into the corresponding region according to its stiffness distribution. To improve the analyzability of a printed spatial lattice structure, it is necessary to define a unit toolpath prototype that its stiffness can be easily adjusted by parameters. In this research, a simple space frame element is selected as the unit toolpath prototype (Fig. 5) filled in a mesh box of 140*100*100 mm with excellent self-supporting performance, and the selection of toolpath prototype also need to consider of the printability of the robotic end-effector. As shown in Fig. 5, the unit toolpath prototype can transform in X, Y, or both X and Y directions parametrically. Under the conditions of printability, some of these options have been eliminated.

Fig. 5. Robotic toolpath prototype selection

Three kinds of toolpath are chosen as the filling material for the regions in different stiffness range, K = 0, K = 0*1, and K = 1. Table 1 summarized the structural performance for the initial prototype, Type A and two other transformed geometries, Type B and Type C. Given a printed spatial structure with minimum thickness of 100 mm and maximum thickness of 200 mm, the improvement of stiffness properties for Type B (t = 100 mm), Type B (t = 200 mm), and Type C (t = 200 mm) are 110, 133, and 256% in Boundary Condition 1, and 102, 312, and 370% in Boundary Condition 2.

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Table 1. Structural analysis on three kinds of toolpath prototypes

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Optimal Selection Process on Robotic Toolpath Layout

The overall toolpath geometry is analyzed by FEM, assuming all joints are rigid and connected by straight bars. Generally, the analytical results need to be compared with the mechanical properties of the material, but due to a spatial printed structure always crack at the joints under tension load, it requires to compare with not only the material properties but also the tensive strength at the joints. If any element exceeds the maximum carrying capacity, it is need to go back to previous step and adjust the value of maximum thickness, t1, to gain more structural rigidity. Adjustment in the range of the stiffness factor, K, could also bring effects on the total structure weight and the structural performance. However, finding the layout of the discrete toolpath elements is indeed a multi-objective optimization problem, structural stiffness and printing material usage are two main optimization goals.

4 Case Study: Cloud Pavilion 2.0 Cloud Pavilion 2.0 is an upgraded version of the Cloud Pavilion 1.0 project and will be completed in 2019. With the implement of the robotic toolpath layout optimization process, the overall structural performance can by controlled by adjusting the toolpath parameters, and analysis results suggest that the stiffness performance in this project has been greatly improved. Since the Cloud Pavilion 1.0 with a uniform thickness of 100 mm appears to have significant deformation after construction, especially at the end of the cantilever at the front. Set the minimum thickness, t0 = 100 mm, the maximum thickness, t1 = 200 mm as the initial thickness values. The topological optimization results generated from Millipede used to calculate the stiffness multiplier on the mesh vertices, the target mesh surface is partitioned into 3 regions based on the K value, Fig. 6 shows the partitioning process according to K = 0, K = 0*0.780, and K = 0.780*1.0.

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Fig. 6. Topologic-optimized meshing process

For example, if a mesh vertex has a stiffness multiplier of 0.6, according to Eq. (1), the actual thickness on this vertex can be calculated from tactual ¼ t0 þ K  ðt1  t0 Þ ¼ 100 mm þ 0:6  ð200 mm  100 mmÞ ¼ 160 mm After the three kinds of toolpath prototype having been filled in its corresponding regions, the initial shell structure transformed into a lattice structure contains numerous bar elements. Figure 7 illustrates the robotic toolpath sample in Cloud Pavilion 2.0 project with various thickness from 100 to 200 mm.

Fig. 7. Robotic toolpath sample

A testing sample is printed at the beginning, random bars and joints are removed from the printed struct for tensile test. The experimental results suggest a failure normally occur at the joints with a tensile load greater than 0.6 kN, the maximum tensile load an extruded bar can carry is 2.2 kN (Fig. 8).

Design Optimum Robotic Toolpath Layout for 3-D Printed

Fig. 8. Tensile tests on printed bars and joints Table 2. Optimal solution on robotic toolpath layout

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The optimal selection process on robotic toolpath layout is summarized in Table 2, it shows that a toolpath layout involves various unit toolpath types could reduce the maximum displacement from 146 to 119 mm, a total reduction of 22.7%. As the maximum thickness, t1 increasing, the overall stiffness is getting higher. Adjusting the stiffness range has a nonlinear effect on its structural performance, the results show that it achieves optimal performance in a stiffness range of K = 0, K = 0*0.78, and K = 0.78*1.0, taking consideration of multi-objective goals of stiffness and weight.

5 Limitations and Conclusion The structural performance analysis of unit toolpath prototype considers only the selfweight as an axial load in Z direction, but in fact, as the complexity of the target geometry increases, the loading conditions applied on each unit mesh box becoming more complex. In actual situation, a unit cube existed in a shell structure is under six primary stress, axial loads in XX, YY, and ZZ directions, and shear stress in XY, XZ, and YZ directions. In future research, it is recommended to establish a toolpath library that allows to select the optimal toolpath prototype according to the actual stress situation. So far, no building codes have been designed for 3D-printed buildings, and therefore it is difficult to define the importance levels for the optimal goals. The optimal selection process in this research is based on past project experience. Acknowledgements. This research is funded by the National Natural Science Foundation of China (Grant No. 51578378), the Special Funds for State Key R&D Program during the 13th Five-year Plan Period of China (Grant No. 2016YFC0702104), the Sino-German Center Research Program (Grant No. GZ1162), and Science and Technology Commission of Shanghai Municipality (Grant No. 16dz1206502, Grant No. 16dz2250500, Grant No. 17dz1203405, Grant No. 18dz1205604).

References 1. Flo&Jet/SHoP Architects: Available from https://www.archdaily.com (2018). Accessed 16 December 2018 2. ONECITYPAVILION: Available from https://www.branch.technology (2018). Accessed 16 December 2018 3. Hack, N., Lauer, W., Gramazio, F., Kohler, M.: Mesh mould: robotically fabricated metal meshes as concrete form work and reinforcement. In: Ferro-11 and 3rd ICTRC (2015) 4. Huang, Y., Carstensen, J., Mueller, C.: 3D truss topology optimization for automated robotic spatial extrusion. In: Proceedings of IASS 2018 (2018) 5. Simondetti, A., Luebkeman, C., Uerz, G.: 2060: an autonomously crafted built environment. Archit. Des. (2017) 6. Yuan, P.F., Chen, Z., Zhang, L.: Application of discrete system design in robotic 3-D printed shell structure. In: Proceedings of IASS 2018 (2018)

Application of Robotic Arm Technology in Intelligent Construction Yue Tong and Zhen Xu(&) School of Architecture in TJU, Room 311, 21 Building, 92 Weijin Road, Nankai District, Tianjin 300072, China [email protected] Abstract. Information technology is booming, and digital fabrication or intelligent construction will be an important key point in the industrialization of buildings. In recent years, the research of digital technology in the field of architecture design is more about the prototype generation in the concept stage, lacking digital entities of physical output that can get feedback. China started late in these two areas, and it is important to study the intelligent construction in the industrialization of buildings. Intelligent construction requires digital text, digital design, digital control processing, digital fabrication, and intelligent management after completion. This reflects informationization to promote the transformation and upgrading of manufacturing. Slip Forming is one of the most widely used construction techniques. Nonlinear geometries produced via algorithmic design processes are not easily achievable through traditional rigid formwork process. Now a more intelligent slip forming process is required to efficiently represent digital physical entities. This paper firstly sorts out the intelligent construction under the background of 4.0 era, its history, construction method, equipment technology and construction practice. The paper presents a digital formwork processing developed to work in conjunction with a 6-axis robotic arm for shaping doubly curved column based on the traditional slip forming technique. The research findings are intended to explore the intelligent production of nonlinear panels, and proved that this unique slip forming is a more sustainable method of robotic construction in 4.0 era. Keywords: Robotic arm
Digital design
Digital fabrication
Programmable physical material
Architecture industrialization

1 Introduction As architects, the tools in our hands have been changing, architecture has evolved to complexity and high integration, and the deep involvement of digital tools is a matter of course. Digital technology has been widely extended and applied in various fields of people’s lives, and architectural design has also been pushed to a new historical process [1]. The penetration and influence of the digital architecture is also becoming increasingly obvious. It has evolved from early auxiliary drawing to current numerical simulation, digital design, digital management, digital construction, etc. At the same time, digital technology expands the extension of architectural culture and promotes a new architectural aesthetic - digital culture. © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 331–345, 2020. https://doi.org/10.1007/978-981-13-8153-9_30

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In recent years, the exploration of digital technology in the field of architectural design is more of the form-finding of the conception stage (digital design), the lack of actual construction (digital construction) that can be tested and fed back, which cannot solve the need for the upgrading of China’s construction industry. The application of digital technology and the industrialization of buildings will be the development trend of the construction industry, reflecting the transformation of manufacturing industry driven by information technology. With the increasing number of digital construction practices in the field of architecture, advances in the output of physical forms have become the focus of attention in the architecture construction. The digital technology seminar of architecture colleges hosted by Chang’an University in 2018 is based on the theme of “Digital Technology
Building Life-Cycle” to discuss its application in such core aspects as design conception, design expression, performance simulation, technology optimization, construction reality and digital management, which are the expansion and transformation of the architectural design paradigm, and the opportunities and challenges for the construction industry are discussed.

2 From Industrial Manufacturing to Intelligent Construction Compared with the architecture construction, the application of information technology and numerical control technology in the manufacturing fields of automobiles and ships has matured practical experience from digital design to digital manufacturing. In the past 100 years, the high-efficiency assembly line developed by Ford Company of the United States is the standard production mode of the manufacturing industry. It completes the design, processing, assembly and inspection of automobiles through the transmission of digital information. Beginning from the assembly line developed by Ford to the application of the industrial robotic arm, industrial manufacturing has completed the leap toward intelligentalization (Fig. 1). Entering a new era of development, with the rapid advancement of digital technology, the continuous updating of construction technology and construction materials has become the most active development factor of AEC (architecture engineering construction).

Fig. 1. Automotive assembly line completed by robotic arm

Such new engineering concepts as “Industry 4.0” and “Made in China 2025” put forward new requirements for the quality of engineering talents. First of all, architecture carries not only imagery information from the cultural perspective, but also the sharing,

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connection and multidimensional space-time integration generated by digits. Secondly, as a new engineering discipline, architecture deeply integrates with structure science, materials science, computer programming, machinery manufacturing, etc. Thirdly, with the introduction of algorithm design and industrial robotic arms, architecture is experiencing the process of integration of virtual and reality. Digitalization, networking and intelligentalization have become the characteristics of new architecture engineering [2]. Professor Xu Weiguo pointed out that since the launch of DADA six years ago, the relevant industries have realized that the future development depends on digital culture. Today, architects are standing in the forefront of the industry to promote new industrial chains. Intelligent construction will become the development direction of the construction industry. As is known, digital culture reflects two basic characteristics of digital architecture in the new era: the first is digital architectural design; the second is intelligent construction based on digital design. The foundation of digital design is to design with parametric tools. The generative design we often refer to is a category of digital design, which refers to the use of computer-run correlation algorithms, digital graphic theory and the philosophical thoughts of complexity science to ultimately help the designer to perform formfinding at the program stage. It can be said that the combination of algorithm design and computer graphics makes digital design begin to touch deeper design thinking, helping designers to more accurately compare and optimize designs. The results include fractal architecture design, the emergence of complex structures, and architectural design of biological forms. Intelligent construction is based on digital architectural design, using professional software programming to control machine tools, 3D printing equipment, industrial robotic arms, etc. through numerical control methods. With a variety of materials, it is possible to build both ordinary buildings and nonlinear buildings. Intelligent construction requires digital text, digital design, digital control processing, digital fabrication, and intelligent management after completion. Therefore, we put forward new requirements for our architecture design: architects need to understand digital design and digital construction, and future designers will complete an entire set of digital processes of intelligent construction such as digital design modeling, path programming, and processing machinery control.

3 Industrial Robotic Arm and Digital Fabrication 3.1

Development of Digital Construction Facilities

In the late 1990s, the imbalance between digital design and construction could not be ignored. After 2000, Digital Fabrication gradually appeared in various experimental programs, and architects began to pay attention to the docking and integration of data from design to construction. The practitioner converts the 3D model into machining data through industrial software analysis and outputs the actual components. These components are particularly suitable for on-site constructing and assembling because of their unprecedented industrial-grade standards in precision [3]. Starting with a three-axis CNC machine developed by MIT Labs in 1952 to laser cutting machines and 3D printers, to five-axis machining centers and industrial robotic arms, the

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upgrading of digital construction methods allows architects to customize digital processing examples to achieve complex designs. It is a new revolution beginning with artificial intelligence, unmanned control technology, virtual reality technology, and quantum technology. Therefore, design method, component production, and actual construction are gradually integrated with digital technology. The future architectural design encourages personalized customization and flexible production. The concept of “modules” in design will be replaced by the concept of “parameters”. Machine adapts to people’s needs, which is also a demand for “Industry 4.0” to complete “intelligent construction.” 3.2

Method Transformation of Digital Construction

At present, the construction industry, which is dominated by traditional construction methods, is gradually being replaced by digital processing methods. Digital construction has just emerged in the field of construction for more than ten years. Although the application of robotic arms in industrial manufacturing has become very popular, in the construction field it is a new tool based on numerical control equipment. Therefore, some European and American universities have taken the lead in trying the application of robotic building in the construction field. For example, the Aachen University of Technology in Germany sets up a construction training course at the master’s level, which includes a series of simulation experiments. As shown in the figure, the graduation design of a graduate student Dai Rushi (Fig. 2) studies the hoisting technology of robotic technology in assembled prefabricated component site. As the population ages, labor is becoming less and less, and labor costs are getting higher and higher. The number of workers in China is now about half that of a decade ago, and the increase in labor costs has led to a significant increase in construction costs. For example, the use of robots can open the transition of component assembly from standardization to customization. Intelligent construction is a concern for human nature, which can free workers from hard work, and the intervention of the robotic arm can make it reach Industry 4.0. Intelligent construction-oriented design will pay more attention to the application of functional modules, as well as the generative design of functions, automatic generation of the component and space assembled design under modules driven by the computer technology. Therefore, we found that the biggest breakthrough for 3D printing technology and industrial robotic technology in the construction industry is that the architect is fully involved in the full data flow from design to construction. It really stimulates the designer’s comprehensive thinking on ontology issues such as material properties, structural properties, and construction logics.

Fig. 2. Intelligent construction of robots (left), future industrialization of buildings (right) (image source: Dai Rushi)

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Industrial Architecture Robot

The connotation of digital design is to replace and optimize the traditional technology on the digital platform, which is different from the communication relationship between “people, drawings and machines” in the electrical age. The second is that the digital age has not only made the communication medium between people more extensive and direct, but also made the communication and operation relationship between people and machines more automated and intelligent [4]. The craftsmen, i.e., the architect’s ancestors, have a natural connection with the site and the materials. Before the architects became a mature profession, they integrated the materials, design and construction process into the entire design process as a craftsmen. Since entering modernism, due to the construction period and production efficiency requirements, the architects are separated from and the construction by factories and machines. The emergence of industrial assembly lines has made mass production a major materialization means for large-scale construction. The design process and construction process were fragmented, and the architect’s role was reduced to “drawers.” This was because such real-world production factors as cost confine the design scope to standard component selection. Therefore, as a tool for intelligent construction, robots let the architect return to a traditional craftsmanship. Before the robot entered the construction field, digital construction equipment generally included CNC machine tools, laser cutting machines, and 3D printers. Traditional 3D printing technology has many advantages, but it is also subject to the constraints of materials and equipment. First of all, in terms of machining scale, 3D printers are limited by the size of the printing platform in the printing large building components, and the CNC equipment is still subject to greater limitations in the general desktop level. The robotic arm has a working range that exceeds the desktop level of the CNC and has the ability to flexibly move. For example, robotic arm can set the working area according to different processing requirements (Fig. 3), and fix it on the wall or ground rail. Secondly, 3D printers materials are also limited by the low cost plastic (PLA) bending resistance, while the robotic arm is less limited by materials. Thirdly, the robotic arm is a multi-axis automated programming machine with an open tool end, so it is also a digital technology process, and its construction mode is quite different.

Fig. 3. Robotic arm fixed on the ground rail (left) or on the mobile platform (right)

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4 Construction Robotic Practice 4.1

Foreign Robot Construction Practices

In the past decade, Fabio Gramazio and Matthias Kohler have been pioneers in the field of architectural robotics at the Eidgenössische Technische Hochschule Zürich, Switzerland, where they are foremost in digital design and digital construction. They were the first to introduce advanced equipment such as robots and drones into the field of building construction. They established the world’s first construction robot laboratory at the Eidgenössische Technische Hochschule Zürich, Switzerland. The two professors as pathfinders actually spawned a new interdisciplinary field: the combination of hardware and software through robotics and computer technology to achieve the architect’s imaginative design through intelligent construction. For example, the latest research focus is on how the architects can broaden the product design scope through the material potential in difference and form complexity based on robotic arm technology. The D-Fab House (Fig. 4) project is a construction practice on site completed by some laboratory professors with robotics under the support of the Swiss government, relevant research departments, and large construction companies. “Smart slab” project, which was one of the research topic in D-Fab House, is a sand-type three-dimensional printer robotic arm technology. The concrete of D-Fab House used in the study is specially made, and concrete slabs and walls are cast by sand molds. It can be seen from the photos that the material employed by the ETH scholars in this study is concrete, which is consistent with the sand-type three-dimensional printing technology they have studied before, i.e., using a three-dimensional sandblasting printer to print concrete molds, and then inject special concrete developed by the school of materials in ETH in the mold.

Fig. 4. Overall assembled D-fab house (image source: D-fab ETH)

Different from the giant sand-type three-dimensional printing components in the past, that time, the modular concrete-formed components are the study of the integration of structure and decoration. This special-shaped component processing based on the robotic arm process was also presented in the study of related template casting technology at the University of Sydney in 2017. Nowadays computational design geometries processes are not precisely reproduced through rigid formwork and are subjected to increase material waste. But the Non-liner fabric formwork is developed to

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work in conjunction with the 6-axis robotic arm for casting doubly curved panels [5]. At that time, the experimenter used the robotic arm to complete the processing of the hyperboloid fabric template. With the advanced digital simulation methods, the digital building design and construction method based on the robot processing platform has some advantages that the traditional construction methods cannot match: the process is rather complicated and the assembly buildings are highly customized. 4.2

Domestic Robot Construction Practice

Each technological breakthrough foreshadows the transformation and innovation of the construction industry, be it in the traditional handicraft industry period or in the mechanical production period after the industrial revolution. In the past, the goal was to achieve or restore a specific single design. After the third industrial revolution led by computer and information technology, construction activities focus on how to achieve automatically loading information multi-objective and customized products. The construction method under numerical control technology directly affects the architectural form and structural design. 3D printer and industrial robot technology make the building transform from design to a continuous and complete industrial chain. Professor Yuan Feng pointed out that as an intelligent construction tool, robots can make architects return to a kind of “artisan spirit”. Robotic construction can directly use digital design information to complete refined design that traditional manual construction cannot complete, improve component manufacturing precision, and improve work efficiency. The “Chishe” digital construction project (Fig. 5), which was designed by Professor Yuan Feng of Tongji University, is best known for its external wall texture, which was completed by robotic arms. First the mortar is prepared, then the worker paints, and then the robotic arm successively changes the direction to pick up the bricks, and find the position positioning. The intelligence is reflected here. The labor cost is reduced during construction, and this combined construction is only one of the ways to realize digital architecture.

Fig. 5. Robotic technology makes the “virtual digital twins” a reality

There are still a large number of projects to be built in China. From the current situation, a lot of manual operations are needed, but in the future, labors will be replaced by machines in mass construction activities, which will be an irreversible trend. In the face of the above challenges, the higher education of construction is also actively responding, and exploring the appropriate teaching content. In recent years, the

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School of Architecture of Tsinghua University has carried out curriculum reforms for undergraduate and postgraduate students, and has joined the theoretical exploration in the fields of digital design and robotic construction. The studies focus on the research of future development ways of digital fabrication with robots. Under the auspices of Professor Xu Weiguo, the School of Architecture of Tsinghua University has set up a “Nonlinear Architectural Design Course” based on algorithmic generative design since 2004, relying on a series of academic activities of DADA, through the construction of workshops, international conference forums, exhibition activities to show the research frontiers and developments in the field of digital design and construction for undergraduates [6]. Since 2015, undergraduate graduation design has begun to explore teaching research on algorithmic design and robotic construction. First, it expands the creative path and implementation of architecture from design to construction. Second, it fully demonstrates the dual role of digital construction in design and creation, and is dedicated to the connection and integration between digital illustration and robotic construction. The whole teaching is carried out with the construction as the core, which mainly includes three links (Fig. 6). The course starts from the prototype study of bionics and explores the intrinsic relevance of “geometry” and “structure”. Through robotic construction, students are encouraged to think about architectural geometry, structural performance, material properties and construction process.

Fig. 6. The scheme of robotic construction curricula

The latest construction practice is the result of the CAADRIA Tsinghua Workshop in 2018. Tsinghua University School of Architecture - Central South Land Digital Building Center is a research team dedicated to systematic research of architecture intelligent construction with Professor Xu Weiguo as its core. Its self-developed multicolor concrete printing technology has narrowed the gap between China and Europe and the United States. As a new construction method, 3D printing technology brings not only the improvement of production efficiency, but also the potential of creating new architectural forms. The “Bending Labyrinth” project demonstrates the precise spatial positioning of the robotic arm, the scientific control of the performance of concrete materials, and the synergistic printing of multiple robotic arms, thus effectively presenting the complex form of digital architecture. This design prototype uses the mitochondrial inner membrane morphology, and the mitochondrial morphology is

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applied to the curved shape by simulating the decidual morphology of the mitochondrial inner membrane fold (Fig. 7). In the construction stage, the large-diameter print head is first used to print the curved base block. After the base is formed, the two robotic arms cooperate to complete the printing of the upper space curved body (Fig. 7).

Fig. 7. Collaborative extrusion printing prototype of robotic arm (image source: CAADRIA 2018 Tsinghua workshop)

5 The “Digital Landscape Wall” Project 5.1

Background: The Mass Customized Robotic Arm Digital Processes

Since the first industrial revolution (1760–1820), manufacturing has flourished in largescale production, construction practices have been simplified into basic processes in factories. This often makes it difficult to reproduce the complex nonstandard components in digital design, and the efficiency of material utilization by this production method is low, indicating that it is difficult to use the traditional standard tools to customize the nonlinear design. Slip Forming refers to the construction of a fixed-size formwork that is pulled by the equipment and is generally applied to the construction of the on-site building. Traditional Slip Forming construction uses hydraulic jack as the lifting power, with a rectangle template about 1 m sliding upward along the concrete surface, and the construction material is poured layer by layer. After reaching a certain strength, the template will continue to slide, and finally reach the design height of the component. It usually can be used to sharp the geometric components which is formed by regular sections. The traditional Slip Forming process is combined with the robotic technique, which means, the unique digital processing can generate nonlinear geometric components, and also can greatly reduce the use of materials. The interactive installation of “Vintage Digital Landscape Wall”, designed by Lei Yu’s studio “ASW”, is the actual construction project which the author participated in. The ASW team aims to develop a digital construction process based on the Slip Forming which is to introduce the robotic technique into the mass nonstandard customized production during the “Industry 4.0”. The research object in this case is special-shaped column, and the research technique is the nonstandard digital componentization of concrete columns. After a series of algorithmic form-finding, structural optimization, design analysis of robotic arm path programming, material experiments, and the fixture tool design, this project made a research for the architecture industrialization of the industrial 4.0 era.

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5.2

Parametric Prototype

The prototype of the landscape wall is parametric design of the special-shaped column (Fig. 8). The shape of the component is not a plane but a hyperboloid. The degree of rotation of the rectangular section is used to control the form-finding of nonlinear shape of concrete column. As mentioned earlier, the advantages of the robotic technique in industrialization: load bearing (bearing hundreds of kilograms of load), flexibility (larger scale of processing space), accuracy (accuracy of industrial scale), so the use of new digital processes can create complex nonstandard forms with traditional materials.

Fig. 8. Parametric form-finding of hyperboloid rotation degree (image source: ASW)

5.3

Structural Optimization

In this part, we combined the concrete material experiments, adjusted the rotation degree of the nonlinear-shaped column by Grasshopper (Fig. 9), optimized the structure and appearance of the special-shaped column, and controlled the curvature of parametric prototype of the wall.

Fig. 9. In grasshopper, the rotation algorithm has been used to create the prototype of 0°, 15°, 30°, and 45°. Different torsion angle of the parametric prototype of the landscape wall (image source: ASW)

5.4

Slip Forming Process Based on the Robotic Arm Path

The robotic technique can embed the Slip Forming process based on the multi-axis spatial positioning lifting process, and the nonlinear-shaped form generated by the

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material construction during the process of the 6-axis robotic arm control is the customized nonstandard design building component (Fig. 10). We can find that digital design and robotic technique are reshaping the connection between design and construction, integrating parametric prototype, materials and construction process. The construction based on this technique is represented by the digital construction process in the physical environment, which firstly is the simulation test of the digital information model in the virtual space, and then the nonstandard prototype is finally converted into the real construction code (KUKA robotic language). Under through the torsion angle of the robotic arm path, nonlinear-shaped column is shaped by the Slip Forming process, and the final shape of the concrete special-shaped column is coagulated and shaped into the hyperboloid form (Fig. 10). The robotic technique provides an effective way to control the form-finding of the nonlinear-shaped parametric prototype, allowing the concrete material to fulfill the complex nonstandard building component.

Fig. 10. The column simulation in the virtual space controlled by the torsion angle of the flange (image source: ASW)

5.5

Concrete Construction Practice

The far-reaching effect of the intervention of the robotic processing is to incorporate the physical properties of the material into the construction action, such as outputting speed, rotating speed of the flange. The construction properties of the material are excited under the robotic arm platform, and the material physical properties which is the matter of material programming can be perceived by the robots. This kind of material programming use the concrete as the “generative form” design method to explore the form of the building component via new technique. It has been proven that fiber concrete can effectively control the concrete condensation time. In addition, many fabrics (polymer or FRP) helps to increase concrete tensile properties. 5.6

Robotic Arm Path Planning

The path planning of the digital Slip Forming process of the hyperboloid column can control the fixture of the robotic arm move on the established path, so that the movement path of the robotic arm is matched with the customized path, which is, let the path of the robotic arm from the simulation of the virtual space to the construction of the physical environment. Therefore, the construction strategy is that geometric

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section planes is rotated at different angles according to the torsion angle of the trajectory curve at different elevations. The path planning make the prototype become facets, lines, and points. So the special-shaped columns will be to extract geometric information: coordinates, curvature, and normal vectors. When this geometric information is converted into the logic motion of the robotic arm, the most important is to associate the coordinates of the tool center point of the robotic arm with the center point of the flange (Fig. 11). Since the robotic arm follows the inverse kinematics algorithm during motion, the offset between the coordinates of the center point of the flange and the tool center point (TCP) is very important. It is related to the real-time conversion between the coordinates of the tool center point (TCP) to determine the space location of the robotic arm (Fig. 11).

Fig. 11. The offset of the flange center and the TCP (image source: AGF)

In the path planning of the digital Slip Forming process, based on the motion trajectory of geometric prototype of each special-shaped column (Fig. 12), the coordinate plane of the tool center point of the robotic arm from the previous point to the next point is obtained. Each trajectory is disassembled for the geometric prototype of 115 special-shaped columns with different postures, depicting the motion trajectories of 115 corresponding robotic arms (Fig. 12).

Fig. 12. 200 sectional planes for each column, center coordinates of each sectional plane constitute a motion trajectory (image source: ASW)

Extract the construction plane of the modified plane of the rectangular center point, input these construction planes into the KUKA|PRC core operator, generate KUKA Command, and then connect KUKA Command operator, KUKA Tool operator, KUAK Simulation operator to KUKA|PRC core operator, generate the movement planned path of the robotic arm manipulated by KUKA Robot Language (Fig. 13).

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Fig. 13. Path planning by KUKA Robot Language, manipulate simulation by robot (image source: ASW)

5.7

Actual Construction of the Robotic Arm

The key to the precise and efficient machining of the robotic arm lies in the development of its end fixture tool (Fig. 14), which is also inseparable from the materials and time when implementing the digital Slip Forming process. The fixture is pneumatically three-dimensionally printed and can be quickly opened and closed to ensure

Fig. 14. Fixture tool (image source: ASW)

Fig. 15. On-site construction (image source: ASW)

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Fig. 16. Day view and night view (image source: ASW)

the length of time which the concrete needs to be coagulated during construction (Fig. 15). The project aims to develop a novel formwork process system for free-form concrete components to create custom, complex concrete buildings (Fig. 16).

6 Conclusion This paper explores the development trend of digital technology in the new industrialization of buildings, and explains the advantages of robotic technique in the field of intelligent construction. The platform for digital design and digital fabrication integration symbolizes the upgrading of manufacturing industry driven by information technology. This will be an important issue for the future of the architectural education community. However, during the late industrial era, the architect and the construction were separated by the factory and machines, so the design process and the fabrication process were separated. Now we see that with the strong support of digital technology, the torch that regains the craftsman spirit is ignited. In this paper, the research on robotic arm technology in intelligent construction is at an early stage. In the future, it is necessary to explore from the aspects of construction tools, materials and processing technology, so as to make the utmost of the advantages, led by intelligent construction, of the digital design, factory customized components and on-site assembly.

References 1. Zhong, G.: The ambition of the robotic arm—the construction thought transformation from the perspective of digital control tools. J. New Archit. 23–25 (2016) 2. Yuan, F., Zhao, Y.: The educational transformation of intelligent new engineering. In: Proceedings of 2018 National Conference on Architecture’s Digital Technologies in Education & Research, pp. 6–12. China Building Industry Press, Xi’an (2018) 3. Xu, Z.C.: BIM Application Design. Tongji University Press, Shang Hai 4. Yu, L., Tong, Y., Zhu, X.: In: CAADRIA2018 Workshop: The 23rd International Conference on Computer-Aided Architecture Design Research in Asia. Journal of Architecture Technology, pp. 22–25 (2018)

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5. Yang, X.Y., Koh, S.J.S.: Robotic variable fabric formwork. In: The 22nd International Conference on Computer-Aided Architecture Design Research in Asia, pp. 873–888. CAADRIA, Hong Kong (2017) 6. Xu, W., Li, N.C.: Architecture Digital Illustration of Biological Forms. China Building Industry Press, Beijing (2018)

Urban Memory Accessor: Mechanical Design of Interactive Installation Based on Arduino Wenhan Feng(&) and Yueyue Wang Shandong University of Science and Technology, Qingdao, China [email protected] Abstract. With the development of cities in China, the old cities usually need to be demolished and transformed, which leads to a lack of urban culture. The project proposes a solution to preserve the memory of the old city through interactions with the interactive installation - “Urban Memory Accessor”, thus continuing the urban context. With the drip glue craft, the installation will use UV resin glue to bond the traces of life left after the old city removed and convert it into craft products - “City Memory Cube” to deepen the public’s perception of urban memory. The installation is controlled by the Arduino microcontroller to implement the interactive process. Rhino and Grasshopper were used for interference detection and mechanical transmission simulation. What’s more, the power system scheme consisting of servos and rods was also used in this project. The installation was ultimately made of resin and acrylic sheets. It combined installation art with urban public spaces in order to save the old memories and improve urban space quality. Keywords: Interactive installation Arduino
Urban memory




Installation art




Mechanical design




1 Introduction With the rapid development of the economy, many cities in China are facing the problem of lacking of valuable urban culture. Rapid urbanization makes urban culture impetuous, single, frivolous and utilitarian, which leads to the problem of large-scale demolition, construction and similarity in urban style [1]. This resulted in a contradiction between urban development and urban culture. In this process, due to the importance of the old city to urban culture, the problem of the demolition of the old city has received more and more attention. In urban development, with the demolition and transformation of a large number of old cities, the urban culture contained in the old city gradually disappeared. It is believed that passively preventing old city reconstruction and urban renewal in urban development is negative and undesirable. In addition to developing effective political solutions through the government at the macro level, it is necessary to find a simple and direct remedy. Urban memory is a very important concept in the transformation of old cities. It is closely related to urban characteristics and urban culture, and it is itself a process of interaction between the public and the urban environment [2]. This paper hopes to solve the shortcomings caused by the demolition of the old city from the perspective of © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 346–354, 2020. https://doi.org/10.1007/978-981-13-8153-9_31

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urban memory, that is, to design an interactive installation to preserve the memory of the old city and to continue the city’s context. By interacting with the installation, the public can convert the traces of life after the demolition into craft products: “City Memory Cube”. The process product is based on drip glue craft, a common process in product design [3]. This paper will discuss the operation of the installation in detail and perform interference detection and mechanical transmission simulation through Rhino and grasshopper. At the same time, the power system scheme consisting of servos and rods was studied in the scheme to ensure the feasibility of the design. The control system of the entire installation is based on the Arduino microcontroller, which is a common control module in interactive devices [4]. The interactive installation was finally made using resin and acrylic sheets. This interactive installation is called “Urban Memory Accessor”.

2 Design of Urban Memory Accessor “Urban Memory Accessor” means that the installation is similar to a distributed storage disk and is able to store and read city memories. The specific process and content of design and research will be described in detail below. 2.1

Design Background

At the beginning of the project, visits and investigations in the old city of Qingdao were conducted. Due to its unique history, a large number of Chinese and foreign eclectic styles of “liyuan” have been formed in the old city of Qingdao, which is one of the city’s business cards in Qingdao. However, due to the development of the city and the aging of the building, from 2017, the Qingdao government began to collect liyuan buildings, trying to carry out a unified transformation. The author of this paper conducted research around Zhongshan Road. Through research, it is found that most citizens have a strong reliance on the community and do not want to move out of the current house. Moreover, almost everyone has raised concerns about Qingdao’s urban culture [5]. Therefore, the author hope to make some positive and interesting attempts for the community through the means of artistic design. Trying to explore the changes that installation art can bring to the community in the current rapid urbanization and urban transformation background. 2.2

Mechanical Design and Operation Simulation

The installation is rectangular in shape and measures 1800 mm  400 mm  400 mm. The “City Memory Cube” is designed as a 200 mm  200 mm cube. The main function of the installation is to enhance the meaning of urban memory through interaction and project the city memories of the old city into the craft products. In this way, urban memories can be preserved by interlocutors in the form of works of art, rather than disappearing as the old city disappears.

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2.2.1 Operational Process Design The installation consists of a processing section and a raw material storage section, the two sections being connected by a rotating shaft. The upper part of the processing section is used to store the glue, and the lower part is the space in which the product is made. The upper part of the raw material storage section is used to store the raw material, and the lower part is used to place the rotating shaft and connect the two sections. Inside the installation, there is a mold for manufacturing the product, and there are push-pull devices and lifting devices to allow the mold to move in the front-rear and up-down directions inside the installation. In the initial state, the mold is located in the processing section. After the interaction process starts, the mold needs to be pushed into the raw material storage section to obtain the raw material, then pulled back to the processing section. The glue will be poured into the mold and solidified, and then the mold will be lifted by the lifting devices so that the product can be taken out from the product outlet. The installation uses UV resin glue, which can achieve a good solidi-

Fig. 1. Design drawing

fication effect within five minutes under the irradiation of ultraviolet light (Figs. 1, 2). The entire interaction process is divided into four steps: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

The people use the phone to scan the QR code to start the interaction process. The people control the material addition process by rotating the shaft. The people wait for the product to be completed. The people take the product. Accordingly, there are seven states of machinery inside the device. Original state. The raw materials enter the mold. The raw materials stop entering the mold. The UV resin is glued into the mold. Turn on the UV lamp to cure the resin drop (5 min). Launch the completed “City Memory Cube”. Return to the original state.

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Fig. 2. Process

2.2.2 Power System and Mechanical Design The power system is the key to achieving mechanical operation. In the installation, servos are used to drive. The servos are a traditional angle control driver widely used in robotics and other fields and can be well matched with Arduino [6]. According to the actual needs of the project (push-pull devices and lifting devices), the author studied the operation of a power system consisting of a servo and three rods to make the machine operation more precise and controllable. The system consists mainly of three rods connected in series, and the two connection positions can be rotated. This system is similar in construction to the classic 3R robotic arm, but has more limitations than the 3R system. Among the three rods, the lengths of the rods on both sides are the same. The unconnected points of the rods on both sides and the midpoint of the middle rod are on the same line. When the intermediate lever is rotated, the positions of the two connection points are changed and the total length is reduced. The reduction amount d can be calculated according to the formula 1. As shown in the Fig. 3, the amount of contraction is represented by d, the length of the middle rod is a, the length of the rods on both sides is b, the angle of rotation of the middle rod is h, and D is the x coordinate of the two endpoints after the movement of the rods on both sides Amount of change. c is a constant, related to the value of a, b. The calculation of c is more complicated, and its value does not affect the trend of the function, so we do not expand in detail.
 a cos ha d ¼ 2 ð þ bÞ  ðD þ Þ c b 2 D¼

a cos h þ sin c

0:03 sin hab0:1 b0:1

2

0:06

c

ð1Þ ð2Þ

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Fig. 3. Schematic diagram of each variable and relationship

When taking a = b = 100, the formula can be simplified to: D1 ¼ 50 cos h þ 554:445 sinð0:0943421 sin hÞ csc h

ð3Þ

d1 ¼ 200 cos h þ 554:445 sinð0:0943421 sin hÞ csc h

ð4Þ

At the same time, the size of the installation can be calculated to expand perpendicular to the telescopic direction, which is calculated by formula 5 and 6. From this, the space required for the power unit can be calculated in order to avoid collisions with each other. pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi b2  D2

ð5Þ

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1002  ð50 cos h þ 554:445 sinð0:093421sin hÞ csc h2 Þ

ð6Þ

l¼ l¼

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Through three Eqs. (3) (4) (6), It can be seen that the trend of each variable as a function of h. Verification shows that even if the values of a and b change, this trend still applies. In the device, the author in this paper need to push and pull the length of 60 mm and need to lift the length of 160 mm. After the experimental comparison, the author

Fig. 4. Rods size and stretchable length

finally determined the length ratio of the lifting device rods as a:b = 2:1, and determined the length ratio of the push-pull device rods as a:b = 1.5:1. The author entered the formula into Grasshopper and used Rhino to model the internal operation of the devices. Its size and the relationship between d and h are as follows (Figs. 4, 5, 6, 7, 8): 2.2.3 Arduino Programming This installation uses the Arduino UNO R3 model as needed. the servos of Push-pull part are number servo (1), servo (2), servo (3), servo (4); the servos of lift part are number servo (5), servo (6), servo (7), servo (8); the servo of the UV resin glue switch valve is servo number servo (9). Among them, (1), (2), (5), (6), and (9) are MG90S models; (3), (4), (7), and (8) are SG90 models (Fig. 5). The entire program control is divided into the following steps: 1. Arduino controls interaction beginning by mobile APP. 2. Turn servo (1), servo (3) in clockwise and turn servo (2), servo (4) in anticlockwise to realize push. 3. Raw material chamber block board was open to drop raw material because of gravity. 4. Turn servo (1), servo (3) in anticlockwise and turn servo (2), servo (4) in clockwise to realize push. 5. Turn servo (9) in anticlockwise to open switch of UV glue chamber. 6. Turn servo (9) in clockwise to close switch of UV glue chamber. 7. Turn servo (5), servo (7) in anticlockwise and turn servo (6), servo (8) in clockwise to realize raise (Watch from the left view). 8. Turn servo (5), servo (7) in clockwise and turn servo (6), servo (8) in anticlockwise to realize down (Watch from the left view).

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Fig. 5. Arduino control schematic diagram

2.3

Interactive Scenarios and Product Design

Interactive installation can often be the focus of space, it will enhance the appeal of urban public spaces [7]. In this project, the author hope to reflect its commemorative value and visual impact through a simple spatial cube form. It will affect the surrounding space and become a center of space within a certain range. The author also designed a certain urban furniture function for the installation. The interlocutor can rely on or sit in the cabin of the installation. Resin and acrylic sheets are used to make the installation by means of 3D printing and laser cutting. Transparent acrylic sheets enable the interactor to see the production process (Fig. 6).

Fig. 6. Installation photo

For the product “City Memory Cube”, The simplest three-dimensional shape is chosen to minimize the interference of the shape on the content and to enlarge the perceptibility of its contents. And the size of 200 mm * 200 mm matches the size of the hands (Fig. 7).

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Fig. 7. City memory cube craft product photo

Since building materials tend to be heavy, it is difficult to control the amount of raw materials entering the mold. In practice, the interactor can effectively control the amount of material by rotating the shaft. The shaft design is shown below (Fig. 8).

Fig. 8. Shaft design schematic diagram

3 Conclusion and Discussion Through the design of the interactive installation, the project explores the issue to the urban culture continuation problem in the transformation of the old city under the background of rapid urbanization and proposed a solution from the perspective of urban memory. After the power system research, mechanical design and Arduino programming, the entity of the installation was completed. The installation can make the “City Memory Cube” through the drip glue craft, which consists of UV glue and old city demolition waste. It shows people’s life traces and cultural scenes in the old city, to retain valuable city memories. After completing the project, through experimental observation, the author found that the interactive installation and installation art can play an important role in the reconstruction of public space. Interactive installations and public spaces can promote each other and enhance their value of urban space. In the design and construction of today’s urban space, especially in the current trend of smart city construction and development, interactive installation should be more involved in the urban public space to play a stronger artistic role [8]. It is believed that future research directions include the combination of interactive installations and IoT technologies and behavioral analysis of audiences targeting certain interactive installation to design more practical and meaningful installation art.

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References 1. Mingying, F., Ning, C.: Cultural Loss and Rational Rebirth during Fast Urbanization. Shanghai Urban Management (2012). https://doi.org/10.3969/j.issn.1674-7739.2012.02.003 2. Fang, W., Lin, Y., Bihu, W.: Collective memory of city planning: Xuanwu district in Beijing as a case study. Urban Plan. Int. 25(1), 71–87 (2010) 3. Na, D.: 3D printing with drop glue technology making fashion heel. China Leather 47(10), 57–61 (2018) 4. Bihong, L., Zhiyi, R., Haocheng, W., et al.: Soft architectural robot: design of a multi-layer composite material apparatus with PAM actuator and its architecture implications. In: Caadria17 International Conference on Computer Aided Architectural Design Research in Asia (2017) 5. Hui, L., Wenhan, F., Jingwei, Z.: Quantitative Evaluation and Improvement Strategies Exploration of the Vigour of Residential Historical and Cultural Streets and Communities. Shanghai City Management (2017). https://doi.org/10.3969/j.issn.1674-7739.2017.01.014 6. Ruiyan, C.: Design of servo control system based on Arduino. Comput. Knowl. Technol. 8 (15), 3719–3721 (2012) 7. Rudolf, F., Dieter, D.: Medien Kunst Netz 2/ Media Art Net 2: Thematische Schwerpunkte/ Key Topics. Springer (2005) 8. Qinghong, Z.: The application of interactive installation art in the exhibition design–Shanghai world expo for example. Doctoral Dissertation, Jiangnan University (2013)

Path-Optimizing Agent-Based Earthwork System: a Microscopically Precise Earthwork System that Is Adaptable to Any Form of Landscape Zixiao Ji1 and Yuqiong Lin2(&) 1

GSAPP, Columbia University, New York, NY, USA [email protected] 2 CAUP, Tongji University, 200092 Shanghai, China [email protected]

Abstract. Along with the development of the landscape design and robotic technology, the traditional methods of the earthwork for the landscape can no longer adapt to highly artistic and customized landscape due to the overwhelming in term of time, effort and cost, as well as the low precision to conduct micro-level earthwork. Thus, the automation of the earthwork operations has been widely studied. This paper introduces an autonomous earthwork system which takes one or several robot agents to detect the difference between the initial terrain and the target terrain, and gradually shape the initial terrain toward the target terrain so that in the end the target terrain is formed from the initial terrain automatically. Different levels of intelligence are added to the system including path-optimizing with mathematic calculation, so that the robot agents are able to consider the factors of efficiency and time when they perform their function, and makes the system more precise and adaptable. Keywords: Autonomous earthwork system Robot agent


Agent-based
Path-optimizing


1 Introduction With the emerging of mobile robotics since last three decades, path planning algorithm and optimization in static as well as dynamic environments are questions becoming the most present research topic addresses [1]. An optimization route of the motion robot has to satisfy goals such as shortest path, lowest energy consumption, or right time, without colliding with the obstacle on its paths [2]. As an active research topics in artificial intelligence and expert systems, agents and agent-based approaches are recently being used as a promising tool for solving problems whose domains are distributed, complex and heterogenous [3]. For a traditional construction site, earthwork could be overwhelming in term of time, effort and cost of all the manual calculation and driving of excavators to move the soil back and forth. Moreover, the traditional methods are not precise enough to conduct micro-level earthwork. These defects make it difficult for the traditional methods to adapt to highly artistic and © Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 355–363, 2020. https://doi.org/10.1007/978-981-13-8153-9_32

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customized earthwork for landscape. To satisfy the increasing requirements of earthwork operations, the construction cry out for automation [4]. Thus, the study seeks to the agent-based approaches utilizing the mobile robot to optimize the earthwork. What the project tries to achieve is an autonomous earthwork system, which takes one or several robot agents to detect the difference between the initial terrain and the target terrain, and gradually shape the initial terrain toward the target terrain so that in the end the target terrain is formed from the initial terrain automatically. To achieve this, different level of intelligence is added to the system including path-optimizing with mathematic calculation, which is done within each iteration so that the agents can update themselves incrementally. This allows the robot agents to consider the factors of efficiency and time when they perform their function, and makes the system more precise and adaptable.

2 Tools 2.1

V-REP Platform

V-REP is a versatile, scalable, yet powerful general-purpose robot simulation framework, a cross-platform integrated development environment, based on a distributed control architecture, which suits for fast algorithm development, factory automation simulations, fast prototyping and verification, robotics related education, remote monitoring, safety double-checking, etc. [5, 6]. In the study, V-REP is used for the modelling of the robot agent and the terrains, as well as the scripting for generation of its motion path. 2.2

Robot Agent

As Fig. 1 shows, the robot is composed by a crawler belt, a soil processing device and a storage tank, which allows it to climb on any form of landscape, and perform functions of gathering, dumping and storage of soil.

Fig. 1. Robot agent of the earthwork system

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3 Methodology and Workflow The essential goal of the system is to make optimized agent behavior so that they could perform the functions of earthwork in a precise and efficient way. For the system to achieve the goal, several steps have to be completed: 1. Make a grid of points from the initial and target terrain. Each point has the same index for the initial and target terrain. 2. For each agent, find the index of the point on which the biggest difference between the initial terrain and the target terrain sits, locate the point and move the agent itself to the point. 3. Once the agent is on the point, there would be two situate/ions: if the target terrain is higher than initial terrain on the spot then the agent would gather the soil so that the initial terrain would fall on the spot; if lower, then the agent would dump the soil so that the initial terrain on the spot would bump. Each agent only moves small amount of soil within each iteration so the system is built up incrementally. 4. Repeat the steps above so that the initial terrain gets closer and closer to the target terrain. 3.1

Agent Path Optimization

In the beginning, the agent would make a grid from both the initial terrain and the target terrain, and detect the height value of the two terrains on each grid point, the Gray-scale figure of them can be seen as Fig. 2, in which the white parts means the positive values and the black means the negative. Since there is difference between the two terrains on each spot, the agent would make a table of difference of the values and automatically generate an image of it as Fig. 3.

Fig. 2. The initial terrain (a) and the target terrain (b)

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Fig. 3. The difference between the two terrains

For the table of differences, the negative values suggest that the initial terrain is lower than the target terrain on the spot, while the positive values suggest that the initial terrain is higher than the target terrain on the spot. For the agent, there would be two steps: 1. Detect the biggest difference in the table first which is a positive one, move to the spot and gather the soil; 2. Detect the smallest difference in the table which is a negative one, move to the spot and dump the soil. As shown in Fig. 4, the path of the robot agent would form a “gather-dump-gather-dump” loop.

Fig. 4. The path of the robot agent

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If for each iteration the agent would move to the spot that has the biggest difference, then it would take quite a while for the system to achieve the goal. So, there should be another factor of distance for the agent to decide which spot it should move to. To add the distance factor to the agent, the difference on each spot is divided by the distance between each spot and the agent, so the agent would consider the two factors of difference and distance and move accordingly. The path of the robot agent with distance factor included can be seen in Fig. 5. The distance factor is adjustable according to how efficient the system should be. With weakened distance factor, the agent would seek the spot that has bigger difference between initial terrain. And the path of the robot agent with weakened distance factor included can be seen in Fig. 6.

Fig. 5. The path of the robot agent (distance factor included)

Fig. 6. The path of the robot agent (weakened distance factor included)

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Multiple Agents Iteration

For each iteration of the agent-based earthwork system, the agent would recalculate the height value of the current terrain and the target terrain in a grid and make a table of the difference, so that the path optimization steps could be repeated. The system could take multiple agents to complete the task, since there is a local distance factor for each agent to optimize its path, they would work collaboratively and simultaneously. With the path-optimizing robot agent system, the process of the terrain’s changing can be seen as Fig. 7, and the final state of the terrain is shown in Fig. 8.

Fig. 7. The process of the terrain’s changing with the robot agents

Fig. 8. The final state of the terrain with the robot agents

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4 Quantification The volume of soil that is gathered within each iteration, which is the negative volume, and the volume of soil that is dumped within each iteration, which is the positive volume, are measured within each iteration incrementally. The changing of the positive and negative volume of soil over time are shown in Table 1 and Table 2 respectively. From the charts we can see that in the same amount of time the system with distance factor moves more than ten times amount of soil than the system without distance factor, Table 1. The changing of the positive volume of soil over time

Table 2. The changing of the negative volume of soil over time

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which means the distance factor could dramatically improve the efficiency of the system. The results show that the strategies can introduce intelligence to the automated system to generate a safe and effective path for remote or automated earthwork operations without human intervention and to execute earthwork in a hazard-free environment.

5 Conclusion Since the system is highly adaptable to any form of landscape and could be very precise in a micro level, the potential application could be small scale artistic landscape such as the dry landscape in traditional Japanese garden, or larger scale urban landscape like street parks, or it could be applied to earthwork of building construction site. The terrain of these landscape can be meshed and shaped by the system as Fig. 9 shows. Also, since the system mainly deals with the dynamic process of deformation, it could also be applied to simulation of soil movement and retention.

Fig. 9. Different forms of landscape

To make the system more intelligent in term of agent behavior, other factors could be considered such as the physical movement of the robot, the natural deformation of the landscape, sensing of obstacles and deeper collaborative work of the agents. Moreover, as the agents evaluate the terrain constantly, the target could be slightly adjusted by the agents within each iteration based on the factors, which would add another layer of intelligence to the system. With different level of intelligence added to the system including path-optimizing with mathematic calculation, the robot agents in this earthwork system balance the factors of efficiency and time when they perform their function, and promote the autonomous earthwork to be more precise and adaptable.

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References 1. Zafar, M.N., Mohanta, J.C.: Methodology for path planning and optimization of mobile robots: a review. Procedia Comput. Sci. 133, 141–152 (2018) 2. Raja, P., Pugazhenthi, S.: Optimal path planning of mobile robots: a review. Int. J. Phys. Sci. 7(9), 1314–1320 (2012) 3. Ratajczak-Ropel, E., Skakovski, A.: Population-Based Approaches to the ResourceConstrained and Discrete-Continuous Scheduling. Springer (2018) 4. Kim, S.-K., Seo, J., Russell, J.S.: Intelligent navigation strategies for an automated earthwork system. Autom. Constr. 21, 132–147 (2012) 5. Rohmer, E., Singh, S.P.N., Freese, M.: V-REP: a versatile and scalable robot simulation framework. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. (2013) 6. Robotics, C. V-rep, virtual robot experimentation platform (2018). http://www. coppeliarobotics.com/resources.html

On-Site Automatic Construction of Partition Walls with Mobile Robot and Computer Vision Hao Meng(&), Zhihao Liang, and Pengcheng Qi Tongji University, Shanghai, China [email protected]

Abstract. This paper demonstrates the implementation of an on-site mobile robot platform, equipped with computer vision system, which can automate the process of fabricating and construct standard partition wall with minimum human intervention. On the basis of this research, the following aspects are presented: (1) the physical setup and the customized multifunctional end effector that enables the robot to fabricate customized partition wall on site (2) the digital workflow that analyzes the geometrical information of the building components and generates robot operational code, while at the same time sets up communication between tracked mobile platform, robotic arm and end effector. (3) its capability to assemble wall panels in space accurately and align the structures dynamically through real time computer vision technology. The experiment provides an outlook to the possibilities of high accuracy construction of large scale building components with location aware mobile robot. Keywords: On site construction Adaptive fabrication




Computer vision




Robotic simulation




1 Introduction Construction has been one of the major social activities in history. With the continuous development of economy, construction work is predicted to keep growing in the coming years, leading to a huge demand in skilled labour force. Despite that traditional construction methods are usually time consuming and labour intensive, according to a recent US statistics report [1], labour shortage has consistently been a major challenge for construction companies. In the meanwhile, it is predicted that construction costs tend to keep rising primarily due to the increasing construction labour cost. Compared to factory manufactured construction components, on-site fabrication and assembly is generally more efficient and allows more possibilities in various construction conditions. By integrating a 6-axis robot arm with tracked mobile base and computer vision technology, an on-site automatic construction process could be established to reduce

© Springer Nature Singapore Pte Ltd. 2020 P. F. Yuan et al. (Eds.): CDRF 2019, Proceedings of the 2019 DigitalFUTURES, pp. 364–372, 2020. https://doi.org/10.1007/978-981-13-8153-9_33

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the human labour required to assemble each partition wall while allowing for certain real-time adjustment of construct those partitions into place. This paper introduces such novel on site robotic construction method and discusses its potential benefits.

2 Background 6-axis robot arm has been utilized in architectural construction in both research and commercial projects for a while in both prefabrication and on-site construction. ETH Zurich has been researching on mobile robotic fabrication in situ for many years [2] on a wide range of projects, including brick layering and steel bar welding [3, 4]. The Danish company Odico [5] is one of the pioneers using 6-axis robot arms to prefabricate building components in complex geometries. Another commercial company, Hadrian X [6], developed a robot arm system which can automatically build brick walls in a much faster speed than human brick layers (Fig. 1).

Fig. 1. Development of In Situ robot platform at ETH DFAB

Meanwhile, the rapid development of computer vision in recent years has also brought many benefits to the field of digital construction in architecture. For example, Bard [7] realized the real-time detection and classification of defects for robotic plastering by convolutional neural network; Asadi [8] used a 3D camera to combine the intensity map and the depth map to detect edge information during the robotic painting process. Recently, robots have evolved through new developments in sensing, real-time communication and data computation, which makes it possible to deploy robotic technology onto construction site which has dynamic and complex spatial conditions. This research tries to establish an on-site mobile robot station that can automate the process of fabricating and construct standard partition wall with minimum human intervention through advanced computational simulation and vision system, whose main features are described in the following sections.

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3 System Configuration 3.1

Physical Configuration

The prototype of the robotic system is designed to assemble and construct aluminum framed lightweight partition walls on site with the ability of customizing wall panels of variable width according to the measurements collected from construction site. As Fig. 2 demonstrates, the on-site automatic robot system consists of a 6-axis (ABB IRB2600 20 kg) robot arm siting on a RP01 mobile platform powered by lithium-ion batteries, which enable the platform to operate unplugged up to 8 h. The robot is armed with a basler industrial camera with 3856*2764 resolution and 0.03 mm/pixel accuracy for computer vision. There is a compact partition wall assembling station that collects raw materials of partitions and assists the robot to fabricate customized partitions.

Fig. 2. Physical setup

The end effector (Fig. 3) of the robot arm is a bespoke multi-functional toolhead combined of gripper, suction cup and screw drivers, which allows it to pick up a plaster panel from the storage area, cut it into various widths by moving it through a fixed table saw, place it to the designed location and then screw the plaster boards onto structure frames. This intelligent end effector enable a single robot arm to perform multiple tasks which normally requires two builders to work collaboratively. 3.2

Digital Work Flow

In the set up phase, the digital workflow starts from uploading a 3D model of the targeted partition wall into Rhinoceros. A script was written in Grasshopper plugin to generate the overall tool path for the 6-axis robot arm to execute the process of

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Fig. 3. Multifunctional end effector

fabricating specific wall panels with unique width parameter (Fig. 4), and then the robotic operational file is generated and uploaded to the control cabinet directly through a portable device carried by the operator through TCP protocols.

Fig. 4. Robotic simulation

Manually controlled by the operator, the mobile tracked platform transports the robot arm to a designated spot whose distance is relatively fixed with the assemble station, then through the portable Human Machine Interface, the operator could trigger

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the robot to conduct the fabrication process. After the panel is being fabricated, the robot uses its suction cups to hold the panel in place, and then the tracked platform carries the robot to the location where the panel needs to be fixed to the ceiling and ground with the help of the operator. During the process, a real-time interaction between the computer vision camera and the robot arm runs constantly to monitor and adjust the coordinates of target location known by the end effector to increase the construction accuracy and avoid accumulative error based on the live spatial data collected from physical site (Fig. 5).

Fig. 5. Digital workflow

4 Computer Vision Considering the structure and weight of the end effector of the robot arm, the camera was fixed in an eye-in-hand configuration while, ensuring that the camera can fully capture the local corner information of two partition wall panels that need to be installed next to each other on site. 4.1

Edge Detection

The complete partition wall edge information was fitted by the corner information, specifically, a smooth canny based on unsupervised learning [9] is used for edge detection. This algorithm based on the edge theory of Marr and Hildreth [10] to validate whether there is a significant luminance change or not along a candidate contour and Canny’s algorithm [11] to obtain the curve candidates. Additionally, on the basis of

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these, Grompone and Randall [12] makes use of the U test of Mann and Whitney [13] to evaluate image contrast and heuristics to accelerate the algorithm. After continuous testing, we found that this algorithm has better stability, accuracy and timeliness than simply using the Canny edge detection algorithm. In addition, the algorithm has been open source, considering the need for development progress; we chose to use this on our system. 4.2

Feature Extraction

After the edge was detected, the target edge points can be obtained by appropriate contour filtering. In order to make the feature extraction more stable and efficient, two algorithms were used here, one was the Hough transform, two edge line of the partition wall panels were obtained, and then the intersection point of the line was calculated to obtain the feature point. The other was to use the maximum distance method to obtain feature points, and then used the least squares method to fit the line information. 4.3

Maximum Distance

The Hough transform can accurately detect a straight line, but its detection speed was relatively slow. When the image was less disturbed (as shown in Fig. 6), the maximum distance combined with the least squares can be used to extract the feature information. Specifically, because there was not much change between images in actual situations, the intersection of the edge line and the edge of the image can be easily determined. For a triangle region consisting of ða1 ; b1 ; c1 Þ or ða2 ; b2 ; c2 Þ, after determining the points a1 ; b1 , searched for the points in the contour and calculated the distance between them and the line connecting a1 ; b1 , point c1 was where the largest distance, and the same as c2 . Then, according to ðc1 ; b1 Þ; ðc2 ; b2 Þ, the straight line information was obtained from the normal equation h ¼ ðX T XÞ1 X T y.

Fig. 6. Obtain feature information by maximum distance

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Finally the coordinate information was converted and delivered to the robot arm for deviation correction. 4.4

Coordinate System Conversion

In the computer vision system, after obtaining the information on the image, it was also necessary to convert it to the world coordinate system where the robot base coordinates were located, which requires camera calibration and hand-eye calibration. Camera calibration mainly relies on the Zhang’s calibration method, using the checkerboard to calibrate the camera’s internal parameters. It mainly includes the focal length of the camera ðfx ; fy Þ, optical center ðcx ; cy Þ. The hand-eye calibration mainly calibrates the conversion matrix between the camera coordinate system and the end tool head coordinate system ðHcg Þ. The camera follows the robot to move together, so a partial eye-in-hand approach was adopted. Here we used the Navy [14] hand-eye calibration algorithm, which used the knowledge of Lie group theory to solve the classical equation of hand-eye calibration After completing these calibrations, the points on the image can be converted to points in world coordinates by equation, and the values in the axial direction can be obtained by other sensors. 2 3 2 3 x u 6 7 1 6 y 7 z4 v 5 ¼ Hpc Hcg Hrg 4z5 1 1 where Hpc was the transformation matrix between the camera coordinate system 1 and the pixel coordinate system. Hrg was the transformation matrix of the end tool head coordinate system to the world coordinate system. Assume, 2

1 Hpc Hcg Hrg

a0 6 a1 ¼6 4 a2 a3

b0 b1 b2 b3

c0 c1 c2 c3

3 d0 d1 7 7 d2 5 d3

Then,    x ua2  a0 ¼ y va2  a1

ub2  b0 vb2  b1

1 

d0  ud2  ðuc2  c0 Þz d1  vd2  ðvc2  c1 Þz



Finally, the points on the image were converted to the robot coordinate system.

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5 Discussion Using this on-site automatic construction robotic system (Fig. 7), a lightweight plaster panel partition wall was assembled within a 10 min time frame and the assembly achieved ± 1 mm accuracy. The system barely needs human operation in the partition wall assembling process. The only labour required in theory is one person operating the portable interface, which therefore could reduce human labour required in such construction process. Although at current stage construction workers still need to further tighten the screws, this can be improved by a new end effector with more reliable capabilities.

Fig. 7. Mobile robotic platform at test ground

According to the measurement, it reduces the assembly time by 30% on average and thus is more efficient than traditional human labour. However, currently, the movement of the mobile platform is limited to programmed linear path. In next phase of research, the mobility of the platform can be improved to automatically generate its path according to the surroundings through 3D model input and environmental scanning. The research of such improvement is currently undergoing. The computer vision system can achieve a certain range of accuracy; however the information acquisition of 2D cameras in 3D space is always incomplete. Although the imaging plane of the camera can be paralleled with the target wall by adjusting the end effector, the three-dimensional information was projected onto two-dimensional plane for processing. Sometimes, the result was not as expected due to processing errors.

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However, despite the fact that the 3D camera can collect relatively complete spatial three-dimensional information, it was difficult to achieve the accuracy of 2D camera recognition when extracting feature information. Therefore, the improvement will combine both 2D and 3D cameras to first estimate the pose using the 3D camera and then adjust the end effector, before projecting the 3D information to the 2D plane, and finally use the 2D camera for image processing.

References 1. News Release: The Employment Situation—December 2018. Department of labour, US (2018) 2. Helm, V.: In-Situ fabrication: mobile robotic units on construction sites. Arch. Des. 84(3), 100–107 (2014) 3. Giftthaler, M., Sandy, T., Dörfler, K., Brooks, I., Buckingham, M., Rey, G., Kohler, M., Gramazio, F., Buchli, J.: Mobile robotic fabrication at 1:1 scale: the In situ Fabricator. Constr. Robot. 1(1–4), 3–14 (2017) 4. Buchli, J., Giftthaler, M., Kumar, N., Lussi, M., Sandy, T., Dörfler, K., Hack, N.: Digital in situ fabrication–challenges and opportunities for robotic in situ fabrication in architecture, construction, and beyond. Cem. Concr. Res. 112, 66–75 (2018) 5. Odico.dk: Odico. https://www.odico.dk/ (2019). Accessed 24 Jan 2019 6. FBR: FBR (Fastbrick Robotics), Industrial Automation Technology. https://www.fbr.com. au/ (2019). Accessed 24 Jan 2019 7. Bard, J., Bidgoli, A., Chi, W.: Image classification for robotic plastering with convolutional neural network. ROBARCH 2018, Robotic Fabrication in Architecture, pp. 3–15. Art and Design. Zurich, Springer Nature Switzerland (2018) 8. Asadi, E., Li, B., Chen, I.: Pictobot: a cooperative painting robot for interior finishing of industrial developments. IEEE Robot. Autom. Mag. 25(2), 82–94 (2018) 9. Grompone von Gioi, R., Randall, G.: Unsupervised smooth contour detection. Image Process. Line 5, 233–267 (2016) 10. Marr, D., Hildreth, E.: Theory of edge detection. In: Proceedings of the Royal Society of London B: Biological Sciences, vol. 207, pp. 187–217 (1980). http://dx.doi.org/10.1098/ rspb 11. Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8, 679–698. http://dx.doi.org/10.1109/TPAMI.19864767851 12. Grompone von Gioi, R., Jakubowicz, J., Morel, J.-M., Randall, G.: LSD: a fast line segment detector with a false detection control. IEEE Trans. Pattern Anal. Mach. Intell. 32, 722–732 (2010). https://doi.org/10.1109/TPAMI.2008.300 13. Mann, H.B., Whitney, D.R.: On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Stat. 18, 50–60 (1947). https://doi.org/10. 1214/aoms/1177730491 14. Park, F.C., Martin, B.J.: Robot sensor calibration: solving AX = XB on the Euclidean group. IEEE Trans. Robot. Autom. 10(5), 717–721 (1994)

Author Index

B Barsan-Pipu, Claudiu, 124 C Cao, Shuqi, 210 Chai, Hua, 303 Chang, Teng-Wen, 312 Chen, Chaoran, 145 Chen, Chun-Yen, 312 Chen, Zhewen, 322 Chen, Zhonggao, 219 Chengyu, Sun, 179 Cui, Qiang, 82 D Dong, Hexuan, 160 F Feng, Qianhui, 104 Feng, Wenhan, 346 G Ge, Kangning, 154 Gorgul, Ercument, 145 Guo, Tianyu, 49 Guo, Weipeng, 136 H Han, Li, 17 He, Wanyu, 189 Hexuan, Dong, 116 Hongling, Li, 116 Hsiao, Chi-Fu, 312 Huang, Hsin-Yi, 312 Huang, Yong, 37

J Ji, Guohua, 219 Ji, Zixiao, 355 Jia, Fulong, 219 Jian, Rao, 179 Jin, Jinxi, 17 Jin, Yunfeng, 274 L Li, Li, 232 Li, Linxue, 154 Liang, ZhiHao, 364 Lin, Yuqiong, 355 Liu, Pengkun, 274 Liu, Shang, 287 Liu, Yige, 232 Li, Hongling, 160 M Meng, Hao, 364 O Okumura, Koki, 3 P Peng, Xi, 274 Pengyu, Zhang, 264 Q Qi, PengCheng, 364 R Rao, Jian, 20

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374 S Shao, Gefan, 199 Shi, Ji, 287 Steenblik, Ralph Spencer, 72 Suehiro, Kaoru, 3 Sun, Chengyu, 20, 102 T Tong, Yue, 331 Tong, Ziyu, 210 W Wang, Yueyue, 346 Wang, Yujie, 287 Wang, Zhengtao, 219 Weiguo, Xu, 264 X Xiao, Wei, 95 Xu, Jiong, 247 Xu, Zhen, 331 Xu, Weiguo, 177

Author Index Y Yang, Xiaodi, 30 Yang, Zongxu, 3 Yao, Jiawei, 136 Yuan, Feng, 136 Yuan, Philip F., 86, 93, 151, 259, 323, 308 Yue, Fei, 82 Z Zang, Wei, 95 Zhang, Liming, 303, 322 Zhang, Longwei, 37 Zhang, Minyi, 37 Zhang, Pengyu, 177 Zhang, Philip F., 303 Zhang, Xiao, 247 Zhang, Ying, 247 Zhao, Bing, 257 Zhao, Yangchen, 247 Zheng, Hao, 169 Zheng, Zhaohua, 27 Zhou, Zilin, 210 Zhuang, Zhi, 136 Zong, Xuan, 95