Spontaneous Combustion of Coal: Characteristics, Evaluation and Risk Assessment [1st ed. 2020] 978-3-030-33690-5, 978-3-030-33691-2

Table of contents :
Front Matter ....Pages i-xiii
Introduction (Xinyang Wang)....Pages 1-27
Historical Perspective on Identifying and Controlling Spontaneous Combustion (Xinyang Wang)....Pages 29-72
Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion (Xinyang Wang)....Pages 73-128
Analytical Model Developed to Estimate Self-Heating Potential (Xinyang Wang)....Pages 129-170
Numerical Modeling of Self-Heating Event and Preventive Measures (Xinyang Wang)....Pages 171-206
Interpretation of Mine Atmosphere Monitoring Data (Xinyang Wang)....Pages 207-231
Back Matter ....Pages 233-240

Citation preview

Xinyang Wang

Spontaneous Combustion of Coal Characteristics, Evaluation and Risk Assessment

Spontaneous Combustion of Coal

Xinyang Wang

Spontaneous Combustion of Coal Characteristics, Evaluation and Risk Assessment

Xinyang Wang Department of Safety Engineering Northeastern University Shenyang, China

ISBN 978-3-030-33690-5 ISBN 978-3-030-33691-2 https://doi.org/10.1007/978-3-030-33691-2

(eBook)

© Springer Nature Switzerland AG 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, express 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 Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

Spontaneous combustion is one of the most serious problems to mine safety and production in the global coal industry. It is considered to be the trigger for fires and explosions in underground coal mines especially for gassy mines. Such thermal events are not easily detectable since they normally occur in inaccessible gobs and sealed areas. It is also difficult to find the most likely hot point accurately. The investigation and study of spontaneous combustion has been an intense effort between industrial safety experts and academic researchers for hundreds of years. They have devoted their efforts to revealing the influential factors underlying the self-heating behavior. However, due to the complexity of intrinsic chemical and physical properties and extrinsic in situ mining conditions, spontaneous combustion mechanisms have not been fully understood. Admittedly, evaluation, prediction, and control of spontaneous combustion before and during mining activity are necessary steps to prevent and reduce self-heating accidents for coal mine safety. This book’s goal is to underline the principle of how to actually understand, analyze, and deal with this issue. Based on experimental and theoretical research findings, the book emphasizes three essential questions that are fundamental to understand spontaneous combustion: What are the root causes? How to evaluate the causative factors to determine the activity of coal? How to bring this issue under control in real longwall panel? To answer the questions, the book introduces the reader to (1) experimental techniques applied to investigate the basic molecular structure of coal and evaluate chemical properties' effect on the self-heating behavior, (2) theoretical analyses to predict the extrinsic effect on low-temperature oxidation of coal in experimental scale and in full-size longwall panel, and (3) risk assessment measures to mitigate this issue using experimental method for retardant screening, numerical simulation for optimal grouting and nitrogen injections, and case studies to analyze thermal events using mine atmosphere gas monitoring data. Along this way, it also addresses and includes research findings (e.g., FTIR spectrum variation along with coalification and temperature rise, specially designed experiments for moist oxidation and retardant screening, and analytical and numerical

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vi

Preface

modeling considering multiple parameters and complicated conditions) in a more concrete manner. Taking the effort to continuously improve coal mine safety as the ultimate goal, the following steps from basic concept to insight knowledge are presented in this book: • Establish the importance of understanding spontaneous combustion of coal. The book starts by introducing the readers to the basic concept of spontaneous combustion, explains the importance of this safety issue by reviewing the accidents that have resulted from self-heating globally, and discusses the impacts associated with this hazard. The potential causal factors contributing to selfheating in terms of intrinsic and extrinsic properties of coal are summarized. • Improve experimental certainty on identifying and evaluating the characteristics of coal and its self-heating potential. Modern techniques have been extensively used to evaluate, predict, and prevent spontaneous combustion experimentally, theoretically, and practically. The book offers a reminder to the readers by summarizing the classic experimental methods, analytical and numerical modeling, and mitigation techniques. To improve the assessment certainty for evaluating propensity of spontaneous combustion, three widely used laboratory-based experimental methods, involving USBM method, adiabatic oxidation method, and thermoanalytical method, have been jointly carried out and updated by a newly designed experimental procedure. Based on the thermoanalytical method, an experiment for optimal screening of oxidation retardant has been specially designed to select the optimal solution to realize the maximum inhibiting effect on self-ignition. Through research findings presented in this book, coals with high and low potentials to spontaneously combust are comparatively studied by FTIR technique. It gives an obvious difference in molecular structure among those samples, indicated by amounts and locations of functional groups and side chains on the absorbance peaks of the spectrum. It also shows a variation spectrum of coal in a large temperature spacing range to demonstrate how the molecular structure changes with temperature evolution. • Develop theoretical framework to reveal the mechanism of this complex phenomenon. In the theoretical analysis section, the book presents a new analytical model developed to study the self-heating behavior of coal from ambient temperature to thermal runaway using the principles of thermodynamics and chemical kinetics. The purpose of the model is to serve as a tool to assist the experiment when it becomes impractically long. Afterward, the developed model is continuously improved, capable of quantifying (i) the effect of moisture condensation in the environment with different relative humidity, (ii) the effect of pyrite oxidation, and (iii) the effect of volatile matter oxidation. The model then is verified with experimental data. The agreement of the predicted results with the measured data is reasonably good. This book also presents a new coal ranking system with the function of updating the qualitative classification method into a quantitative one. With this quantitative coal ranking system, mathematical correlation of US coal rank and propensity for spontaneous combustion has been developed. The classic USBM method is improved accordingly based on the ranking system.

Preface

vii

To identify spontaneous combustion evolution characteristics in complicated geological and challenging mining conditions in underground coal mine, numerical modeling is applied to simulate designated spontaneous combustion scenario in a longwall gob of ultra-close coal seam and evaluate influence of ventilation types on the variation of oxidation zone in the gob. As widely used preventive measures, inerting effects of grouting and nitrogen injection to mitigate mine fire accidents in gob are investigated by numerical modeling. As a result, the grouting spread pattern with different coal seam angles and the optimal grouting plan are determined. The modeling results also depict a changing pattern of oxidation zone in gob area when adjusting nitrogen injecting positions and quantities. • Provide supportive solutions for decision-making to guide subsequent actions. As a key step for planning and implementing mitigation measures to bring thermal events under control, mine atmosphere gas monitoring data are prudently evaluated. Based on the firsthand information of great value obtained from tube bundle system, a number of common fire ratios (hydrocarbon ratio, ICO ratio, Trickett ratio, relative intensity, and Litton ratio) are calculated based on the real-time data to confirm the findings from direct analysis. A causational analysis, locating and determining the status of two thermal events occurred in longwall gob and longwall panel, is presented through case studies. This book offers an outline for better understanding spontaneous combustion of coal and associated approaches to deal with this problem. It will be of interest to individual readers, academic institutions for higher education and research, and coal mining-related industry. It will be suitable for readers with basic knowledge of chemistry and mining engineering background, such as university-level teachers and second year undergraduate and graduate students majoring in mining engineering and coal mine safety engineering. Upper-level scholars with in-depth study in this field can profit from the book. It will also be helpful for decision-makers, engineers, and practitioners to quickly estimate potential issues related to spontaneous combustion. It will provide guidelines and useful references for risk assessment for coal mine development in each individual stage. I will be most grateful for any comments, suggestions, and criticisms on subjects presented in this book. Please send email at [email protected]. Shenyang, Liaoning, China July 8, 2019

Xinyang Wang

Acknowledgments

This book is a 10-year outcome of my academic career. It is originally based from my Ph.D. study and the following research work supported by Liaoning Natural Foundation (20180550757) and the National Key Research and Development Program (2017YFC0804703). I would like to express my gratitude to Dr. Yi Luo for his full support, advice, and inspiration to my Ph.D. study in the West Virginia University (WVU). His tremendous efforts are vital for the completion of this work. I appreciate very much the efforts of Professor Jiren Wang, Professor Gang Li, and Professor Cunbao Deng for generously offering their valuable comments, guidance, and suggestions throughout the preparation of this book. I would like to offer my words of appreciation to William (Bill) Comstock for his help on the establishment of the experimental facilities and to the staff members and graduate students for their generous assistance in experiment performance and data processing. Finally, special thanks go to Aaron Schiller and Chandhini Kuppusamy from Springer team for their patient help and support in the book publication from beginning to end.

ix

Contents

1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 What Is Spontaneous Combustion . . . . . . . . . . . . . . . . . . . . . . 1.2 The Impacts and Hazards of Spontaneous Combustion . . . . . . . 1.3 Affecting Factors on Spontaneous Combustion . . . . . . . . . . . . . 1.3.1 Intrinsic Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.2 Extrinsic Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Overview of This Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Experimental Approaches for Determining Propensity of Spontaneous Combustion . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 USBM SHT Method . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2 Adiabatic Oxidation Method . . . . . . . . . . . . . . . . . . . . . 2.1.3 Thermoanalytical Methods . . . . . . . . . . . . . . . . . . . . . . 2.1.4 Isothermal Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.5 Crossing Point Temperature (CPT) Method . . . . . . . . . . 2.2 Theoretical Techniques to Analyze and Predict Self-Heating Behavior of Coal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Kinetic Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Arrhenius Reaction Rate Model . . . . . . . . . . . . . . . . . . 2.2.3 Shrinking Core Model . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.4 Numerical Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Monitoring and Preventive Measures to Mitigate Spontaneous Combustion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1 Gas Monitoring System . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Index Gases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . .

1 1 2 5 6 18 22 24

.

29

. . . . . .

29 29 31 33 39 39

. . . . .

40 40 42 44 46

. . .

49 49 52

xi

xii

Contents

2.3.3 Fire Ratios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.4 Preventive Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

4

Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Adiabatic Oxidation Method . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Samples Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Experimental Instruments . . . . . . . . . . . . . . . . . . . . . . . 3.2.3 Experimental Procedures . . . . . . . . . . . . . . . . . . . . . . . 3.2.4 Results and Discussions . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Thermoanalytical Analysis Method . . . . . . . . . . . . . . . . . . . . . 3.3.1 Experimental Instruments . . . . . . . . . . . . . . . . . . . . . . . 3.3.2 Experimental Procedures . . . . . . . . . . . . . . . . . . . . . . . 3.3.3 Results and Discussions . . . . . . . . . . . . . . . . . . . . . . . . 3.3.4 Determination of Coal Composition with TGA . . . . . . . 3.3.5 Retardant Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 FTIR Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.1 FTIR Spectra for Coals with Different Propensity of Spontaneous Combustion . . . . . . . . . . . . . . . . . . . . . 3.4.2 Variation of Chemical Structure and Functional Groups in Self-Heating Process . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Analytical Model Developed to Estimate Self-Heating Potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Model Developed Based on the Adiabatic Experiment . . . . . . . . 4.2.1 Energy Conservation Law . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Conditions and Assumptions . . . . . . . . . . . . . . . . . . . . 4.2.3 Heat Generation Rate . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.4 Oxidation Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.5 Results and Discussions . . . . . . . . . . . . . . . . . . . . . . . . 4.2.6 Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Improved Model for Quantifying the Effect of Moisture Condensation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.1 Heat of Rewetting . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 Modeling Results and Discussions . . . . . . . . . . . . . . . . 4.4 Improved Model for Quantifying Pyrite Oxidation . . . . . . . . . . 4.4.1 Shrinking Core Model . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.2 Modeling Results and Discussions . . . . . . . . . . . . . . . . 4.5 Improved CSHT Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5.1 Quantification of US Coal Rank . . . . . . . . . . . . . . . . . . 4.5.2 Improvement of SHT Method . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . .

55 59 68 73 73 74 74 77 82 85 97 97 99 100 103 104 108

. 110 . 119 . 126 . . . . . . . . .

129 129 130 131 132 133 136 136 138

. . . . . . . . .

140 141 145 147 147 151 155 157 162

Contents

xiii

4.5.3 Correlation of Quantified Coal Rank and SHT . . . . . . . . . 165 4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 5

6

Numerical Modeling of Self-Heating Event and Preventive Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Characteristics of Spontaneous Combustion in Gob . . . . . . . . . . . 5.2 Numerical Modeling of Spontaneous Combustion in Ultra-Close Coal Seams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1 Numerical Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.2 Assumptions and Boundary Conditions . . . . . . . . . . . . . . 5.2.3 Geometric Model and Parameters . . . . . . . . . . . . . . . . . . 5.2.4 Modeling Results and Discussions . . . . . . . . . . . . . . . . . 5.2.5 Spontaneous Combustion Affected by Ventilation Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Numerical Modeling of Grouting to Mitigate Residual Coal Oxidation in Gob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Numerical Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.2 Geometric Model and Parameters . . . . . . . . . . . . . . . . . . 5.3.3 Modeling Results and Discussions . . . . . . . . . . . . . . . . . 5.4 Numerical Modeling of Inerting Effect of Nitrogen Injection in Gob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.1 Geometric Model and Parameters . . . . . . . . . . . . . . . . . . 5.4.2 Modeling Results and Discussions . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interpretation of Mine Atmosphere Monitoring Data . . . . . . . . . . . . 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Case 1: Identifying Status of Coal Oxidation in a Longwall Gob . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.2 Coal Sample Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.3 Gas Sampling and Monitoring . . . . . . . . . . . . . . . . . . . . 6.2.4 Locating the Original “Oxidation” Spot . . . . . . . . . . . . . . 6.2.5 Fire Ratios and Indications . . . . . . . . . . . . . . . . . . . . . . . 6.2.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Case 2: Causational Analysis of a Thermal Event in a Longwall Panel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.2 Gas Monitoring Data . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.3 Fire Ratios and Indications . . . . . . . . . . . . . . . . . . . . . . . 6.3.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

171 171 173 173 178 179 183 187 191 192 193 194 198 198 199 205 207 207 208 208 211 214 218 218 223 224 224 227 229 230 231

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233

Chapter 1

Introduction

Abstract Coal, as a fuel, has the potential to start burning itself without being artificially ignited when certain conditions are present. Spontaneous combustion of coal has posed a serious safety threat in the coal industry and other related industries. Hazards, accidents, and impacts of this issue as current global scenarios are introduced. In the USA 97 underground coal fires were caused by coal self-heating from 1952 to 1999. A total of 125 incidents resulted from coal self-heating occurred in the New South Wales state of Australia during the period from 1960 to 1991. More recently, on 13 May 2014, an explosion at Eynez coal mine in Soma, Manisa, Turkey, caused 301 people killed in the worst mine disaster in Turkey’s history. The potential causal factors contributing to self-heating in terms of intrinsic (chemical structure, coal composition parameters, pyrite porosity, and coal rank) and extrinsic factors (humidity, particle size, aging effect, etc.) of coal are summarized. Keywords Spontaneous combustion · Hazards · Affecting factors · Intrinsic factors · Extrinsic factors

1.1

What Is Spontaneous Combustion

Coal, as a fuel, has the potential to start burning itself without being artificially ignited when certain conditions are present. Such spontaneous combustion of a coal generally starts as a slow oxidation process that occurs without an external heat source (Nelson and Chen 2007). In a suitable environment, the heat generated is accumulated inside the coal leading to a rise in temperature (Walters 1996). It usually happens with sufficient oxygen supply but insufficient means to dissipate the heat generated. As the oxidation process of the coal continues, more and more heat released is stored by the coal making the temperature increase exponentially. This can eventually result in a thermal runaway and burning the coal (Rosema et al. 2001).

© Springer Nature Switzerland AG 2020 X. Wang, Spontaneous Combustion of Coal, https://doi.org/10.1007/978-3-030-33691-2_1

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1.2

1 Introduction

The Impacts and Hazards of Spontaneous Combustion

Spontaneous combustion of coal has posed a serious safety threat in the coal industry and other related industries. It was reported that 65 coal mine fires in the USA were attributed to spontaneous combustion for the period from 1952 to 1969 (Table 1.1) and led to three injuries and three fatalities (Kuchta et al. 1980). Analysis of US underground coal fires indicates that 21 mine fires were caused by spontaneous combustion during the period from 1978 to 1992 (Pomroy and Carigiet 1995). It was responsible for 17% of 89 reportable mine fires which lasted 30 min or longer after being discovered or causing injury occurring in US underground coal mines during the period 1990–1999 (De Rosa 2004). According to the analysis of US coal mine fires from United States Bureau of Mines (USBM) and National Institute for Occupational Safety and Health (NIOSH), Table 1.1 shows 97 underground coal fires were caused by coal self-heating from 1952 to 1999. Significant spontaneous combustion events over the last four decades are tabulated in Table 1.2 (Grubb et al. 2015). Spontaneous combustion not only creates safety problems to surface and underground coal miners but also causes problems in storage and transportation worldwide. Coal reserves are vast, over 10 trillion metric tons worldwide. A great number of coal seam fires are found in abandoned coal mines. In Fig. 1.1, each flame shape dot indicates a nest or series of spontaneous coal fires in the surface or underground coal mines. These fires represent a significant portion of the overall greenhouse gas emissions contributing to global warming. Statistics show that, in France and Great Britain, about seven to eight cases of spontaneous combustion in coal mines each year (Kuchta et al. 1980). In South African collieries, spontaneous combustion of coal is the major cause of underground fires, which is responsible for more than one Table 1.1 Number of fires for underground coal mines by ignition source and time period, 1952– 1969a, 1978–1992b and 1992–1999c

Ignition source Welding and flame cutting Electrical Spontaneous combustion Friction Other Total a

Time period 1952– 1978– 1969 1982 – 10

1983– 1987 10

1988– 1992 6

1992– 1993 2

1994– 1995 3

1996– 1997 2

1998– 1999 2

Total 35

602 65

27 8

20 9

10 4

7 2

9 4

1 3

6 2

682 97

91 – 758

8 3 56

13 1 53

11 – 31

1 – 12

1 – 17

– – 6

– 1 11

125 5 944

Derived from Spontaneous Combustion Susceptibility of US Coals, USBM Report, 1980 Derived from Analysis of Underground Coal Mine Fire Incidents in the United States from 1978 through 1992, USBM, 1995 c Derived from Analysis of Mine Fires for all US Underground and Surface Coal Mining Categories: 1990–1999, NIOSH, 2004 b

1.2 The Impacts and Hazards of Spontaneous Combustion

3

Table 1.2 Significant spontaneous combustion events over the last four decades (Grubb et al. 2015) Year 1972 1975 1991 1994 1997 1997–1998 1999 2000 2003 2013 2014

Mine Box Flats (Australia) Kianga (Australia) Ulan (Australia) Moura No. 2 (Australia) Galatia (USA) North Goonyella (Australia) Sanborn Creek (USA) West Elk (USA) Southland (Now Austar-Australia) Elk Creek (USA) Deer Run Mine (USA)

Consequences 18 fatalities 13 fatalities Loss of US$60 million 11 fatalities Loss of US$38 million Loss of longwall Mine idled 9 months Loss of US$60 million Loss of Longwall-mine closed/sold Loss of longwall-mine closed Loss of 3 weeks of production

0

Spontaneous Coal Fires in the surface Underground Coal Fires

500 km

Coal Field Fires Coal Mine Fires Based on Kijk (1995, no. 8,p. 29)

Fig. 1.1 Localization of coal mine fires worldwide and in China

third of the 254 fires reported during the period from 1970 to 1990 (Gouws and Knoetze 1995). Additionally, spontaneous combustion also occurs in surface mines in the Witbank and Sasolburg coalfields in South Africa burning the entire length of the main pit, about 4.5 km. This fire in turn led to poor fragmentation and difficult digging conditions for the draglines and shovels (Phillips et al. 2011). A total of 125 incidents resulted from coal self-heating occurred in the New South Wales state of Australia during the period from 1960 to 1991 (Cliff et al. 1996). China has 115 billion ton coal reserves. Coal production was 1.3 billion ton in 1997. Annually 100–200 billion ton coal is lost due to coal fires, leading to large economic loss and enormous CO2 emissions. The coal fires stretch across a 5000 km-wide belt in the north of the country as shown in Fig. 1.1. Coal outcrops fires have spread over a large area of 720 km2 resulting in 4.2 billion tons of coal burned in seven provinces of Northern China. Half of all the state-owned coal mines have the potential of spontaneous combustion leading to 5 billion yuan (about $782 million) financial losses every year (Xu 2001). In a recent series of four Coal Age articles (Gambrel 2010), an explosion on an ocean-going coal ship as a result of coal’s spontaneous combustion has caused a serious safety concern for the shipping industry. Fires caused by the spontaneous combustion can cause explosions. In June 1991, a coal

4

1 Introduction

bunker at coal-fired plant experienced an explosion which is believed to have been triggered by spontaneous combustion. The fire ignited coal dust that eventually resulted in a massive explosion (Hossfeld and Hatt 2005). More recently, on May 13, 2014, an explosion at Eynez coal mine in Soma, Manisa, Turkey, caused 301 people killed in the worst mine disaster in Turkey’s history. The cause of the accidents is still under investigation, but official reports concluded that the disaster was caused by spontaneous combustion due to the coal left in the old production panels (Düzgün and Leveson 2018). Spontaneous combustion causes enormous economic losses and environmental problems. It can result in a direct loss of valuable resources through the undesired burning of coal reserves. In addition, it interrupts the mining operation which in turn results in indirect loss of coal resources when the underground working areas must be shut down. The unmined coal seams will be blocked and the coal reserves not involved in the fire cannot be extracted. Equipment and personnel will stand idle. It was estimated that 353 million tons of unexploited coals were reserved in Wuda coal basin, Inner Mongolia, China, but 100 million tons of the coal reserve have been blocked by coal fires (Stracher et al. 2005). Coal fires release various harmful pollutants which are toxic for the human body. Carbon monoxide, nitrogen oxides, sulfur oxides, and volatile organic compounds are those toxic pollutants produced by burning coal. Carbon dioxide also contributes to the greenhouse effect. Although self-ignition hazards continuously impose safety issues to mining activities and production, the mechanisms of spontaneous combustion are not fully understood due to the complex chemical structure and physical condition of the coal. Under the interaction between the chemical and physical properties, the same rank coals or even the same coals existing in different conditions will have different potentials of spontaneous combustion. For instance, the low-rank coals are relatively young at an immature metamorphic stage in the long process of formation. This type of coal has high volatile-matter content, plentiful porous structures, and large internal surface and contains a great amount of moisture. If drying and rewetting occur during handling, heat of wetting will be generated through the effect of water vapor condensation when the coal adsorbs the humidity from the surrounding environment. Although a small amount of heat is generated in this process, it provides the initial heat for coal self-heating. Once the heat accumulates gradually without fully dissipating, coal self-heating will occur. With the indispensable initial heat and sufficient oxygen, coal will be oxidized by oxygen on the surface of the porous structure, and more heat will release. Since these factors influencing the potential of self-heating are controlled by physical conditions, chemical properties, and ambient situation, both experimental and theoretical methods are needed to analyze and quantify the oxidation process. In addition, self-heating incidents in underground coal mines often occur in gob or sealed areas and may not be easily detectable. In storage and shipment conditions, spontaneous combustion normally starts under the surface of the coal storage pile and may not be detected initially. Therefore, a better understanding about the propensity of spontaneous combustion of coal could greatly benefit the scheduling

1.3 Affecting Factors on Spontaneous Combustion

5

of these coal handling operations, design of the ventilation system, as well as mining operations in coal mines. Up until now, the propensity of spontaneous combustion of coals can be evaluated using a wide variety of laboratory testing methods with different techniques. R70 adiabatic test is a widely accepted standard method in Australia. Critical selfheating temperature (CSHT) method is first developed from USBM. Thermal gravimetric analyzer (TGA) test is a relatively new quantitative method. It can measure temperature and weight changes in a short testing period. Each of the methods has its unique characteristics and index for classifying the propensity of self-ignition of coals. Accountable relationships among the propensity indices of different methods should be established. The certainty for assessing the propensity of spontaneous combustion will be greatly improved by using the combination of the three widely used methods. On the other hand, improvement of a theoretical basis should be another very important advancement to unveil the mechanism of spontaneous combustion. In this regard, sound scientific experimental techniques and setups and a mathematical model that take into account the relevant factors should be developed to assist managing the coal spontaneous combustion prevention tasks. To sum up, methods for accurate measurement of spontaneous combustion behavior need to be established. Additionally, a mathematical model developed to both quantify the factors that influence the potential of coal self-heating and simulate the temperature changes over time in an adiabatic condition is needed. This experimental and theoretical combined approach can be used to improve the mine safety management and provide helpful guidance for the ventilation system design and mining operation planning.

1.3

Affecting Factors on Spontaneous Combustion

Coal was formed from decomposed plant material which had accumulated in waterlogged places (Speight 1994). Through burial and metamorphism under elevated temperature and pressure for millions of years, it was formed as layers within the surface rocks of the earth. Coal contains the elements (e.g., C, H, O, and N) and sun’s energy that the plants collected into their own constituent compounds when they grew many millions of years ago as shown in Fig. 1.2 (Edmunds 2002). The plant debris consisted of several thousand species. The relative amounts of similar types of plants vary considerably in different ranks of coals. On this basis, coal differs markedly in composition from one location to another. As a result, coal has many properties that affect its ability to combust and to spontaneously ignite.

6

1 Introduction

C

H

O

C

H O

Stored energy, C,H,O, and N

d of

Energy on cti e tr u ect ri s e t D te ro unp t ma plan

al

Sun’s energy

N tio va , N er O es H, Pr C,

n , a of p nd lan en t m erg ate y a rial b re s y bur ial. tore d.

N fro m s oil

Coal

Fig. 1.2 Source of the chemical elements and energy stored in coal (Edmunds 2002)

1.3.1

Intrinsic Factors

Kaymakçi and Didari (2001) investigated the intrinsic properties that affect the potential of coal self-heating. In their survey, pyrite, moisture content, particle size, and ash content are analyzed as the main factors. Their respective influences to self-heating are (a) pyrite content may accelerate spontaneous combustion; (b) changes in moisture content, i.e., the drying or wetting of coal, have apparent influence on the propensity for coal to self-heat; (c) as the particle size decreases and the exposed surface area increases, the tendency of coal toward spontaneous combustion increases; and (d) it is widely recognized that lower-rank coals are more susceptible to spontaneous combustion than higher-rank coals. Ash content generally decreases the propensity of coal to spontaneously heat. Certain constituents of the ash, such as lime, soda, and iron compounds, may have an accelerating effect, while others, such as alumina and silica, produce a retarding effect. However, chemical structure of coal as another important intrinsic property was never mentioned by the authors in the literature above.

1.3.1.1

Chemical Structure

Coal structural models have been developed by many researchers (Baset et al. 1980; Bodzek and Marzec 1981; Marzec 1986). These models have been developed to demonstrate the properties and behavior of coal during the conversion process. Generally, research findings show that coal is made up of large aromatic ring clusters

1.3 Affecting Factors on Spontaneous Combustion Loop Structure

R

Mobile Phase Group H2

H C H

H2

H2 H2

O

Side Chain

H2 H C H

CH3

H

7

OH

H2

O H

H

H

Bridge Structures

C H

O

Bi-aryl Bridge

O R OH H

H2

H C H

H2

H2

O C OH

H C H

N

N

H2 H2

O HO

S C

CH3

H2

Pyridinic Nitrogen

O

Pyrrolic Nitrogen

H2

C

OH CH2

Aromatic Cluster

R

Fig. 1.3 A hypothetical model of coal structure (Malumbazo 2011)

which form the primary network in the complex macromolecular structure (Fuchs and Sandhoff 1942; Given et al. 1975; Shinn 1984; Solomon 1981). These aromatic clusters are linked to each other by bridges. These bridges are formed from a variety of structures, made up of different kinds of bonding (covalent, non-covalent, van der Waals forces, etc.) (Krichko and Gagarin 1990). Most of these bridges contain aliphatic oxygen, such as ethers as shown in Fig. 1.3. Other bridges are bi-aryl linkages between the aromatic clusters (Spiro and Kosky 1982). Functional groups in abundant quantity make up the bridge structures which decide the bond strength of coal structures (Kidena et al. 2008). As the coalification increases, the functional groups in the organic coal structure significantly reduce, and the aromatic structures increase instead as shown in Fig. 1.4. It shows that coal contains a wide range of functional groups including aldehyde, alcohol, ketone, ether, ester, and carboxylic acid. These functional groups are much more reactive than the pure hydrocarbon groups (Cliff 2009). The numbers and activity of these functional groups play an important role in low-temperature oxidation of coal (Weiqing et al. 2011). Side chain, mainly composed of aliphatic and carbonyl functional groups, is also an important part attached to aromatic clusters. Another aromatic cluster, known as mobile phase, consists of smaller molecular structures. It is either trapped in the molecular structure of coal or weakly bonded to the coal macromolecule by hydrogen bonds or van der Waals-type interactions (Marzec and Schulten 1991). In coal petrography, coal is a physically and chemically heterogeneous substance which mainly consists of organic material. It is generally agreed that the organic

8

1 Introduction

Fig. 1.4 Structure models for low-, intermediate-, and high-rank coal (Spiro and Kosky 1982)

material has been formed from precursors of coal which is the organic portions of plants including lignin, carbohydrates, and proteins as well as other polymers. In beginning of coalification, peat was laid down and sedimented under the influence of pressure and temperature for several hundred million years. The organic sedimentary substance composed of fossilized plant debris called macerals. The macerals are microscopically distinct areas and are classified into three major groups: vitrinite, exinite (or liptinite) and inertinite, which can be determined by petrographic analysis. Vitrinite is the most prevalent group, accounting for 80%, and is believed to be derived from woody plant material (mainly lignin). Exinite developed from lipids and waxy plant substances. Char formed by prehistoric pyrolysis is the possible origin of inertinite (Haenel 1992). As shown in Fig. 1.5, Chen et al. (2012) presented photomicrographs of different ranks of coal including (a) peat with small sporinite (a kind of exinite maceral) clusters surrounded by inhomogeneous ulminite and gelinite in it, (b) lignite with inertinite and vitrinite in it, (c) high-volatile bituminous with secretinite surrounded by vitrinite and liptinite macerals, (d) mega-sporinite in high-volatile bituminous, (e) fusinite and semifusinite in medium-volatile bituminous, and (f) homogenous structure in anthracite which makes it difficult to distinguish vitrinite from inertinite. Statistical analysis was carried out by correlating the samples intrinsic properties and spontaneous combustion liability indices (Onifade and Genc 2018). However, few significant relationships were found between the liability indices and petrographic composition (total vitrinite, total exinite, and total inertinite). The widely accepted reason for self-ignition is the chemical adsorption between activated functional groups of coal macromolecule and oxygen molecules resulting in exothermic chemical reaction (Xu 2001). Ogunsola and Mikula (1992) concluded that liability to spontaneous combustion of coal was reduced when oxygencontaining functional groups lost from the coal. Kadioğlu and Varamaz (2003) pointed out that the concentration of oxygen-containing functional groups of drying coal samples increased with increase of contact time with air and thus the liability of spontaneous combustion of the samples increased. Garcia et al. (1999) suggested

1.3 Affecting Factors on Spontaneous Combustion

9

Fig. 1.5 Photomicrographs of coal with different ranks involving peat, lignite, high-volatile bituminous, medium-volatile bituminous, and anthracite in ascending order of coalification. Ro is vitrinite reflectance which is widely accepted as important coalification index. (a) Peat, Ro ¼ 0.28%. (b) Lignite, Ro ¼ 0.33%. (c) High-volatile bituminous, Ro ¼ 0.87%. (d) High-volatile bituminous, Ro ¼ 0.98%. (e) Medium-volatile bituminous, Ro ¼ 1.21%. (f) Anthracite, Ro ¼ 5.04%

that coal structures such as hydroaromatic and oxygenated functional groups contribute the oxidation heat in low-temperature reaction with molecular oxygen.

10

1.3.1.2

1 Introduction

Coal Composition Parameters

General coal quality parameters are moisture, volatile matter, fixed carbon, ash content, sulfur content, calorific value, size and Grinding Hardgrove Index, as well as other parameters such as elemental analysis in the ash content (SiO2, Al2O3, P2O5, Fe2O3, etc.), analysis of the composition of sulfur (pyritic sulfur, sulfate sulfur, organic sulfur), and the melting point of ash (ash fusion temperature). The composition of a coal is usually reported in terms of its proximate analysis and its ultimate analysis. The proximate analysis consists of four items: fixed carbon, volatile matter, moisture, and ash, all on a percentage of weight basis. The ultimate analysis provides an element-by-element composition of the coal’s organic fraction, namely, carbon, hydrogen, oxygen, and sulfur, all on a percentage of weight basis. USBM researchers Litton and Page (1994) proposed an empirical equation to link some of the quality parameters moisture, volatile matter, and fixed carbon determined from proximate analysis to the critical self-heating temperature (CSHT) for assessing the potential of self-heating of coal. Studies have also been done by many other researchers on quality parameters. They used different methods and techniques to investigate the influence of each parameter such as moisture, volatile matter, ash content, and sulfur on spontaneous combustion independently (Beamish and Blazak 2005; Bhattacharyya 1971; Guney 1971; Sweeny et al. 1988). The effect of moisture on the self-ignition of coal is two-step process (Nordon and Bainbridge 1983). The first heating step occurs when water vapor condenses into liquid. The heat it gained is called heat of vaporization or the latent heat of condensation from vapor to liquid, Hv. The second heating step occurs when the heat is generated from the physical adsorption between coal and water and is called heat of wetting, Hw. It evolved when a solid is wetted by a liquid. The total or integral heat of adsorption is Ht ¼ Hv þ Hw

ð1:1Þ

When the coal is pre-dried, a promotion of self-ignition process by the wetting of coal can be expressed by Dry coal þ moisture ! wet coal þ heat

ð1:2Þ

Water adsorption is not essential stage but provides initial heat and eventually leads to self-heating, especially for low-rank coals (Berkowitz 1951). Low-rank coals have much higher heat of wetting than the higher-rank coals as shown in Table 1.3. The heat of wetting is proportional to the internal surface of coal such that one calorie of heat is equivalent to 10 m2, and the low-rank coals have large internal surfaces. For example, a sub-bituminous coal having 77.5% carbon on dry and mineral matter-free basis (dmmf) or 45% VM can generate over 25 cal/g of wetting heat. For lignite this heat may raise the temperature of coal by about 80  C (Das and Hucka 1986). Water plays an important role in the coal oxidation process. However,

1.3 Affecting Factors on Spontaneous Combustion

11

Table 1.3 Heat of wetting for different ranks of coal (Das and Hucka 1986) Coal rank Sub-bituminous High-volatile bituminous Medium-volatile bituminous Low-volatile bituminous Semianthracite Anthracite

Volatile matter (dmmf), % 45 35 30 20 12 5

Fixed carbon (dmmf), % 77.5 82.5 85.0 89.0 91.5 93.3

Heat of wetting cal/g kcal/mole 25 52.5 10–15 9–13.5 3–6 2.7–5.4 2 1.34 3–4 – 6–9 –

so far there has been no conclusive information on whether it participates in the chemical reactions or just acts as a catalyst during coal oxidation. The influence of moisture on the self-heating of coal is complex. Many studies are published to help providing a better understanding the related experimental and theoretical work. Kadioğlu and Varamaz (2003) used crossing point method to evaluate the spontaneous combustion characteristics of moisture and air-dried lignite at varying times. It was found that if moist coals were air-dried, their propensity for self-heating increased as the drying time increased. In other words, the samples became more reactive as their moisture content was decreased. Ren et al. (1999) tested dry and wet coals with saturated air, respectively. It was found the dry coal reacted under saturated air condition is more reactive than the wet one. The temperature of the wet coal-saturated air system was observed to decrease initially due to evaporation of moisture from the coal. Beamish and Hamilton (2005) found the similar phenomenon when they tested Callide coal in an adiabatic oven to assess the effect of moisture on the R70 self-heating rate of coal. As the moisture content was progressively increased, from the dry state of the test, the R70 value decreased dramatically. However, some studies indicated that a wet coal is more prone to react with oxygen than a dry one (Chen and Stott 1993; Clemens and Matheson 1996; Sondreal and Ellman 1974; Vance et al. 1996). Those research findings mainly focused on explaining the influence of moisture content on self-heating behavior of coal, while some studies suggested that heat of wetting plays important role in enhancing self-heating for dry coal and thereby accelerating oxidation (Nordon and Bainbridge 1983; Nugroho et al. 2008). It was found that with an increased relative humidity, the gas supply has a marked influence on the self-heating rates of the coal. The sub-bituminous coal sample undergoes oxidation most rapidly when the relative humidity of the gas supply is about 70%. But the heat of wetting also decreased rapidly with increasing moisture content in the coal. The techniques above for evaluating the moisture and heat of wetting only used experimental methods and could not explain this phenomenon theoretically in a mathematical manner. Smith and Glasser (2005) investigated a range of coal properties and properties of the reaction system with a semi-adiabatic reactor. Based on this reaction system, they developed a mathematical modeling with a shrinking-core theory to determine the

12

1 Introduction

self-heating rate, heat capacity, heat of reaction with oxygen, and activation energy for the reaction. Effects of moisture contents and humidity variations on porous medium or coal stockpile have been simulated (Arisoy and Akgün 1994; Chen 1992; Ejlali et al. 2011; Gong et al. 1999; Gray et al. 2002). All of the methodologies used to perform the simulation are numerical modeling. The volatile matter consists mainly of combustible gases such as hydrogen, carbon monoxide, methane, plus other hydrocarbons. The composition of the volatile matter evolved from coal is substantially different for the different ranks of coal. The proportion of incombustible gases increases as the coal rank decreases (Speight 1994). The higher the amount of volatile material in coal, the more likely the coal will suffer from spontaneous combustion. At least to a certain extent, the process of coal oxidation might be attributed to an increase in volatile-matter content. Ash is the residue derived from the mineral matter during complete incineration of the coal. It is quantitatively and qualitatively different from the mineral matter originally present in the coal. The ash content has been considered as having retardant effects on coal self-ignition. R70 index decreases significantly with increasing ash content (Beamish and Blazak 2005). This effect is due to the mineral matter in the coal acting as a heat sink. Onifade and Genc (2018) conducted intensive experiment for evaluating the proximate and ultimate parameters’ influence on self-heating of coal. They concluded that except moisture, oxygen, and total sulfur, as the volatile matter, carbon content, hydrogen content, nitrogen content, and pyritic sulfur increase, the oxidation capacity of coals is more likely to increase in general. When ash content increases, the spontaneous combustion liability decreases as shown in Fig. 1.6.

Fig. 1.6 Influence of coal compositions from (a) to (i) determined by proximate and ultimate analysis on propensity of spontaneous combustion (Onifade and Genc 2018)

1.3 Affecting Factors on Spontaneous Combustion

1.3.1.3

13

Presence of Pyrite

Pyrite (FeS2) and the related mineral marcasite exist frequently in coal (Speight 1994). Pyrite oxidation takes place when the mineral is exposed to air and water. The process is complex because it involves chemical, biological (Lorenz and Stephan 1967), and electrochemical reactions (Clark 1966) and varies with environmental conditions. The real cause of spontaneous combustion cannot be attributed to presence of pyrite, since it does not account for the numerous cases of the spontaneous combustion of coal in which sulfur is not present (Barr 1900). But it is an important factor in the spontaneous ignition of coal and cannot be discarded in an offhand way (Parr and Kressman 1910). Under suitable conditions the pyrites in coal will oxidize rapidly and may be a dominating factor in certain cases for the selfheating of coal (Li and Parr 1926). It is recognized that self-heating of coal will be promoted when pyrite concentration is above 2% (Walters 1996). However, it is the type of pyrite present in the coal that controls the promoting rate rather than the amount of pyrite (Beamish and Beamish 2012). The low-temperature oxidation of pyrite is exothermic, and the heat liberated is found in Table 1.4 (Parr and Kressman 1910): Among the possible reaction paths, the ones with H2O involved generally produce much more heat than those without H2O. It is further verified by Beamish et al. (2012). They conducted a test to investigate the influence of reactive pyrite on self-heating of a high-volatile bituminous coal containing sulfur from 0.62% to 17.95% with a moist coal adiabatic oven. Thus, storing coal where it would be repeatedly wetted by rain may favor pyrite oxidation. In underground coal mines, the relative humidity of the air is high, for the ventilating current picks up moisture from the walls and the coal dust. When the outside air is colder than the mine air, as in winter, the entering air is rapidly warmed to the mine temperature. Consequently, its relative humidity is low. Thus, during cold weather the effect of the ventilating current is to dry the mine. However, in hot weather, relative humidity of mine air will become higher. That will be helpful for pyrite oxidation and generation of heat of wetting for the coals remained in gob area, eventually leading to self-heating of coal. A well-known shrinking core model was used to describe pyrite oxidation and pollutant leaching processes in waste dump sites (Cathles and Apps 1975; Levenspiel 1999; Singh and Ardejani 2004). This model combined surface reaction with accumulation of product layer on the surface. It is assumed that the reaction rate is first-order with respect to the principal gas reactant and the surface area of remaining solids and that the reaction rate is also controlled by the steady-state diffusion of the reactant gas through the accumulated layer of product on the unreacted core (Evangelou 2018). The time required for a specified quantity (X) of pyrite to oxidize can be expressed as a function of the reaction rate constant of pyrite (Kp), the effective diffusion coefficient for O2 through any ash layer on surface of pyrite particle (De), and the concentration (CAg) of O2 as follows:

Reaction FeS2 + 11O ! Fe2O3 + 4SO2 2Fe + 3O ! Fe2O3 2FeS2  2Fe + 8O ! 4SO2 4SO2 + 4O + 4H2O ! 4H2SO4 2FeS2  2Fe + 12O + 4H2O ! 4H2SO4 2Fe + 2H2SO4 ! 2FeSO4 + 2H2 2FeS2 + 12O + 4H2O  2H2SO4 ! 2FeSO4 + 2H2 2O2 + 2H2 ! 2H2O 2FeS2 + 14O + 2H2O  2H2SO4 ! 2FeSO4 Or, FeS2 + 7O2 + 2H2O ! 2FeSO4 + 2H2SO4

* 1 kcal ¼ 4.19 kJ; Minus sign indicates an exothermic reaction

Reaction sequence (i) (ii) (i)  (ii) (iii) (i)  (ii) + (iii) (iv) (i)  (ii) + (iii) + (iv) (v) (i)  (ii) + (iii) + (iv) + (v)

Table 1.4 Reaction steps of low-temperature oxidation of pyrite ΔH (kcal/kJ) 37.3/156.3 19.8/83.0 17.5/73.3 25.6/107.3 43.1/180.6 9.4/39.4 52.5/220.0 11.7/49.0 64.2/269.0

14 1 Introduction

1.3 Affecting Factors on Spontaneous Combustion

t¼

1  3ð1  X Þ2=3 þ 2ð1  X Þ 1  ð1  X Þ1=3 þ De  CAg K p  C Ag

15

ð1:1Þ

The first term accounts for the effect of increased thickness of surface coating on the reaction rate, while the second term accounts for the effect of the decreased amount of pyrite on the reaction rate. During oxidation of pyrite by O2 alone, the first term is omitted, and it turns to t¼

1  ð1  X Þ1=3 Ks  C

ð1:2Þ

Thus, Eq. 1.2 describes first-order kinetics with respect to FeS2. Therefore, as expected, the plot of t versus [1  (1  X)1/3] should display a straight line.

1.3.1.4

Porosity

Coal is a material with a complex pore structure and very high surface area. The nature of American coals’ porosity in a number of 40  70 (i.e., 40 + 70) mesh size, varying in rank from anthracite to lignite, has been studied (Gan et al. 1972). In the lower-rank coals, porosity is primarily due to the presence of macropores, whereas in the coals of higher rank, microporosity predominates. Falcon and Ham (1988) mentions that porosity is a characteristic of extreme importance to spontaneous combustion. Firstly, it provides an indication of the total surface area, which may be subjected to oxidation. Secondly, it provides an indication of the total volume of the voids or spaces, a factor directly proportional to the amount of moisture and gas which may be stored in such a coal. Mercury intrusion method was used to study pore structure in coal. The results showed that total pore volume and specific surface area decrease as coal rank increases. In the coal oxidation process, the rate of temperature increases, and the rate of heat release decreases when pore volume and specific surface area of the coal decrease. If all pores were filled with water in nature, the inherent seam moisture would give direct information on the pore volume, as shown in Fig. 1.7. Pores in coal usually contain small amounts of gaseous and liquid hydrocarbons and CO2, but as a first approximation, the natural moisture content can be assumed to fill most of the pore space of a coal (Thomas and Damberger 1976).When the coal is dried, the internal moisture will be removed. The internal surface area which was occupied initially by internal moisture will be available for oxygen. The oxygen absorbed by the coal will impose high potential for self-heating.

16

1 Introduction

Fig. 1.7 Relation between inherent moisture content and volume-percent porosity in Illinois coals

1.3.1.5

Coal Rank

Coal rank is the degree of transformation or coalification. Coalification is the alteration of vegetation to form peat, followed by the transformation of peat through lignite, sub-bituminous, bituminous, semianthracite to anthracite coal. As the process of progressive transformation takes place, the heating value and the fixed carbon content of the coal increase, and the amount of volatile matter in the coal decreases. The method of ranking coals used in the United States and Canada was developed by the American Society for Testing and Materials (ASTM). The ASTM ranking system is presented in Table 1.5. Peat is an organic sediment. Burial, compaction, and coalification will transform it into coal, a rock. Peat has a carbon content of less than 60% on a dry ash-free basis. Lignite is the lowest rank of coal. It is a brown-black coal transformed from a peat into a rock. By definition it has a heating value of less than 8300 Btu per pound on a mineral matter-free basis. It has a carbon content of between 60% and 70% on a dry ash-free basis. Sub-bituminous coal is a lignite that has been subjected to an increased level of organic metamorphism. This metamorphism has driven off some of the oxygen and hydrogen in the coal. That loss produces coal with a higher carbon content (71–77% on a dry ash-free basis). Sub-bituminous coal has a heating value between 8300 and 13,000 Btu/lb on a mineral matter-free basis. On the basis of heating value, it is subdivided into sub-bituminous A, B, and C ranks. Bituminous is the most abundant rank of coal. It accounts for about 50% of the coal produced in the

1.3 Affecting Factors on Spontaneous Combustion

17

Table 1.5 Simplified classification of coals by rank

Class and group Anthracite 1. Meta-anthracite 2. Anthracite 3. Semianthracite Bituminous 1. Low-volatile bituminous coal 2. Medium-volatile bituminous coal 3. High-volatile A bituminous coal 4. High-volatile B bituminous coal 5. High-volatile C bituminous coal Sub-bituminous 1. Sub-bituminous A coal 2. Sub-bituminous B coal 3. Sub-bituminous C coal Lignite 1. Lignite A 2. Lignite B

Fixed carbon (dmmf, %) Equal or Less greater than than

Volatile matter (dmmf, %) Greater Equal or than less than

Calorific value (moist mmf, Btu per lb) Equal or Less greater than than

98 92 86

– 98 92

– 2 8

2 8 14

– – –

– – –

78

86

14

22

–

–

69

78

22

31

–

–

–

69

31

–

14,000

–

–

–

–

–

13,000

14,000

–

–

–

–

11,500

13,000

–

–

–

–

10,500

11,500

–

–

–

–

9500

10,500

–

–

–

–

8300

9500

– –

– –

– –

– –

6300 –

8300 6300

United States. Bituminous coal is formed when a sub-bituminous coal is subjected to increased levels of organic metamorphism. It has a carbon content of between 77% and 87% on a dry ash-free basis and a heating value that is much higher than lignite or sub-bituminous coal. On the basis of volatile content, bituminous coals are subdivided into low-volatile, medium-volatile, and high-volatile bituminous. Anthracite is the highest rank of coal. It has a carbon content of over 87% on a dry ash-free basis. Anthracite coal generally has the highest heating value per ton on a mineral matter-free basis. It is often subdivided into semianthracite, anthracite, and meta-anthracite on the basis of carbon content. Baughman (1978) graphically illustrated the relationship of the data from proximate analysis to coal rank in Fig. 1.8. Lu et al. (2013) demonstrate the variation in chemical and physical properties of coal with rank from bituminous to anthracite coals as shown in Fig. 1.9. As the rank increases, the vitrinite reflectance, carbon content, and C/H ratio of coal increase, while the coal volatile matter decreases.

18

1 Introduction

Meta-anthracite Anthracite Semianthracite Low-volale Bituminous Medium-volale Bituminous High-volale A Bituminous High-volale B Bituminous High-volale C Bituminous Subbituminous A Subbituminous B Subbituminous C Lignite 0

10

Fixed Carbon

20

30

40

Volale Maer

50

60

70

80

90

100

Moisture

Fig. 1.8 Fixed carbon, volatile matter, and moisture content of different rank of coal on dry and ash-free basis

Suggate (1982) proposed the Suggate rank (Sr) for New Zealand coal. This coal ranking method is a quantitative classification for coal rank distribution based on coal quality parameters of volatile matter and calorific value on dry mineral matter and sulfur-free basis or the atomic O/C and H/C ratios of the coal on a mineral matter-free basis. Rank of lignite is equal to 0–3, sub-bituminous is 3–8, bituminous is 8–16, semianthracite is 16–20, and anthracite is 20–25 as shown in Fig. 1.10a. It is generally accepted that self-ignition is a rank-related phenomenon. Kim (1977) demonstrated that coal rank has a major influence on coal self-ignition. Low-rank coals are more susceptible to self-heating than high-rank coals. Beamish (2005) defined a nonlinear relationship for coals between R70 self-heating rate and Suggate rank as shown in Fig. 1.10b. He concluded that sub-bituminous coals have the highest R70 self-heating rate of more than 21  C/h indicating sub-bituminous coals have the highest potential of self-heating. The propensity of high-volatile bituminous coals varies greatly from about 14  C/h to 0.5  C/h. Higher-rank coals have lower potential of self-ignition than the lower-rank coals. From this relationship, an initial risk assessment can be obtained by estimating the R70 value of a new coal as long as its Suggate rank is known.

1.3.2

Extrinsic Factors

Extrinsic factors classified by Guney (1968) are temperature, moisture, barometric pressure, oxygen concentration, bacteria, coal seam and surrounding strata, method of working, ventilation system and flow rate, timbering, and roadways. Chakravorty

1.3 Affecting Factors on Spontaneous Combustion

19

Fig. 1.9 Variation in chemical and physical properties of coal with rank

and Kolada (1988) grouped the critical factors contributing to spontaneous combustion into intrinsic, i.e., those that cannot be controlled (coal properties and geological features), and extrinsic, i.e., those that can be controlled (mining practices). Table 1.6 shows these factors. Grubb (2008) investigated the in situ affecting factors by performing a worldwide leading practice survey with visits to 28 mines and agencies and concluded regarding propensity testing: “Leading practices for understanding the propensity and contributing conditions of spontaneous combustion in a particular mine include (a) accurate and detailed record-keeping of spontaneous combustion events at the mine both on the surface and underground,

20

1 Introduction

Fig. 1.10 (a) Suggate rank (Sr) for quantitative classification of New Zealand coal based on volatile matter and calorific value on dry mineral-matter and sulfur-free basis, and (b) variation of coal ranks denoted by Suggate rank (Sr) with R70 self-heating rate of coal

Table 1.6 Critical factors contributing to spontaneous combustion Coal properties High volatile matter High moisture High pyrites High exinite High friability

Geological features Thick seams

Mining practices Leaving roof and floor coal during mining

Presence of inferior pyrite bands and carbonaceous shale Presence of faults

Poor maintenance of roadways and old districts Inadequate measures to prevent air leakage through air crossings, doors, mine seal Caving to surface under shallow overburden Close proximity to multi-seam working

Weak and disturbed strata conditions High strata temperature

Poor ventilation management

(b) propensity testing of splits of the seam mined as well as rider seams above and below the seam in zones of caving and fracturing, (c) confirmation of the propensity by at least two methods, (d) medium to large scale laboratory gas evolution testing to identify signature gases, (e) annual small scale and large scale testing as appropriate for changes encountered, (f) use of numerical modelling or an expert system such as NIOSH’s SponCom 2.0 to identify contributing factors and (g) intensive evaluation of geological and other contributing factors.” The extrinsic properties mainly discussed in this section that will influence the propensity testing experiments are environmental humidity, particle size, and aging effect. More detailed research findings for extrinsic affecting factors related to real underground coal mine, please refer to the literature published by Grubb et al. (2015).

1.3 Affecting Factors on Spontaneous Combustion

1.3.2.1

21

Humidity

Humidity in the surrounding atmosphere is in equilibrium with moisture contained in the coal under normal conditions. In such circumstances, there is no net heat transfer due to adsorption and desorption. When the equilibrium is broken, the adsorption and desorption processes will play an important role in controlling heat generation. Humidity normally facilitates oxidation (Misra and Singh 1994), when moist air flows over a dry coal. The moisture adsorbed that contributes to spontaneous combustion could either come from humidity or from other coals. For example, when new coal added over old coal may create more heat at their interface (Hossfeld and Hatt 2005). The most dangerous scenario for spontaneous combustion is when wet and dry coals are combined. The interface between wet and dry coal becomes a heat exchanger (Smith et al. 1991). If the coal partially dried during its mining, storage, or processing, with the potential to reabsorb moisture from environmental humidity, the coal will produce heat. The adsorption of moisture on a dry coal surface is an exothermic process generating heat. Coal drying is an endothermic process, in which heat is absorbed by the moisture to evaporate, and the temperature of the coal is lowered. With moisture gradually adsorbed from the ambient humidity, the moisture content in the coal increase which has a major retarding effect on spontaneous heating. Heat generated by adsorption and oxidation is used to vaporize the moisture in the coal, forming a competing influences of heat of wetting and moisture evaporation (Arisoy and Akgün 1994). Nugroho et al. (2008) pointed out that the sub-bituminous coal has the most rapid self-heating rate at the relative humidity of 70% rather than at 90%. Küçük et al. (2003) found that the tendency of Turkish lignite to self-heating increased with decreasing humidity of the air.

1.3.2.2

Particle Size

The rate of coal oxidation has a linear relationship to the surface area of coal (Sujanti et al. 1999). Smaller particles have a larger surface area per unit volume of the coal particle (Akgün and Arisoy 1994). Studies pointed out that the liability of spontaneous combustion of coal was increased with decreasing particle size. (Kadioğlu and Varamaz 2003; Küçük et al. 2003). The smaller particle size of the coal, the greater the surface area exposed to oxidation, thus releasing more heat per unit volume of coal (Carras and Young 1994; Krishnaswamy et al. 1996). However, the oxidation rate does not always keep increasing with decreasing particle size. When the particle size is below a critical diameter, it has little effect on the oxidation rate (Palmer et al. 1990; Ren et al. 1999). Although particle size of coal shows an effect on the rate of oxidation for some types of coal, the nature of this effect is still not fully understood. Sondreal and Ellman (1974) indicated that the effect of particle size was represented by the following equations:

22

1 Introduction

r¼


k 1  e5:5m m 1:22 m¼ s

ð1:3Þ ð1:4Þ

where r is oxidation rate, kg/h; k is an oxidation rate constant; m is the mean sieve size, inches; and s is specific surface area of coal particles excluding internal pore area, ft2/lb.

1.3.2.3

Aging Effect

The aging of coal refers to the physical and chemical changes when coal is exposed to air and oxidized by oxygen. The changes can affect the behavior and properties of coal and therefore affect the coal as it is processed and utilized. Aging can affect the propensity of the coal’s spontaneous combustion in the following three ways: (a) slow oxidation at ambient temperature to increase the retardant in the coal, (b) reaction and consumption of the active chemical fractions of the coal making the coal intrinsic properties inert, and (c) evaporation of the coal moisture. Based on the parameters considered in the USBM CSHT method, these three coal quality parameters could retard the coal’s self-heating process. As the coal cores are stored in ambient environment, the self-heating rate value decreases noticeably as the storage time increases. Many tests have been conducted by Beamish to show the aging effect on self-heating potential of coal (Beamish et al. 2000). Coal samples were collected from Huntly East, BBL, and New Vale coal mines in New Zealand. The tests were performed with different time lengths after the samples were taken. Huntly East coals have been stored for 2, 7, 14, and 33 days before the R70 tests and marked as HE1, HE4, HE8, and HE10, respectively, as shown in Fig. 1.11. It was found that as the storage time increased the self-heating rate decreased. The HE1 coal sample with a storage time of only 2 days has the most rapid self-heating rate, 19.53  C/h, and the earliest thermal runaway. The HE10 coal sample with a 33-day storage time has a self-heating rate of 13.47  C/h. This is also confirmed by the results for the repeat tests on samples from BBL and New Vale mines. BBL samples have a considerable drop in R70 of 6.05  C/h over a 56-day period between tests. The coal sample from New Vale only has 1.89  C/h selfheating rate after 609-day storage.

1.4

Overview of This Book

In this book, characteristics of coal to spontaneous combustion have been comprehensively studied using experimental, theoretical, and numerical approaches. The book is organized into six chapters. In this Chapter, hazards, accidents, and impacts

1.4 Overview of This Book

23

200 180 2 days elapsed 160

7 days elapsed 14 days elapsed

Temperature (°C)

140

33 days elapsed 120 100 80 60 40 20 0 0.0

0.5

1.0

1.5 2.0 Time (hours)

2.5

3.0

3.5

Fig. 1.11 Repeat self-heating profiles for Huntly East samples (Beamish et al. 2000)

of spontaneous combustion of coal as current global scenarios are introduced. The existing problems and importance of this study has been presented. The understanding of the spontaneous combustion phenomenon is reviewed including the causal factors in terms of intrinsic and extrinsic affecting factors. Classic experimental methods (USBM method, adiabatic method, isothermal and CPT methods, and thermoanalytical method including TG, DTA, and DSC), analytical and numerical modeling, monitoring, and mitigation techniques (TBS, GC, fire ratios, and inhibiting techniques) are summarized in Chap. 2. Then, Chap. 3 is mainly focused on laboratory experiments jointly conducted by R70 and moist R70 experiments, TGA experiment, TGA-based proximate analysis experiment, retardant optimal screening experiment, and FTIR experiment. Chapter 4 presents in-depth research findings associated with theoretical approaches for further understanding the mechanism to what extent the affecting factors exert their influence on self-heating behavior. A new analytical model capable of quantifying the effect of moisture condensation, relative humidity, pyrite oxidation, coal oxidation in terms of activation energy, and ambient temperature on propensity of spontaneous ignition is developed. A new coal ranking system with the function of updating the qualitative classification method into a quantitative one is also proposed in this chapter. Longwall gob, a favorable remote space for broken coal oxidation, as primary study object is investigated in Chap. 5. Spontaneous combustion behavior in ultraclose coal seam, variation of oxidation zone under different ventilation types, and mitigation effect due to grouting and inert gas injection are simulated by numerical modeling in this chapter. As the last chapter, Chap. 6 presents two cases of thermal

24

1 Introduction

event occurred in longwall gob and longwall panel. Analyzed the tube bundlechromatography monitoring data, a number of common fire ratios as important indicators are calculated to identify the status of the thermal events. From this chapter to Chap. 6, this book offers a systematic methodology for fully recognizing the characteristics of spontaneous combustion and risk assessment.

References Akgün, F., & Arisoy, A. (1994). Effect of particle size on the spontaneous heating of a coal stockpile. Combustion and Flame, 99(1), 137–146. Arisoy, A., & Akgün, F. (1994). Modelling of spontaneous combustion of coal with moisture content included. Fuel, 73(2), 281–286. Barr, W. M. (1900). A catechism on the combustion of coal and the prevention of smoke. New York: NW Henley & Company. Baset, Z. H., Pancirov, R. J., & Ashe, T. R. (1980). Organic compounds in coal: Structure and origins. Physics and Chemistry of the Earth, 12, 619–630. Baughman, G. L. (1978). Synthetic fuels data handbook, Cameron Engineers, Inc., Denver, CO, 118. Beamish, B., (2005). Comparison of the R70 self-heating rate of New Zealand and Australian coals to Suggate rank parameter. International Journal of Coal Geology, 64(1–2), 139–144. Beamish, B. & Beamish, R. (2012). Testing and sampling requirements for input to spontaneous combustion risk assessment. Australian Mine Ventilation Conference 2011, Sydney, Australia, 5–6 September 2011. Carlton, Vic., Australia: Australasian Institute of Mining and Metallurgy. Beamish, B. B., & Blazak, D. G. (2005). Relationship between ash content and R70 self-heating rate of Callide Coal. International Journal of Coal Geology, 64(1), 126–132. Beamish, B. B., & Hamilton, G. R. (2005). Effect of moisture content on the R70 self-heating rate of Callide coal. International Journal of Coal Geology, 64(1–2), 133–138. Beamish, B. B., Barakat, M. A., & St George, J. D. (2000). Adiabatic testing procedures for determining the self-heating propensity of coal and sample ageing effects. Thermochimica Acta, 362(1–2), 79–87. Beamish, B., Lin, Z., & Beamish, R. (2012). Investigating the influence of reactive pyrite on coal self-heating. Coal Operators’ Conference, The University of Wollongong (pp. 294–299). Berkowitz, N. (1951). Heats of wetting and the spotaneous ignition of coal. Fuel, 30, 94–96. Bhattacharyya, K. (1971). The role of sorption of water vapour in the spontaneous heating of coal. Fuel, 50(4), 367–380. Bodzek, D., & Marzec, A. (1981). Molecular components of coal and coal structure. Fuel, 60(1), 47–51. Carras, J. N., & Young, B. C. (1994). Self-heating of coal and related materials: Models, application and test methods. Progress in Energy and Combustion Science, 20(1), 1–15. Cathles, L., & Apps, J. (1975). A model of the dump leaching process that incorporates oxygen balance, heat balance, and air convection. Metallurgical Transactions B, 6(4), 617. Chakravorty, R., & Kolada, R. (1988). Prevention and control of spontaneous combustion in coal mines. Mining Engineering, 40, 952–956. Chen, X. D. (1992). On the mathematical modeling of the transient process of spontaneous heating in a moist coal stockpile. Combustion & Flame, 90(2), 114–120. Chen, X. D., & Stott, J. B. (1993). The effect of moisture content on the oxidation rate of coal during near-equilibrium drying and wetting at 50  C. Fuel, 72(6), 787–792. Chen, Y., Mastalerz, M., & Schimmelmann, A. (2012). Characterization of chemical functional groups in macerals across different coal ranks via micro-FTIR spectroscopy. International Journal of Coal Geology, 104, 22–33.

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Clark, C. S. (1966). Oxidation of coal mine pyrite. Journal of the Sanitary Engineering Division, 92 (2), 127–146. Clemens, A. H., & Matheson, T. W. (1996). The role of moisture in the self-heating of low-rank coals. Fuel, 75(7), 891–895. Cliff, D. (2009). Spontaneous combustion management-linking experiment with reality. Coal Operators’ Conference, University of Wollongong (pp. 281–286). Cliff, D., Rowlands, D., & Sleeman, J. (1996). Spontaneous combustion in Australian coal mines. Redbank: SIMTARS. Das, B., & Hucka, V. (1986). Control of spontaneous combustion of coal through an analysis of its mechanism and the affecting factors. Society of Mining Engineers of AIME, Presented at the SME annual meeting, New Orleans, LA (pp. 86–62). De Rosa, M. I. (2004). Analysis of mine fires for all US underground and surface coal mining categories: 1990–1999. Information Circular-United States, NIOSH. Düzgün, H. S., & Leveson, N. (2018). Analysis of soma mine disaster using causal analysis based on systems theory (CAST). Safety Science, 110, 37–57. Edmunds, W. E. (2002). Coal in Pennsylvania. Harrisburg: Commonwealth of Pennsylvania, Department of Conservation and Natural Resources. Ejlali, A., Mee, D. J., Hooman, K., & Beamish, B. B. (2011). Numerical modelling of the selfheating process of a wet porous medium. International Journal of Heat & Mass Transfer, 54 (25), 5200–5206. Evangelou, V. (2018). Pyrite oxidation and its control. Boca Raton: CRC press. Falcon, R., & Ham, A. (1988). The characteristics of South African coals. Journal of the Southern African Institute of Mining and Metallurgy, 88(5), 145–161. Fuchs, W., & Sandhoff, A. G. (1942). Theory of coal pyrolysis. Industrial & Engineering Chemistry, 34(5), 567–571. Gambrel, D. (2010). Safety at sea and the shipper’s duty to warn. Coal Age, 115(8), 18. Gan, H., Nandi, S., & Walker, P., Jr. (1972). Nature of the porosity in American coals. Fuel, 51(4), 272–277. Garcia, P., Hall, P. J., & Mondragon, F. (1999). The use of differential scanning calorimetry to identify coals susceptible to spontaneous combustion. Thermochimica Acta, 336(1), 41–46. Given, P. H., et al. (1975). Dependence of coal liquefaction behaviour on coal characteristics. 2. Role of petrographic composition. Fuel, 54(1), 40–49. Gong, R., Burnell, J., & Wake, G. (1999). Modelling spontaneous combustion in wet lignite. Combustion Theory and Modelling, 3(2), 215–232. Gouws, M., & Knoetze, T. (1995). Coal self-heating and explosibility. Journal of the Southern African Institute of Mining and Metallurgy, 95(1), 37–43. Gray, B. F., Sexton, M. J., Halliburton, B., & Macaskill, C. (2002). Wetting-induced ignition in cellulosic materials. Fire Safety Journal, 37(5), 465–479. Grubb, J. W. (2008). Preventative measures for spontaneous combustion in underground coal mines. Colorado School of Mines. Arthur Lakes Library, Colorado, US. Grubba, J. W. et al. (2015). Managing the risk of spontaneous combustion in underground coal mines. Proceedings of 15th North American Mine Ventilation Symposium, Virginia Tech, Virginia (pp. 1–10). Guney, M. (1968). Oxidation and spontaneous combustion of coal: Review of individual factors. Colliery Guardian, 216(105–110), 137–143. Guney, M. (1971). An adiabatic study of the influence of moisture on the spontaneous heating of coal. CIM Bulletin, 64(3), 138–146. Haenel, M. W. (1992). Recent progress in coal structure research. Fuel, 71(11), 1211–1223. Hossfeld, R. J., & Hatt, R. (2005). PRB coal degradation: Causes and cures. PRB Coal Users Group, http://www.prbcoals.com/pdf/paper_archives/56538.pdf. Kadioğlu, Y., & Varamaz, M. (2003). The effect of moisture content and air-drying on spontaneous combustion characteristics of two Turkish lignitesa. Fuel, 82(13), 1685–1693.

26

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KaymakçI, E., & Didari, V. (2001). Relations between coal properties and spontaneous combustion parameters. Turkish Journal of Engineering and Environmental Sciences, 26(1), 59–64. Kidena, K., Murata, S., & Nomura, M. (2008). A newly proposed view on coal molecular structure integrating two concepts: Two phase and uniphase models. Fuel Processing Technology, 89(4), 424–433. Kim, A. G. (1977). Laboratory studies on spontaneous heating of coal: A summary of information in the literature. Washington, DC: Dept. of the Interior, Bureau of Mines. Krichko, A. A., & Gagarin, S. G. (1990). New ideas of coal organic matter chemical structure and mechanism of hydrogenation processes. Fuel, 69(7), 885–891. Krishnaswamy, S., Bhat, S., Gunn, R. D., & Agarwal, P. K. (1996). Low-temperature oxidation of coal. 1. A single-particle reaction-diffusion model. Fuel, 75(3), 333–343. Kuchta, J., Rowe, V., & Burgess, D. S. (1980). Spontaneous combustion susceptibility of US coals. Washington, DC: US Dept. of the Interior, Bureau of Mines. Küçük, A., Kadıoğlu, Y., & Gülaboğlu, M. Ş. (2003). A study of spontaneous combustion characteristics of a turkish lignite: Particle size, moisture of coal, humidity of air. Combustion and Flame, 133(3), 255–261. Levenspiel, O. (1999). Chemical reaction engineering. Industrial & Engineering Chemistry Research, 38(11), 4140–4143. Li, S. H., & Parr, S. W. (1926). The oxidation of pyrites as a factor in the spontaneous combustion of coal. Industrial & Engineering Chemistry, 18(12), 1299–1304. Litton, C. D., & Page, S. J. (1994). Coal proximate analyses correlations with airborne respirable dust and spontaneous combustion temperature. Fuel, 73(8), 1369–1370. Lorenz, W. C., & Stephan, R. W. (1967). Factors that affect the formation of coal mine drainage pollution in Appalachia. Pittsburgh: U.S. Dept. of the Interior, Bureau of Mines, Area I Mineral Resource Office. Lu, L., Devasahayam, S., & Sahajwalla, V. (2013). Chapter 14 – Evaluation of coal for metallurgical applications. In D. Osborne (Ed.), The coal handbook: Towards cleaner production (pp. 352–386). Oxford: Woodhead Publishing. Malumbazo, N. (2011). Chemical and physical structural studies on two inertinite-rich lump coals. Ph.D. dissertation. The University of the Witwatersrand, Johannesburg, South Africa. Marzec, A. (1986). Macromolecular and molecular model of coal structure. Fuel Processing Technology, 14, 39–46. Marzec, A., & Schulten, H.-R. (1991). Chemical nature of species associated with mobile protons in coals. Coal Science II. ACS symposium series. American Chemical Society (pp. 61–71). Misra, B. K., & Singh, B. D. (1994). Susceptibility to spontaneous combustion of Indian coals and lignites: An organic petrographic autopsy. International Journal of Coal Geology, 25(3), 265–286. Nelson, M. I., & Chen, X. D. (2007). Survey of experimental work on the self-heating and spontaneous combustion of coal. Reviews in Engineering Geology, 18(1), 1831–1883. Nordon, P., & Bainbridge, N. (1983). Heat of wetting of a bituminous coal. Fuel, 62(5), 619–621. Nugroho, Y. S., Iman, R. R. R., & Saleh, M. (2008). Effect of humidity on self-heating of a sub-bituminous coal under adiabatic conditions. Fire Safety Science, 9, 179–189. Ogunsola, O. I., & Mikula, R. J. (1992). Effect of thermal upgrading on spontaneous combustion characteristics of western Canadian low rank coals. Fuel, 71(1), 3–8. Onifade, M., & Genc, B. (2018). Modelling spontaneous combustion liability of carbonaceous materials. International Journal of Coal Science & Technology, 5(2), 191–212. Palmer, A., Cheng, M., Goulet, J.-C., & Furimsky, E. (1990). Relation between particle size and properties of some bituminous coals. Fuel, 69(2), 183–188. Parr, S. W., & Kressman, F. W. (1910). The spontaneous combustion of coal, with special reference to bituminous coals of the illinois type. University of Illinois Bulletin, No. 46, Urbana, Illinois, US.

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Phillips, H., Uludag, S., & Chabedi, K. (2011). Prevention and control of spontaneous combustion, Best practice guidelines for surface coal mines in South Africa Coaltech research association annual colloquium. Pomroy, W. H., & Carigiet, A. M. (1995). Analysis of underground coal mine fire incidents in the United States from 1978 through 1992. Washington, DC: Information Circular-United States, Bureau of Mines. Ren, T., Edwards, J., & Clarke, D. (1999). Adiabatic oxidation study on the propensity of pulverised coals to spontaneous combustion. Fuel, 78(14), 1611–1620. Rosema, A., Guan, H., & Veld, H. (2001). Simulation of spontaneous combustion, to study the causes of coal fires in the Rujigou Basin. Fuel, 80(1), 7–16. Shinn, J. H. (1984). From coal to single-stage and two-stage products: A reactive model of coal structure. Fuel, 63(9), 1187–1196. Singh, R., & Ardejani, F. D. (2004). Finite volume discretisation for solving acid mine drainage problems. Archives of Mining Sciences, 49(4), 531–556. Smith, M. A., & Glasser, D. (2005). Spontaneous combustion of carbonaceous stockpiles. Part I: The relative importance of various intrinsic coal properties and properties of the reaction system. Fuel, 84(9), 1151–1160. Smith, A. C., Miron, Y., & Lazzara, C. P. (1991). Large-scale studies of spontaneous combustion of coal. Pittsburgh: United States Dept. of the Interior, Bureau of Mines. Solomon, P. R. (1981). Coal structure and thermal decomposition, New Approaches in Coal Chemistry. ACS symposium series. American Chemical Society (pp. 61–71). Sondreal, E. A., & Ellman, R. C. (1974). Laboratory determination of factors affecting storage of North Dakota lignite: Computer simulation of spontaneous heating. [28 refs; graphs], Bureau of Mines, Grand Forks, N. Dak. (USA). Grand Forks Energy Research Lab. Speight, J. G. (1994). The chemistry and technology of coal. Boca Raton: CRC press. Spiro, C. L., & Kosky, P. G. (1982). Space-filling models for coal. 2. Extension to coals of various ranks. Fuel, 61(11), 1080–1IN2. Stracher, G. B., et al. (2005). New mineral occurrences and mineralization processes: Wuda coalfire gas vents of Inner Mongolia. American Mineralogist, 90(11–12), 1729–1739. Suggate, R. (1982). Low-rank sequences and scales of organic metamorphism. Journal of Petroleum Geology, 4(4), 377–392. Sujanti, W., Zhang, D.-K., & Chen, X. D. (1999). Low-temperature oxidation of coal studied using wire-mesh reactors with both steady-state and transient methods. Combustion and Flame, 117 (3), 646–651. Sweeny, P., Grow, D., & McCollor, D. (1988). Studies on ignition of coal: the effects of rank, temperature, volatile content, and lithotype. Prepr. Pap., Am. Chem. Soc., Div. Fuel Chem.; (United States) 33(CONF-8809272-). Thomas, J., & Damberger, H. H. (1976). Internal surface area, moisture content, and porosity of Illinois coals: Variations with coal rank. Circular no. 493. Urbana: Illinois State Geological Survey. Vance, W. E., Chen, X. D., & Scott, S. C. (1996). The rate of temperature rise of a subbituminous coal during spontaneous combustion in an adiabatic device: The effect of moisture content and drying methods. Combustion and Flame, 106(3), 261–270. Walters, A. (1996). Joseph Conrad and the spontaneous combustion of coal part 1. Coal Preparation, 17(3–4), 147–165. Weiqing, Z., et al. (2011). Study on coal spontaneous combustion characteristic structures affected by ionic liquids. Procedia Engineering, 26, 480–485. Xu, J. (2001). Determination theory of coal spontaneous combustion zone. Beijing: China Coal Industry Publishing House.

Chapter 2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

Abstract This chapter summarizes the experimental, theoretical, and preventive methods on identifying and controlling spontaneous combustion. Classic experimental methods for evaluating lability of self-heating are reviewed including USBM method, adiabatic method, isothermal and CPT methods, and thermoanalytical method which involves TG, DTA, and DSC. Theoretical techniques including kinetic model, Arrhenius reaction rate model, shrinking core model, and numerical model are presented. Tube bundle system (TBS), gas chromatography (GC) and fire ratios for monitoring system and inert gas injection, sealant technology, and chemical retardant for mitigation measures are summarized. Keywords Experimental method · Arrhenius reaction · Kinetic method · Numerical modeling · Gas monitoring system · Fire ratios

2.1 2.1.1

Experimental Approaches for Determining Propensity of Spontaneous Combustion USBM SHT Method

The concept of minimum self-heating temperature (SHTmin) was originally proposed by Smith and Lazzara 1987. It is determined by an adiabatic experiment. In the experiment, grounded dry coal samples were placed in an adiabatic vessel and then exposed to a continuous steady flow of moist air of predetermined temperature. The experiment was repeated at various temperatures with fresh samples for each run until the lowest heating temperature demonstrating thermal runaway is obtained as shown in Fig. 2.1. The lowest initial temperature at which a coal can sustain an exothermic reaction or thermal runaway was termed as the SHTmin of coal. The lower the SHTmin, the higher the self-heating potential of the coal. Two empirical equations were derived to predict the SHTmin based on ultimate analysis and proximate analysis. One is correlated with oxygen content on dry, ash-free (DAF) basis (Smith and Lazzara 1987). The independent variable, oxygen content, in the © Springer Nature Switzerland AG 2020 X. Wang, Spontaneous Combustion of Coal, https://doi.org/10.1007/978-3-030-33691-2_2

29

30

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

Fig. 2.1 Temperature history for (a) one coal at initial temperatures of 70, 75, 80, and 90  C and (b) for various coals at their SHTmin (Smith and Lazzara 1987)

equation can be determined from ultimate analysis of coal. The SHTOX can be determined using the following equation: SHT min OX ¼ 139:74  6:57  ODAF

ð2:1Þ

where SHTminOX is the minimum self-heating temperature in  C and ODAF is the oxygen content on a dry, ash-free basis in %. The other one is proposed by Litton and Page which is correlated with moisture fuel ratio (MFR) as independent variable, a new concept developed by them (Litton and Page 1994). The MFR is expressed by coal quality parameters which can be obtained from proximate analysis (ASTM D-5142), in which coal is determined to be composed of moisture, volatile matter, fixed carbon, ash, and sulfur. The SHTVOL can be determined using the following equation:
 SHTminVOL ¼ 117 1  e2:6x

ð2:2Þ

where SHTminVOL is the critical self-heating temperature in  C and x is the “moist fuel ratio” which is expressed as x¼


%fixedcarbon  %volatilematter

%moisture

ð2:3Þ

If the SHTmin is less than 70  C, the coal will be classified as having a high potential for spontaneous ignition. Coals having a SHTmin at or above 70  C, but less than 100  C, are considered as having a moderate potential for spontaneous ignition. For coals having a SHTmin equal to or greater than 100  C, the potential for spontaneous ignition will be low. It should be noted that these two methods are not associated with each other. They are only related in that Litton and Page used Smith and Lazzara’s experimental data

2.1 Experimental Approaches for Determining Propensity of Spontaneous Combustion

31

to do their analysis and develop the SHTminVOL. Both used SHTmin as the dependent variable for evaluating the tendency of spontaneous combustion. SHTmin is not a factor but an index. Smith and Lazzara only used 19 bituminous data sets out of 24, excluding 2 lignites, 2 bituminous, and 1 anthracite. Litton and Page used 23 of Smith and Lazzara’s experimental data sets when they proposed their SHT method. Only the anthracite was not included, because its SHTmin was not determined experimentally. However, there were still no sub-bituminous coal data sets in Smith and Lazzara’s and Litton and Page’s works. Kuchta et al. (1980) presented the sub-bituminous coal’s data in their study. The first advantage of this method is that the determination of the SHT is easy, just using the empirical equation, as long as proximate analysis data, which is usually easily obtained by ASTM standard test, are available. Second, it reflects the effects of the factors of moisture, volatile matter, and fixed carbon on the coal’s propensity for spontaneous combustion. This method not only classifies self-heating potential quantitatively and provides a risk index for rating coals but also reveals the most likely causes of this phenomenon.

2.1.2

Adiabatic Oxidation Method

Adiabatic methods, sometimes called adiabatic oxidation methods, are considered to be good at simulating the initial stages of coal oxidation in situ (Singh et al. 2002). The heat generated at the beginning of oxidation was made to be stored by the coal itself without losing heat to the surroundings. A reaction container holding a certain amount of coal sample is placed in an adiabatic oven. After the sample is preheat and dried in the nitrogen atmosphere, pure oxygen as the major reaction gas is used to pass through the sample. A thermometer is buried inside the coal sample, while another is used to measure the oven temperature. Ideally, the oven temperature should be controlled to be equal to that of the coal sample to avoid heat exchange between the coal sample and its testing surrounding. Through such control, it is ensured that only and all the heat generated by the oxidation of the coal sample is used to sustain the reaction and to raise the temperature of the coal. R70 test is one of the typical adiabatic methods. Originally developed by Davis and Byrne (1924), it is currently a widely accepted and used method worldwide. This method was then further developed by proposing the definition of the index R70 to express the selfheating rate in the liner part of the adiabatic self-heating curve from 40 to 70  C as shown in Fig. 2.2. (Humphreys et al. 1981). Once the temperature increases past 70  C, the rate of temperature rises dramatically leading to a thermal runaway. As the testing technique develops, the R70 method has been continuously improved and is capable of testing the coal samples in both dry and moist adiabatic environment to evaluate the effect of moisture content on the coal (Arisoy and Beamish 2015; Arisoy et al. 2017; Beamish et al. 2000; Beamish and Blazak 2005; Beamish and Hamilton 2005).

32

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Historical Perspective on Identifying and Controlling Spontaneous Combustion

160

Temperature (°C)

140

120

100

80

R70 = 2.18 °C/h

60

40 0

2

4

6

8

10

12

14

16

18

20

22

24

Time (hours)

Fig. 2.2 Typical R70 self-heating curve of coal

The standard procedure for conducting an adiabatic R70 test is as follows: (1) crush 150 g of coal to size smaller than 212 μm, (2) place the samples in an insulated reaction vessel, (3) dry the sample in nitrogen at 110  C for 16 h, (4) cool the sample to 40  C in nitrogen, (5) start the oxidation test by passing a 50 mL/min oxygen flow through the reaction vessel, (6) measure and record the temperature of coal sample in the vessel and the oven temperature simultaneously, (7) adjust the oven temperature to match the coal temperature, and (8) determine the R70 values – the average coal self-heating rate from 40 to 70  C based on the measured selfheating curve, expressed in  C/h. Research efforts have been made to assess the selfheating behavior of coal at low temperature from ambient to thermal runaway and to study the influences of rewetting heat and moisture vaporization under different environmental conditions. Beamish and Beamish (2012) developed a Moist Adiabatic Benchmark (MAB) test method. In the MAB testing procedure, (1) coal is tested with its as-received moisture content, and the ambient mine temperature is used as the starting temperature, (2) approximately 200 g coal sample is placed to the reaction vessel, (3) oxygen is used to flow into the container at 10 mL/min, (4) temperature change is recorded by thermometer and computer, and (5) the actual self-heating time on mine site of other samples is extrapolated based on the predetermined benchmark coals. Propensity rating is updated to a seven-tier system based on Queensland (extremely high  16, 8  ultrahigh < 16, 4  very high < 8, 2  high < 4, 1  medium < 2, 0.5  low-medium < 1, low < 0.5) and New South Wales (extremely high  32, 16  ultrahigh < 32, 8  very high < 16, 4  high < 8, 2  medium < 4, 1  low-medium < 2, low < 1) coal conditions from three-tier

160

160

140

140

Coal Temperature (°C)

Coal Temperature (°C)

2.1 Experimental Approaches for Determining Propensity of Spontaneous Combustion

120 100 80 60

33

120 100 80 60 40

40 0

1

2

3

4

5

6

7

8

9

10

0

20

40

60

Coal B (subB)

Coal C (subA)

Coal D (hvCb)

80 100 120 140 160 180 200 220 240 Time (h)

Time (h) Coal A (subC)

Coal E (hvBb)

Coal F (hvBb)

Coal G (hvAb)

Coal H (hvAb)

Coal I (mvb)

Coal J (lvb)

Fig. 2.3 Temperature history for various ranks of coals from sub-bituminous C to low-volatile bituminous determined from R70 adiabatic experiment (Beamish et al. 2001)

system (high risk > 0.8, medium risk ¼ 0.5–0.8, low risk < 0.5) used by Australian Coal Industry Research Laboratories (ACIRL) since 1981. Based on the R70 adiabatic testing method, research findings that considers many other affecting factors have been made since this method have been widely used. Beamish et al. (2000) studied the aging effects on self-heating tendency of coal and proposed the equation R70(t) ¼ atb to describe the pre-oxidation effect, where t is the time in days, b a constant dependent on storage method and particle size, and a the R70 value of fresh coal; Beamish et al. (2001) pointed out that self-heating behavior is rank dependence for New Zealand coals, with sub-bituminous coals of 14.91–17.23  C/h, lignite 7.768  C/h, and high-volatile bituminous B coals 0.31–2.238  C/h as shown in Fig. 2.3; Beamish et al. (2003) presented kinetic parameters in terms of activation energy and pre-exponential factor in the temperature range of 40–70  C and 70–140  C, respectively, based on the adiabatic selfheating tests data; Beamish and Blazak (2005) concluded that R70 decrease significantly with increasing mineral matter (ash) content and trend line equation was proposed as R70 ¼ 0.0029  ash2  0.4889  ash + 20.644; Beamish and Hamilton (2005) pointed that as the moisture content increased, the R70 value decreases, especially above a critical level of moisture content at 40–50%, making the coal self-heating significantly delayed; Beamish and Arisoy (2008) conducted adiabatic experiment on samples with mineral matter content of 11.2–71.1% and argued that mineral matter in coal is inhibiting the oxidation reaction due to physicochemical effects; Beamish and Sainsbury (2008) performed R70 tests on a series of US coals from longwall mine, found that presence of high sodium (Na2O) resulted in a low R70 value, and developed a self-heating rate prediction equation for high-volatile bituminous coal as R70 ¼  0.6351  ash  0.1767  Na2O + 7.63, where ash and Na2O are in dry weight percent; a new moist coal adiabatic oven test has been proposed to measure the influence of moisture and pyrite on low-temperature selfheating of coal, showing the effects of moisture and pyrite on coal self-heating leading to thermal runaway (Beamish and Beamish 2010, 2011), Beamish and Beamish (2012) updated the previously developed testing method as Moist Adiabatic Benchmark (MAB) test to investigate the competing influences of moisture in the coal and in the surrounding environment; Beamish et al. (2012) used the updated

34

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

testing method to investigate the influence of reactive pyrite on self-heating of a high-volatile bituminous coal containing sulfur concentrations from 0.62% to 17.95%.

2.1.3

Thermoanalytical Methods

2.1.3.1

Thermal Gravimetry (TG) and Differential Thermal Analysis (DTA)

Thermoanalytical methods are usually considered to be a micron-scale investigation only with 10–20 mg samples. The thermal gravimetrical analysis (TGA) is a typical thermoanalytical method in studying coal’s self-heating potential (Mthabela 2016). In a relatively short period of experiment on a small coal sample, the oxidation process of coal can be simulated in a precisely controlled environment. Through processing the testing data with kinetic theory, the measured temperature and weight can be used to calculate pre-exponential factor and activation energy of the coal which in turn is a good indicator for the propensity of spontaneous heating (Meng et al. 2010; Saleh and Nugroho 2013; Wang et al. 2003a). The temperatures and weights of the specimen are precisely measured by the analyzer during the process and plotted as shown in Fig. 2.4. Typically, a complete oxidation process can be divided into three stages according to the changing pattern of the T-G curve. In the initial stage, the specimen loses its weight due to the evaporation of the contained moisture, and this stage ends at the first inflection point t1, the first TG peak. Then the specimen could experience a weight gain stage as the low-temperature oxidation

Fig. 2.4 Typical thermal gravimetric experiment curve

2.1 Experimental Approaches for Determining Propensity of Spontaneous Combustion 100

100

35

110 256.95ºC 301.85ºC 131.26ºC

90

0.9307%

95

80

Weight (%)

Weight (%)

Weight (%)

100

90

125.13ºC

4.279%

90 70

60

85

0

50

100

150

200

250

Temperature (ºC)

300

80

0

50

100 150 200 250 300 350 Temperature (ºC)

80

0

50 100 150 200 250 300 350 4 Temperature (ºC)

Prone coal

Reactive

Low reactive Wider temperature range

Mass increase not seen

Narrow temperature range

Fenosa, North Dakota, and

(In this case 125ºC)

(In this case 175ºC)

Orukpa shown same profile

Slight mass increase

High mass increase

(In this case 0.93%)

(In this case 4.28%)

Fig. 2.5 Weight loss profiles obtained by TGA for demonstrating coals with different reactivities (Avila 2012)

occurs before ignition point t2, the second TG peak. Point t1 and t2 are two inflection points to define the weight loss and weight gain stages. The third stage is the combustion process of the specimen during which the weight of the specimen decreases rapidly, and this stage ends at tend (TGA end) when all the combustibles in the coal specimen are fully consumed (Zhang et al. 2018). If a coal has self-ignition potential, only a little activation energy is needed for the coal to be oxidized, and the weight gain in oxidation stage on TGA curve is not obvious as shown in Fig. 2.5 (Avila 2012). Therefore, the less activation energy and more weight gain, the higher is the potential of self-ignition and vice versa. Activation energy and pre-exponential factor at dehydration stage are E1 and A1, at oxidation adsorption stage are E2 and A2, and at combustion stage are E3 and A3, in this book. The activation energy (an indicator of spontaneous combustion propensity) as an independent kinetic parameter of a coal can be obtained from a data analysis procedure of the TGA testing results as follows which is the Coats and Redfern method (Borah et al. 2005). For a chemical reaction involving substance A and B to produce C (Gold and Bethell 1976), the reaction form and the reaction rate are expressed as AþB!C dc ¼ k ðT Þf ðcÞ dt

ð2:4Þ

36

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

In Eq. 2.4, dc is the differential concentration of substance C within a time duration of dt, k(T ) is reaction rate constant that quantifies the speed of a chemical reaction, and f(c) is the function of reaction mechanism. In Eq. 2.4, the reaction rate constant can be expressed by Arrhenius equation: kðT Þ ¼ AeE=RT

ð2:5Þ

In this equation, A is the pre-exponential factor in unit of s1, R is the gas constant and equal to 8.314 J/molK, and E is the activation energy in kJ/mol. When Eq. 2.5 is substituted into Eq. 2.4, it becomes dc ¼ AeE=RT f ðcÞ dt

ð2:6Þ

Equation 2.6 denotes the homogeneous and isothermal reaction in gas or liquid state. Since the oxidation of coal is a solid-state and non-isothermal reaction, the fractional conversion (α) in % for solid reaction is introduced to replace c. Temperature increment rate (β) in K/min is introduced for non-isothermal reaction: β¼

dT dt

ð2:7Þ

Substitute Eq. 2.7 into Eq. 2.6, and it becomes dα 1 E=RT ¼ Ae F ðαÞ dT β

ð2:8Þ

Integrate both sides of Eq. 2.8: Z 0

α

dα A ¼ F ðαÞ β

Z

T

E

e RT dT

ð2:9Þ

T0

Let F ðαÞ ¼ ð1  αÞn

ð2:10Þ

then Z 0

When n 6¼ 1

α

8 <  ln ð1  αÞ, n ¼ 1 dα 1n ¼ 1 ð1  αÞn : ð1  αÞ , n 6¼ 1 n1

ð2:11Þ

2.1 Experimental Approaches for Determining Propensity of Spontaneous Combustion

 ð1  αÞ1n  1 ART 2  2RT E ¼ e RT 1 n1 E βE

37

ð2:12Þ

Take the logarithm of both sides: ln

  ð1  αÞ1n  1 AR 2RT E ¼ ln 1  2 βE E RT T ð n  1Þ

ð2:13Þ

When n ¼ 1   ln ð1  αÞ AR  2RT E ¼ 1  e RT βE E T2

ð2:14Þ

Take the logarithm of both sides: 

    ln ð1  αÞ AR 2RT E 1   ln ¼ ln 2 βE E RT T

ð2:15Þ

E 2RT 2RT  1, E  RT, 0, 1  1 RT E E So 

  ln ð1  αÞ AR E ln  ¼ ln 2 βE RT T α¼

ð2:16Þ

m0  m Δm ¼  100% m0 m0

ð2:17Þ

where m0 is the initial mass of the sample h and miis the mass of the sample at time t. Þ Based on Eq. 2.16, the plotting of ln  lnTð1α against 1/T within the temperature 2 range from T1 and T2 would produce a quasi-straight line of slope –E/R and intercept of ln AR βE as shown in Fig. 2.6.

–10

–10 –11 –11

–12 –12

–12

–14 lnF(x)

lnF(x)

lnF(x)

–13 –13

–14

–14 –15 –15 –16

Data points in moisture loss Linear fit y=–1.54–3697.13x R2=0.86

–16

–16

–18 Data points in oxidation Linear fit y=7.81–10838.53x 2 R =0.98

–20

Data points in combustion Linear fit y=3.16–12851.19x R2=0.96

–17

–22

–17 0.0022

0.0024

0.0026

0.0028 x

0.0030

0.0032

0.0034

0.0017

0.0018

0.0019

0.0020 x

0.0021

0.0022

0.0023

0.0011

0.0012

0.0013

0.0014

0.0015

0.0016

0.0017

0.0018

x

Fig. 2.6 Linear regression of the data from TGA to determine activation energy in moisture loss stage, weight gain stage, and combustion stage

38

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

Based on the TGA analysis, other risk assessment indices are also proposed by researchers. Avila et al. (2014) developed a TGspi index which links the mass loss rate and temperature to estimate the spontaneous combustion potential of coal. The higher the TGspi value, the higher reactivity of the coal. Li et al. (2014) developed a non-isothermal TGA-DSC method to measure the kinetic parameters of coal oxidation at low temperature and compared with the value determined from basket heating methods. Saleh and Nugroho (2013) used the TG and DTA thermogram to calculate activation energy based on Coats-Redfern formula to investigate the particle size influence on self-heating behavior of coal, showing that propensity increases by decreasing particle size. Differential thermal analysis (DTA) is a thermal analysis using a reference. The sample and the reference material are heated in one furnace. The difference of the sample temperature and the reference material temperature is recorded during programmed heating and cooling cycles. The DTA curve is a curve of temperature difference between the sample material and the reference material versus temperature or time. The plot of the temperature difference reveals exothermic and endothermic reactions that may occur in the sample. DTA can be used to study the selfheating phenomenon of coals by following the heat generation during the experiment. DTA-TG curves have been used to characterize the propensity for spontaneous combustion and determine the kinetic parameters (Pis et al. 1996).

2.1.3.2

Differential Scanning Calorimetry (DSC)

DSC is a non-isothermal method, in which the environment temperature is usually increased at a constant rate. In DSC equipment, two pans are used for tests. One contains a coal sample and the other is empty. The two pans are maintained at the same temperature. The difference in the amount of heat required to achieve this is measured as a function of the changing environment temperature. This allows endothermic and exothermic processes to occur within the coal, both of which are related to self-heating processes (Garcia et al. 1999). As shown in Fig. 2.7, in the region of first endothermic peak of DSC (below the red baseline), the oxidation is mainly due to release of moisture. The onset temperature of first exothermic peak

Fig. 2.7 DSC curves of coal samples in (a) air atmosphere and (b) oxygen atmosphere (Mohalik et al. 2009)

2.1 Experimental Approaches for Determining Propensity of Spontaneous Combustion

39

(above the green baseline) in oxygen atmosphere could be a measure of the susceptibility of coals toward spontaneous combustion. DSC can not only provide the temperature at which the reaction occurs and how much heat is evolved but can also provide valuable information about the kinetics of reaction (Mohalik et al. 2009).

2.1.4

Isothermal Method

Isothermal can be classified into two methods. One is a static isothermal method and another is dynamic isothermal method. The static isothermal method measures the rate of reaction of coal under conditions in which the oxygen concentration is effectively a constant (Smith and Glasser 2005a, b). In the dynamic method, oxygen was allowed to flow into the coal with a constant flow rate at a constant temperature. The amount of oxygen adsorbed by the coal was determined by desorption of the oxygen when the coal was flushed with nitrogen (Xu 2001).

2.1.5

Crossing Point Temperature (CPT) Method

In the CPT method, 30–60 g samples are contained in a reaction vessel which is placed in a programmed oven or temperature bath, 30 g (Sensogut and Cinar 2000), 40 g (Fatia Umar et al. 2005), and 60 g (Kadioğlu and Varamaz 2003; Küçük et al. 2003). Dry air is preheated to the oven’s temperature before it flows into the reaction vessel. The temperature of the oven increases at a constant rate that raises the inlet gas temperature (Qi et al. 2011). The temperatures of the oven and the reaction vessel are recorded continuously. The crossing temperature is defined as the temperature at which the coal is equal to that of the oven as shown in Fig. 2.8. The CPT indicates the tendency of self-heating of coal. The lower the CPT, the higher the risk to spontaneously combust. Instead of defining the CPT by comparing the temperature of the coal against the surroundings, various indices have been used to evaluate CPT data, such as FCC, MR, and WITS-EHAC. Risk classification for each index is as follows: FCC (low, 0–5; medium, 5–10; high, >10) (Feng et al. 1973), MR (low, 0–10; medium, 10–20; high, >20) (Mahadevan and Ramlu 1985), and WITS-EHAC (low, 0–2.5; medium, 2.5–5; high, >5) (Gouws and Wade 1989).

40

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

200

Temperature in deg. C.

Crossing-point Temperature 160

120 Furnace Co2 appeared 80 Coal 40

0

0

10

20

Illinois Coal Moritgomery County Fresh, 60 Mesh Using Dry Oxygen

30 40 50 Time in Minutes

60

70

80

Fig. 2.8 Crossing point temperature method (Li and Parr 1926)

2.2 2.2.1

Theoretical Techniques to Analyze and Predict SelfHeating Behavior of Coal Kinetic Model

Kinetic model has been developed by researchers for determining the rate of oxygen consumption and production of carbon oxides during the oxidation of coal at different temperature intervals, 60–90  C (Wang et al. 2002, 2003a), 25–90  C (Krishnaswamy et al. 1996a, b), 150–160  C (Karsner and Perlmutter 1982), and 200–225  C (Kam et al. 1976). Based on fundamental steps during the oxidation process, modeling the kinetics of coal oxidation can predict the rate of oxygen consumption and distribution of the consumed oxygen among gaseous oxidation products. Many proposed theories on reaction sequence and COx gases generation path of coal oxidation at low temperature are listed in Table 2.1. Two parallel sequences consuming oxygen and two thermal decomposition pathways producing carbon oxides in chemical reactions involving burn-off reaction occur at some of the active sites, and sorption reaction sequence at the remaining active sites is considered in the model (Wang et al. 2003a). The direct burn-off reaction has been widely proposed, but there is no direct evidence to confirm this mechanism. Two parallel reactions, on the other hand, are supported by evidence from the oxidation and the subsequent thermal desorption experiments. Wang et al. (2003b) found that 70  C was a critical temperature for the thermal decomposition reactions and for the direct burnoff reaction. Kinetic modeling reveals that with the formation of stable and unreactive oxygenated complexes in a coal’s structure, the oxidation of coal is dominated by thermal decomposition of oxygenated complexes as shown in Fig. 2.9.

2.2 Theoretical Techniques to Analyze and Predict Self-Heating Behavior of Coal

41

Table 2.1 Reaction sequence and COx gases generation path of coal oxidation at low temperature (Liang et al. 2019) References Kam et al. (1976)

Reaction sequences

COx generation paths 1. CO and CO2 can be generated from direct burn-off sequence 2. CO and CO2 can also be generated from decomposition of unstable complex

Karsner and Perlmutter (1982)

1. CO and CO2 can be generated from direct burn-off sequence 2. CO and CO2 can also be generated from decomposition of adsorbed complex

Itay et al. (1989)

CO and CO2 can only be generated from decomposition oxycoal produced in adsorption sequence 1. CO2 can be generated from direct burn-off sequence 2. CO2 can also be generated from decomposition oxycoal produced in adsorption sequence 3. Amount of CO liberation is negligible for sub-bituminous coal 1. CO and CO2 can be generated from direct burn-off sequence 2. CO2 can also be generated from decomposition of adsorbed complex 3. CO and CO2 can be generated from decomposition of stable complexes

Krishnaswamy et al. (1996a, b)

Wang et al. (2003a)

Reactions (11)–(14) are fast compared to the other reactions. Concentration of singleboned oxygenated groups, phenols, or ethers is much higher than that of carbonylcontaining groups at low temperature. Reactions (27) and (28) are also key steps in coal oxidation, which not only regenerate active sites for oxygen adsorption but also

42

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

Fig. 2.9 A schematic diagram of the chemical mechanism of the chemisorption sequence (Wang et al. 2003a)

liberate carbon oxides. Reactions (13) and (22) indicate that the very reactive hydride groups convert into less reactive or unreactive groups, such as ether and anhydrides, resulting in a dramatic decrease in the rate of coal oxidation.

2.2.2

Arrhenius Reaction Rate Model

The rate of oxygen consumption in the low-temperature oxidation reaction of coal can be expressed by a single Arrhenius expression (Krishnaswamy et al. 1996a): r O2 ¼ AeE=RT ρm ½O2 n

ð2:18Þ

r h ¼ QAeE=RT ρm ½O2 n

ð2:19Þ

The rate of heat release is

A is the pre-exponential factor (the units of which depend upon m and n), E is activation energy, R is the universal gas constant, T is the temperature, ρ is the density of the coal, [O2] is the concentration of oxygen, m is the order of reaction with respect to coal, assumed to be unity, and n is the order of reaction with respect to oxygen.

2.2 Theoretical Techniques to Analyze and Predict Self-Heating Behavior of Coal

43

It is often simply assumed in mathematical models that n ¼ 1. A value of n ¼ 0.63 (R2 ¼ 0.995) has been reported from experiments in a semi-adiabatic reactor (Smith and Glasser 2005a), and a value n ¼ 0.70 has been reported from experiments in a static isothermal reactor (Smith and Glasser 2005b). It is commonly assumed that consumption of oxygen is negligible when investigating solid fuels undergoing self-heating. With the additional assumption that m ¼ 1, the rate of heat release becomes r h ¼ QAeE=RT ρ

ð2:20Þ

Arrhenius plots have been applied to determine the values of the kinetic parameters (A and E) from Eq. 2.20. Studies show that values of A and E only apply to the designated coal, since different coals have different values. When a gas-solid reaction occurring within a porous solid, the pre-exponential factor can be written as A0 ¼ ASg

ð2:21Þ

where Sg is the effective surface area per kilogram of coal. The amount of surface area of the coal, determined by the particle size, is a direct factor in self-heating tendency. In Frank-Kamenetskii analysis (Frank-Kamenetskii 2015), the behavior of a coal will be influenced by two factors: the heat generation due to oxidation which follows the Arrhenius reaction rate and heat losses to the surroundings. Based on the energy conservation law, an energy balance gives  ∂T ∂ ∂T ρc ¼ λ þ QAeðE=RT Þ ρ ∂t ∂x ∂x

ð2:22Þ

with boundary conditions T ð x ¼ LÞ ¼ T a

ð2:23Þ

∂T ðx ¼ 0Þ ¼ 0 ∂x

ð2:24Þ

and

where c is the specific heat capacity, λ is the thermal conductivity, T is the absolute temperature, L is the half-width of the pile, and Ta is the ambient temperature. In Eq. 2.22, it assumes that heat transfer in a reactive porous slab of coal is one-dimensional. Convective flow can be ignored within the sample. Depletion of the reactants (fuel and oxygen) can be neglected up to the time of ignition, and there is no moisture evaporation influence. The left-hand side of Eq. 2.22 is the local

44

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

enthalpy change rate in the solid, the first term on the right-hand side is the conductive heat transfer in a porous solid, and the second term is the heat generated by low-temperature oxidation. The boundary condition Eqs. 2.23 and 2.24 defines a constant temperature at the solid-gas surface and a symmetry condition at the center of the slab. The Eq. 2.22 describes the basic ignition behavior of a solid that is applicable to Arrhenius reaction. However, the Frank-Kamenetskii theory does not include many aspects that are important in the oxidation of coal, such as oxygen concentration, gas absorption, moisture content of both coal and surrounding atmosphere, coal-pore structure, particle size and coal chemical composition, etc. (Nelson and Chen 2007). Improved models that consider more factors are developed based on it. The model for predicting the ignition time for coal from low-temperature self-heating to ignition has been proposed as shown in Eq. 2.25 (Boddington et al. 1983): t ab ¼

RT 2R c RTE e R E QA

ð2:25Þ

In this equation, c is the specific heat, Q is the heating value, R is the gas constant, and TR is the initial temperature of the coal. A value of 1260 J/kgK was used for c and 25 MJ/kg for Q. The prediction model was derived from an adiabatic condition. Therefore, the values of tab calculated for the coals will be the lower limit of the actual times the coal needed to ignite. Ignition temperatures of six coals have been calculated using the ignition model at initial temperature of 300 K (Jones 2000). The shortest time for coal to ignite is 2 days and the longest one is 73 days. However, the activation energy and pre-exponential factor used in the model have to be determined from adiabatic testing results. If the coal has low potential of selfheating, it will be very difficult to obtain a complete self-heating curve to determine these two parameters. Chen (1992) further developed the model and considered the terms of convection heat transfer in the gas stream and rate of heat release due to drying or the rate of heat adsorption due to wetting in his energy equation.

2.2.3

Shrinking Core Model

The combustion of coal particle is also often described by the shrinking core model. In this model, a burning coal particle is divided into a number of concentric volume elements (Mitchell et al. 2007). It considers the effects of chemical reaction and diffusion. The model could take into account the initial structural properties of the coal, namely, surface area and porosity, and predicts the particle’s burning rate, temperature, diameter, apparent density, and specific surface area during the combustion process (Everson et al. 2006). The reacting particle is divided into two parts, the shrinking reacted core and the shrinking unreacted core. In the shrinking unreacted core, a burning coal particle has an unreacted core with diameter rpc

2.2 Theoretical Techniques to Analyze and Predict Self-Heating Behavior of Coal Surface of particle

Gas film Moving reaction surface

Ash

Shrinking unreacted core containing B

Time

Concentration of gaseous reactant A and product R

45

Time

CAg CAs CA

CAc

rps

rpc

0

rpc r rps

Radial position

Fig. 2.10 Schematic representation of a coal particle undergoing combustion for shrinking core model

which changes with time as shown in Fig. 2.10. This core shrinks during the combustion process. It is completely surrounded by converted material and inert solid, except at the start of the process. In the shrinking reacted core model, the reaction rate is based on the particle volume (Abdel-Hafez 1988). Reaction at the surface of the particle is faster than that inside, so the carbon at the surface will react first, forming an ash layer. As the reaction proceeds, the thickness of the ash layer increases and the radius of the porous core decreases (Ishida and Wen 1968). The reaction rate, rs, of coal is given by the equation below: rs ¼

  E dX ¼ k0 exp ðPO2 Þn f ðX Þ RT dt

ð2:26Þ

46

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

where X is conversion, k0 is the pre-exponential factor, PO2 is the partial pressure of oxygen, n is the reaction order with respect to oxygen, and f(X) is the function describing the shrinking core model which cab determined as f ðX Þ ¼

S0 ð1  X Þ2=3 ð 1  ε0 Þ

ð2:27Þ

where S0 is the initial surface area of the particle per unit volume and ε0 is the initial porosity of the particle.

2.2.4

Numerical Model

Although spontaneous combustion of coal can be evaluated experimentally by laboratory approaches, it is not completely successful to extrapolate the experimental results to the real mining environment, because of the complicated scaling effects that cannot be reproduced in small-scale experiment (Yuan and Smith 2008). In small-scale tests, the radiative heat transfer is often neglected, which is not the same case in large-scale mining condition when coal temperature is high enough that the radiative heat transfer cannot be ignored. Self-heating of coal in mines often occurs in a gob area where it cannot be accessible and is not easily detected. It is also very difficult to conduct full-scale tests in this area due to the very nature and large size of the longwall gob. Numerical modeling provides an alternative approach to investigate the self-heating risk for various geological and ventilation conditions with different coal properties in a relatively short time and at low cost. One-, two-, and three-dimensional models have been developed to understand the mechanisms of spontaneous combustion. One- or two-dimensional models mainly focused on small-size coal stockpiles and experimental system (Akgün and Arisoy 1994; Badr and Harion 2005; Chen 1992; Ejlali and Hooman 2011). Arisoy and Akgün (1994) proposed a one-dimensional non-steady-state model to simulate the rate of evaporation or condensation of moisture of coal as a function of particle size, isothermal temperature, energy of water-coal bonding, and water content of coal. Based on semi-adiabatic experiment, Smith and Glasser (2005a) proposed a model capable of considering the intrinsic properties of material and properties of the reaction system to study the low-temperature oxidation of carbonaceous stockpiles. Arisoy et al. (2006) developed a model to simulate a bulk-scale, one-dimensional 2 m test column. The influence of coal moisture on self-heating is studied by this model. Arisoy and Beamish (2015) used adiabatic experimental data to a proposed numerical model to study the mutual effects of pyrite and moisture on coal selfheating rates. It concluded that less heat was consumed by moisture evaporation, since the moisture is consumed by pyrite oxidation. Michalec et al. (2010) developed

2.2 Theoretical Techniques to Analyze and Predict Self-Heating Behavior of Coal

47

a CFD model to simulate self-heating of coal in an adiabatic calorimeter and study the consumption of oxygen, production of CO, and CO2 exhaust and heat in the oxidation process. Two-dimensional numerical modeling was developed to study the spontaneous combustion in longwall gob and gassy longwall panel (Saghafi et al. 1995; Saghafi and Carras 1997). Balusu et al. (2001) conducted a CFD study of gob gas flow mechanics to develop gas and spontaneous combustion control strategies for a highly gassy mine. Three-dimensional numerical modeling was proposed to simulate spontaneous combustion in a large-scale coal chamber with a force ventilation system, but this model does not consider water vapor transfer and the effect of heat wetting. (Yuan and Smith 2009). Self-heating of coal in real underground mining environment influenced by various affecting factors, such as coal properties (Yuan and Smith 2008), barometric pressure (Yuan and Smith 2010), ventilation flow paths (Yuan et al. 2006), and inter gas injection (Trevits et al. 2010; Yuan and Smith 2014), has been systematically evaluated by CFD modeling. The modeling results suggested that temperature rise was greatly dependent on the available coal reaction surface area. For larger coal particle size, the reaction surface area and the maximum temperature rise were both significantly reduced as shown in Fig. 2.11a

Fig. 2.11 CFD modeling of spontaneous combustion for (a) three coals involving No. 80-1, E-1, and Pittsburgh (Yuan and Smith 2008), (b) with and without barometric pressure changes: gob permeability increased 100 times (Yuan and Smith 2010), (c) with and without nitrogen injection (Yuan et al. 2006)

48

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

a

Iso-surface of 18% oxygen

b 200 Dissipation zone

Iso-surface of 5% oxygen Intake tunnel

Suffocation zone

160

(a) ‘Oxidation zones’ liable to spontaneous heating - plan view

Working face

W(m)

Danger zone

120

Iso-surface of 18% oxygen

80

Oxidation zone O2 concentration=5 vol%

Iso-surface of 5% oxygen

40 Return tunnel

0 (b) ‘Oxidation zones’ liable to spontaneous heating - 3Dview

40

80

120

160

0 200

L (m)

Fig. 2.12 CFD modeling of the (a) oxidation zone (Ren and Balusu 2010) and (b) distribution of “three zones” in the gob (Deng et al. 2018)

(Yuan and Smith 2008). Change of barometric pressure causes the gob to breathe in and out in such a way that low barometric pressure expends the volume of gas in the gob and vice versa. The net effect of barometric pressure changes on the spontaneous heating depends on the gob permeability and the coal oxidation rate as shown in Fig. 2.11b (Yuan and Smith 2010). The potential critical velocity zones may occur immediately behind the shields toward the center of the gob for the one-entry and two-entry ventilation systems. For the three-entry bleeder ventilation system, the critical velocity zone may occur farther away from both the shields and the back end of the gob where a permeability gradient exists (Yuan et al. 2006). Without any N2 injection, the maximum temperature in the gob continually increased with time. When N2 was injected at location 1, the maximum temperature increased faster than without injection at the beginning, probably because of slightly increased air velocity caused by the injection increasing the amount of O2 at the hot spot. After reaching about 320 K, temperature started to decrease quickly because the N2 dilution injection blocks the airflow pathway to the hot spot as shown in Fig. 2.11c. CFD modeling was used to investigate oxygen flow into the gob and identify oxidation zones where spontaneous heating of coal is most likely to take place (Deng et al. 2018; Pan et al. 2013; Su et al. 2016; Xu 2001). Based on oxygen concentration, gob can be divided into three zones, dissipation zone (18%). Figure 2.12 shows the CFD modeling results of oxygen penetration pattern into the gob and the mapping of oxidation zones in the gob using isosurface of oxygen concentrations and distribution of “three zones” in the gob. Results show that gob heating is likely to occur in gob areas at about 50–200 m behind the face, along the gob edge of tailgate side, and in the vicinity of face start-up line (Ren and Balusu 2010).

2.3 Monitoring and Preventive Measures to Mitigate Spontaneous Combustion

2.3

49

Monitoring and Preventive Measures to Mitigate Spontaneous Combustion

2.3.1

Gas Monitoring System

2.3.1.1

Tube Bundle System

A tube bundle system (TBS) for mine air monitoring for the early detection of spontaneous combustion is used to monitor the development of the gob atmosphere. TBS monitors trending of the mine atmosphere at regular intervals and in areas that do not require immediate warning of contaminants through sample points (Belle 2014; Griffin et al. 2011; 2012; Zipf Jr et al. 2013). The TBS consists of four sub-systems, namely, the sampling system, the analysis system, the control system, and the display system. The sampling system draws sampled gas up via vacuum pump to the surface from the remote sampling points as shown in Fig. 2.13. It also cleans and dries the gas sample through air filter before ingress to the analyzers. The analysis system consists of the appropriate gas analyzers, often infrared (IR) analyzer, which typically analyzes gas concentrations including oxygen, methane, carbon dioxide, and carbon monoxide. This information is then passed on to the control system, where it is evaluated and stored for later use. The control system is responsible for the continuous operation of the TBS and for the acquisition and storage of data. The core of the sampling system is the tube bundle itself which is mounted in a tube bundle trailer on the surface as shown in Fig. 2.14. The tube bundle connects the pit-bottom box, from which individual sampling tubes extend to the surface installations. The fundamental components of the system include a series of plastic tubes extended from the surface to selected locations underground. The tubes are general high-grade quality non-leaching materials with a

Fig. 2.13 Tube bundle system (Griffin et al. 2011)

50

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

Sample gas exhaust stack

Sample lines from mine

Pump room

Analysis room

Fig. 2.14 Outside and inside views of gas analysis trailer of tube bundle system on the surface (Zipf Jr et al. 2013)

Fig. 2.15 Typical sample lines for a TBS in an underground coal mine (Zipf Jr et al. 2013)

variable diameter from 6 mm to 20 mm (depending on the length) and lengths of up to several kilometers as shown in Fig. 2.15. It could collect a great amount of information about the conditions of the gob atmosphere before, during, and after the sealing. Although the analyzers used for tube bundle systems are generally accepted as high-quality sensors for telemetry gas monitoring systems and do not have crosssensitivity issues associated with some fixed type sensors, moisture in sample tubes can cause significant problems. Most tube bundle systems will have moisture removal devices that remove moisture from the gas sample streams. However, if these devices are not maintained and functioning efficiently, then any moisture entering the analyzers will affect the accuracy of the readings. Mine sites with tube bundle systems will commonly have switching mechanisms that distract a dry calibration gas into the analyzers to confirm the accuracy of the system. When the moisture removal devices are not working efficiently, the monitoring result will be a discrepancy between the analyzers and a gas chromatograph through comparative analysis. TBS advantages include (a) no explosion-proof instruments required when flame traps are incorporated, (b) easier maintenance as major components are located on the surface, (c) no underground power requirements, (d) a wide range of gases can be analyzed, and (e) analyzers can be calibrated on the surface. Disadvantages are

2.3 Monitoring and Preventive Measures to Mitigate Spontaneous Combustion

51

(a) results are not in real time, (b) leaks in tubes may not be immediately obvious, (c) condensation in tubes can results in blockages and erroneous readings on some types of analyzers if moisture removal systems are not working efficiently, (d) faults in tube system may not be immediately obvious, and (e) tubes may be damaged by fires or explosions.

2.3.1.2

Gas Chromatography

Gas chromatographs (GC) have been used as an analytical tool for the analysis of underground coal mine atmospheres for decades (Adamus et al. 2011; Brady 2008; Su et al. 2008). They have been useful in providing accurate analysis of components that are not routinely monitored by telemetry or tube bundle gas monitoring systems. These components include hydrogen and hydrocarbons such as ethylene (C2H4) and propylene (C3H6) which are critical in determining the statues of the thermal event. When TBS is not capable of measuring the high carbon monoxide concentrations and hydrogen after a fire or explosion occurred, GC will be the only approach to evaluate the underground atmosphere. In the GC analyzing process, a gas sample is injected with an inert “carrier gas” (argon, helium, or nitrogen) into a column from the gas inlets as shown in Fig. 2.16. Different gas components have unique interaction with the packing in the column when they pass through it and thus exit the column in different time orders. As a

Fig. 2.16 Gas chromatography system

52

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

result, detector placed at outlet of the column can detect the individual components quantitatively. However, the conventional GC systems used for coal mine emergency were too slow when processing the high volume sampling rates. Moreover, frequent maintenance and a high level of skilled user are required to keep it working efficiently. Therefore, the conventional systems are not considered any more to be an appropriate analytical tool for monitoring self-heating incident. Alternatively, the ultrafast micro GC with many advantages is introduced to replace the traditional technique into the coal mine sites. It receives wider acceptance after being introduced, since it is relatively simple to operate and can rapidly analyze the gas components in typically 1–3 min with only one type of detector required when using this type of GC for the analysis of coal mine atmospheres. It can also be used to confirm the results and accuracy of other monitoring systems like TBS.

2.3.2

Index Gases

It was widely reported that during coal oxidation process, a number of gaseous products such as CO, CO2, H2, CH4, and a few other saturated/unsaturated hydrocarbon complexes are evolved progressively at “footprint” temperatures (Hitchcock et al. 2008; Lu et al. 2004; Luo and Qian 2003; Singh et al. 2007). The appearance of certain amount of the oxidized products can be used to describe the status of heating in the remote and inaccessible gob area. However, not all gaseous products generated from the low-temperature oxidation of coal are suitable as the index gases for identifying self-heating incident in coal mines. It depends on the chemical composition of the coal and the gases presence naturally within a coal seam. For example, hydrogen cannot be used if it occurs naturally in a coal seam. Both methane and carbon dioxide often absorbed by coal and are therefore not suitable as the index gases (Xie et al. 2011). It needs further crossover analysis with more index gases or even fire ratios to improve the monitoring certainty on the heating status.

2.3.2.1

COx Gases

Carbon oxides are the most common and critical gaseous products from coal oxidation at low temperature. At temperature of 30–45  C, oxygen are consumed, and carbon oxides (i.e., CO and CO2) begin to form. When the temperature further increases to 70–90  C, emission of CO and CO2 and oxygen consumption significantly increase. Consequently, CO and CO2 are good indicators for spontaneous combustion of coal at early heating stage. With the density less than air, CO will well diffuse with surrounding gases, favorable for modern monitoring techniques to detect even very slight trace of CO nearby. As a very important gaseous product formed during the entire coal oxidation process, many major coal-producing nations use it as effective precautionary indicator more frequently than any other gas for spontaneous combustion incidents as shown in Table 2.2. However, sometimes

2.3 Monitoring and Preventive Measures to Mitigate Spontaneous Combustion Table 2.2 Gas index for determination of spontaneous combustion in major coalproducing countries

Country China Australia US India UK Russia Japan Poland German France

Major index gas CO, C2H4, C2H2 CO, H2 CO, H2 CO, CO/ΔO2 CO, C2H4 CO CO, C2H4 CO CO CO

53

Additional index gas CO/ΔO2, C2H6/CH4 CO/ΔO2 CO/ΔO2 C/H CO/ΔO2 C2H6/CH4 CO/ΔO2, C2H6/CH4 CO/ΔO2 CO/ΔO2 CO/ΔO2

solely depending on CO as detection gas will misunderstand the real fire status in underground coal mine. CO could be produced from incomplete combustion of other carbon-based material not coal itself. CO can be also from effluent of diesel engine of underground vehicles. Even through increasing trend of detected CO rather than absolute value could normally indicate an escalation of fire status, it is still unable to identify if CO is produced from coal oxidation at low temperature or intensive heating at a localized area. Therefore, other index gases are also used additionally to make detection more accurately by the nations in Table 2.2. As one of the major gaseous products of coal oxidation and combustion, CO2 is usually not considered as a good indicator for early warning of self-ignition, since it could be significantly affected by diverse distractions. It could be liberated from coal oxidizing by microorganisms. Mixing acidic mine water with calcium carbonate will also produce CO2. It is often absorbed in surrounding strata or occurred in rock faults as coal seam gas, resulting in more CO2 contained in gas samples than that actually being generated from coal oxidation. On the other hand, CO2 is soluble in water, leading less CO2 to be contained in samples than that actually being evolved.

2.3.2.2

H2

Since carbon oxides ratio could be easily affected by diverse distractions, such as effluent of diesel engine or coal seam gas, more independent index gases are therefore needed. Hydrogen is one of the independent gases chosen as index gases in Australian and US coal mines. At temperature of 55–95  C, small amounts of molecular hydrogen can be produced in coal oxidation (Grossman et al. 1993). When the temperature is above 100  C, the amount of hydrogen will exponentially increase (Wang et al. 2017). The molecular hydrogen was from the hydrogen of C–H bonds within the coal macromolecule rather than adsorbed water (Grossman et al. 1994). Later study found that the hydrogen is from methylene when it is easily attacked by molecular oxygen at low temperature (Lopez et al. 1998). Formaldehyde was suggested as one of the ambient temperature oxidation products of coal (Nehemia et al. 1999). More recently study indicated that molecular hydrogen was

54

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Historical Perspective on Identifying and Controlling Spontaneous Combustion

Table 2.3 Emerging temperature of ethylene and propylene for various ranks of coal in China Coal ranks ascending order Lignite Jet coal Gas coal Fat coal C2H4 ( C) 109 119 124 127 C3H6 ( C) 124–134 121–132 121–142 136–147

Coking coal 148 156–160

Lean coal 150 151–157

Meagre coal Anthracite 150 148 150–168 150–162

mainly from aldehyde group when it reacts with oxygen rather than thermal decomposition of inherent hydrogen-containing groups (Wang et al. 2017).

2.3.2.3

CxHy Gases

CxHy gases can be divided into two groups: saturated gaseous hydrocarbon (e.g., alkane, like CH4, C2H6, C3H8, C4H10) and unsaturated gaseous hydrocarbons (e.g., alkenes, like C2H4, C3H6, and C4H8, and alkyne, like C2H2). Generation paths of CxHy gases are more complicated, mainly through oxidation of certain functional groups and decomposition of stable complexes at higher temperature. Although CH4 will be generated with temperature increase during coal oxidation, considering it is a major source of coal seam gas, it is not a good indicator for early warning of spontaneous combustion. Other low hydrocarbons (e.g., C2H6, C3H8, C2H4, C3H6) might be good ones. C3H6 was released at 137  C with maximum release at about 230  C, and C2H4 was released at 155  C (Chamberlain et al. 1976). For different ranks of coals, emerging temperatures of C2H4 and C3H6 are tabulated in Table 2.3 (Luo and Qian 2003). It can be seen that the temperatures of emission of detectable C2H4 and C3H6 generally increase with coal ranks in ascending order. Detectable amount of C2H6 was generated in temperature range 80–110  C, and C3H8 is unlikely to be produced before 120  C (Lu et al. 2004). The typical evolution of index gases of a coal during oxidation heated up by temperature increment program is shown in Fig. 2.17. Compared to C2H2, C2H4, and C2H6, the generated amount of CO, CO2, and CH4 are significant with increasing temperature in this case. Starting from the ambient temperature of mine atmosphere 10–30  C, CO and CO2 will be formed by oxidation at 30–45  C. With temperature rise above 45  C, the oxidation and formation rate of CO and CO2 increase. Before reaching 100  C, significant amount of CO2 begin to be generated by decomposition of the solid complexes using the oxygen in the coal or in the surrounding environment. In temperature range 100–150  C, CH4, H2, and low hydrocarbons (C2H6) begin to be produced in small quantities. Trace concentration of C2H4 observed from some coals. When temperature increases to 150–200  C, more significant quantities of CH4, H2, and C2H6 will be generated, and the C2H4 may be present in 10’s ppm in this temperature range. 200–300  C is the ignition temperature of coal dust layers; distillation of coal increases generation of gases including higher hydrocarbons. Between 300 and 600  C, methane and airborne coal dust will be ignited. Fractional

2.3 Monitoring and Preventive Measures to Mitigate Spontaneous Combustion

55

Fig. 2.17 Typical evolution of index gases of coal with increasing temperature

undiluted products of oxidation and distillation remain in percent concentration. Selecting the appropriate index gas for predicting the spontaneous combustion should be based on specific condition of individual mines.

2.3.3

Fire Ratios

Although the generation history of a single index gas may reflect the real status of coal heating, there are many problems with only absolute value of gas concentrations to identify the heating status including (Cliff et al. 1996) (1) air flow will dilute the gas concentrations to make it undetectable or cause underestimation on the severity of the heating based on the reduced results, (2) index gas could be contaminated by other sources (e.g., vehicle emissions and seam gases), and (3) no indication for assessing the heating intensity. For example, a small but intense heating may be mistakenly treated as a broad but moderate heating by the same amount of general gas concentration produced in these two scenarios. To overcome these problems, indicators also known as fire ratios, combined with various gas concentrations and/or air velocity, have been proposed. The most common fire ratios are the following.

56

2.3.3.1

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

Graham’s Ratio

Gases produced related to adsorbed oxygen. Based on this observation, Graham’s ratio (GR) is developed by Graham (1920) to determine the heating severity through comparing the CO generation rate with O2 consumption rate. As temperature increases, more and more oxygen will be consumed to produce carbon monoxide, and the ratio of CO produced to oxygen depleted can be used to indicate heating intensity. It is useful in low oxygen environments such as gobs and is also applicable in ventilated entries. The equation is commonly expressed as GR ¼

100  CO 0:265  N2  O2

ð2:28Þ

where CO is concentration of carbon monoxide in %, N2 is concentration of nitrogen in %, and O2 is concentration of oxygen in %. The CO/O2 deficiency ratio may underestimate the state of progression of a heating, but combined with other analysis methods, it provides a good indication of a heating. The trend of the readings is more important than absolute values. An increasing trend indicates increasing temperature within the fire. Another advantage of GR is it can distinguish between a large mass of coal oxidation and a small intense heating.

2.3.3.2

CO/CO2 Ratio

This ratio is independent from oxygen deficiency and thus overcomes the problems that other ratios have, the dependence on oxygen deficiency. It is based on the change in ratio of carbon monoxide produced to carbon dioxide produced as a function of the coal temperature during the initial development of a heating. Obviously, this index can be used only where no carbon dioxide occurs naturally in the strata. It is determined as CO=CO2 Ratio ¼

COf  COi CO2f  CO2i

ð2:29Þ

where f is the gas concentration in final or return conditions and i is the gas concentration in initial or intake conditions.

2.3.3.3

CO Make

CO Make is the volume of carbon monoxide flowing past a fixed measuring point per unit time. This indicator removes the effect of dilution by air stream and is determined as

2.3 Monitoring and Preventive Measures to Mitigate Spontaneous Combustion

CO Make ¼ K  CO  Q

57

ð2:30Þ

where CO Make is measured in L/min, Q is airflow in m3/s, CO is the concentration of carbon monoxide in the air, and K is a factor determined as follows: CO is measured in ppm then K ¼ 0.06. CO is measured in % then K ¼ 600. As air velocity is required in this calculation, CO Make is only valid for entries with airflow and cannot be used behind seals or closed space. Because this indicator only changes with airflow and CO concentration, it is suitable for monitoring a heating incident when oxygen is deprived.

2.3.3.4

Young’s Ratio

Young’s ratio is the same as Graham’s ratio except that CO is replaced by CO2. Different from Graham’s ratio, since the quantity of the CO2 concentration is often large, it is not usually multiplied by 100, and thus the fraction is not in percentage: YR ¼

CO2 0:265  N2  O2

ð2:31Þ

The ratio trend is more important than absolute ratio values. The limitations of this ratio include carbon dioxide generation as a function of temperature is very coal dependent, CO2 from seam gas or vehicle exhaust, the potential loss of CO2 when it dissolves in water, and the same problems with oxygen deficiency as Graham’s ratio.

2.3.3.5

Morris Ratio

This ratio is developed by Morris (1988), essentially the inverse of GR and YR. It is a measure of the amount of oxygen absorbed/consumed by the coal to the amount of oxidation produced by the coal. The consumed oxygen is determined by the excess of nitrogen over that required to balance the amount of oxygen present in the air. When the inlet is fresh air, the ratio is expressed as MR ¼

2.3.3.6

N2  3:774  O2 CO þ CO2

ð2:32Þ

Jones-Trickett Ratio

The Jones-Trickett Ratio (JTR) was originally developed to evaluate sample reliability and to differentiate between gas or coal dust explosions (Jones and Trickett

58

2

Historical Perspective on Identifying and Controlling Spontaneous Combustion

1954). This ratio is based on the measurement of the amount of oxygen required to produce the oxidation products compared to the amount of oxygen actually removed from the inlet gas stream. Increasing ratio indicates intensifying heating or temperature increase. It is expressed as JTR ¼

CO2 þ 0:75CO  0:25H2 0:265ðN2 þ ArÞ  O2

ð2:33Þ

Note that the JTR is invalid if the intake air is oxygen deficient by nitrogen or carbon dioxide injection or in high methane environment. In addition, the dilution with fresh air of the combustion products has no effect on the ratio.

2.3.3.7

Litton’s Ratio

This ratio is designed to reduce the potential for reignition when a mine or section is reopened and oxygen is reintroduced. Only four gases are monitored: oxygen, carbon monoxide, methane, and ethane. The atmosphere is divided into three parts: air, methane and ethane, and residual gas. Litton’s ratio is determined as 8 1 > > >

2 > if O2 < 1% > : 3
3=2 R

ð2:34Þ

g

where CO is carbon monoxide concentration in ppm and O2 is oxygen concentration in percent. Rg ¼ 100  4:774  O2  CH4  C2 H6

2.3.3.8

ð2:35Þ

Willett Ratio

Willet (1952) analyzed gas samples collected from sealed fire areas, integrating CO, black damp (a term generally applied to carbon dioxide and nitrogen), and combustible gases produced as an index to indicate the heating in coal mine: WR ¼

CO % CO2 þ N2 þ Combustibles

ð2:36Þ

where Combustibles is all combustible gases present (methane, carbon monoxide, hydrogen, and any higher hydrocarbons).

2.3 Monitoring and Preventive Measures to Mitigate Spontaneous Combustion

59

Level of activity is indicated by the value obtained, with a falling trend indicating decreasing activity. Stable values may indicate no activity. This ratio has been found to be more effective than Graham’s ratio in determining the state of spontaneous combustion activity behind sealed areas. 2.3.3.9

C/H Ratio

To identify the characteristics of fires in sealed area and the nature of oxidation process, a new index (C/H ratio) was developed using the ratio of carbon, available hydrogen, and oxygen consumption from the mine gases (Ghosh and Banerjee 1967; Singh et al. 2007). The CO2, CO, and hydrocarbons produced by combustion are used to calculate the carbon. The available hydrogen is calculated from evolved hydrogen, from hydrocarbons, and from hydrogen used in the formation of water. The index is calculated as C=H Ratio ¼

6ðCO2 þ CO þ CH4 þ 2C2 H4 Þ 2ðN2 =3:78  O2  CO2 þ CH4 Þ  CO þ C2 H4 þ H2

ð2:37Þ

Risk ratings, advantages and limitations of each fire ratio are listed in Table 2.4. Table 2.4 Risk rating, advantage, and limitations of each fire ratio (Liang et al. 2019) Fire ratios Graham’s ratio

Risk rating 0.4 possible early heating >1.0 event almost certain >2.0 serious event >3.0 active fire

Advantages 1. The ratio remains independent to dilution of air or methane 2. Gives early detection of fire if it increases continuously 3. Indicates the intensity of the heating

CO/CO2 ratio

FR0809 > FR0910 > FR0801 > FR0802. 4. TGA tests on all the other samples Apart from the samples that are already tested in the previous sections, the TGA results of all the other samples in the sample bank are listed in Table 3.4. However, the samples marked as SPE, Trapper, and BBCC have no weight gain stage in T-G curve. The activation energy E2 of the three samples is much lower than the other samples, indicating they have higher tendency of self-ignition. BBCC sample has been tested with R70 method. It has very high potential in moist environment. Two experimental results confirm well with each other. The other two samples will be tested using improved USBM method in the following chapter. In the TGA tests, Indiana sample has more significant weight gain stage and smaller activation energy than the other samples. The order for the potential of self-ignition classified based on activation energy is SPE > PRB > BBCC > Trapper > KM4 > KM3 > Suancigou No. 6 > New Elk > Nanyangpo No. 4 > Nanyangpo No. 3 > Suancigou No. 4 > WR > Xuandong No. 3 > Sewi WV > Murray > Sewi GM1012 > Sewi GM1013 > Pittsburgh > RB > FR0913/14 > FR0804 > FR0809 > FR0803 > FR0910 > FR0801 > FR0802. For the low-rank coals, the activation energy of PRB, SPE, Trapper, and BBCC is much lower than the other samples, indicating they have a high risk of self-heating. In the previous section, the testing results have indicated that PRB and BBCC samples have very high tendency of self-heating in moist oxygen condition. The mechanism of spontaneous combustion can be explained by kinetic theory. A coal contains various functional groups. The abilities of these substances to be oxidized are different. The substances which are more easily oxidized will be activated first with a very small amount of energy with the heat released from physical and chemical adsorption. Then the chemical reaction will occur between activated substances and oxygen. As more oxygen is adsorbed and heat

3.3 Thermoanalytical Analysis Method

103

accumulated, the temperature of the coal will increase. The functional groups which are easier to be activated become more sensitive and more prone to be activated. Some substances which are difficult to be activated are not consumed at low temperature (40–70
C). They can only be activated by more energy as the temperature continues to increase.

3.3.4

Determination of Coal Composition with TGA

The propensity of coal’s spontaneous combustion can be assessed using the coal quality parameters of moisture, volatile matter, and fixed carbon that are normally obtained from proximate analysis of coal. Traditionally, various proximate analysis determination processes are guided by ASTM standards. However, these determinations are time-consuming and require a significant amount of laboratory equipment. TGA technique, on the other hand, could provide an alternative method to perform the proximate analysis with a faster procedure to determine the coal quality parameters (TA brief). In addition, not all coal samples tested in our laboratory had been tested for the proximate analysis, or the analysis results are not provided. The TGA can also be used to fill the data voids. The coal sample is grounded to less than 50 mesh (< 297 μm) before the test was conducted. An approximately 40 mg of the sample was placed in the platinum pans and loaded into the furnace of the equipment. The sample is heated to 110
C at a constant ramp rate of 85
C/min with a constant nitrogen gas supply of 60 mL/min. Then the sample is kept in isothermal condition for 3 min. The weight loss during this process is the amount of moisture in the coal. The sample continues to be heated to 900
C at a rate of 80
C/min in pure nitrogen environment. Then the temperature is maintained at 900
C for 7 min. The weight loss during this process is the amount of volatile matter in the coal. After a 7 min isothermal condition, with the temperature still maintained at 900
C, the gas supply is switched to pure oxygen at a flow rate of 60 mL/min. The process will continue for 5 min, and no further weight loss is observed on the sample. The weight loss during this process is the fixed-carbon content of the coal. The residual weight at the end of the test is the ash content of the coal. The testing environment and the rest results of one of the tests (Coal MU) are shown in Fig. 3.27. Three plateaus are apparent on the weight-time curve. The test results in Fig. 3.27 show that the tested coal sample contains 2.0% moisture content, 39.0% volatile matter, 48.7% fixed carbon, and 12.3% ash content. TGA-based proximate analysis results for all the samples in the sample bank are listed in Table 3.5. Variation of activation energy of moisture loss (E1), oxidation (E2), and combustion (E3) along with quantified coal rank and the relationships between E1 and moisture content, E2 and volatile matter, and E3 and fixed carbon are investigated as shown in Fig. 3.28. As coal rank increases, activation energy of moisture loss decreases. Low-rank coals contain more moisture than high-rank coals, so the higher moisture content, the more energy required to evaporate the moisture. The oxidation energy, E2, and combustion, E3, present a different trend. As the coal rank increases,

104

3 Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion

Fig. 3.27 T-G curve for proximate analysis of coal

activation energy, E2, and E3 increase accordingly. It may be because higher-rank coals need more energy to oxidize and combust than low-rank coals. In the moisture loss stage, the activation energy is mainly used for moisture evaporation, so the relationship of activation energy of moisture loss and moisture content is studied. As moisture content increases, activation energy of moisture loss increases. It is the same as the first condition, since the higher moisture content contained in the coal, the more energy consumed to evaporate the moisture. In the oxidation and combustion stages, E2 and E3 are primarily consumed for volatile oxidation and fixed-carbon combustion. As for the volatile oxidation, there is no obvious relation between oxidation energy and volatile matter. As fixed carbon increases, activation energy of combustion increases. The more fixed carbon, the more activation energy required for carbon to combust. The relationship indicates that the TGA-based activation energy and composition analysis are reasonable for evaluating risk of spontaneous combustion.

3.3.5

Retardant Selection

Six high tendency coals, labeled as DBW, JX, QX, SFT, XA, and XB, are collected from major mining fields in China for retardant selection. M-, C-, N-, and V-type metal halide compounds are selected to prepare the inhibitors. In the testing procedure, various amounts of the prepared inhibitor were added to the coal sample of

Moisture content 1.6 1.8 1.2 9.8 9.5 2.0 2.1 1.4 1.4 1.2 1.1 1.5 1.5 1.4 1.4 1.5 25.9

13.2 11.2 1.9

Coal sample WR RB SEW KMT KMF MU PI SETH SETW FR01 FR02 FR03 FR04 FR09 FR10 FR13 PRB

SPE TRA NE

44.2 33.5 27.4

Volatile matter 36.0 34.5 33.4 35.3 32.1 39.0 37.7 34.9 37.4 34.8 39.3 40.0 40.0 32.4 36.1 39.4 37.7

TGA (Wt %)

38.4 43.1 38.8

Fixed carbon 57.1 42.7 52.5 48.1 52.9 48.7 52.2 37.3 48.3 58.5 52.5 52.2 52.6 58.9 56.5 53.2 31.9

4.2 12.2 31.9

Ash content 5.3 21.0 12.8 6.8 5.5 12.3 8.0 26.4 12.9 5.5 7.1 6.3 5.9 7.3 6.0 5.9 4.5

18.4 30.2 100.1

USBM SHT (
C) 109 98 113 35 42 94 97 102 106 114 112 104 105 113 111 105 9.5

Table 3.5 Experimental results of the samples collected

29.3 30.0 82.7

Modified SHT (
C) 84.6 82.7 86.5 43.4 45.6 81.7 81.6 84.2 84.8 86.8 86.4 84.3 84.4 86.2 85.5 84.5 29.4 42.0 35.6 25.4

E1 (kJ/mol) 30.7 28.1 21.1 28.8 29.6 31.1 22.1 22.0 23.7 24.0 22.6 22.3 22.7 24.3 23.1 22.8 38.2 E2 (kJ/mol) 90.1 105.3 91.3 65.9 64.3 92.2 101.0 97.2 95.3 167.8 205.0 137.9 125.2 134.9 156.7 124.5 26.3 19.0 41.1 86.1

A1 (s1) 7.95  103 2.11  103 3.35  102 1.31  104 1.50  104 7.79  103 4.14  102 4.08  102 7.62  102 3.45  102 2.23  102 2.70  102 3.10  102 4.52  102 2.46  102 3.51  102 2.73  105 1.17  106 9.38  104 2.02  103

Kinetic parameters E3 (kJ/mol) 106.8 110.2 92.7 86.4 93.6 101.5 90.7 86.0 90.7 119.3 106.3 104.9 104.8 111.0 118.1 100.5 60.1 93.9 69.1 97.9

A2 (s1) 2.69  108 1.06  1010 2.42  108 1.87  106 1.30  106 4.82  108 2.74  109 1.13  109 7.68  108 4.54  1015 1.32  1019 7.31  1012 4.83  1011 3.05  1012 3.73  1014 3.98  105 1.72  102 1.73  101 7.21  103 5.93  107

9.87  105 1.11  104 4.63  105

A3 (s1) 3.02  106 4.94  106 2.17  105 1.32  105 4.77  105 1.01  106 1.60  105 5.85  104 1.50  105 1.83  107 1.70  106 1.41  106 1.59  106 3.44  106 1.28  107 8.11  105 3.39  103

R70/ moist (
C/ h) – – – – 0.86 – 0.06 – 0.23 – 0.06 – – 0.03 – – 0.29/ 15 – – –

10.6 11.4 12.1

Coal rank 12.6 11.8 12.5 12.0 12.0 12.4 12.2 11.5 12.0 13.8 13.4 13.1 13.2 13.9 13.5 13.3 10.1

(continued)

HvCb HvCb HvAb

ASTM rank HvAb HvAb HvAb HvCb HvCb HvAb HvBb HvAb HvAb HvAb HvAb HvAb HvAb HvAb HvAb HvAb SubA

SCG06 NYP03 NYP04 XD03

Coal sample BBCC SCG04

3.5 3.2 3.4 1.2

Moisture content 18.9 4.4

19.4 26.7 32.1 29.3

Volatile matter 49.8 34.0

TGA (Wt %)

Table 3.5 (continued)

28.1 47.5 49.5 53.1

Fixed carbon 26.9 39.8

49.0 22.6 15.0 16.4

Ash content 4.4 21.8

77.1 89.4 81.1 114.7

USBM SHT (
C) 8.5 58.4 74.8 77.2 75.6 87.2

Modified SHT (
C) 19.2 69.6 18.0 25.0 23.7 24.5

E1 (kJ/mol) 36.7 24.9

E2 (kJ/mol) 37.0 88.2 83.4 87.6 86.3 90.5

A1 (s1) 1.23  105 1.94  103 1.41  102 1.80  103 1.01  103 1.29  103

Kinetic parameters

7.58  107 1.96  108 1.51  108 1.71  108

A2 (s1) 1.90  103 3.66  108 93.6 93.7 86.8 94.9

E3 (kJ/mol) 89.5 83.4 2.74  105 2.94  105 7.38  104 1.94  105

A3 (s1) 7.19  105 6.17  104

R70/ moist (
C/ h) /20 0.95/ 1.18 – – – –

HvBb HvBb HvBb HvAb

ASTM rank SubA HvBb

11.4 12.0 12.2 12.1

Coal rank 8.8 11.3

3.3 Thermoanalytical Analysis Method

40

Activation energy of moisture loss, E1

35

Reference line

30 25

50 45 E1 (kJ/mol)

E1 (kJ/mol)

45

107

20

35 30 Activation energy of moisture loss, E1

25 20

15

Reference line

15 10

200

Activation energy of oxidation, E2

150

Reference line

12 Coal rank

0

14

100

5

10

15 20 Moisutre (Wt %)

25

30

Activation energy of oxidation, E2

200 E2 (kJ/mol)

8

E2 (kJ/mol)

40

Reference line 100

50 0

0 8

12 Coal rank

14

15

20

25

30 35 40 Volatile (Wt %)

45

50

55

Activation energy of combustion, E3

Activation energy of combustion, E3

120

Reference line

E3 (kJ/mol)

E3 (kJ/mol)

10

90

Reference line 100

60 8

10

12 Coal rank

14

20

30

40 50 Carbon (Wt %)

60

Fig. 3.28 Activation energy of moisture loss (E1), oxidation (E2), and combustion (E3) vs. quantified coal rank (as shown on the left column). E1 vs. moisture content, E2 vs. volatile matter, and E3 vs. fixed carbon (as shown on the right column)

500 mg for making inhibitors with different concentrations, stirred evenly, and placed in a heating water bath with constant temperature of 30
C for 120 h. After the mixture of coal and retardant was filtered and washed, it was placed in a vacuum drying oven and dried for 24 h. Finally, the mixed sample is stored in a glass dryer for later use. These coal samples retarded with and without inhibitors are tested with TGA for calculating the activation energy in oxidation stage. The calculated activation energy then can be used as indicator to evaluate the retarding effect of each inhibitor. For different coals, the retarding effects of the inhibitor with various concentrations are diverse. The M-type metal halide compound inhibitor is selected to exemplify the retarding effect and optimal retardant selection. The M-type inhibitor with different concentrations of 0.08%, 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 0.6%, 1%, 2%, 3%, and 4% are added to the six coal samples, respectively. The oxidation activation energy of coal with and without (0%) inhibitor input is then calculated based on TGA experiment as shown in Fig. 3.29. Except for SFT and XB samples, the universal trend of the rest of the sample is that as inhibitor concentration increases, the activation energy increases, indicating that M-type inhibitor with concentration of 4% is the best one for inhibition of DBW, JX, QX, and XA samples. For the SFT and XB samples, the inhibitor with 1% is the optimal one for these two samples.

108

3 Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion 150

200

JX E2 (kJ/mol)

E2 (kJ/mol)

DBW 150 100 50

0

1

2 3 M-type inhibitor (%)

100

50

4

150

0

1

2 3 M-type inhibitor (%)

150 SFT E2 (kJ/mol)

E2 (kJ/mol)

QX 100

50

0

1

2 3 M-type inhibitor (%)

100

50

4

0

1

2 3 M-type inhibitor (%)

4

200

300

XB

XA

250

E2 (kJ/mol)

E2 (kJ/mol)

4

200 150

150 100

100 50

0

1

2 3 M-type inhibitor (%)

4

50

0

1

2 3 M-type inhibitor (%)

4

Fig. 3.29 Activation energy determined for each coal sample after being processed with retardant of M-type inhibitor with different concentrations from 0 to 4%

For one coal, the retarding effects of different types of inhibitor with various concentrations are also different. For the DBW sample, M-, C-, N-, and V-type metal halide compound inhibitors with concentrations of 1% and 4% are used to investigate the optimal retardant selection. Following the same procedure, DBW sample is mixed with the four types of inhibitor and then tested by TGA for determining the activation energy as shown in Fig. 3.30. The higher the activation energy, the better the retarding effect. After adding the inhibitor, the activation energy generally increases, especially the C-type with 4% increasing the most, indicating C-type inhibitor with 4% is the optimal one for DBW coal.

3.4

FTIR Experiment

Fourier-transform infrared spectroscopy (FTIR) is a versatile analytical technique to study fundamental molecular structure of organic and inorganic components (Ammari et al. 2013; Giroux et al. 2006; Guo and Bustin 1998; Ibarra et al. 1996). The underlying mechanism of the FTIR technique is associated with transitions between quantized vibrational energy states (Smith 2011). Not all adsorptions are IR detectable. There are two requirements that need to be satisfied, identical frequency

3.4 FTIR Experiment

109

140 Activation energy of oxidation

130

E2 (kJ/mol)

120 110 100 90 80 70 60 -1

0

1

2

3

4

5

6

7

8

9

Inhibitor

Fig. 3.30 0 is the sample without inhibition; 1 is C-type inhibitor with 1%; 2 is M-type inhibitor with 1%; 3 is N-type inhibitor with 1%; 4 is V-type inhibitor with 1%; 5 is C-type inhibitor with 4%; 6 is M-type inhibitor with 4%; 7 is N-type inhibitor with 4%; 8 is V-type inhibitor with 4%

and dipole moments. In FTIR analysis, IR radiation will launch a photon to a molecule. The molecule will be excited to a higher energy state by absorbing the photon whose frequency is identical to the inherent vibration of the molecule. However, this adsorption cannot be definitely detected. When the molecule vibrates (i.e., stretching, bending, twisting, rocking, wagging, and out-of-plane deformation) with dipole moment changes and absorbs the photon with the same frequency, the adsorption can be guaranteed to be detected at related wave numbers (or frequencies) in the IR region of the spectrum. IR absorbance peak is determined by the intrinsic physicochemical properties of the corresponding molecule and is thus diagnostic, like a fingerprint of that particular functional group (e.g., C–H, O–H, C¼O, etc.) (Chen et al. 2015). Most used FTIR in geological sciences focuses on the mid-infrared (MIR) region, approximately 4000–400 cm1. Coal is a multicomponent polymeric material composed of macromolecular network structure connected with covalent and non-covalent chemical bonds, various functional groups, and organic or inorganic compounds (Baset et al. 1980; Bodzek and Marzec 1981; Haenel 1992). The complex composition determines it has highly chemically heterogeneous characteristics. Continuous development of study approach and rise in the instrumental sophistication offers in-depth understanding of what coal really is (Marzec 1986, 2002; Qin 2018). Fourier-transform infrared spectroscopy (FTIR) is one of the most powerful and versatile techniques for characterization of coal due to its capability of identifying vibrational signatures attributed to specific types of chemical bonds and functional groups (Giroux et al. 2006; Oikonomopoulos et al. 2010; Zhang et al. 2018). Composition profile is

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3 Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion

1.4

C=C aromatic stretch

CH2, CH3

C-O stretch, O-H bend groups

CH3

1.2

Kubelka-Munk

1

C-H aromatic stretch

C=O stretch C-H aliphatic stretch

Aromatic C-H out-of-plane bend

0.8 O-H groups 0.6

0.4

0.2

Waterberg

Highveld 0 4000 3800 3600 3400 3200 3000 2800 2600 2400 2200 2000 1800 1600 1400 1200 1000 800

600

400

Wavenumber (cm-1)

Fig. 3.31 A typical FTIR spectrum of coal in Highveld bottom and Waterberg coals (Malumbazo 2011)

reflected by a frequency band known as FTIR spectrum. It reads the information of the amount of possible functional groups available in the organic structure of coal quantitatively by spectral peaks determined by absorbance intensity (absorbance unit) and position (wave number) on the spectrum as shown in Fig. 3.31. In this section, both band assignments of functional groups in coal with high and low tendency of spontaneous combustion (short for “high or low tendency coals” instead in the following context) and chemical structure evolution during the process of oxidation with temperature rise are evaluated by FTIR. A total of eight coal samples from different mining fields in China are collected. For comparative study, four coal samples are collected intentionally with high risk of self-heating behavior. The other four are low tendency coals. Band assignment and absorbance intensity of functional groups contained in the eight coal samples are investigated comparatively. In the second experiment, one of the eight samples with high potential of selfignition is selected representatively for identifying the chemical structure and functional groups evolution in oxidation process with temperature rise.

3.4.1

FTIR Spectra for Coals with Different Propensity of Spontaneous Combustion

The analysis of the infrared spectrum is mainly based on the information given by the frequency band to derive the possible molecular structure of the sample. However, not every peak in the spectrum can give an exact assignment and intensity

3.4 FTIR Experiment

111

Fig. 3.32 Typical FTIR spectra for different ranks of coals from anthracite, bituminous coal, and sub-bituminous coal to lignite

of the functional group it stands for. Some of the peak is vibration of a pure molecular structure, for example, C–H stretching modes and C¼O stretching modes are relatively localized without influence from others. Conversely, some of the vibrations are more or less coupled or mixed with other vibrations, such as the vibrations of an ether linkage in a –C–C–O–C– type of structure are mechanically coupled to the vibrations of the adjacent C–C bond. Therefore, absorption peaks sometimes are actually the results of frequency doubling or frequency combination of other multiple peaks, for example, the IR bands characteristic of the –C–C–O–C– vibrations cannot be separately assigned to C–C and C–O stretch but have a mixture character including various contributions from these or other bonds. There are many factors affecting the number, frequency, intensity, and shape of the absorption peaks in the infrared spectrum, and thus the analysis of the infrared spectrum is more or less empirical. Consequently, the only bands that can be used for quantitative analysis of functional groups should be those in which vibration motion is well-defined. Although coal is an extraordinarily heterogeneous material, the general features of the IR spectrum do not vary significantly with ranks as shown in Fig. 3.31. The variations are principally in the relative intensities (peak height) of the bands in each spectrum, which determines the activity of the coal in chemical reaction with oxygen. In Fig. 3.32, a relative strong adsorption peak with broad band observed at 3424 cm1 is assigned to O–H and N–H groups. Due to hydroxylation of hydroxyl groups, the band of 3300 cm1 where O–H appear normally is moved to somewhere close to 3450 cm1. H–O vibration of moisture in KBr is also a contribution at this region. Therefore, the observed peak could be attributed to O–H, N–H, or O–H in moisture or any combination of the three. The weak peak at 3075–2988 cm1 is due to aromatic C–H or unsaturated C–H on olefin stretching vibrations. The double

112

3 Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion

peaks at 2919 cm1 and 2855 cm1 are assigned to aliphatic –CH2 stretching vibration. An extremely strong peak observed at 1601 cm1 is due to aromatic C¼C stretching vibration. The spectral peaks observed at 1439 cm1 are assigned to aliphatic –CH3 and –CH2 vibration modes, but the presence of –CH2 is greater than – CH3. A sharp peak at 1378 cm1 is due to the aliphatic –CH3 stretching vibration. The prominent bands in the 1340–1120 cm1 and 1120–1060 cm1 regions are attributed to C–O stretching vibrations of ether groups. At 1029 cm1, the peak could be assigned to saturated aliphatic skeletal C–C vibrations and C–O stretching vibrations. Due to dipole moment great change in C–O vibration, the peak is mainly assigned to C–O stretching vibrations. Low-intensity aromatic –CH bands were observed between 900 and 700 cm1 in all rank coals. These bands were due to aromatic C–H out-of-plane bending vibrations. The multiple peaks appearing below 700 cm1 are due to 1,2-substituted (four neighboring aromatic C–H) or long aromatic alkane ((CH2)n; n > 4) side ring vibration. The specific peak assignment of FTIR spectrum for coals in general is listed in Table 3.6.

3.4.1.1

Experimental Instrument

Bruker Tensor 27 FTIR spectrometer is used for the two designed experiments for band assignment of functional groups in coal with high and low risk of self-ignition and chemical structure evolution during oxidation as shown in Fig. 3.33. It is equipped with DigiTectTM detector system and high sensitivity DLATGS, a standard KBr beam splitter. Spectral range is 7500–370 cm1. Maximum resolution is 1 cm1, and wave number accuracy is better than 0.01 cm1. Other instruments for sampling are agate pestle and mortar, sample pellet and sample holder, pellet dies, and hydraulic press. For drying the sample, SK-2.5-13 T tubular electric resistance furnace, oven, and crucibles are also used for sampling in the experiment.

3.4.1.2

Experimental Procedure

The coal samples are directly collected from longwall panel of underground coal mines in major mining fields in China. When the samples are collected, they are immediately sealed in plastic bag to keep them from further oxidation before delivering to our lab. The eight samples are labeled as DBW, SY, BB, and DQ (predetermined high tendency coals) and CGY, DAS, XC, and YMZ (predetermined low tendency coals), respectively, for subsequent experiment. The samples are grounded to less 58 μm, then dried for 24 h in vacuum, and stored in dry container for later use. Dry the KBr in the oven for a couple of hours to remove the moisture absorbed in it. Then place the KBr in a dryer for cooling down. After the temperature is closed to ambient temperature, store the KBr in a sealed container for later use. Then the KBr pellet is prepared as follows:

3.4 FTIR Experiment

113

Table 3.6 Band assignment of FTIR spectrum of coal in general Wave number (cm1) 3680– 3100 3419– 3359 3300 3100– 3000 3030 3000– 2800 2980 2975– 2955 2950 2925– 2919 2920 2900 2863 2850

2848 2324 1940 1835 1800– 1650 1775– 1765 1745– 1730 1735 1700 1720– 1690

Band assignments O–H and N–H stretching vibrations –OH stretching vibration Hydrogen-bonded OH Aromatic C–H stretching vibration

Aromatic OH Aromatic C–H stretching vibration Asymmetric aliphatic CH3 stretching vibration Aliphatic CH3 asymmetric stretching vibration CH3 Aliphatic CH2 asymmetric stretching vibration Aliphatic CH, CH2, and CH3 Symmetric aliphatic CH2 or CH stretching vibration Aliphatic CH3 asymmetric stretching vibration Aliphatic CH3 or CH2 symmetric stretching vibration Aliphatic CH2 asymmetric stretching vibration C¼C stretching vibration C¼C stretching vibration C¼O, anhydride Oxygenated groups C¼O, ester with electronwithdrawing group attached to single-bonded oxygen Aliphatic (grease, acid, ketone, aldehyde) (C¼O) C¼O, ester Aliphatic C¼O and -COOH stretching vibration C¼O, ketone, aldehyde, and COOH

Reference Neupane et al. (2017); Okolo et al. (2015) Dun et al. (2013); Oikonomopoulos et al. (2010); Xuguang (2005) Chen et al. (2012); Painter et al. (2012) Chen et al. (2012); Dun et al. (2013); Neupane et al. (2017); Okolo et al. (2015); Xuguang (2005) Painter et al. (2012) Chen et al. (2012); Neupane et al. (2017); Okolo et al. (2015) Neupane et al. (2017); Okolo et al. (2015) Dun et al. (2013) Painter et al. (2012); Xuguang (2005) Dun et al. (2013); Oikonomopoulos et al. (2010) Okolo et al. (2015); Painter et al. (2012); Xuguang (2005) Dun et al. (2013); Neupane et al. (2017); Xuguang (2005) Dun et al. (2013) Oikonomopoulos et al. (2010); Okolo et al. (2015); Painter et al. (2012); Xuguang (2005) Dun et al. (2013) Neupane et al. (2017) Neupane et al. (2017) Painter et al. (2012) Chen et al. (2012) Painter et al. (2012)

Dun et al. (2013); Xuguang (2005) Painter et al. (2012) Neupane et al. (2017); Okolo et al. (2015) Dun et al. (2013); Painter et al. (2012); Xuguang (2005) (continued)

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3 Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion

Table 3.6 (continued) Wave number (cm1) 1680– 1500 1650– 1630 1615– 1585 1600 1560– 1590 1510 1500– 1450 1460– 1450 1490 1460 1458 1452 1450 1435 1430– 1420 1400 1380 1375

1330– 1110 1312 1300– 1000 1280– 1000

Band assignments Aromatic C¼C stretching modes C¼O, highly conjugated Aromatic nucleus (C¼C)

Reference Chen et al. (2012); Neupane et al. (2017); Okolo et al. (2015) Okolo et al. (2015); Painter et al. (2012) Dun et al. (2013); Oikonomopoulos et al. (2010) Okolo et al. (2015); Painter et al. (2012)

Aromatic C¼C stretching vibrations of aromatic rings Carboxyl group in salt form COO

Painter et al. (2012)

C¼O stretching vibration (C–C)ar stretching

Oikonomopoulos et al. (2010) Dun et al. (2013)

Aliphatic chains (CH3, CH2)

Dun et al. (2013); Xuguang (2005)

Aromatic ring stretch Aromatic C¼C stretching vibration Asymmetric aliphatic C–H deformation of methylene and methoxy Aromatic C¼C stretching vibration CH2 and CH3 bend; possibility of some aromatic ring nodes Aliphatic CH2 and CH3 bending vibration Aromatic C¼C stretching vibration Aromatic C¼C stretching vibration Symmetric deformation CH2 (bending) Symmetric aliphatic C–H bending of methyl groups CH3

Painter et al. (2012) Okolo et al. (2015)

CO stretch and OH bend in phenoxy structures, ethers Aliphatic CH in-plane bending vibration Phenolic deformation C–O–C (stretching) Aliphatic skeletal C–C; C–O stretching; and –OH bending vibration

Oikonomopoulos et al. (2010) Neupane et al. (2017) Painter et al. (2012) Okolo et al. (2015) Oikonomopoulos et al. (2010) Neupane et al. (2017) Dun et al. (2013) Oikonomopoulos et al. (2010); Okolo et al. (2015); Painter et al. (2012); Xuguang (2005) Painter et al. (2012) Okolo et al. (2015) Dun et al. (2013) Neupane et al. (2017); Okolo et al. (2015); Xuguang (2005) (continued)

3.4 FTIR Experiment

115

Table 3.6 (continued) Wave number (cm1) 1266 1251 1224 1100– 1000 1066 1031 900– 700 880– 860 869 860 849 833 815 800 776– 730 750 738 730– 720 720– 680

Band assignments C–O stretch vibration (in ligningualacyl ring with C–O stretch) C¼O stretching vibration C–O stretch vibration (in ligningualacyl ring with C–O stretch) Aliphatic ethers, alcohols Amorphous carbon C–O–H deformation in cellulose Out-of-plane aromatic C–H bending vibrations Aromatic nucleus (CH), one adjacent H deformation Aromatic nucleus CH bending vibration Isolated aromatic H Aromatic nucleus (CH), two adjacent H deformation 1,4-substituted aromatic groups Isolated H and/or two neighboring H Aromatic nucleus CH bending vibration Aromatic nucleus (CH), three to four adjacent H deformation 1,4-substituted aromatic groups, four neighboring H Aromatic nucleus CH bending vibration Alkanes side rings [(CH2)n, n > 4] Long aromatic alkane ((CH2)n; n > 4) side rings

Reference Oikonomopoulos et al. (2010) Neupane et al. (2017) Oikonomopoulos et al. (2010) Painter et al. (2012) Neupane et al. (2017) Oikonomopoulos et al. (2010) Chen et al. (2012); Dun et al. (2013); Neupane et al. (2017); Okolo et al. (2015); Painter et al. (2012) Dun et al. (2013); Okolo et al. (2015) Neupane et al. (2017); Xuguang (2005) Painter et al. (2012) Dun et al. (2013); Oikonomopoulos et al. (2010); Okolo et al. (2015) Painter et al. (2012) Painter et al. (2012); Xuguang (2005) Neupane et al. (2017) Dun et al. (2013); Okolo et al. (2015); Xuguang (2005) Painter et al. (2012) Neupane et al. (2017) Dun et al. (2013) Neupane et al. (2017); Okolo et al. (2015); Xuguang (2005)

1. Take 2 mg sample powder and 300 mg KBr (spectroscopic grade) and mix them together evenly into an agate mortar (Fig. 3.33b). 2. Further grind the powder sample and KBr together in the agate mortar with agate pestle until it sticks to the mortar like fine flour. 3. Transfer the ground mixture into the cylinder bore of the die as shown in Fig. 3.33d. 4. Place the die assembly into a hydraulic press as shown in Fig. 3.33e and press for 2 min under pressure of 150 tons to form a pellet.

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3 Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion

5. Remove the die from the press and disassemble the die set to get the KBr pellet out. 6. Put the pellet to a spectrometer disk holder (Fig. 3.33c) and mount the disk holder in the spectrometer (Fig. 3.33a). It should be noted that KBr powder extremely tends to absorb moisture, so the environment with high relative humidity should be avoided when grinding the sample and preparing the pellet. Pure agate pestle and mortar should be used, since agate is non-absorbing in the infrared spectroscopic region. Agate bowl with 4 cm diameter is the ideal tool for manually grinding solid samples. The KBr pellet should be thin and transparent, since the opaque pellets will block the infrared beam that passes through, resulting in a poor spectrum.

3.4.1.3

Results and Discussions

Based on the experimental procedure, each of the eight samples is tested by FTIR spectrometer. The obtained testing results in terms of IR spectrum for each coal sample are shown in Fig. 3.34. From the comparative IR spectrum of high and low tendency samples, it can be obviously seen that the trends and features of FTIR spectra for high and low propensity coals are basically similar. Variations only appear in adsorption peak height and intensity, indicating that the number of functional groups and the chemical structure of coals are quite different from one to another. The figures on the left and right column are the spectrum for coals with high and low tendency of spontaneous combustion. Although the coal samples are collected from different mining fields and they occurred far away from each other geologically, the shape of IR spectrum does not vary significantly. All the samples have comparable spectral peaks observed at positions of 3400 cm1, 3010–3040 cm1, 2926 cm1, 2855 cm1, 1600 cm1, 1450 cm1, 1210–1160 cm1, 1150–1170 cm1, and below 900 cm1. In general, the peaks of low tendency coals (CGY, DAS, XC, and YMZ) at 1450 cm1 are weak. Less peaks are observed at 1000–1500 cm1 and the region below 900 cm1. Only two strong peaks appear at 1450 cm1 and 900 cm1 for CGY and DAS samples, while only one peak is observed at 900 cm1 in XC and YMZ samples compared to high tendency coals (BB, DBW, DQ, and SY). Those peaks are related to corresponding functional groups including –OH, –NH, aromatic C¼C, aliphatic –CH3 and –CH2, and aliphatic ether and aromatic ether for both high and low tendency coals. Based on the specific band assignment of general coal in Table 3.6, the peak assignment and the exact position where the peaks appear for each high and low tendency coal are listed in Table 3.7. The properties of peaks at their corresponding position are described with strong, medium, and weak for intensity and broad and sharp for shape. Base on the peak properties shown in Table 3.7, a more visualized heat map for presenting the distinction of chemical structures between high and low tendency coals is plotted as shown in Fig. 3.35. It can be seen that the number of functional groups (dark color, mostly distributed on the left) in high tendency coals is much more than that (light color mainly distributed on the right) in low tendency coals. The adsorption of

3.4 FTIR Experiment

117

a

b

e c

d

2.0 BB with high potential

2.0 CGY with low potential

1.5

1.5

1.0

1.0

0.5

0.5

0.0 2.0 DBW with high potential

0.0 2.0 DAS with low potential

1.5

1.5

1.0

1.0

Absorbance units

Absorbance units

Fig. 3.33 FTIR experimental instrument involving (a) Bruker Tensor 27 FTIR spectrometer, (b) agate pestle and mortar, (c) sample pellet and sample holder, (d) pellet dies, and (e) hydraulic press

0.5 0.0 2.0 DQ with high potential 1.5 1.0

0.5 0.0 2.0 XC with low potential 1.5 1.0

0.5

0.5

0.0 2.0 SY with high potential

0.0 2.0 YMZ with low potential

1.5

1.5

1.0

1.0

0.5

0.5

0.0 4000

3500

3000

2500

2000

Wave number (cm-1)

1500

1000

500

0.0 4000

3500

3000

2500

2000

1500

1000

500

Wave number (cm-1)

Fig. 3.34 FTIR spectra for coals (BB, DBW, DQ, and SY) with high self-heating tendency (as shown on the left column) and for coals (CGY, DAS, XC, and YMZ) with low self-heating tendency (as shown on the right column)

Band assignments O–H and N–H stretching vibrations Aromatic C–H stretching vibration Symmetric aliphatic –CH2 stretching vibration Asymmetric aliphatic –CH3 stretching vibration Aromatic C¼C stretching vibration Aliphatic –CH2 and –CH3 asymmetric bending vibration Aromatic ether oxygen bond stretching vibration of alcohol, phenol, and acid Aromatic ether oxygen bond stretching vibration of alcohol, phenol, and acid Aliphatic ether oxygen bond stretching vibration, or Si–O–Si, Si–O–C Out-of-plane aromatic C–H bending vibration with isolated aromatic H Out-of-plane aromatic C–H bending vibration with two adjacent aromatic H Out-of-plane aromatic C–H bending vibration with four adjacent aromatic H Out-of-plane aromatic C–H bending vibration with five adjacent aromatic H 676

746

810

868

1029

1116

1214

1601 1434

2850

w

m

m

m

m

w

s

s s

m

Sample DBW WN I 3416 s 3023 w 2919 m

694

752

810

873

1029

1099

1255

1596 1434

2855

SY WN 3412 3029 2919

WN wave number (cm1), I intensity, s strong, m medium, w weak, b broad

720–680

750

815

900–700

1100–1000

1330–1110

1251

1600 1400–1450

2850

Wave number (cm1) 3680–3100 3100–3000 2920

m

m

m

s

m

m

w

s s

m

I m w m

689

740

798

873

1029

1110

1240

1601 1440

2855

BB WN 3416 3034 2919

m

m

m

m

s

w

w

m s

w

I m w m

700

752

798

908

1024

1099

1250

1607 1440

2854

DQ WN 3433 3034 2919

w

w

m

m

s

m

w

m m

m

I m w m

695

706

798

873

1018

1110

1251

1613 1422

2855

CGY WN 3410 3200 2919

Table 3.7 Band assignments of functional groups in coals with high and low tendency of spontaneous combustion

b

w

w

m

s

b

b

w s

w

I m b w

700

750

792

879

1018

1110

1251

1619 1428

2855

DAS WN 3416 3020 2925

b

b

w

w

s

b

b

w m

w

I m b w

700

750

758

827

1018

1110

1251

1619 1425

2850

XC WN 3410 3200 2920

b

b

w

w

s

b

b

w b

b

I m b b

700

746

815

821

1018

1110

1251

1590 1425

2850

YMZ WN 3416 3200 2920

b

w

b

w

s

b

b

w b

b

I w b b

118 3 Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion

YM Z

XC

119

D AS

C G Y

D Q

BB

SY

D BW

3.4 FTIR Experiment

O-H and N-H stretching vibrations Aromatic C-H stretching vibration Symmetric aliphatic -CH2 stretching vibration Asymmetric aliphatic -CH3 stretching vibration Aromatic C=C stretching vibration Aliphatic -CH2 and -CH3 asymmetric bending vibration Aromatic ether oxygen bond stretching vibration of alcohol, phenol, and acid Aromatic ether oxygen bond stretching vibration of alcohol, phenol, and acid Aliphatic ether oxygen bond stretching vibration, or Si-O-Si, Si-O-C Out-of-plane aromatic C-H bending vibration with isolated aromatic H with two adjacent aromatic H with four adjacent aromatic H with five adjacent aromatic H

0 0.6 1.2 1.8 2.4 3

Fig. 3.35 Heat map for the peak intensity related to the functional groups for high and low tendency coals

–OH and –NH at 3416 cm1 decreases obviously in low tendency coals. The adsorption intensities at 2920 cm1, 2850 cm1, and 1428 cm1 ascribed to aliphatic –CH2 and –CH3 group decrease significantly. Such reduce in aliphatic structure is favorable for decreasing the reactivity of coal. The peaks at 1110 cm1 and 1029 cm1 disappear in low tendency coals, indicating a great number of ether oxygen bond reduction in those coals compared to high tendency coals. The shape and strong peaks at 1018 cm1 of low tendency coals are observed. It is mainly due to the stretching vibration of minerals, such as Si–O–Si or Si–O–C, resulting in more minerals in low tendency coals (Zhang et al. 2015). Mineral matters have retardant effects on coal self-ignition. This effect is due to the mineral matter acting as a heat sink in coal (Beamish and Blazak 2005). Based on the analysis of the spectrum, it can be concluded that the number of functional groups in high tendency coals is more than that in low tendency coals, which causes the coal to be more prone to react with oxygen.

3.4.2

Variation of Chemical Structure and Functional Groups in Self-Heating Process

3.4.2.1

Experimental Instrument and Procedure

In this section, the second experiment follows the same experimental instrument and sampling process presented in Sects. 3.4.1.1 and 3.4.1.2. After the coal samples are grounded into powers and the agent KBr cools down to the ambient temperature, an additional step is adopted before preparing the KBr pellet. Take sufficient amount of grounded coal samples at a time and put it into the crucible. Then transfer the

120

3 Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion

crucible into the SK-2.5-13 T tubular electric resistance furnace. Starting at room temperature, heat the sample with temperature increasing rate of 5
C/min. Stop heating the sample at each temperature increment of 20
C. From 20 to 600
C, a total of 22 oxidized samples are obtained. It should be noted that among them the last two samples are prepared at 500
C and 600
C, respectively. Then following the experimental procedure, the samples prepared at each temperature interval are taken to make the KBr pellets.

3.4.2.2

Results and Discussions

The coal sample labeled as DBW is taken as an example to study the chemical structure variation during oxidation process. The sample heated at each 20
C temperature interval is mixed with KBr. Then the mixture is further grounded manually to prepare the testing pellet. A total of 22 FTIR spectrum of coal oxidized at different temperatures are obtained by scanning the pellet in the spectrometer as shown in Fig. 3.36. From Fig. 3.36, it can be seen that although the coal reacted chemically with oxygen and repeatedly oxidized in rising temperature, the general feature of the IR spectrum for each sample does not change greatly, indicating there is no any new functional groups produced during oxidation, but only varies in numbers. The band (in light green) separately located in the lowest part of the spectrum is from the last sample oxidized at 600
C. The broad and weak peaks on the band indicate that most of the functional groups reacted, and the chemical structure of the coal varies

Fig. 3.36 Illustration by combination of 22 FTIR spectra for functional group variation of DBW coal in the process of spontaneous combustion from 20 to 600
C

3.4 FTIR Experiment

121

24

92 11

50

14

10

aromatic C-O in ether or Si-O-Si

Aromatic C=C

Alipatic -CH2 and -CH3

Aliphatic -CH2

16

00

30 3040 1 29 0 2829 53

Aromatic -CH

Absorbance Units

-OH and -NH

34

00

significantly at high temperature. In general, the adsorption peaks of the samples basically appear in the regions of 3400 cm1, 3010–3040 cm1, 2919 cm1, 2855 cm1, 1600 cm1, 1450 cm1, 1210–1160 cm1, 1150–1170 cm1, and 1100–1000 cm1. In order to more clearly demonstrate the changes in the infrared spectrum of the DBW sample during the temperature rising process, several representative infrared spectra of the sample heated at 20
C, 100
C, 160
C, 300
C, 400
C, and 600
C were selected, respectively, as shown in Fig. 3.37. From Fig. 3.37, it can be seen that the broad peak at 3400 cm1 is due to the –OH and –NH stretching vibration. The peak is gradually diminished with temperature rising from 20 to 600
C. Before 300
C, –OH and –NH do not change too much. At 600
C, the peak intensity is very weak, indicating the number of functional groups – OH and –NH becomes less at this temperature. It is the same variation trend for the aromatic –CH at 3010–3040 cm1 and aliphatic –CH2 at 2853–2929 cm1. Both of them show spectral peaks in low temperature, very weak for aromatic –CH, but progressively disappear at high temperature. The aromatic C¼C and aliphatic –CH2 at 1600 cm1 and 1450 cm1 follow the same variation character with temperature increase. Actually, the C¼C peak at 1600 cm1 indicates that the C¼O groups exist in the coal. Carbonyl originates from the reactions of aromatic C¼C with hydroxyl and hydroxide groups. The generation of carbonyls is the main reaction during coal

600°C

400°C

300°C

160°C

100°C

20°C 4500

4000

3500

3000

2500

2000

1500

1000

500

0

Wavenumber (cm-1)

Fig. 3.37 Selective FTIR spectra for demonstrating the process of spontaneous combustion of DBW coal at temperatures of 20
C, 100
C, 160
C, 300
C, 400
C, and 600
C

122

3 Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion

oxidation (Zhang et al. 2015). However, as temperature increases, the generated carbonyl groups continue to react with oxygen forming carboxyl species and turn into CO2 eventually. The only strong peak observed at 600
C at 1024 cm1 is attributed to C–O–C in ether. During the oxidation process, the very reactive hydride groups convert into unreactive ether (Wang et al. 2003b). Due to the high chemical stability, the cleavage of the C–O bond in ether is uncommon without specialized reagents or under extreme conditions (Levi et al. 2017; Ranu and Bhar 1996). In order to further investigate the functional group modifications of the coal as a function of temperature in the oxidation process, adsorption peaks of the spectra are studied by curve-fitting analysis. The absorbances of molecular vibrations are proportional to the abundance of the functional groups. The absorbance of each vibrational band is often measured by the maximum height or the integrated area between the peak and a baseline. The integrated areas under the peak of –OH and – NH at 3400 cm1, aromatic C–H at 3010–3040 cm1, aliphatic –CH2 at 2853–2929 cm1, aromatic C¼C at 1600 cm1, aliphatic –CH2 and –CH3 at 1450 cm1, and aromatic C–O in ether at 1024–1192 cm1 are calculated for samples oxidized at temperatures from 20 to 600
C. A linear line connects the two points which are tangent to the minima on each side of the peak, as the most widely used baseline is applied in the peak-fitting analysis (Behrens et al. 1996). This type of baseline is easy to define and highly reproducible between operators (von Aulock et al. 2014). The DBW coal at ambient temperature of 20
C is selected as an exemplary sample to demonstrate the multiple curve-fitting analysis for calculation of the areas under adsorption peaks as shown in Fig. 3.38. The resulting areas determined of each functional group are 57.23 for the peak produced by –OH and –NH adsorption at 3400 cm1, 2.56 for aromatic C–H at 3010–3040 cm1, 51.37 for aliphatic –CH2 at 2853–2929 cm1, 58.88 for aromatic C¼C at 1600 cm1, 29.72 for aliphatic –CH2 and –CH3 at 1450 cm1, and 19.83 for aromatic C–O in ether at 1024–1192 cm1. It should be noted that the calculated area is not the exact amount of a specific functional group in the coal. It is a reference value for investigating the variation of those functional groups in oxidation process with temperature rise in later analysis. Through this way, the trajectory of each functional group can be tracked quantitatively at 22 desired temperatures from 20 to 600
C as shown in Fig. 3.39. The peak value of the H–O and N–H groups decreases linearly at about 100–200
C, and the amplitude of the decrease is larger than that of other groups. Before the temperature reaches 150
C, the contents of –OH gradually decrease, since –OH reacts with hydrogen atoms to produce water. The water begins to evaporate at critical temperature of 100
C, resulting in an obvious decrease of – OH in the coal. After the temperature reaches higher than 150
C, primary –OH groups in the coal have been exhausted. As temperature increases, a great amount of –OH groups is generated, higher than the rate of decomposition, leading to an obvious increase in –OH group at high temperatures of 240
C (Cai et al. 2019). When the coal is completely burned at 600
C, the integral area of the absorption peak decreases, and the H–O and N–H groups are mostly oxidized. The adsorption peak area of the aromatic C–H group changes a little before 200
C. In the 30–70
C

3.4 FTIR Experiment

123 0.10

Absorbance units

Absorbance units

0.4

FTIR data Peak-fitting curves Cummulative peak fit R2=0.9947

0.2

FTIR data Peak-fitting curves Cummulative peak fit R2=0.9765

0.05

0.00

0.0

3200

3300

3400

3500

2980

3600

3000

3020

(a)

0.4

FTIR data Peak-fitting curves Cummulative peak fit R2=0.9855

1.5

0.2

0.0

FTIR data Peak-fitting curves Cummulative peak fit R2=0.9921

1.0

0.5

2850

2900

2950

3000

1500 1520 1540 1560 1580 1600 1620 1640 1660 1680 Wavenumber (cm-1)

Wavenumber (cm-1)

(d)

(c) 0.6

FTIR data Peak-fitting curves Cummulative peak fit R2=0.9564

Adsorbance units

Absorbance units

3080

0.0 2800

0.4

3060

(b) 2.0

Absorbance units

Absorbance units

0.6

3040

Wavenumber (cm-1)

Wave number (cm-1)

0.2

0.0

0.4

FTIR data Peak-fitting curves Cummulative peak fit R2=0.9923

0.2

0.0

1420

1440

1460

1480

950

1000

1050

Wavenumber (cm-1)

Wavenumber (cm-1)

(e)

(f)

1100

Fig. 3.38 Multiple curve-fitting analysis of DBW coal as an example for determining absorbance peak area of each functional group on the band at 20
C. The peaks are assigned to (a) O–H and N– H stretching vibration at 3400 cm1, (b) aromatic C–H stretching vibration at 3010–3040 cm1, (c) aliphatic –CH2 asymmetric stretching vibration at 2853–2929 cm1, (d) aromatic C¼C stretching vibration at 1600 cm1, (e) aliphatic –CH2 and –CH3 asymmetric bending vibration at 1450 cm1, and (f) aromatic C–O–C in ether at 1024–1192 cm1

range, the presence of aliphatic carbon groups decreased, then increased at the 70–180
C range, and finally decreased again in the 180–200
C range (Qi et al. 2014). But the value decreases sharply between 200 and 300
C. The decrease of aromatic C–H was attributed to the evaporation of small molecules with aromatic rings (Niu et al. 2016b). However, the increase of aromatic C–H during the following temperature range is attributed to the dehydrogenation of naphthenic structure (Murakami et al. 1997). When the temperature reaches 600
C, the area becomes

124

3 Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion 8

150 -OH and -NH2 Linear fit 95% Confidence band 95% Prediction band

120 90

Aromatic -CH Linear fit 95% Confidence band 95% Prediction band

6 4

60

2

30

Area of absorbance peak

Aliphatic -CH2 Linear fit 95% Confidence band 95% Prediction band

125 100 75 50 25 0 -25 70 60 50 40 30 20 10 0 -10

Area of absorbance peak

0

0

150

Aromatic C=C Linear fit 95% Confidence band 95% Prediction band

120 90 60 30 80

Aliphatic -CH2 and -CH3 Linear fit 95% Confidence band 95% Prediction band

Aromatic C-O in ether or Si-O-Si Linear fit 95% Confidence band 95% Prediction band

70 60 50 40 30 20 10 0

0

50 100 150 200 250 300 350 400 450 500 550 600 650 Temperature (oC)

0

50 100 150 200 250 300 350 400 450 500 550 600 650 Temperature (oC)

Fig. 3.39 Peak area trajectory of each functional group of DBW sample oxidized in the process of chemical reaction with oxygen from 20 to 600
C

0, and the absorption peak of the C–H group disappears. It is indicated that the C–H group is completely oxidized. The intensity of total aliphatic groups increases slightly below 150
C, and then began to decrease with rising temperature, especially above 250
C. In the temperature region of 20–150
C, the additional CH2 was probably converted from methyl through hydrogen abstraction by free radicals. Between 150 and 400
C, the decline was attributed to the evaporation of small molecules connected by weak interaction with macromolecular structure of coal to form gas products (Li et al. 2018; Niu et al. 2016a). When the temperature increases to 600
C, the areas of the –CH2 and –CH3 group entirely disappear, indicating that – CH2 and –CH3 are completely oxidized as shown in Figs. 3.35 and 3.36. The aromatic C¼C has a slow decomposition rate between 200 and 300
C but increases after 300
C. The dehydrogenation of naphthenic structure would result in the increase of aromatic C¼C and the formation of hydrogen gas (Lin et al. 2014; Niu et al. 2016b; Wu et al. 2014). When the temperature rose up to 400
C, the C¼C bond began to crack, resulting in the primary decomposition of aliphatic groups and the increased aromatic C–H. Formation of unstable carbon-oxygen complexes is illustrated in Fig. 3.40. At ambient temperature, carbon-oxygen complexes are initially formed by heat changes due to moisture condensation and evaporation processes. Oxidation further occurs between oxygen molecule and aliphatic groups through chemisorption on the surfaces of pores (Wang et al. 2003a). With the help of initial heat and chemisorption, peroxides and hydroperoxides are formed as the first step in the oxidation reaction (Choudhury et al. 2016; Liotta et al. 1983). At 50
C, alkyl structures, the methylene

3.4 FTIR Experiment

125

20 oC

CH3

+

O2

50 oC

CH3

+

O2

+

O2

H2 C O OH

O

C H

50-150 oC

CH3

aldehyde (-CHO)

C H

O

150 oC

hydroperoxides (-COOH) peroxides (-COO)

O C OH

carboxyl (-COOH)

O

OH

>150 oC

C R

+ O2 + R +

O

O2

quinone O

O C R

ketone (R-C=O-R')

+

O2

CO2

+

O2

CO2

carbonyl (C=O)

O C OH

170 oC >170 oC

O C OH

+

O

O O

C OH

C C

O O

O

C C

ether

O

O C OH

anhydride

O

lactone

Fig. 3.40 Functional groups formed during low-temperature oxidation

(–CH2) is oxidized to aldehydes (–CHO) which is further oxidized to carboxylic acids at 150
C. At the temperature range 50–150
C, methylic groups are oxidized to ketones and phenolic structures to quinones (Yürüm and Altuntaş 1998). As temperature is higher than 150
C, ketonic carbonyl and carboxyl groups are separated from coal structure and oxidized to CO2. At 170
C, adjacent carboxyl groups will condense to anhydrides which may undergo thermal decomposition to produce ether-type oxygen bridges. Simultaneously, carboxyl groups will condense hydroxyl groups to generate lactone-type products (Banerjee et al. 1989). Among the oxygen-containing complexes, ether is unreactive, and the aromatic C–O in ether is relatively stable over long-term oxidation. The ether bonds experience up and down process before 300
C. It is because the ether dominate phenomena is changed to carboxyl groups. General trend of ether rises from low level to high value with the formation rate being faster than the decomposition rate at low temperature, but it tends to decrease again with temperature increases (Ge and Li 2003; Wang and Zhou 2012). However, with an obvious strong peak still left at 600
C, it is speculated that the peak is a contribution from the Si–O–Si bond, in the form of quartz with concentration of 3–5% in coal ash. Formation of the oxygen that contained

126

3 Laboratory Experiment for Evaluating Characteristics of Spontaneous Combustion

functional groups is exothermic in nature, but with increase in temperature, carboxyl, carbonyl, and ether will finally decompose. Conclusively, the abundance of carboxyl, hydroxyl, and carbonyl groups in DBW coal contributes to its high reactivity, instability, and susceptibility to oxidation and spontaneous combustion.

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Chapter 4

Analytical Model Developed to Estimate Self-Heating Potential

Abstract A mathematic model has been developed to link the three methods for testing the propensity of coal’s spontaneous combustion theoretically based on R70 self-heating test setup and the testing procedure. The model considers the heat losses and gains caused by coal moisture, inlet oxygen flow and exhaust air, conduction and convection heat transfers between coal and outside, and heat diffusion in the sample. Using the shrinking model and mobile core model, the previously developed model is improved which is capable of quantifying the effects of sulfur, moisture condensation, humidity, activation energy, and initial temperature on the selfheating process. The model was verified with experimental data which gives a reasonably good result to the predicted one. A new coal ranking system is also suggested with the function of updating the qualitative classification method into a quantitative one. With this quantitative coal ranking system, mathematical correlation of US coal rank and propensity for spontaneous combustion has been developed. The classic USBM method is improved accordingly based on the ranking system. Keywords Shrinking core model · Mobile core model · Moisture condensation · Humidity · Self-heating curve · Quantified coal rank

4.1

Introduction

A mathematic model has been developed to link the three methods for testing the propensity of coal’s spontaneous combustion theoretically. In other words, the mathematic model is developed based on adiabatic energy conservation due to the fact that the R70 method is considered as the most reliable experimental technique to determine the propensity of coal’s spontaneous combustion. Heat generation rate is determined by kinetic parameters and heating value, which is considered to be generated by volatile matter and fixed carbon as the only sources for coal to generate heat. These kinetic and coal quality parameters can be determined using TGA equipment under different testing procedures. The R70 self-heating test has been used as one of the major laboratory methods for testing the intrinsic properties of © Springer Nature Switzerland AG 2020 X. Wang, Spontaneous Combustion of Coal, https://doi.org/10.1007/978-3-030-33691-2_4

129

130

4 Analytical Model Developed to Estimate Self-Heating Potential

coal that influences its propensity for spontaneous combustion. The R70 test is conducted in an artificially created adiabatic environment so that only and all the heat generated by the coal sample is used to prompt the oxidation process and to increase the temperature of the sample. The key to create such an artificial adiabatic testing environment is to eliminate any heat exchange between the coal sample in the testing container and the outside environment through a precise temperature control. Even a minor of amount of heat exchange in the testing duration could produce unreliable testing results, especially for the coals having low propensity. Based on the law of energy conservation, a mathematical model has been developed to quantify the effects of any imperfection of the testing adiabatic environment on the testing results for a R70 self-heating test setup and the testing procedure. The model considers the heat losses and gains caused by coal moisture, inlet oxygen flow and exhaust air, conduction and convection heat transfers between coal and outside, and heat diffusion in the sample. The mathematical model can be applied to correct the testing results in terms of the heat generation rate at a given temperature caused by the system imperfection. Coupled with the experimentally determined parameters such as the specific heat of coal, heating value of various combustibles in the coal, etc., the accuracy of the R70 testing could be greatly improved. The mathematical model also allows the determination of heating value, activation energy, and pre-exponential factor from the experiment-generated temperature development curves. This model can serve as a tool to simulate the coal self-heating behavior with respect to time and temperature in an adiabatic condition. For coal having very low propensity of spontaneous combustion, the model can provide a complete self-heating curve which is unable to be obtained experimentally using the R70 method. It is well-known that sulfur, moisture content, and volatile matter can greatly influence the process of coal’s spontaneous combustion. Their effects are quantified and incorporated into the developed mathematical model. It enhances the model’s ability to consider the effects of these three important properties in the coal. Sulfur exists in coal primarily in the form of pyrite which will be oxidized rapidly under suitable conditions. Shrinking core model is used to quantify the oxidation of pyrite. Heat of moisture condensation which provides initial energy for low-temperature oxidation is incorporated into the model. Volatile matters, higher in low-rank coals, are more easily oxidized.

4.2

Model Developed Based on the Adiabatic Experiment

Adiabatic oxidation method is considered to be a good method to simulate the initial stage of the coal oxidation process at a relatively low temperature. It becomes a standard way to assess the intrinsic properties of self-heating propensity of coal. The adiabatic test of coal is conducted in a reaction vessel which has been designed to minimize heat loss and ideally act as a perfect insulation (Beamish et al. 2000). The reaction vessel is placed inside an adiabatic oven which can be controlled

4.2 Model Developed Based on the Adiabatic Experiment

131

automatically for adjusting the temperature to be equal to that of the coal in the reaction vessel. Consequently, there is no heat transfer between the oven environment and the coal sample. This requires the use of a data logging thermometer to monitor the temperatures of the coal and the oven. The inlet gas of oxygen is preheated before it flows into the reaction container. Through such control, it is ensured that only and all the heat generated by the oxidation of the coal sample is used to sustain the reaction and to raise the temperature of the coal. The self-heating rate is measured by monitoring the temperature development of the coal sample in the reaction vessel. The average hourly temperature increase rate for the coal to selfheat from 40 to 70
C under an adiabatic condition is used to classify the self-heating risk (Humphreys et al. 1981) as shown in Fig. 3.1. Once the temperature increases above 70
C, the rate of temperature change could accelerate leading to a possible thermal runaway. However, to maintain a perfect adiabatic condition is a difficult task for the adiabatic test methods. A best way to avoid heat loss is to minimize the temperature differences among the coal sample, the oven environment, and inlet oxygen gas during the test. Although mathematical models have been developed to analyze the heat transfer in the coal, most of them are about coal stockpiles, and few of them are developed for adiabatic experimental condition. Beamish and Arisoy (2008) proposed a specific self-heating rate prediction equation for a high-volatile bituminous coal. This empirical equation was about the calculation of R70 value using ash and sodium (Na2O) contents. Smith and Glasser (2005) developed the heat transfer model using parameters such as heat capacity, heat of reaction, reaction rate, and activation energies determined from the experimental data. Schmal et al. (1985) developed a one-dimensional model to describe the spontaneous heating process for dry coal at relatively low temperatures ( T0. Therefore, the imperfect testing environment could result in inaccurate self-heating rate.

4.2 Model Developed Based on the Adiabatic Experiment

139

110 PiƩsburgh Sewickley Lvb

100

Temperature (°C)

90 80 70 60 50 40 0

50

100

150

200

250

300

350

Days

Fig. 4.3 R70 predicted self-heating curves of samples from the Pittsburgh and Sewickley coal seams

110 100 TTo

80 70 60 50 40 0

5

10

15

20

25 30 Time (hours)

Fig. 4.4 Sensitivity analysis with different oven temperatures

35

40

45

50

140

4.3

4 Analytical Model Developed to Estimate Self-Heating Potential

Improved Model for Quantifying the Effect of Moisture Condensation

It is believed that sulfur and volatile-matter contents in coals are the main intrinsic properties to cause the self-heating of coal. Their oxidation at lower temperatures than that of fixed carbon to initiate coal’s self-heating should be quantified. This study is aimed to improve the previous mathematical model developed by the authors for studying the coal’s propensity for spontaneous combustion. It enhances the model’s ability to consider the effects of sulfur, volatile-matter, and moisture contents in the coal – three important factors affecting the coal’s self-heating process. Sulfur exists in coal primarily in the form of pyrite which will be oxidized rapidly under suitable conditions. Volatile matters, higher in low-rank coals, are more easily to be oxidized than the fixed carbon. The heat of water condensation provides initial energy for low-temperature oxidation. The heat release rates for pyrite oxidation and moisture condensation are built in the model. Finally, the simulation results in terms of time versus temperature on pyrite oxidation and moisture condensation are validated with the adiabatic testing data, respectively. The R70 self-heating adiabatic test is considered to be a reliable method to evaluate the potential of coal self-ignition. However, for a coal with low propensity, it is difficult to obtain a complete self-heating curve for the investigation of its thermal runaway characteristics – the critical information for assessing coal’s spontaneous combustion. In this regard, a mathematic model has been developed by the author to simulate the coal’s self-heating process in a R70 testing environment (Luo and Wang 2012). This model can serve as a tool to assist the test plan design and to generate a complete self-heating curve when an experiment becomes impractically long. It can also quantify the effects of any imperfection of the testing adiabatic environment on the testing results for a R70 self-heating test setup. However, the previous model was developed base on the standard R70 testing procedure in which the coal was totally dried in nitrogen and then oxidized with oxygen at the initial temperature of 40
C. In addition, it is simplified by assuming that the self-heating rate was not affected by other chemical and physical properties, such as the oxidation of pyrite and volatile matter, moisture condensation, relative humidity, and initial ambient temperature. The primary role of water condensation was to supply an initial heat of adsorption which raised the temperature to a point where the oxidation reactions are selfsustaining. The adsorption of moisture on a dry coal surface is an exothermic process generating heat. If the coal has been partially dried during its mining, storage, or processing, it has the potential to reabsorb moisture from environmental humidity and absorbs the condensation heat. This phenomenon is called heat of wetting. Low-rank coals have larger internal surface which is proportional to the heat of wetting (Das and Hucka 1986). The effects of moisture content and humidity on porous medium or stockpiled coal have been simulated using numerical modeling techniques (Ejlali et al. 2011; Gong et al. 1999; Gray et al. 2002). An improved analytical model is developed based on mobile core theory, different from the

4.3 Improved Model for Quantifying the Effect of Moisture Condensation

141

Arrhenius kinetics on moisture condensation used in the numerical modeling. The pyrite and volatile matter’s roles in promoting self-heating of coal have been discussed in Chap. 1. In this section, the mathematical model has been improved by quantifying the effects of pyrite and volatile-matter oxidation, moisture condensation, and relative humidity variation on the process of coal self-ignition. Heat release rates of pyrite oxidation and moisture condensation have been derived theoretically with shrinking core and mobile core models. The improved model is considered to be the first mathematical description that correlates coal and the effects of pyrite and moisture to the propensity of spontaneous combustion. Experiments were performed with specially designed procedures to verify the improved model.

4.3.1

Heat of Rewetting

A mobile core model, used for quantifying the heat of rewetting, is incorporated into the model. In the adiabatic condition, an isothermal coal particle with radius ro and temperature T is presented in a gaseous environment at the same temperature. Evaporation or condensation takes place on the surface of core with radius rc. Water vapor concentration in the bulk phase is Cvb which is affected by the relative humidity, RH. Water vapor concentration inside the coal is Cvc. Water vapor concentration at the surface is Cvs as shown in Fig. 4.5. In pseudo steady state, the liquid moisture in the core is in equilibrium with moisture in the form of vapor. The rate of water vapor diffusion into the particle from the bulk phase is equal to the rate of water vapor diffusion to the core, which also equates to the change rate of concentration of the liquid moisture core. The relationship among them can be expressed by the following equation: 4πr 2o kg

 ðC vb  C vs Þ ¼

4πr 2c De



 dC v d 4 3 πr c C mc  ¼ dr r¼rc dt 3

ð4:18Þ

where kg is the mass transfer coefficient between the film layer and the particle, De is water vapor diffusivity, Cv is water vapor concentration at position r, and Cmc is liquid moisture concentration in the core. In the region rc < r < ro, change rate of water vapor concentration is determined by the following equation:  dC v 1 d dC r 2  De  v ¼ 0 ¼ 2 dt dr r dr

ð4:19Þ

On integrating Eq. 4.19 with the boundary conditions, Cv ¼ Cvs at r ¼ ro and Cv ¼ Cvc at r ¼ rc, the following equations are obtained:

142

4 Analytical Model Developed to Estimate Self-Heating Potential

Film diffusion layer

Water vapor concentration in bulk phase, Cvb Mobile region: Liquid moisture core varies as reaction progresses,

Water vapor concentration on the surface, Cvs

Cmc Water vapor concentration at the core, Cvc

Fig. 4.5 Mobile core model of single coal particle with radius ro and a moisture core with radius rc in it. Water vapor concentration in bulk phase is Cvb; water vapor concentration on the surface is Cvs and that at the core is Cvc. The liquid moisture concentration in the core is Cmc

C vs ¼ ðC v  C vc Þ

1  r c =r o þ Cvc 1  r c =r

 ðC  C vc Þr o dC v ¼ vs dr r¼rc ðr o  r c Þr c

ð4:20Þ ð4:21Þ

In order to eliminate, Cvs and dCv/dr, substituting Eq. 4.20 into Eqs. 4.18 and 4.21, respectively, and then substituting Eq. 4.21 into Eq. 4.18, it will become Cv  Cvc ¼

k g ðC vb  Cvc Þr 2o ð1  r c =r Þ De r c þ kg r o ðr o  r c Þ

ð4:22Þ

Introducing BiM ¼ kg ro=De , then Eq. 4.22 will be C v  C vc ¼

BiM ðC vb  Cvc Þr o ð1  r c =r Þ r c þ BiM ðr o  r c Þ

ð4:23Þ

Then Eq. 4.18 can be written as

 ðC  C vc Þr o d 4 3 πr c C mc ¼ 4πr 2c De vs dt 3 ðr o  r c Þr c

ð4:24Þ

when Cv ¼ Cvs, r ¼ ro, then substituting Eq. 4.23 into Eq. 4.24, the following equation is obtained:

4.3 Improved Model for Quantifying the Effect of Moisture Condensation

 4πD Bi ðC  C Þr d 4 3 e M vb vc o πr c Cmc ¼ dt 3 1 þ BiM ðr o =r c  1Þ

143

ð4:25Þ

The mobile core model relates the moisture content to the radius of the inner core and the coal particle. When the radius of the inner core is rc ¼ 0, the moisture content from condensation is ϕ0 m ¼ 0. When heat of rewetting occurred, rc and ϕ0 m all gradually increased until rc ¼ ro: r c
0 13 ¼ ϕm ro

ð4:26Þ

Substituting Eq. 4.26 into Eq. 4.25, Eq. 4.27 is obtained:

 4πr D Bi ðC  C Þ d 4 3 o e M h
vb 1 vci πr c Cmc ¼  dt 3 ϕ0 3  1 1 þ Bi M

ð4:27Þ

m

For N particles, N¼

mc ρc 43 πr 3o

ð4:28Þ

The heat generation rate by moisture condensation can be expressed by N

 d 4 3 πr c C mc H vap dt 3

ð4:29Þ

Substituting Eqs. 4.27 and 4.28 into Eq. 4.29, then the following equation is obtained: N

 d 4 3 m 3 D  Bi  ðC  C Þ πr c Cmc H vap ¼ c 2 e h
M 1vb i vc H vap dt 3 ρc r o Bi  ϕ0 3  1 þ 1 M m

ð4:30Þ

The equilibrium relation between liquid moisture in the core and water vapor at the surface of the core within the coal is assumed to follow the Brunauer-EmmettTeller (BET) equation: P 1 c1 P þ ¼ cV m Pv V a ðPv  PÞ cV m

ð4:31Þ

where Va is total amount of water absorbed, Vm is water absorbed in monolayer, c is BET constant which reflects the absorb capability between coal and water vapor, P is the partial pressure of the vapor in equilibrium, and Pv is saturation vapor pressures. If there is no capillary condensation that occurred, then Va ¼ Vm; thus the total water absorbed is in a monolayer. Equation 4.31 then becomes

144

4 Analytical Model Developed to Estimate Self-Heating Potential

P 1 c1 P ¼ þ Pv  P c c Pv

ð4:32Þ

Equation 4.32 can be rearranged to obtain P/Pv:  2 P P ð c  1Þ þ 2  1 ¼ 0 Pv Pv

ð4:33Þ

Then the ratio of the equilibrium and saturation vapor pressures can be written as θ¼

pffiffiffi c1 P ¼ Pv c1

ð4:34Þ

Then the concentration of water vapor in the bulk phase and on the surface of the core is determined as RH  Pv RT θ  Pv C vc ¼ RT

C vb ¼

ð4:35Þ ð4:36Þ

Antonie equation is used to represent the saturation vapor pressure  Pv ¼ ln A1 

A2 T  A3

ð4:37Þ

where Ai is Antoine constants A1 ¼ 10.196, A2 ¼ 1730.63, and A3 ¼ 39.574. Assuming the oven is ideally controlled and the inlet oxygen is preheated sufficiently in the oven and taking the heat of rewetting on dry coal into account, and then combining Eqs. 4.17 and 4.30, it becomes 

C c ð1  ϕm Þmc þ mg C g

  dT E d 4 3 ¼ ð1  ϕm Þmc QA0 eRT þ N πr c C o H vap ð4:38Þ dt dt 3

The R70 test is conducted in an artificially created adiabatic environment so that only and all the heat generated by the coal sample is used to prompt the oxidation process and to increase the temperature of the sample. The key to create such an artificial adiabatic testing environment is to eliminate any heat exchange between the coal sample in the testing container and the outside environment through a precise temperature control. Even a minor of amount of heat exchange in the testing duration could produce unreliable testing results, especially for the coals having low propensity. To quantify the effects of any imperfection of the testing adiabatic environment, the mathematical model has been developed as the first step. The model considers the heat losses and gains caused by coal moisture, inlet oxygen flow and exhaust air, and heat convection between coal and outside. The mathematical model can be

4.3 Improved Model for Quantifying the Effect of Moisture Condensation

145

applied to correct the testing results in terms of the heat generation rate at a given temperature cause by the system imperfection. Coupled with the second step of the model on effect of rewetting heat, the previous developed model could quantify the influence of many affecting factors. With the assist of the experiment-based model, the adiabatic oxidation method will be greatly improved.

4.3.2

Modeling Results and Discussions

According to the testing procedure, sample mass, mc, for each coal is set to 200 g, and coal particle radius is 1.06  104 m for modeling. The proximate analysis parameters (moisture, ϕ0m (amount of moisture condensed); volatile matter, ϕv; fixed carbon, ϕc) used for the model are determined by TGA technique. The activation energy, E, and pre-exponential factor, A0 , of each sample are determined by an independent programmed temperature rising experiment with TGA, listed in Table 4.3. The relative humidity, RH, is assumed to be 100% in the modeling. The initial temperature is 40
C. The other fixed parameters used in the model are also listed in Table 4.3. The ordinary differential equation, Eq. 4.38, was solved using the fourth-order Runge-Kutta method. The relationship between temperature variation and time with initial condition, T ¼ Tinitial, at t ¼ 0 was obtained as shown in Fig. 4.6. The model was calibrated with experimental data from moist and dry tests performed on different samples including BBCC, Cer-C, Cer-D, and Cer-E. Good model fittings were obtained for all the samples previously mentioned as shown in Fig. 4.6. However, there are some deviations between the modeling results and experimental data in the reaction at low temperature, indicated by highertemperature rise between 40 and 70
C during an experiment. It could be because the model assumes constant activation energy from the beginning of the experiment to the end. Alternatively, physical adsorption dominates the beginning of the reaction and generates more heat before the chemical reaction occurred, thus causing the inconsistencies appeared. The coal experiences a fairly rapid self-heating process in the temperature range from 40 to 45
C showing a convex curve. Actually, at the beginning of the test, physical and chemical adsorptions between coal and oxygen occurred first and generated a significant amount of heat. The activation energy deducted in this temperature range is smaller than the activation energy in the temperature range of 50–70
C and in the later thermal runaway process. As the model is calibrated with the testing data and good model fittings are obtained, then the verified model can be used to study the self-heating pattern under different parameters or one parameter with different values, such as coal mass, activation energy, heating value, moisture condensation, and relative humidity. Since the main purpose of this paper is to investigate the contribution of heat of rewetting, in this regard, the simulation is conducted to mainly focus on moisture condensation and relative humidity at different levels. However, the experimental adiabatic apparatus is incapable of quantifying all the affecting factors previously mentioned in different amounts, and no testing data of designated coal sample with

146

4 Analytical Model Developed to Estimate Self-Heating Potential

Table 4.3 Fixed parameters used in the model Parameter Coal-specific heat, Cc Coal density, ρc Air-specific heat, Cg Gas constant, R Mass of the gases, mg Radius of coal particle, ro Activation energy, E

BBCC Cer-C Cer-D Cer-E Pre-exponential factor, A0 BBCC Cer-C Cer-D Cer-E Heating value, Q BBCC Cer-C Cer-D Cer-E Heat of moisture condensation, Hvap Molecular diffusivity of water vapor, De Mass transfer Biot number, BiM BET constant, c

BBCC Cer-D Cer-E dry test Cer-C by model Cer-D by model

130 120

Value 1.38 kJ/kgK 1.5  103 kg/m3 1 kJ/kgK 8.314 J/molK 0.2 g 1.06  104 m 45 kJ/mol 51 kJ/mol 57 kJ/mol 52 kJ/mol 3.23  102 1/s 1.14  103 1/s 4.05  103 1/s 1.41  103 1/s 20.1  103 kJ/kg 26.7  103 kJ/kg 25.6  103 kJ/kg 24.7  103 kJ/kg 44.3 kJ/mol 1.78  105 m2/s 2 12

References Tool box

Wang and Luo (2012)

Wang and Luo (2014)

Noppel (1999) Bhat and Agarwal (1996)

Cer-C Cer-E BBCC by model Cer-E by model Cer-E dry test by model

Temperature (oC)

110 100 90 80 70 60 50 40 0

5

10

15

20 25 Time (hours)

30

35

40

45

Fig. 4.6 Comparison between model results and experimental data for moist tests on samples of BBCC, Cer-C, Cer-D, and Cer-E and dry test on sample Cer-E

4.4 Improved Model for Quantifying Pyrite Oxidation 300

2% 10%

300

5% 20%

200 150 100

200 150 100 50

50 0

RH=40% RH=60% RH=90%

250 Temperature (oC)

Temperature (oC)

250

147

0

50

100 150 Time (hours)

(a)

200

0

0

50

100 150 Time (hours)

200

250

(b)

Fig. 4.7 (a) Effect of heat of rewetting by water condensation in the amount of 2%, 5%, 10%, and 20% and (b) effect of relative humidity of 40%, 60%, and 90% on the self-heating rate of coal predicted by the model

different relative humidity is available to verify the modeling results because of this shortage. Considering this point, the mathematical model is developed to assist this study. The modeling results are shown in Fig. 4.7a and b. With 20% moisture condensed, the heat of rewetting is apparently sufficient to promote self-heating of the coal and makes it to reach thermal runaway within 50 h. Heat released from 2% moisture condensation could only promote the temperature rise of 17
C within the same time duration. At starting temperature of 23
C, the coal with 10% moisture condensation spends 75 h to reach 100
C, while with the contribution of heat of rewetting from 5% moisture condensation, the coal lags 25 h to reach thermal runaway as shown in Fig. 4.7a. The impact of relative humidity is demonstrated in terms of self-heating curves as shown in Fig. 4.7b. As the relative humidity enhances from 40% to 90% at a temperature of 23
C, the time for the temperature to rise to thermal runaway is shortened to 115 h. It should be noted that this model doesn’t consider the competing influences of heat of rewetting and moisture evaporation on the coal. Rewetting heat gained is from water vapor condensation in dried or partially dried particle. After the coal particle is fully wetted, some of heat will be consumed by evaporation of the moisture condensed, which might decrease the temperature to rise and thus form competing influences between heat of rewetting and moisture evaporation on the coal.

4.4 4.4.1

Improved Model for Quantifying Pyrite Oxidation Shrinking Core Model

The shrinking core model has been used to describe pyrite oxidation and pollutant leaching processes in waste dump sites (Cathles and Apps 1975; Levenspiel 1999;

148

4 Analytical Model Developed to Estimate Self-Heating Potential

Singh and Ardejani 2004). This model combined surface reaction with accumulation of product layer on the surface. The following major assumptions have been made in applying the shrinking core model: 1. The reaction rate is first-order with respect to the principal gas reactant and the surface area of remaining solids. 2. Chemical reaction governs the pyrite oxidation. The ash layer has a structure with high porosity. The progress of reaction is unaffected by ash layer. 3. Pyrite particle is isothermal, and the reaction process is in a pseudo steady state, in which the diffusion rate of gaseous reactant through the ash layer outside the unreacted core is much faster than the rate of core shrinkage. 4. All the pyrite particles are in the shape of spherical without changing size during the reaction. Concentration gradients of reactants and shrinkage of the unreacted core are illustrated as shown in Fig. 4.8. The pyrite particle with radius rps is partially oxidized having an unreacted core with radius rpc inside. The particle is exposed to the gaseous environment. The gas in the bulk phase with highest concentration CAg gradually decreases to CAs at the surface of the particle through the gas film and eventually to concentration CAc at the moving reaction surface through the ash layer. Moving along with the shrinkage of the core, the ash layer becomes thicker and thicker resulting in the decrease of gas concentration before it reaches the unreacted core. In a pseudo steady state, the rate of oxygen diffusion into the particle from the bulk phase is equal to the rate of oxygen diffusion to the unreacted core through the ash layer which is also equal to the rate of reaction of oxygen with the unreacted core. The rate of oxygen diffusion is 


 dnp ¼ 4πr 2ps kg CAg  C As dt

ð4:39Þ

In Eq. 4.39, kg is the mass transfer coefficient between fluid and particle, and np is moles of pyrite. The negative sign means the depletion of the pyrite in the reaction. The rate of oxygen diffusion to the unreacted core through the ash layer is  dnp dCA 2  ¼ 4πr pc De dt dr r¼rpc

ð4:40Þ

where De is the diffusion coefficient and CA is the gas concentration at any radius of r in the ash layer. The rate of reaction of oxygen with the unreacted core is 

dnp ¼ 4πr 2pc kp C Ac dt

where kp is reaction rate constant of pyrite.

ð4:41Þ

4.4 Improved Model for Quantifying Pyrite Oxidation

149 Surface of particle

Gas film Moving reaction surface

Ash

Shrinking unreacted core containing B

Concentration of gaseous reactant A and product R

Time

Time

CAg CAs CA

CAc

rps

rpc

0

rpc r rps

Radial position

Fig. 4.8 Representation of reactants and products for the reaction, A(g) + bB(s) ! products for a shrinking core model

In general, the rate of oxygen diffusion in the region rpc  r  rps is determined by the following equation:  d dC r 2 De A ¼ 0 dr dr

ð4:42Þ

Integrating Eq. 4.42 with the boundary conditions, CA ¼ CAs at r ¼ rps and CA ¼ CAc at r ¼ rpc, the following equation is obtained to represent the function of gas concentration CA at any radius r:

150

4 Analytical Model Developed to Estimate Self-Heating Potential r

C A  C Ac ¼ ðC As  C Ac Þ

1  rpc r 1  rpcps

ð4:43Þ

Taking the first derivative of Eq. 4.43 at r ¼ rpc, then it becomes  dC A C  C Ac

 ¼ As dr r¼rpc r 1  rpc pc r ps

ð4:44Þ

Substituting Eqs. 4.39, 4.40, and 4.41 into Eq. 4.44 to eliminate the unknowns CAs and CAc, then " #1
 2 r r r  r dnp 1 ps ps pc ps  þ þ ¼ 4πr 2ps C Ag De r pc kg dt k p r 2pc

ð4:45Þ

The fractional conversion of pyrite can be written as xp ¼ 1 

 3 r pc r ps

ð4:46Þ

Substitute Eq. 4.46 into Eq. 4.45 and then integrate Eq. 4.45. We find the time required for conversion is t¼

ρp bM p CAg ( )
2=3
i r ps h
1=3 i r 2ps h r ps  x þ 1  3 1  xp þ 2 1  xp þ 1  1  xp 3kg p 6De kp ð4:47Þ

where Mp is molar mass of pyrite and ρp is density of pyrite. Taking the first derivative of Eq. 4.47, the reaction rate of pyrite is " #1 dxp 3bM p CAg 1 2r ps 1 þ þ ¼ k g D
1  x 1=3 k
1  x 2=3 dt ρp r ps e p p p

ð4:48Þ

Since the particle size of the samples in the test are all less than or equal to 70 mesh (212 μm), it assumes the pyrite oxidation process is chemically controlled according to assumption 2. In other words, pyrite can be oxidized thoroughly without ash layer accumulated outside the particle. Therefore, the oxidation rate of the unreacted core becomes

4.4 Improved Model for Quantifying Pyrite Oxidation

 dxp 3bk p M p C Ag tbk p M p CAg 2 1 ¼ dt ρp r ps ρp r ps

151

ð4:49Þ

For n moles, the heat generation rate by the oxidation of pyrite is n

 3ϕp mt bk p C Ag dxp bk p M p C Ag 2 1 t Hp Hp ¼ dt ρp r ps ρp r ps

ð4:50Þ

Combined with Eq. 4.38, then the equation for determining coal oxidation, heat of rewetting, and pyrite oxidation is 


  dT
 E d C c 1  ϕp  ϕm m c þ m g C g ¼ 1  ϕp  ϕm mc QA0 eRT þ N dt dt

 dxp 4  πr 3c Co H vap þ n H 3 dt p

ð4:51Þ

ϕ m

P In Eq. 4.50, n ¼ Mp p t and C Ag ¼ RT . ϕp is the pyrite content in the coal, P is the standard atmospheric pressure, and Hp is the heat generated in the pyrite oxidation. The heat production of the oxidation of pyrites has been studied by Parr and Kressman (1910). The reaction could generally be presented by the following equation:

2FeS2 þ 7O2 þ 2H2 O ¼ 2FeSO4 þ 2H2 SO4 þ 64, 200 cal

4.4.2

ð4:52Þ

Modeling Results and Discussions

The ordinary differential equation, Eq. 4.51, was solved using the fourth-order Runge-Kutta method with the fixed parameters listed in Table 4.4 to obtain the relationship between temperature variation and time with initial condition, T ¼ Tinitial at t ¼ 0. Moisture content, volatile matter, fixed carbon, pyrite content in weight percent, and total mass of the coal are independent variables in the model and can be changed as input to perform the self-heating simulation. This model is considered to be the first theoretical description that facilitates adiabatic test to generate a complete selfheating curve using coal quality test data as input parameters which can be easily obtained through proximate analysis. Comparison of the simulation results between the previous model and the improved model is shown in Fig. 4.9. As the solid line indicates, without consideration of the effect of pyrite and moisture condensation, the self-heating curve simulated by the previous model spends more than 225 h to reach 160
C from initial temperature of 30
C. For comparison, the self-heating

152

4 Analytical Model Developed to Estimate Self-Heating Potential

Table 4.4 Fixed parameters used in the model Parameter Coal-specific heat, cc Air-specific heat, cg Standard atmospheric pressure, P Gas constant, R Pyrite density, ρp Molar mass of pyrite, Mp Mass of the gases, mg Activation energy of coal, Ec Stoichiometric number, b Heat generation per mole from pyrite oxidation, Hp Pyrite reaction rate constant, kp Radius of pyrite particle, rps Radius of coal particle, r0

Value 1.38 kJ/kgK 1 kJ/kgK 1.01  105 Pa 8.314 J/molK 5.01  103 kg/m3 120 g/mol 0.2 g 63 kJ/mol 1/7 268.6 kJ/mol 9.91  103 m/s 1.06  104 m 1.06  104 m

References Tool box

Luo and Wang (2012) Powell and Parr (1919) Clark (1966) Testing procedure

180 160 Moisture 15% Pyrite 10% Moisture 0% Pyrite 0%

Temperature (°C)

140 120 100 80 60 40 20 0

50

100

150

200

250

Time (hours)

Fig. 4.9 Comparison of the simulation results between the previous model (solid line) and the improved model (dashed line)

process of a sample with 10% of pyrite and 15% of moisture condensation with the same fixed parameters listed in Table 4.4 is simulated by the improved model. As the dash line shows in Fig. 4.9, only 20 h is spent for the sample to reach 160
C from the same initial temperature. To validate the model, two cases were considered with the adiabatic testing data from experiments conducted by Beamish et al. (2012a) and Kuchta et al. (1980) on the pyrite oxidation and moisture condensation, respectively.

4.4 Improved Model for Quantifying Pyrite Oxidation

153

Table 4.5 Coal quality analysis of the samples for modeling Sample Coal A Coal B Coal C Coal D

M (%) 12.7 11.7 10.3 11.7

VM (%) 38.0 34.8 25.1 38.0

FC (%) 41.4 37.8 35.3 46.9

Ash (%) 7.9 15.7 29.3 3.4

Sulfur (%) 4.38 7.34 17.95 0.60

Case I is used to investigate the effect of pyrite oxidation on coal self-heating rate. Coal samples with different pyrite contents, 4.38%, 7.34%, and 17.95% (Coal A, B, and C listed in Table 4.5), were selected representatively to perform the adiabatic tests starting at the ambient temperature around 25
C (Beamish et al. 2012b). In the test, 200 g samples of crushed coal ( > 0:22M  6:31 V þ 29:0 > > > > > C > < 0:13M þ 2:36 þ 25:5 V SHT ¼ C > > > 4:95M þ 2:66 þ 88:3 > V > > > > C > : 36:1M  5:29 þ 108:3 V

25 < M  35 10 < M  25 1 < M  10

ð4:55Þ

0 > ffi db v < d pffiffiffiffiffi ¼ 1:72 pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 3 εμ vb  1 þ C v > > : vb ¼ μeff μ

ð5:13Þ

where Cv is empirical constant, Cv  100, and Rε is additional term of average strain rate ε, making the model more adaptable to rapid strain and high streamline curvature Rε ¼

C μ ρη3 ð1  η=η0 Þ ε2 k 1 þ βη3

ð5:14Þ

where η0, β, and Cμ are empirical constants, η0 ¼ 4.38, β ¼ 0.012, and Cμ ¼ 0.0845.

178

5.2.2

5 Numerical Modeling of Self-Heating Event and Preventive Measures

Assumptions and Boundary Conditions

1. Assumptions In development of the numerical model related to the flow field, the gob is usually treated as a porous medium composed of coal and rock. The pores and pathways formed by the loose coal and the falling rock are irregular, and the gas flow state is also unstable. In order to simplify the analysis and fully reflect the basic feature of the issues, the following assumptions are made: (a) The permeability of gob does not change with time, that is, the gob is incompressible, and the porous medium in the gob is approximately regarded as homogeneous. (b) The gas of each component in gob is treated as an incompressible gas, and its flow is approximated as a stable flow. (c) There is no chemical reaction between components in the gas, that is, there is only convective mass transfer. (d) The working face and the boundary of gob are regarded as fixed wall. Air leakages from roof and floors and from adjacent gobs are not considered. 2. Boundary conditions The essence of finite element calculation in numerical model is to solve differential equations. Solution of differential equations obtained is mainly based on definite conditions. The expressions of these definite conditions in numerical simulation are initial conditions and boundary conditions. In development of the flow field control model, it assumes that there is no air loss or gain inside the gob. Air velocity at the inlet of intake airway depends on the air supply volume of the working face, which can be measured on site. It is called the first-type boundary condition. Since there is no air leakage through the rib of the gob and the change of air velocity at the outlet of the return airway is 0, they are all set to the second-type boundary condition. Then the boundary conditions of the flow field are 8 < vjΓ1 ¼ vðx, zÞjðx,zÞ2Γ1   : ∂p ¼0 ∂n

ð5:15Þ

n¼x,y,z2Γ2

For the gob with no external air leakage in retreat mining, the component concentration at the inlet of intake airway can be directly determined by the airflow from the working face. It belongs to the first-type boundary condition. At the outlet of the return airway, the concentration of each component is determined by calculation, which is not a fixed value, and the change to the boundary has little effect on the simulation result. Therefore, it is set as the second-type boundary condition diffusion flux equal to 0. For solid rib of the panel, the component diffusion flux has been set to 0 in the basic assumption, so it is the second-type boundary condition. The concentration field boundary condition of the component is

5.2 Numerical Modeling of Spontaneous Combustion in Ultra-Close Coal Seams

(

cjΓ1 ¼ cðx, zÞjðx,zÞ2Γ1  dc  ¼0

179

ð5:16Þ

dn n¼x,y,z2Γ2

The boundary conditions of the temperature field model are much more complicated. For the temperature field, air temperature at inlet of intake airway is equal to the temperature of supply air. It is the first type boundary condition. The outlet of return airway is treated as the second type boundary condition.  8  < t g Γ1 ¼ t g ðx, zÞðx,yÞ2Γ1  : dtg  ¼0 dn

ð5:17Þ

n¼x,y,z2Γ2

The heat transfer in the caving space of the gob is not limited to the actual boundary of the gob. Heat exchange circulates among roof and floor of the gob, solid rib of the panel, and the caving rock in the gob from time to time. Therefore, when the boundary temperature and the heat flux cannot be determined, the actual boundary of the temperature field needs to be reasonably expanded until the region where the temperature change is not affected by the mining activity. Heat flux at the boundary of temperature field determined through this way is equal to 0. Accordingly, the upper and lower boundaries of the temperature field in gob are expended by 20 m, respectively, when fully considering the thickness of solid rib of the panel. The temperature at the final boundary is approximately equal to the original temperature of the rock, which is the first-type boundary condition: t s jΓ1 ¼ t gu

ð5:18Þ

where tgu is original temperature of surrounding rocks, K.

5.2.3

Geometric Model and Parameters

The developed geometric model is to simulate the spontaneous combustion in ultraclose coal seam. In this model, the upper and lower coal seam is very close to each other with only an interlay (thickness of 1 m) between them. The upper coal seam has been mined out. Intake and return entries of upper and lower longwall panels are in the same position. In the upper gob area, the residual coal thickness is 0.5–1.2 m with average thickness of 0.8 m. With support of recovery room and solid coal off the intake and return entries, an O-shaped low-stress zone with large porosity after caving is formed in the upper gob area. When the lower face retreats, if there are air pathways formed by the cracks connected the upper and lower gobs, air can flow into the lower gob through the loose medium. In addition, according to experience, the area where seepage occurs is mainly between intake and return airways in upper gob

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5 Numerical Modeling of Self-Heating Event and Preventive Measures

Air quantity: 350 m3/min Cross section: 9.6 m2 Velocity: 0.61 m/s O2: 20.96% CO2: 0.04% Residue coal thicknesses: 0.6-1.2 m @ upper gob 1.8-3.5 m @ lower gob

400m

Z X

Gobs

Upper and lower gob areas, 25 m

Y

Gob above & Coal seam below Return

Upper layer gob area, 19 m

114m Rock interlayer, 1 m Lower unextracted coal seam, 5 m

Intake

Fig. 5.1 Geometric model of ultra-close coal seam for CFD modeling

area, 20 m height away from the bottom of the lower coal seam. In the horizontal direction, due to the pressure on the lower coal seam is similar in each stage when face retreats, the factors affecting spontaneous combustion such as the void ratio and seepage resistance in the upper gob will not change too much. Therefore, considering the risk of spontaneous combustion near the recovery room in the upper gob and the calculation capability, take the lower working face retreats to 200 m away from the recovery room as the model basis as shown in Fig. 5.1. Based on the previous analysis, the dimension of the geometric model of the longwall panel is determined as follows: width of the panel is 114 m. The length of upper and lower gob areas is set to 200 m considering the suffocation zone in the gob. The height of the model is referenced to the height of the caving zone in the lower coal seam, 25 m. The height of the upper gob is 19 m. The height of the lower coal seam is 5 m. There is an interlayer of rock with thickness of 1 m between them. The physical model is shown in Fig. 5.1. According to the actual air supply volume of 350 m3/min for the working face and the entries cross-sectional area of 9.6 m2, the inlet of intake airway is set as the velocity inlet with air velocity of 0.61 m/s. Since the standard U-shaped ventilation type is used, the outlet of the return airway is defined as a free-flow outlet. The oxygen concentration in the air inlet is 20.96%, and the carbon dioxide concentration is 0.04%. The solid rib of gob is considered to be an airtight and adiabatic wall. 1. Exothermic intensity of spontaneous combustion

5.2 Numerical Modeling of Spontaneous Combustion in Ultra-Close Coal Seams

181

When the air passes through the caving zone in the gob, the oxygen concentration gradually decreases. This is mainly due to the oxygen consumption in terms of adsorption and oxidation by coal and dilution by other gases emission. The former is dominant in gob. The main factors affecting oxygen consumption in spontaneous combustion process are coal itself and its surrounding environment where the coal exists. Based on the research findings, the total oxygen consumption can be determined by 8    > < V O ¼ CO2 V T 1  α1 ln d þ α2 ½1  exp ðβðε  1ÞÞ 2 C0 O2 d0 > : V T ¼ γ eb 0 T 0 O2

ð5:19Þ

where V O2 is oxygen consumption rate per unit volume of residual coal, mol/m3; V TO2 is oxygen consumption rate of coal sample under sufficient oxygen supply test conditions, mol/m3; C02 is oxygen concentration in environment, %; C0 is oxygen concentration in air, equal to 20.96%; T is environment temperature,
C; D is average particle size of coal, m; d0 is reference particle size in test, m; ε is percentage of rock in coal, %; and γ 0, b0, α1, α2, and β are parameters determined by test. In spontaneous combustion, heat is generated from physical adsorption between coal and oxygen. Subsequently, chemical reaction with oxygen occurred with gases such as CO and CO2 and heat produced. According to the theory of chemical kinetics and chemical equilibrium, the chemisorption heat of coal to oxygen is 58.8 kJ/mol. The standard heat of formation of CO and CO2 by oxidation at normal temperature and pressure is 110.59 kJ/mol and 393.77 kJ/mol, respectively. It is assumed that except the oxygen consumed to produce CO and CO2, the rest are all consumed by chemical adsorption. Then exothermic intensity of coal can be calculated by h i h
i  1 qðT Þ ¼ qa V To2  V Tco  V Tco2 þ V Tco h0298 co þ Δh0co 2 h
i  þ V Tco2 h0298 co2 þ Δh0co2

ð5:20Þ

where q(T ) is exothermic intensity per unit volume of coal, kJ/(m3s); qa is chemical adsorption heat of oxygen in coal, equal to 58.8 kJ/mol; V to2 is oxygen consumption rate at ambient temperature t, mol/s; V tco is generation rate of CO, mol/s; V tco2 is
 generation rate of CO2, mol/s; h0298 co is generating heat of CO under standard
 conditions, kJ/mol, equal to 110.59 kJ/mol; h0298 co2 is generating heat of CO2 under standard conditions, kJ/mol, equal to 393.77 kJ/mol; and Δh0co and Δh0co2 are difference between generating heat and standard generated heat of CO and CO2 at standard atmospheric pressure when temperature is T, kJ/mol. In the same way, the effect of oxygen consumption can be simplified to a fixed value, and then the actual oxygen consumption and exothermic intensity of the coal are

182

5 Numerical Modeling of Self-Heating Event and Preventive Measures

8 CO > < V O2 ¼ 2 kd k ε V TO2 C0 > : QðT Þ ¼ C O2 kd kε qðT Þ C0

ð5:21Þ

where kd is influential coefficient of particle size and kε is influential coefficient of rock percentage. 2. Porosity in the gob The air leakage and its distribution in the gob play an important role in oxygen supply and heat accumulation. Porosity is the key parameter affecting the air leakage and its distribution in the gob. It is affected by fragmentation and compaction of the falling rock. The porosity of porous medium in gob can be calculated by fragmentation coefficient of the caving coal: γ ¼1

1 K

ð5:22Þ

The fragmentation coefficient can be determined by K ðx,yÞ ¼ K min þ ðK max  K min Þ  ð1  exp ðm0 d 0  exp ðξm1 ðd1 þ φÞÞÞÞ

ð5:23Þ

where K(x,y) is fragmentation coefficient in gob; Kmax is initial fragmentation coefficient; Kmin is fragmentation coefficient after compaction; m0 and m1 are decreasing rate of ribs and working face, m1; d0 and d1 are distance of point (x,y) off boundaries of ribs and face; φ ¼ d0/30 is adjusting coefficient; and ξ is adjusting coefficient for controlling distribution pattern of the model. When m1 ¼ 0.036 8, m0 ¼ 0.268, and ξ ¼ 0.233, the fragmentation coefficient distribution of caving rock in gob is obtained as shown in Fig. 5.2. Based on Eqs. 5.21 and 5.22, the porosity of upper and lower caving zones in gob are determined as shown in Fig. 5.3. 3. Thickness of residual coal The amount of coal left in the gob is positively correlated with the risk of spontaneous combustion. The more the amount of coal left, the greater the risk of spontaneous combustion in the gob. The amount of residual coal can be expressed by the thickness of the coal, which is determined by
 H 1 ¼ M 1 þ ðM  M 1 Þ  exp a  Dy

ð5:24Þ

where H1 is thickness of the residual coal, m; M is thickness of coal seam, m; M1 is thickness of residual coal in center of gob, m; a is adjusting coefficient for residual coal distribution; and Dy is distance of point (x,y) off the rib of entry.

5.2 Numerical Modeling of Spontaneous Combustion in Ultra-Close Coal Seams

183

Fig. 5.2 Fragmentation coefficient distribution of caving rock in gob

Fig. 5.3 Porosity of upper and lower caving zones in gob of ultra-close coal seam

According to Eq. 5.23, the thickness of residual coal varies with the distance off the rib of entry which is demonstrated as shown in Fig. 5.4.

5.2.4

Modeling Results and Discussions

1. Analysis of airflow field The airflow field of working face is the key factor affecting the spontaneous combustion of coal. In the vicinity of entries and recovery room in upper gob area, due to the support of abutment wall and the cantilever beam structure formed by caving of immediate roof and main roof, compactness of collapsed rock in this area

184

5 Numerical Modeling of Self-Heating Event and Preventive Measures

Fig. 5.4 Thickness distribution of residual coal in gob

Gobs Gob above & Coal seam below Return

Intake

Fig. 5.5 Airflow field of gobs in upper and lower coal seam

is low. Connected air leakage pathway is formed along the surrounding of the gob. There is a circle-shape crack zone close to intake and return airways around working face in the lower coal seam, forming connecting channels and fractures between airways and upper gob area. For the mined-out area in the lower coal seam, the upper and lower gobs are connected, presenting a more complicated situation for airflow. By solving the developed model, three-dimensional airflow field of gobs in the upper and lower coal seam and air velocity in lower airways at level of z ¼ 1.2 m are obtained as shown in Figs. 5.5 and 5.6. From the airflow field, it can be seen when the air passes airways and working face; under the influence of pressure, a small amount of air leakage enters the caving zone in the upper gob through the fissure at the top of intake airway of the lower longwall panel. For the areas closed to recovery room, the air also enters the upper gob area from lower intake airway and then flows into the return airway through the rock fissures. Meanwhile, some of the air leakage enters the working space from the lower return airway. In the lower gob, based on the center line of working face as

5.2 Numerical Modeling of Spontaneous Combustion in Ultra-Close Coal Seams

185

Fig. 5.6 Simulation results of the model involving oxygen concentration at levels of z ¼ 6.5 m and z ¼ 1.0 m, air velocity at level of z ¼ 1.0 m, temperature at levels of z ¼ 6.5 m and z ¼ 1.0 m

symmetry axis, the air leakage appears a standard one-source-one-sink distribution. The air enters the gob from intake airway and flows out to the return side, most through the upper corner. Affected area by air leakage almost covers the entire gob. From the distribution of the air velocity field at the level of z ¼ 1.2 m, it can be seen that the air mainly flows in intake and return airways and the space of working face. The velocity continuously decreases before reaching the middle part of the panel. When the air passing through the midline of the working face, the velocity gradually rises. It finally flows out from the outlet of the return airway. The velocity distribution in airways and the air circulation from intake to return in the three-dimensional airflow field confirm each other. It can be seen that the fissures in roof at the top of intake and return airways of the lower panel are the main pathways for the air flowing into the upper gob from the lower panel. Under the influence of pressure and compactness of carving rock, the air quantity close to recovery room reaches the highest level. Without any air leakage control measures, the air will leak until the panel is mined out. In other words, air leakage duration in this area is equivalent to the entire panel’s retreat time, greatly promoting the selfheating risk of coal in this area. 2. Analysis of high-risk zone in gob Coexistence of loose coal and oxygen from air supply impose a great potential for spontaneous ignition. In favorable conditions for heat storage, the heat generated by oxidation of residual coal causes the ambient temperature to rise continuously until spontaneous combustion of coal occurs. Therefore, air leakage and oxygen supply

186

5 Numerical Modeling of Self-Heating Event and Preventive Measures

are one of the necessary conditions for self-ignition of coal. Temperature rise, caused by heat release from residual coal oxidation, is an important indicator for identifying spontaneous combustion behavior of coal. During the upper coal seam extraction, the residual coal experienced primary oxidation. Temperature of the residual coal has increased to some extent. During the recovery of the lower coal seam, the air leakage flowed into the upper gob brings a secondary oxidation to the residual coal. These twice oxidized coals fall into the lower gob during longwall panel retreat. It not only increases the thickness of the coal in lower gob but accelerates the oxidation, resulting in a great risk of spontaneous combustion for the lower coal seam extraction. According to the characteristics of ultra-close coal seam mining, considering the thickness and relative position of the residual coal in the upper and lower gobs, the oxygen concentration field and temperature field at levels of z ¼ 6.5 m and z ¼ 1.0 m are analyzed, respectively. (a) Analysis of self-heating risk in upper gob Figure 5.6 shows the oxygen concentration field at the level of z ¼ 6.5 m. It can be seen that the high oxygen concentration area in the upper gob presents a “Γ” shape. Oxygen concentration in the upper part of intake airway of the longwall panel reaches the highest level and that around recovery room is slightly lower than it. Oxygen concentration gradually decreases from intake airway to return side. Since the upper part of return airway is the main exit of air, oxygen with high concentration only appears in the upper part of airway closed to the recovery room. It is generally believed that the lower limit of the oxygen concentration to inhibit selfheating of coal is 5%, which is used as indicator to study the oxidation range in upper gob. In dissipation zone, oxygen concentration is greater than 18%, less than 5% for the suffocation zone, and between 5% and 18% for the oxidation zone. Located between recovery room and working face, the width of the oxidation zone close to intake side is about 200 m, in the middle of the gob is about 20 m, and close to the return side is 52 m. Temperature field of coal at the level of z ¼ 6.5 m is shown in Fig. 5.6. The hightemperature area of the upper gob with the temperature of residual coal exceeding 313 K appears near the recovery room with width of 30–80 m. It gradually narrows from intake to return. The center of high temperature appears on the intake side of the recovery room with the maximum temperature of 323 K. Based on the analysis above, area with high oxygen concentration and high temperature in upper gob are mainly located in the vicinity of the recovery room and intake airway. There is a large amount of loose residual coal near the recovery room. When the panel is mined out, it will take a long time to recover the shield for next panel retreat and seal the gob. The coal will expose to air within the same time duration, which increasing the risk of self-heating. In addition, with the highest ventilation pressure difference, the upper recovery room is located between the inlet of intake and outlet of return airway of the lower panel. It will also be affected by air leakage from lower panel ventilation for quite a while from the time of entry development to the time of entire panel mined out and gob seals. Air leakage

5.2 Numerical Modeling of Spontaneous Combustion in Ultra-Close Coal Seams

187

location is fixed, and the oxygen supply is sufficient. It is the key area in the upper gob for implementing preventive measures. (b) Analysis of self-heating risk in lower gob During the lower coal seam retreat, the broken coal in the upper gob falls into the mined-out area of the lower panel. It enhances the amount of residual coal left in the lower gob and chances of secondary oxidation, increasing the risk of self-heating accidents. Oxygen concentration field at the level of z ¼ 1.0 m is shown in Fig. 6.5. The oxidation zone is defined based on the oxygen concentration of 5–18%. The distribution of three zones in the lower gob is dissipation zone locates at 0–30 m. Oxidation zone is at 24–53 m, and behind 73 m away from working face will be the suffocation zone. Temperature field at the level of z ¼ 1 m is shown in Fig. 5.6. The distribution of high-temperature area of residual coal in the lower gob is basically consistent with the variation trend of oxidation zone. The peak of high temperature (333 K) appears in the oxidation zone located in center part of the gob. In the dissipation zone, when the air from the bottom of intake side of the panel flows through the floating coal, due to low-temperature oxidation, the oxygen in air is continuously consumed. The heat generated moves with the air to the deeper part of gob area and gradually accumulates in return side, resulting in temperature rise. In the oxidation zone, air velocity decreases, which is not enough to take away the heat generated by the oxidation of the residual coal. The temperature rises faster and finally reaches the highest level. After entering the suffocation zone, oxygen concentration reduces rapidly, and the oxidation of residual coal is basically stopped. Heat brought by the leakage air is also limited. Therefore, temperature gradually decreases until equals to the temperature of original rock in deeper part of the gob. The width of the oxidation zone in the lower gob does not change too much from intake to return. However, due to the ultra-close coal seam mining method, the thickness of residual coal in the gob is up to 3.0 m. The lower gob has a large amount of air leakage, and the loose coal provides good conditions for heat storage. The maximum temperature of the residual coal is about 10 K higher than that in the upper gob, reaching more than 333 K. Risk of spontaneous combustion is significantly higher in this area.

5.2.5

Spontaneous Combustion Affected by Ventilation Type

In the high gassy mine, “U”-type ventilation method often causes the gas at working face or in the upper corner to exceed the limit. “U+L”-type and “Y”-type ventilation method can better solve the gas accumulation issue in the upper corner and the limitexceeding problem in return airway. However, these two ventilation types tend to increase the risk of spontaneous combustion by enhancing the amount of air leakage and oxygen concentration in gob. In this section, numerical simulation is carried out

188

5 Numerical Modeling of Self-Heating Event and Preventive Measures U Type

Return

U+L Type

Return

Return Intake (a)

Y Type

Intake (b)

Intake (c)

Fig. 5.7 Airflow fields simulated by numerical modeling for different types of ventilation system (a) U type, (b) U+L type and (c) Y type

Fig. 5.8 Simulation results of methane concentration, oxygen concentration, and temperature in longwall gob areas with U, U+L, Y types of ventilation method

to investigate self-heating behavior in gob with three ventilation modes. Variation of “three zones” and temperature field are quantitatively analyzed. It could provide references for ventilation design of new mine development and targeted prevention measures to mitigate self-heating issues. 1. U-type ventilation system The “U”-type ventilation method is simple in airflow system, and air leakage is less than the other types. After longwall panel is extracted, gob is usually sealed along its boundary. It is likely to cause gas accumulation in the upper corner when using this ventilation mode. Three-dimensional flow field, gas concentration field, range of “three zones,” and temperature field of residual coal are studied using the “U”-type ventilation method as shown in Figs. 5.7a and 5.8.

5.2 Numerical Modeling of Spontaneous Combustion in Ultra-Close Coal Seams

(a) Width of oxidation range (m)

Fig. 5.9 Variation of (a) width of oxidation range with distance off the intake airway and (b) width of high temperature range with distance off the intake airway for U-type, U+L-type, and Y-type ventilation systems

189

120 Y Type U+L Type U Type

100 80 60 40 20 -20

Width of high temperature range (m)

(b)

0

20 40 60 80 100 120 Distance off the intake airway (m)

350

140

U Type U+L Type Y Type

300 250 200 150 100 50 -20

0

20

40

60

80

100

120

140

Distance off the intake airway (m)

From Fig. 5.7a, it can be seen that regarding the center of working face as axis, the trajectory of the airflow in gob is symmetrically distributed, showing a typical “one source and one sink” airflow pattern. The area filled with high methane concentration in gob with U-type ventilation system is obviously greater than other types as shown in Fig. 5.8. Methane exceeds the lower limit in upper corner, seriously threatening safe production in working face. Width of oxidation zone is 52 m close to intake side, 43 m in the middle, and 33.7 m close to return side as shown in Fig. 5.9a. Compared with the other two ventilation systems, high-temperature area is much closer to the working face, and the range is less. High-temperature area locates at intake side in the gob 50–60 m away from the working face. It imposes high risk of spontaneous combustion.

190

5 Numerical Modeling of Self-Heating Event and Preventive Measures

2. U+L-type ventilation system In the “U+L”-type ventilation system, the entry “L” for methane drainage is arranged outside of the return airway, connected to the gob through crosscuts. Fresh air moves to the back side of working face, taking methane to the “L” shape entry. The gas flowing through the area is discharged. Three-dimensional flow field, gas concentration field, range of “three zones,” and temperature field of residual coal are studied using the “U+L”-type ventilation method as shown in Figs. 5.7b and 5.8. From Fig. 5.7b, it can be seen that the air distribution is not symmetrical. Some of the air enters the return airway, and some moves to the methane drainage airway, presenting a “one source and two sinks” airflow pattern. In the airflow field diagram, the air moves in two ways. One goes to the return airway driven by the pressure difference between intake and return. The other flows to deeper area in gob driven by the negative pressure for methane drainage and exhausted through “L” shape airway. Methane filled in large area could be exhausted through the methane drainage airway. It ensures the methane will not exceed the limit in the upper corner area. It also reduces methane concentration in the entire gob area as shown in Fig. 5.8. Although the gas concentration in the gob and in the upper corner are reduced, the crosscut as the exhaust port locates deep in the gob. It brings more oxygen to the gob, increasing the risks of spontaneous combustion. High-temperature region will appear in the airflow pathway between intake and exhaust port. It is close to the intake side with 50–70 m away from the working face and locates inside the oxidation zone. The width of high temperature range is shown in Fig. 5.9b. Compared with the U-type ventilation system, the high-temperature area of the residual coal is deeper into the gob, and range also becomes greater. It is further indicated that the residual coal is more prone to spontaneously combust using U+L-type ventilation method. 3. Y-type ventilation system The “Y”-type ventilation system mainly has two sub-types: one-in-two and twoin-one types. In most cases, two-in-one ventilation system is adopted, which consists of two intake airways for conveyer belt and material transportation and one return airway. In this ventilation mode, the high concentration gas generated during coal extraction can be diluted by fresh air from the one intake airways. Gas in the upper corner is taken away by the other intake airway. Gas in gob will gradually enters the return airway. However, the two-in-one “Y”-type ventilation will increase velocity of the air that enters into the gob. Oxygen concentration in the gob will become higher accordingly, promoting the risk of spontaneous combustion. Threedimensional flow field, gas concentration field, range of “three zones,” and temperature field of residual coal are studied using the “Y”-type ventilation method as shown in Figs. 5.7c and 5.8. Since both head gate and tail gate of the panel are used as intakes, airflow is most concentrated on the upper corner of T-junctions. Driven by pressure difference, air from the intakes, called “two sources,” leaks into the gob and will merge into the return airway, called “one sink.”

5.3 Numerical Modeling of Grouting to Mitigate Residual Coal Oxidation in Gob

191

Methane concentration is controlled well below the lower limit in the upper corner as shown in Fig. 5.8. Air leakage in gob is obvious. Widths of oxidation zone near upper and lower intakes are 91 m and 104 m and 80 m in the middle as shown in Fig. 5.9a. A strip-shaped region with high oxygen concentration is formed near the return airway. Temperature of a broad area in the gob increases. Hightemperature locations appear on the upper and lower sides of the intakes closed to the working face. The location near upper intake with high potential of self-heating is 35–55 m away from the working face and for the location near lower intake is 62–90 m away from the working surface. In summary, for gas control capability, “Y” type > “U+L” type > “U” type. Although gas accumulation in the upper corner and exceed-limit issue in return airway are under control, the risk of spontaneous combustion of residual coal also increases accordingly. Therefore, Y-type ventilation is suitable for the case that residual coal left in gob is less and risk of spontaneous combustion is low. When double entry is adopted in panel development and integrity of the isolated coal pillar is maintained and when self-ignition risk of isolated coal pillar and residual coal in gob is controllable, U+L ventilation can be used to solve gas problem. When there is a large amount of residual coal left in gob and when solving the problem of coal spontaneous combustion has become a top priority, U-type ventilation system should be considered to use. Admittedly, combined with other gas drainage techniques (such as the corner pipe, roof entry drainage), numerical simulation and on-site observation should be used comprehensively to control gas emission and self-heating hazards.

5.3

Numerical Modeling of Grouting to Mitigate Residual Coal Oxidation in Gob

The grouting technology in major mining fields in China was originally developed for grouting and sealing of coal mine shafts in the early 1950s. After 1980, the research and application of grouting technology experienced a significant development in grouting materials, construction technology, equipment, automatic control, and inspection methods, making the grouting technology applied more extensively. However, due to the complicated geological conditions, difficulties in monitoring of grouting injection, and limitations in testing approaches, some critical grouting parameters cannot be determined. Especially the determination of grouting position in gob with different coal seam angles is still based on empirical and analogy methods. The prediction by grouting design is quite different from the actual grouting result. Therefore, in this section, the reasonable position of grouting in gob with different coal seam angles is studied by numerical simulation.

192

5.3.1

5 Numerical Modeling of Self-Heating Event and Preventive Measures

Numerical Model

The flow of the slurry in the gob belongs to the category of multiphase flow, so the Euler multiphase flow model is selected for the CFD simulation. In the single-phase flow model, only one set of conservation equations of momentum and continuity is solved. In order to transfer from the single-phase flow model to the multiphase one, an additional conservation equation should be introduced. The original settings should be modified during the introduction of additional conservation equations. This modification involves the introduction of multiphase volume fractions α1, α2, . . ., αn and the mechanism of momentum exchange between phases. The description of the multiphase flow as a continuous interpenetration constitutes the concept of phase volume fraction, denoted here as αq. The volume fraction represents the space occupied by each phase, which satisfies the law of conservation of mass and momentum by itself. The conservation equation can be obtained using the local transient balance of the average of each phase or using a hybrid theory approach. The volume Vq of the q phase is defined as Z Vq ¼

αq dV

ð5:25Þ

αq ¼ 1

ð5:26Þ

V

where

n X q¼1

The effective density of the q phase is ρbq ¼ αq ρq

ð5:27Þ

where ρq is the physical density of the q phase. Based on multiphase flow mass conservation, the continuous equation of the q phase is 
 X ∂
αq ρq þ ∇  αq ρq vq ¼ mpq ∂t p¼1 n

ð5:28Þ

where vq is the velocity of the q phase and mpq represents the mass transfer from the pth phase to the q phase. Obtained from the mass conservation equation mpq ¼ mqp

ð5:29Þ

mpq ¼ 0

ð5:30Þ

Based on multiphase flow conservation, the momentum balance of the q phase produces the following equation

5.3 Numerical Modeling of Grouting to Mitigate Residual Coal Oxidation in Gob


 ∂
αq ρq vq þ ∇  αq ρq vq vq ∂t n
X 
 Rpq þ mpq vpq þ αq ρq F q þ F lift,q þ F Vm,q ¼ αq ∇p þ ∇  τq þ

193

ð5:31Þ

p¼1

where τq is the pressure strain tensor of the qth phase and vpq is the velocity between phases, and defined as if mpq > 0 (the mass of phase p is passed to phase q), vpq ¼ vp; if mpq < 0 (the mass of phase q is passed to phase p), vpq ¼ vq and vpq ¼ vqp.     2 τq ¼ αq μq ∇vq þ ∇vTq þ αq λq  μq ∇  vq I 3

ð5:32Þ

where μq and λq are the shear and bulk viscosities of the q phase, Fq is the external volume force, Flift, q is the lift force, FVm, q is the virtual mass force, Rpq is the interaction force between the phases, and p is the pressure sharing with phases. There should be a suitable expression for Eq. 5.31 for interphase interaction Rpq closure. This force is dependent on friction, pressure, cohesion, and other effects and is subject to the conditions of Rpq ¼ Rqp and Rpq ¼ 0. The following interaction terms are used: n X p¼1

Rpq ¼

n X


 K pq vp  vq

ð5:33Þ

p¼1

where Kpq and Kqp (Kpq ¼ Kqp) are phase-to-phase momentum exchange coefficients.

5.3.2

Geometric Model and Parameters

The actual dimensions of the panel, gob, and grouting pipe are shown in Table 5.1, and the three-dimensional physical model is shown in Fig. 5.10. The grouting slurry is mainly composed of fly ash and belongs to non-Newtonian body. During the grouting process, the properties of the slurry change with time which is the time-varying fluid. The solution area is set as follows: The non-steady fluid is used; the grouting port is set as velocity inlet with velocity of 0.56 m/s; the gob is defined as the full jet outlet (outflow); the Euler model is selected as the multiphase flow model; and the standard k-epsilon model is used as the turbulent model in FLUENT. The gob is set as a porous medium, and the Table 5.1 Related parameters

Model Grouting pipe Gob

Length (m)  Width (m)  Height (m) 3  0.15  0.15 200  114  3

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5 Numerical Modeling of Self-Heating Event and Preventive Measures

200 m 114 m

Intake 3m

Return

58 m68 m 28 m 38 m 48 m

Fig. 5.10 Three-dimensional physical model

porosity, viscous drag, and inertial resistance are compiled into FLUENT in the form of UDF function to solve the equations.

5.3.3

Modeling Results and Discussions

In the process of grouting fly ash mortar to prevent spontaneous combustion, it mainly plays the mitigating role in preventing coal-oxygen contact by the pulverized mortar, the effect of heat absorption and cooling, and accelerating the coal-rock cementation to increase the airtightness. Therefore, the migration and diffusion path of the fly ash into the gob and coverage fraction to the broken coal can be used as the indicating index to evaluate the prevention effect of the grouting. In the simulation, the grouting inclination angle is set to 15
, 20
, 25
, 30
, 35
, and 40
, and the grouting position is at 28 m, 38 m, 48 m, 58 m, and 68 m away from the working face on the return side of the gob.

5.3.3.1

Grouting Spread Behavior Based on Different Seam Angles

1. Analysis of slurry diffusion with coal seam angle at 15
From Fig. 5.11 it can be observed that the slurry diffuses from the grouting nozzle to the surroundings in the gob during the injecting process with the grouting angle of 15
. As time goes by, after injecting for 6 h, the slurry diffused to some extent at different injection locations, and the coverage of the slurry in the center part is over 95%. The proportion of the coverage on the residual coal gradually decreases from the center to both sides. After the slurry is injected for 6 h at 28 m, the slurry flows to the working surface, indicating that the slurry is running and could not cover the oxidation zone in the gob. The coverage in the panel is about 0.2. The same slurry running scenario happens when the slurry is injected at 38 m after 6 h. Only part of the oxidation zone is covered with coverage of about 0.05. After slurry is injected at 48 m, 58 m, and 68 m for 6 h. There is no potential risk of slurry running into the face, and the slurry diffusion is similar to an ellipsoid. As injection progresses, when

5.3 Numerical Modeling of Grouting to Mitigate Residual Coal Oxidation in Gob

195

Fig. 5.11 Slurry mitigation and diffusion behavior with different injecting position and coal same angles

the slurry reaches a certain depth along the inclined direction of the panel, longitudinal flow gradually becomes slow, and the lateral diffusion gradually increases (longitudinal flow increases initially, followed by lateral flow subsequently). As the gob is compacted in deep area, the porosity becomes increasingly smaller, and as the distance between the injection position and the working face increases, the diffusion area of the slurry decreases. 2. Analysis of slurry diffusion with coal seam angle at 20
When the slurry has been injected for 6 h with grouting angle of 20
, it can be seen the slurry diffuses at different injection locations with coverage more than 95% as shown in Fig. 5.11. Compared to case (1), the trend of slurry injected at different positions flowing to the working face is not obvious. But injected at 28 m for 6 h, the slurry runs into the working face. The oxidation zone of the gob could not be covered with coverage about 0.1. The coverage at 38 m is about 0.025. With low coverage of the residual coal and slurry running, the oxidation zone was not completely wrapped. Injecting at 48 m, 58 m, and 68 m, the slurry can well cover the oxidation zone, isolate oxygen, and cool down the temperature, and there is no potential risk of slurry running into the face. When the slurry reaches a certain depth along the inclined direction of the panel, longitudinal flow gradually becomes slow, the lateral diffusion gradually increases, and the diffusion area in this condition is less than any other injecting conditions. 3. Analysis of slurry diffusion with coal seam angle at 25
Compared to the case (1) and (2), the tendency of slurry injecting at different positions flowing to the working surface is much lower. Injected at 28 m for 6 h, only a small amount of slurry runs into the working surface. A great amount of slurry covers dissipation zone, but it could not cover the oxidation zone. At 38 m, no slurry flows into the working surface, and part of the oxidation zone is covered in this

196

5 Numerical Modeling of Self-Heating Event and Preventive Measures

condition. After the slurry is injected at 48 m, 58 m, and 68 m for 6 h, there was no hidden danger for slurry running into the working face. At 48 m and 58 m, most of the oxidation zone is covered. The slurry spread approximately in an ellipsoid when injected at 58 m and 68 m. Longitudinal flow increases initially, followed by lateral flow increasing subsequently. 4. Analysis of slurry diffusion with coal seam angle at 30
Compared to the case (1), (2), and (3), the slurry injected at different positions will not flow to the working face but flow smoothly to the gob on the inlet side. There is no hidden risk of slurry running. After the slurry is injected from 28 m to 58 m for 6 h, the area of slurry covering the oxidation zone is continuously expanding. At 68 m, the slurry covers part of the oxidation zone. 5. Analysis of slurry diffusion with coal seam angle at 35
The proportion of the coverage for the residual coal from the center area to both sides gradually decreases. There is no slurry running potential injected at different positions. Compared with the case (1), (2), (3), and (4), the slurry diffusion is more sufficient, and it is more favorable to cover the oxidation zone in this condition. After the slurry is injected from 28 m to 58 m for 6 h, the area of slurry covering the oxidation zone is continuously expanding. Injected at 68 m, the slurry could only cover part of the oxidation zone. 6. Analysis of slurry diffusion with coal seam angle at 40
Injecting slurry at different positions will not flow to the working face. Compared with the previous injecting conditions, the longitudinal flow tends to be smooth with the injection of the slurry, and the lateral diffusion tendency is gradually reduced. After the slurry is injected at 28–58 m for 6 h, the area of slurry covering the oxidation zone is continuously expanded. Injected at 68 m for 6 h, most of the slurry flows into the suffocation zone, which could not inhibit the spontaneous combustion in the gob.

5.3.3.2

Determination of the Optimal Grouting Plan

In summary, the distance between each grouting point and the working face should not be too large or too small. If it is too large, the slurry cannot be injected by blocking from the falling rocks compacted in the gob. If it is too small, the slurry will easily flow into the working space. The distance of 7 m away from the working face is treated as a safe upper limit as shown in Fig. 5.12a. When the slurry spread close to working face shorter than this distance, there will be a potential risk of slurry running. When the grouting angle is 15
, the safe grouting position which will not exceed the upper limit is from 46 to 68 m; when the grouting angle is 20
, the safe grouting position is within 46–68 m; grouting at angle of 25
, the safe grouting position is 38–68 m; when the grouting angle is 30
, the safe grouting position is 33–68 m; at 35
, the position is 31–68 m; at

5.3 Numerical Modeling of Grouting to Mitigate Residual Coal Oxidation in Gob

(a)

30.8

50

Distance off the face (m)

Fig. 5.12 The safe upper limit (a) 7 m away from the working face and (b) 114 m away from the return airway for slurry injection

38

197

44

40 30 15º 20º 25º 30º 35º 40º

20 10 7 0 20

30 33.5

40

46

50

60

70

60

70

Injection position (m)

(b)

32.5

Distance off return airway (m)

120

41.5

52

40 44

50 53

114 110 100 90

15º 20º 25º 30º 35º 40º

80 70 60 20

30

Injection position (m)

40
, the position is 28–68 m. Distance of 114 m away from return airway is set as the lower limit as shown in Fig. 5.12b. When the slurry spread could not reach this lower limit, the oxidation zone could not be covered completely by the slurry. Grouting at 15
, the favorable position is 28–38 m; when the grouting angle is 20
, the grouting position is 28–46 m; at 25
, the grouting position is 28–48 m; at 30
, the position is 28–52 m; at 35
, the grouting position is 28–55 m; at 40
, the grouting position is 28–68 m. Combining the safe upper limit and lower limit, the optimal grouting position is not available when the grouting angle is 15
. Grouting at 46 m could be the relatively optimal position in this condition. When grouting at angle of 20
, the best grouting position is 44–46 m. When the grouting angle is 25
, the optimal grouting position is 38–48 m. When the grouting is 30
, the optimal grouting position is at 33–52 m.

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5 Numerical Modeling of Self-Heating Event and Preventive Measures

154 m 300 m

Gob

N2 injection @ Return

17.5 m

50 m 40 m 30 m 20 m 10 m

Intake

Fig. 5.13 Geometric model for simulation of nitrogen injection at different positions

When the grouting angle is 35
, the best grouting position is 31–55 m. When grouting angle is 40
, the optimal grouting position is 28–68 m.

5.4 5.4.1

Numerical Modeling of Inerting Effect of Nitrogen Injection in Gob Geometric Model and Parameters

1. Geometric model The model refers to an active panel of underground coal mine. The designed mining height is 3.0 m. Retreat longwall mining with comprehensive mechanical top coal caving method is adopted. U-type ventilation system is used with the air quantity of 450 m3/min, and the cross-sectional area is 9.6 m2. The absolute amount of gas emission is 4.54 m3/min, which does not exceed the limited value specified in the coal mine safety regulations. The height of the gob is 17.5 m. The initial collapse coefficient is 1.6, and the compaction coefficient is 1.1. According to the actual situation of the longwall panel, the size of geometric model of the gob is determined as follows: width of the panel is 154 m, length is 300 m, and the height is 17.5 m as shown in Fig. 5.13. The gas injection port is located at X ¼ 10 m, 20 m, 30 m, 40 m, and 50 m, and the injecting height is 0.5 m above the floor. The geometric model and mesh are shown in Fig. 5.13. 2. Boundary conditions The boundary condition of the gob is the inlet airway is set as velocity inlet. Considering that the air intake is 450 m3/min and the cross-sectional area of the inlet airway is 9.6 m3, then the air inlet velocity is determined as 0.781 m/s. Define the return airway as full jet outlet (outflow), and the flow rate weight is converted

5.4 Numerical Modeling of Inerting Effect of Nitrogen Injection in Gob

199

according to the actual value. The solid wall of the gob is considered to be airtight and adiabatic. Oxygen concentration in the inlet airway is 20.96% in the air, and the carbon dioxide concentration is 0.04%. Methane concentration in the inlet airway is 0, and the absolute gas emission at working face is 4.54 m3/min. Concentration of the nitrogen injected is 97%. The simulation is modeled in ICEMCFD, then calculated using FLUENT software, and finally imported into Tecplot software for post-processing. The grid is a hexahedral mesh and is locally densified with respect to the calculation area near the nitrogen injection borehole. The change of the source term of the momentum equation caused by the porous medium is automatically calculated by the FLUENT-embedded program. The oxygen concentration, gas concentration, nitrogen concentration equations, and the heat release source by floating coal oxidation are imported and compiled by user-defined functions. The above control equations are solved by the control volume method based on staggered grid. The 2nd-order center difference format is used in the convection term and the diffusion term in the discrete process, respectively. Each discrete equation is solved by a line-by-line iterative method. Each iteration line is calculated by a combination of a threediagonal matrix algorithm and a relaxation factor. The SIMPLE algorithm is used in coupling between velocity and pressure. The maximum error of the iteration is less than 104. After determining the boundary conditions of the model, the numerical solution can be used to obtain the analytical solution. Gas flow and distribution in the gob during nitrogen injection can be obtained to compare and optimize the technical parameters in the injecting technology.

5.4.2

Modeling Results and Discussions

5.4.2.1

“Three Zones” Variation Affected by Injecting Positions

The flow path of nitrogen into the gob can be divided into two parts. One flows into the working face from the gob near the lower corner, and the other flows into the deep gob. The two nitrogen flows then merge into the return air through upper corner. If the nitrogen injection port is too close to the working face, the flow path of nitrogen inside the gob will be short. Therefore, most of the nitrogen enters into the working face from the gob. It is unfavorable for controlling self-heating in middle and deep gob areas as shown in Fig. 5.14a. The mitigating efficiency of nitrogen will also be low. If the injection port is too far from the working face, the injected nitrogen will not cover the oxidation zone close to the working face. It will cause heat accumulation in local areas where has a potential of spontaneous combustion as shown in Fig. 5.14b. Therefore, the distance between the nitrogen injection port and the working face is an important parameter to ensure the prevention effect of nitrogen. It is necessary to consider both the prevention effect and the utilization efficiency of nitrogen when determining the parameter.

200

5 Numerical Modeling of Self-Heating Event and Preventive Measures

(a)

(b)

Fig. 5.14 Distribution of streamline at z ¼ 0.7 m in the gob during injection (a) at 10 m and (b) at 50 m Injection quantity Q: 540 m3/h 0.18

Injection @ 10 m

Injection @ 20 m

0.05

0.18

0.05

0.05

0.18

0.18

Injection @ 30 m

Injection @ 40 m

Injection @ 50 m

0.05

0.18

0.18

0.05

0.18

0.05

Injection quantity Q: 720 m3/h

0.05

0.18

0.18

No injection

Injection @ 10 m

No injection

Injection @ 20 m

0.05

0.18 0.05

Injection @ 40 m

0.18

0.05

0.18

Injection @ 30 m

Injection @ 50 m

Fig. 5.15 Oxygen concentration variation vs. nitrogen injection positions with injection quantities of 540 m3/h and 720 m3/h

In this section, the average thickness of the residual coal in the gob is 1.5 m. The broken coal at the level of 0.7 m (Z ¼ 0.7) is selected to study spontaneous combustion in the oxidized zone. Figure 5.15 shows the oxygen concentration fields at Z ¼ 0.7 level with nitrogen injection quantities, Q at 540 m3/h and 720 m3/h, respectively. After the nitrogen injection measures are taken with 540 m3/h and 720 m3/h injection quantities, compared with the oxygen concentration in the original gob, the boundary of the oxidation zone is changed when the injection port at X ¼ 10 m is

5.4 Numerical Modeling of Inerting Effect of Nitrogen Injection in Gob

201

opened as shown in Fig. 5.15. The lower oxygen concentration boundary moves to the deep gob, and the higher oxygen concentration boundary shifts toward the working face, greatly increasing the width of the oxidized zone. Most of the injected nitrogen flows from the shallow part of the gob to the working face and to the upper corner. The dilution effect to the oxygen in air leakage from the deep gob is limited. When X ¼ 20 m injection port is opened, the boundary of oxidation zone in deep gob is sharply reduced on the inlet side. Dilution effect on oxygen begins to appear. The higher oxygen concentration boundary of the oxidation zone from the center part of gob to the return side is basically the same as no nitrogen injection. The maximum width of the oxidation zone begins to decrease to the 1/2 of the width of the original oxidation zone. When the X ¼ 30 m injection port is opened, the dilution effect on oxygen in air leakage is fully reflected by the nitrogen injection. The oxidation zone boundary on deep gob side moves further close to the working face at the inlet side, while the change is not obvious on the return side. The overall width of the oxidation zone is reduced to 1/3 of the width of the original oxidation zone. When the injection ports at X ¼ 40 m and X ¼ 50 m are turned on, the trend of the oxidation zone boundary and the maximum width is basically the same as that at X ¼ 30 m with only slight changes. With further analyzing the oxygen concentration field in the gob, the widths of the oxidation zone on the inlet side, at the center of gob, and on the return side and the maximum width of the oxidation zone in the gob are listed in Table 5.2. According to the simulation results, when nitrogen injection is applied, there are two main effects on the prevention and control of spontaneous combustion in the gob: one is lowering the temperature of hot point and the other is affecting the width of oxidation zone. The affecting area is mainly from the intake side of the gob to the center part of the gob. Variation of the maximum width of the oxidation zone at different injection positions is shown in Fig. 5.16. From Fig. 5.16, it can be observed when the injection is conducted at position X ¼ 10, the injected nitrogen can only cover part of the broken coal in oxidation and dissipation zones. Most of the nitrogen from dissipating zone and part of the nitrogen from oxidation zone near the working face enter the return airway, while the nitrogen Table 5.2 “Three zones” variation in gob during nitrogen injection at different positions

Position No injection 10 20 30 40 50

Injection quantity at 540 m3/h Return Intake side Center side 11 31 92 16 14 12 12 11

42 42 37 34 31

63 2 2 2 2

Wmax 92

Injection quantity at 720 m3/h Return Intake side Center side 11 31 92

Wmax 92

125 64 38 35 33

15 15 11 14 13

110 48 33 31 28

46 41 32 28 25

44 2 2 2 2

202

5 Numerical Modeling of Self-Heating Event and Preventive Measures 140 Q at 540 m3/h Maximum width of oxidation zone (m)

120

Q at 720 m3/h

100

80

60

40

20 0

10

20

30

40

50

Injection position (m)

Fig. 5.16 Variation of the maximum width of the oxidation zone at different injection positions with injection quantities at 540 m3/h and 720 m3/h

passing oxidation zone in deep gob is less. Therefore, dilution effect is not obvious in this area. Due to the injection of nitrogen, oxygen consumption decreases in the gob. As a result, the width of oxidation zone increases. Starting from X ¼ 20, most of the injected nitrogen enters the oxidation zone of the gob, and the dilution effect begins to appear. The maximum width of oxidation zone is significantly reduced. When X ¼ 30, the dilution effect is fully appeared. The maximum width of the oxidation zone is reduced to about 35 m. When the injection port is further moved to the deep gob area to 40 m or 50 m, the width of the oxidation zone is not reduced significantly. Therefore, considering the inerting effect of nitrogen injection on the oxygen concentration in the gob, the reasonable injection position obtained from the graph is 30–50 m away from the working face.

5.4.2.2

“Three Zones” Variation Affected by Injecting Quantities

As one of the important parameters affecting the inerting effect, nitrogen injection quantity directly influences the dilution of oxygen and cooling of broken coal, thus further affecting the width and temperature of the oxidation zone in the gob. If the injection quantity is too small, purpose of inerting the gob cannot be achieved. If the injection quantity is too large, unnecessary resource waste will be caused, and the local nitrogen concentration close to the working face may be exceeded. Therefore, a

5.4 Numerical Modeling of Inerting Effect of Nitrogen Injection in Gob

203

Injection @ 20 m

0.05

0.18

0.05 0.18

Q: 360 m3/h

Q: 540 m3/h

0.18 0.05

0.05

0.18

Q: 720 m3/h

Q: 900 m3/h

Injection @ 30 m 0.05

0.05 0.18

0.18

Q: 540 m3/h

Q: 360 m3/h 0.18

0.05

0.05

0.18

Q: 720 m3/h

Q: 900 m3/h

Fig. 5.17 “Three zones” variation vs. different nitrogen injection quantities at injection positions at 20 m and 30 m

reasonable injection quantity is especially important for ensuring the inerting effect and cost efficiency. In the simulation of the reasonable nitrogen injection position in the previous section, it has been confirmed that the injection position where the nitrogen inerting effect begins to appear is 20 m away from the working face. The injection position where the nitrogen inerting effect is fully exerted is 30 m away from the working face. Therefore, two injection positions, X ¼ 20 and X ¼ 30, are selected respectively to simulate oxygen concentration field in the gob with injection quantities of 360 m3/ h, 540 m3/h, 720 m3/h, and 900 m3/h. The modeling result of oxygen concentration field at Z ¼ 0.7 m level is shown in Fig. 5.17. Analyzing oxygen concentration field with different injection quantities, it can be observed that the change of nitrogen injection quantity mainly affects the width of oxidation zone from the inlet side to the center part of the gob. With the injection quantity increase, the width of oxidation zone on the inlet side and in the middle of

204

5 Numerical Modeling of Self-Heating Event and Preventive Measures

Table 5.3 “Three zones” variation in gob during nitrogen injection with different quantities

Quantity No injection 360 540 720 900

Injection position at X ¼ 20 m Return Intake side Center side 11 31 92 12 14 15 14

43 42 41 38

2 2 2 2

Wmax 92

Injection position at X ¼ 30 m Return Intake side Center side 11 31 92

Wmax 92

110 64 48 40

12 12 11 13

48 38 33 30

42 37 32 27

2 2 2 2

the gob is greatly reduced, while the width of oxidation zone on the return side does not change significantly. This is because the nitrogen injection port is located on the inlet side of the gob. After the nitrogen injection, it diffuses and migrates inside the gob. The migration path is curved, and it is continuously mixed with the air leakage during the migration process, resulting in the concentration of nitrogen gradually decreasing from injection port to the return side. The dilution effect on oxygen in the air leakage is weakened consequently. Therefore, the inerting effect of nitrogen on the width of zone oxidation on the return of the gob is not significant. In order to visually analyze the effect of nitrogen injection on the inhibiting effect at X ¼ 20 m and X ¼ 30 m, the widths of the oxidation zone on the inlet side, at the center of gob, and on the return side and the maximum width of the oxidation zone in the gob are listed in Table 5.3. The variation of maximum width of oxidation zone with different injection quantities at positions of X ¼ 20 m and X ¼ 30 m is shown in Fig. 5.18. From Fig. 5.18, it can be seen the effect on controlling the width of oxidation zone is quite different by increasing the quantity of nitrogen injection at different positions. When the same injection quantity is applied at X ¼ 20 m and X ¼ 30 m, the maximum difference between the widths of the oxidation zone can reach 60 m, which is more obvious when the injection quantity is less. It indicates that the choice of nitrogen injection location is extremely important when using nitrogen for inhibiting spontaneous combustion. When the nitrogen injection port is 30 m away from the working face, the injection position is within a reasonable interval. With the increase of injection quantity, the maximum width of oxidation zone decreases exponentially. When the injection quantity is 540 m3/h, if the nitrogen injection measures are taken at the position of X ¼ 30 m, the maximum width of oxidation zone will be 38 m, which satisfies the basic requirements of fire prevention. If continues to increase the injection quantity, the maximum width of oxidation zone will decrease. But it will not be cost-efficient when injection quantity is greater than 720 m3/h, since the inerting effect will not be obvious after that. Therefore, based on the comprehensive analysis, injection quantity at 540 m3/h to 720 m3/h will be more reasonable to use for this case.

References

205

Maximum width of oxidation zone (m)

120

X=20 m 100

X=30 m

80

60

40

20 0

200

400

600

800

1000

Injection position (m)

Fig. 5.18 Variation of the maximum width of the oxidation zone with different injection quantities at injection positions at X ¼ 20 m and X ¼ 30 m

References Balusu, R. et al. (2001). Goaf gas flow mechanics and development of gas and sponcom control strategies at a highly gassy coal mine. Australia-Japan Technology Exchange Workshop (pp. 3–4). Dai, G., Zhang, S., & Tang, M. (2012). Determination of spontaneous combustion “three zones” in goaf of no. 713 fully mechanized longwall of Qinan Coal Mine. AGH Journal of Mining and Geoengineering, 36(3), 99–113. Gilmore, R. et al. (2014). CFD modeling explosion hazards-bleeder vs. progressively sealed gobs. 10th International Mine Ventilation Congress (pp. 47–53). Hao, S., Shuguang, J., Lanyun, W., & Zhengyan, W. (2011). Bulking factor of the strata overlying the gob and a three-dimensional numerical simulation of the air leakage flow field. Mining Science and Technology (China), 21(2), 261–266. Kong, B., Li, Z., Yang, Y., Liu, Z., & Yan, D. (2017). A review on the mechanism, risk evaluation, and prevention of coal spontaneous combustion in China. Environmental Science and Pollution Research, 24(30), 23453–23470. Lea, C. (1994). Computational modelling of mine fires. Mining Engineer, 154(394), 17–21. Li, Z.-X. (2008). CFD simulation of spontaneous coal combustion in irregular patterns of goaf with multiple points of leaking air. Journal of China University of Mining and Technology, 18(4), 504–515. Liu, W., & Qin, Y. (2017). Multi-physics coupling model of coal spontaneous combustion in longwall gob area based on moving coordinates. Fuel, 188, 553–566. Pan, R., Cheng, Y., Yu, M., Lu, C., & Yang, K. (2013). New technological partition for “three zones” spontaneous coal combustion in goaf. International Journal of Mining Science and Technology, 23(4), 489–493.

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Querol, X., et al. (2011). Influence of soil cover on reducing the environmental impact of spontaneous coal combustion in coal waste gobs: A review and new experimental data. International Journal of Coal Geology, 85(1), 2–22. Ren, T., & Balusu, R. (2005). CFD modelling of goaf gas migration to improve the control of spontaneous combustion in longwalls. Coal Operators’ Conference, University of Wollongong (pp. 259–264). Ren, T., Balusu, R., & Humphries, P. (2005). Development of innovative goaf inertisation practices to improve coal mine safety. Coal Operators’ Conference, University of Wollongong (pp.315–322). Tanguturi, K., Balusu, R., Morla, R., & Khanal, M. (2013). Effect of buoyancy on methane gas distribution and gas control strategies at tailgate region in a gassy coal mine. 9th International Conference on CFD in the minerals and process Industries, Melbourne (pp. 1–6). Taraba, B., & Michalec, Z. (2011). Effect of longwall face advance rate on spontaneous heating process in the gob area–CFD modelling. Fuel, 90(8), 2790–2797. Wang, Y., Shi, G., & Wang, D. (2013). Numerical study on thermal environment in mine gob under coal oxidation condition. Ecological Chemistry and Engineering S, 20(3), 567–578. Xia, T., et al. (2015). Evolution of coal self-heating processes in longwall gob areas. International Journal of Heat and Mass Transfer, 86, 861–868.

Chapter 6

Interpretation of Mine Atmosphere Monitoring Data

Abstract Two cases of thermal events occurred in longwall gob and longwall pane are present in this chapter. Mine atmospheric monitoring data from the two events have been prudently analyzed. Efforts have been made to identify the possible causes, locations, and statuses of these events using the obtained gas data, as well as other ventilation, geological, and mining parameters. The effect of injected inert gas to control the events has also been quantified. The collected gas data are used to derive a number of fire ratios for recognizing the status before the inert gas injection when air-gas mixture had not been disturbed by the injected inert gases and the status after the inert gas injection. For case 1, the stabilized and very low Litton ratio after the completion of the inert gas inject and the low hydrocarbon ratio also show the oxidation is occurring at ambient temperature. For case 2, the flame fire in the longwall panel was indeed a methane-burning-only thermal event. The fire was not ignited by any suspicious thermal event deep in the longwall gob. It was completely extinguished by the face crew. The fire did not penetrate further into the gob to cause combustion of the broken coal in the gob. Keywords Mine atmosphere · Atmospheric monitoring system · Fire ratios · Thermal events · Monitoring data

6.1

Introduction

Concealed thermal events in longwall gobs present safety hazards for underground coal miners and can significantly interrupt mining production. The probable causes for such thermal events range from coal oxidation at slightly above ambient temperature to smoldering fires due to spontaneous combustion of the broken coal left in the gobs. Locating such “hot spots” is the key step for planning and implementing mitigation measures to bring such thermal events under control. If a mine section, or even an entire mine, has to be sealed, understanding the status of the sealed mine atmosphere is important for the decisions guiding subsequent actions. The gas composition data obtained through the tube bundle mine atmospheric monitoring system is firsthand information of great value. Fire ratios proposed by various © Springer Nature Switzerland AG 2020 X. Wang, Spontaneous Combustion of Coal, https://doi.org/10.1007/978-3-030-33691-2_6

207

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6 Interpretation of Mine Atmosphere Monitoring Data

researchers and derived from gas composition data are useful in determining the fire status and even approximating the source locations (Timko and Derick 2006). However, the applicability of each of these ratios under particular conditions should be carefully evaluated. The use of properly combined fire ratios can enhance the certainty of analysis. The explosibility of a sealed mine atmosphere deserves primary concern for safety reasons during seal construction, idle time, and reopening of the sealed area. Two cases of thermal events that occurred in longwall gob and longwall panel have been studied. Mine atmospheric monitoring data from the two events have been prudently analyzed. Efforts have been made to identify the possible causes, locations, and statuses of these events using the obtained gas data, as well as other ventilation, geological, and mining parameters. The effect of injected inert gas to control the events has also been quantified.

6.2

Case 1: Identifying Status of Coal Oxidation in a Longwall Gob

Elevated CO concentration as a suspicious “oxidation” event was found in a crosscut adjacent to the gob area on the tailentry side of longwall panel 9F in ACO Mine. As a precautionary measure, intensive gas monitoring programs have been carried out by A and B companies, respectively. Mitigation measures such as water pumping and CO2-N2 injection have been employed to control. Gas monitoring data and other relevant information have been provided in the efforts to characterize the nature of the suspicious “oxidation event,” to estimate its occurring location, to find the possible cause of ineffective water pumping, and to determine the inert effects of the CO2-N2 injection and the latest status of mine atmosphere. The collected data, data analysis methodology, and results are presented in this section.

6.2.1

Background

A part of the ACO Mine as well as the location of longwall panel 9F is shown in Fig. 6.1. This panel is the first panel mined in the 9 Haulage area. The longwall panel with a plow operation is 304.8 m (1000 ft) wide (center to center) and about 3048 m (10,000 ft) long. Figure 6.2 shows the portion of the longwall panel of interest. The mining direction is from the top to the bottom in the figure. The tailentry of the panel is on the left, while the headentry is on the right. The bleeder shaft for the longwall district is located about 169.2 m (555 ft) away from the panel setup of the panel. The first methane drainage gob well of this longwall panel is located about 125.0 m (410 ft) inside the setup entry and 65.5 m (215 ft) inside the tailentry. The bottom of the gob well is located at an elevation of 220.7 m (724 ft) or about 4.6 m (15 ft) above the coal seam. The coal bottom elevation under the gob well is

6.2 Case 1: Identifying Status of Coal Oxidation in a Longwall Gob

209

Fig. 6.1 Part of ACO mine and longwall panel 9F

about 214.6 m (704 ft). The diameter of the bottom 30.1 m (115 ft) long section of the gob well is 0.25 m (9–7/8 inches), and it is left open, while the remaining length was cast with 0.30 m (11–3/4 inches) steel pipe. At the time of this reported elevated CO event, a 475.2 m (1500 ft) long block of the longwall panel has been mined, and the face is between breaks 55 and 56 as shown in Fig. 6.2. The face advance rate varied considerably during the time in which the panel has been mined, and the average rate is about 9.1 m/day (30 ft/day). The ventilation airflow pattern in panel 9F is also shown in Fig. 6.2. The ventilation air reaches the longwall face from both sides of the panel. On the headgate side, the air enters the longwall face from the last open crosscut at a rate of 2797.7 m3/min (98,800 cfm). A major part of this should flow through the longwall face. An estimated 51,203 cfm intake air passes the check curtains and flows to the back side of longwall face on the headgate side. On the tailentry side, a 421.0 m3/min (14,868 cfm) intake air passes the T-junction and continues toward the backside of the panel. Except for some leakage through the stoppings, the return and bleeder airs exit the panel at examination point 9E-2 (near the corner of tailentry and setup entry) at a rate of 4269.6 m3/min (150,780 cfm). The total airflow entering the bleeder shaft is about 7115.1 m3/min (251,269 cfm) with an estimated methane concentration of 0.74%.

210

6 Interpretation of Mine Atmosphere Monitoring Data 0.8% CH4 39,120 CFM

0.8% CH4 64,680 CFM

0.6% CH4 74,814 CFM

0.74% CH4 251,269 CFM 0.8% CH4 72,655 CFM

0.1% CH4 5,171 CFM

0.5% CH4 150,780 CFM

0% CH4 94,560 CFM EP 9E-1

EP 9F-2

0.1% CH4 28,386 CFM EP 9F-4

EP 9E-2

Break 62 Monitoring Location

Least Ventilation Area

VBH 9F - 1

Break 61 Monitoring Location

9G - 1

409 ft

9E

Total leakage through these stoppings 9,100 CFM

216 ft Suspected ĀOxidationā Area

Compacted Gob

0.45% CH4 2 PPM CO 81,000 CFM

Est. 51,203 CFM 0.054% CH4 98,800 CFM

Longwall Face

0.1% CH4 14,868 CFM

Est. 96,652 CFM

9F - 2

VBH 9F - 2

0.1% CH4 53,352 CFM

0% CH4 19,285 CFM

0% CH4 45,448 CFM

Break 53 Monitoring Location

0

400'

800'

Fig. 6.2 Estimated bleeder airflow pattern and suspicious “oxidation” area

The vertical gob well 9F-1 started draining methane from the longwall gob on April 7 when the longwall face has just past its location. The gas drainage effort was stopped on May 28 right before the gob well is used for water pumping and later inert gas injection. The gas production from this hole is shown in Fig. 6.3.

6.2 Case 1: Identifying Status of Coal Oxidation in a Longwall Gob

211

Fig. 6.3 Gas drainage of VGB 9F-1

As expected, the airflow and the gas concentration were high initially at about 48.1 m3/min (1700 cfm) and 85%, respectively. The methane production in the initial stage was about 39.2 m3/min (2 mmscf/day). The gas production decreases to some degrees thereafter. At the time the elevated CO level (May 23) was found, the gas drainage was low (rate: 21.8 m3/min (770 cfm), CH4 concentration: 44%). Two methods have been tried to control the suspicious “oxidation” event. The first effort was to pump water to cool down any potential “hot” spots in the gob. The pumping through the gob well 9F-1 started on May 31 and ended on June 4. A total amount 7154.4 m3 (1,890,000 gallons) of water has been pumped into the mine without seeing significant reduction of CO level. Then about 50–50% CO2/N2 mixture was injected initially through the gob well 9F-1 and then through ASCO fan shaft. Temporary seals were constructed at the mouths of the panel on both 9E (tailgate) and 9F (headgate) sides. By June 13, an inert state in the monitored area in the panel has been reached.

6.2.2

Coal Sample Analysis

In order to identify the possible root cause of this suspicious “oxidation” event, the provided geological information and the coal sample analysis data from three nearby coreholes have been used. The mineable thickness of the coal seam ranges from 1.2 (4.05) to 1.5 m (4.95 ft) at the locations of the three boreholes. The mining company states that the mining height is 1.2 m (4.0 ft (48 inches)). Since it is a plow operation with a preset mining height of 1.2 m (4.0 ft), there will be some roof or floor coal

212

6 Interpretation of Mine Atmosphere Monitoring Data

inevitably left in the longwall gob area after the coal seam is extracted. The strata of the immediate roof where caving took place is up to eight times of mining height. No coal seam was found in the caving horizon from the core logs. Therefore, any broken coal left in the longwall gob will be from the mined coal seam and stay at the bottom of the gob. The laboratory coal quality analysis data from these three boreholes are listed in Table 6.1. The potential of spontaneous ignition of the coal samples has been assessed using the USBM method which determines the minimum (critical) selfheating temperature (CSHT). It is a well-known fact that the chemical and physical properties of the coal play a significant role in spontaneous ignition. Of particular importance concerning the chemical and physical properties are the ability of the coal to absorb water vapor, the amount of volatile matter within the coal, and the amount of oxygen contained within the chemical structure of the coal. Kuchta et al. (1980) found that self-heating of coal tends to be a two-step process. The first heating step occurs when dry coal adsorbs water vapor. In order to change from a liquid to a vapor, water must absorb a significant amount of heat. When the opposite process (water vapor condensing back into a liquid) occurs, the heat that it gained during evaporation is released to the surrounding environment. This process is referred to as the “heat of wetting.” When coal adsorbs water vapor, the heat of wetting raises the temperature of the coal. The more moisture the coal can adsorb, the more heat that can be generated by the heat of wetting. The rate of oxidation of coal at ambient temperatures is usually insufficient to initiate a self-sustained heating process. However, with sufficient heat of wetting, the rate could be increased, and a critical temperature may be reached. Two additional factors affect the likelihood of this happening. They are the amount of volatiles in the coal and the amount of inherent oxygen. Volatile matter in the coal is generally easier to oxidize than nonvolatile content, and additional oxygen in the coal further supports the oxidation process. Therefore, coals with higher volatile matter and oxygen content have lower critical oxidation temperatures. Even though the coal in this mine has low potential of spontaneous ignition as shown in Table 6.1, the ambient temperature oxidation of the broken coal left in the gob still takes place but at a slow rate. The following operational factors might have accelerated the oxidation rate and to raise the temperature of the broken coal to some degrees. The slow advance rate of the longwall face, about 30 ft/day, could have given more time for the coal to oxidize. The existence of apparent conduit between the 9F-1 degas borehole and crosscut 61 (reflected in in-gassing and out-gassing activities of the borehole observed by the mining company) allows oxygen-rich air (indicated by the lower methane concentration in the later stage shown in Fig. 6.3) being pulled to the gob well to react with the broken coal along the path. However, the low air velocity passing through the conduit makes the air less capable of carrying the generated heat away from the coal causing temperature rise of the broken coal. Such oxidation process in the gob at or slight above the ambient temperature could produce some CO to cause the observed event.

Sample 9H-10 9H-11 9H-14 Average Standard dev

BTU 14,685 14,788 14,743 14,739 52

M% 0.71 0.77 0.75 0.74 0.03

VM% 15.50 16.64 17.99 16.71 1.25

C% 85.09 84.67 83.98 84.58 0.56

A% 6.57 6.37 6.35 6.43 0.12

O2 (dry) % 1.87 1.93 2.90 2.23 0.58

Table 6.1 Coal quality and potential of spontaneous combustion O2 (daf) % 2.00 2.06 3.10 2.39 0.62

MFR(x) 7.73 6.61 6.22 6.81

CSHTOX 126.6 126.2 119.4 124.1

CSHTVOL 117.0 117.0 117.0 117.0

Ave. 121.8 121.6 118.2 120.5

Potential Low Low Low Low

6.2 Case 1: Identifying Status of Coal Oxidation in a Longwall Gob 213

214

6 Interpretation of Mine Atmosphere Monitoring Data

6.2.3

Gas Sampling and Monitoring

6.2.3.1

Gas Sampling

Once the elevated CO level has been detected at break 61, underground gas sampling was expanded to the locations of 9F and 9E crosscuts along longwall gob perimeter as shown in Figure 6.2. The last survey was performed on May 23, and the last gas monitoring readings from the gas sampling program are shown in the read boxes in Fig. 6.2. Then sample lines were established at crosscuts 61 and 62 on the panel tailgate side (Fig. 6.2) so that the atmosphere at those locations can be monitored from surface location. Two parallel intensive gas monitoring programs have been carried out by A and B companies, respectively. The A gas monitoring program started on May 23 and monitored gases of H2, O2, N2, CH4, CO, CO2, C2H2, C2H4, C2H6, and argon. The B company’s program monitored gases of CO2, O2, N2, H2, C2H4, C2H2, C2H6, CH4, and CO and started on June 10 after the CO2-N2 injection has started. On June 10, an additional sample tube in No. 3 entry of break 53 was installed in order to provide a monitoring point outby the longwall face area during inert activities. Both A and B companies started to monitor the atmosphere at this new sampling point from surface location on June 10.

6.2.3.2

Gas Monitoring Data

The underground gas monitoring along the perimeter of the longwall gob is shown in Fig. 6.2. It shows that measured CO level on the headgate side is all zero. At crosscuts 60 and 61, higher methane levels (0.84% and 0.63%) are measured. The airflow at those two crosscuts also shows out-gassing condition from the longwall gob that explains the higher methane concentrations found. On the tailgate side, the gas samples obtained from the first three crosscuts and the last two crosscuts showed no sign of CO. CO was found at the crosscuts 59, 60, 61, and 62 at 5, 5, 13, and 3 ppm, respectively. Higher methane concentrations were also found at these locations, especially 5.51% CH4 concentration found at crosscut 61. Higher concentrations of CO2, ranging from 0.08% to 0.13%, were also found at these locations. The composition change of the gas samples collected through the sampling lines at crosscuts 61, 62, and 53 by both A and B is plotted in Fig. 6.4a–f. In these figures, the atmospheric pressure history is also plotted. It is hard to find any good correlations between the atmospheric pressure and the gas concentrations. The timings of the water pumping and N2-CO2 injection activities to stop the suspicious oxidation event have also been plotted. The water pumping seems to have no significant effects on the gas concentrations. The CO2-N2 injection indeed had strong impacts on the gas compositions in the panel. The most significant change is the CO2 concentration which even reached up to about 40% at the location of break 53. The concentration of N2 at the location of

6.2 Case 1: Identifying Status of Coal Oxidation in a Longwall Gob

215

Fig. 6.4 Gas monitoring results conducted by companies A and B. (a) Break 61 monitored by A. (b) Break 61 monitored by B. (c) Break 62 monitored by A. (d) Break 62 monitored by B. (e) Break 53 monitored by A. (f) Break 53 monitored by B

break 62 reached as high as 85.7%. Due to the stopped ventilation, methane concentration in the area increased, and the oxygen level decreased significantly as expected. The concentration changes of four combustible gases (CH4, C2H6, CO, and H2) from the three monitoring stations are plotted in Fig. 6.5a–d. At each monitoring station, the A data are plotted in solid lines while the B data in dashed lines. The two sets of data agreed fairly well in the development patterns and magnitudes. However,

216

6 Interpretation of Mine Atmosphere Monitoring Data

Fig. 6.5 Gas monitoring results conducted by companies A and B. (a) CH4 at breaks 61, 62, and 53 monitored by A and B. (b) C2H6 at breaks 61, 62, and 53 monitored by A and B. (c) CO at breaks 61, 62, and 53 monitored by A and B. (d) H2 at breaks 61, 62, and 53 monitored by A and B. (e) CO2 + N2 at breaks 61, 62, and 53 monitored by A and B. (f) O2 at breaks 61, 62, and 53 monitored by A and B

A data show more sudden and large changes, particularly in CH4 concentration in the later stage of monitoring, than the B data most possibly due to instrumental errors. The methane concentrations at all stations (Fig. 6.5a) showed significant increase after June 10. Before the inert gas injection, break 61 had significantly higher methane concentration (5.51% on May 23) than break 62. It went down to as low

6.2 Case 1: Identifying Status of Coal Oxidation in a Longwall Gob

217

as 0.74% on June 10. After the injection of inert gases and especially after the tuning off of the ASCO fan on June 12, the three monitoring stations experienced significant increases in methane concentration. Among them, break 61 had witnessed the significant change first, followed by break 53 and then 62. However, the methane concentration at break 61 reached a relatively stable condition earlier in the range from 5.0% to 5.8% for a while. It went up again and reached about 10.5%. The methane concentration at break 62 also reached a relatively stable condition in the range of 6.0–7.2% for a while and up again to 11.6%. The methane concentration at break 53 is highest among the three monitoring stations and continued to increase until June 28 with the maximum being about 15.7%. All stations show decreasing trends after June 28, and the last readings were 8.6%, 10.8%, and 13.5%, at breaks 61, 62, and 53, respectively. The development trends of C2H6 concentration shown in Fig. 6.5b are somewhat similar to those of methane. It reached at or above 1800 ppm at break 61 a number of times before the inert gas injection. After the injection, C2H6 concentrations at break 61 experienced significant drop since June 13 and stabilized at a level of around 800 ppm for a while and then increased again. Break 62 reached a relatively stable condition and increased again in the level slightly lower than that at break 61. Again C2H6 level at break 53 was much higher than the other two locations. The final readings of C2H6 are about 1800, 1516, and 4000 ppm at breaks 61, 62, and 53, respectively. The development trends of the CO concentrations are plotted in Fig. 6.5c. Before the inert gas injection, elevated CO was only observed at the location of break 61. It should be noted that since the CO detectors used in belt entries have a detectable level of 5 ppm, CO concentration lower than 5 ppm is considered as normal (Litton et al. 1991). After the inert gas injection, the CO level at all monitoring stations began to decrease on June 15. The last readings of CO levels at breaks 61, 62, and 53 were 5, 5, and 6 ppm. The development trends of H2 (Fig. 6.5d) are similar to those of CH4. The last readings were 11, 13, and 17 ppm at breaks 61, 62, and 52, respectively. Figure 6.5e shows the development trends of inert gases (i.e., CO2 and N2) at the three monitoring stations. Before the inert efforts, the inert gases made up between 76% and 77.64% of air at breaks 61 and 62, respectively. The inert efforts significantly increased the percent of the inert gases at those locations mainly by significantly increasing the percent of the CO2 in the area as shown in Fig. 6.4a–f. In the later stage of the monitoring program, the percent of inert gases at breaks 61 and 62 (about 88%) are higher than that at break 53 which was actually slowly decreasing after it peaked at 87% around June 18. Slight increases in the total inert gas were observed after June 27, and the latest readings were 85%, 86%, and 84% at breaks 61, 62, and 53, respectively. The measured oxygen levels are shown in Fig. 6.5f. Before the inert effort, the oxygen level at break 61 was about 19.5%, while that at break 62 was about 20.73%. After the inert gas injection, the oxygen level decreased significantly to the level of 5%, 3%, and 2% at breaks 61, 62, and 53, respectively.

218

6.2.4

6 Interpretation of Mine Atmosphere Monitoring Data

Locating the Original “Oxidation” Spot

Locating the suspicious “oxidation” spot that could have caused the first elevated CO level is important to determine the reason for the ineffective water pumping effort to lower down the CO level in the mine. The knowledge about vertical stress distribution, the air pressure differentials, the airflow pattern around and behind longwall face, and the measured O2, CH4, CO2, and CO along the perimeter of the longwall gob are used to estimate the flow pattern of bleeder air inside the longwall gob as shown in Fig. 6.2. The black arrows indicate the direction and relative velocity of the bleeder airflow. The central portion of the gob has been tightly compacted without bleeder air penetrating through. Based on the estimated airflow pattern, the area with least bleeder ventilation is located near the gob well 9F-1 as marked by the blue oval. The high CO concentrations detected between breaks 59 and 62 also suggested that the suspicious “oxidation” event should occur in an area marked by the red oval. The contour map of the coal bottom is generated from the elevation readings at the intersections using Surfer program and is shown in Fig. 6.6. The general trend is that the coal seam dips from the upper left corner toward the lower right corner of the figure. However, a localized higher area can be observed near the gob well. Compared to the locations of the water submerged areas in the top figure, the surface of the water pool formed by the water pumping effort is estimated to be at the elevation of 501 ft. The steepest gradient from the gob well location is toward the lower left corner of the figure. This fact suggests that the water pumped into the mine through the gob well would most possibly flow toward the tailentries first along a path indicated by the blue arrow. Therefore, the pumped water is unlikely to reach the area of suspicious “oxidation” event directly. This may be the reason that the pumped water was ineffective in cooling down the suspicious oxidation event.

6.2.5

Fire Ratios and Indications

In order to identify the cause of the elevated CO level, the collected gas data are used to derive a number of fire ratios. The process is divided into two stages, the one before the inert gas injection when air-gas mixture had not been disturbed by the injected inert gases and the second stage after the inert gas injection. 1. Status of oxidation before inert gas injection In the first stage without artificially added inert gases, index of carbon monoxide (ICO or also called Graham’s ratio) and Trickett ratios can be used to evaluate the status of a mine fire event and to identify the burning material. In using these fire ratios, their long-term trends should be analyzed. Graham’s Ratio (ICO/GR) Graham’s ratio (ICO/GR) is used to evaluate the status of a mine fire event and is defined by Eq. 6.1, in which CO, N2, and O2 are in volume percentages of the respective gases. The term 0.265N2-O2 is an indicator of oxygen deficiency:

6.2 Case 1: Identifying Status of Coal Oxidation in a Longwall Gob

219

Fig. 6.6 Contour of coal bottom and possible flow path of the water pumped through gob well 9F-1 top: observed water submerged area

ICO ¼

100  CO 0:265  N2  O2

ð6:1Þ

The resulting ICO values can be used in the following two ways. If an individual ICO value is obtained, a value larger than 0.5 indicates an active fire, while a value smaller than 0.2 shows that the fire is under control. When multiple ICO values have been determined, an ICO rise over time indicates the existence of fire and temperature increases, while a decreasing trend shows the oxygen has been consumed and the temperatures fall to near ambient levels. A level and stable ICO trend is indicative that fire is under control. Trickett’s Ratio (TR) Trickett’s ratio (TR) also called Jones-Trickett ratio not only indicates the fire status but also shows what is burning. It is based on the principle that the number of molecules of matter consumed in a fire is proportional to the number of molecules or the volume of gas produced at constant temperature.

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6 Interpretation of Mine Atmosphere Monitoring Data

The TR is defined by Eq. 6.2 in which CO2, CO, N2, Ar, and H2 are in volume percentages of the respective gases: TR ¼

CO2 þ 0:75CO  0:25H2 0:265ðN2 þ ArÞ  O2

ð6:2Þ

The implications of Trickett’s ratio are shown in the following table. TR value 1.6

Implications Fire probably out Methane probably burning Coal, oil, or conveyor belting probably burning Wood probably burning Not normally possible in a coal mine fire; sample is suspicious

In the first stage, only A data were available for determining these two fire ratios. The gas data obtained from break 62 often resulted in near zero or negative oxygen deficiency, making the resulting ICO and TR unreliable. Therefore, only gas data from break 61 monitoring station were used. The resulting ICO and TR plots are shown in Fig. 6.7a. The decreasing trend and the magnitude around 0.2 of ICO are indications of non-active smoldering or flaming fire in the suspected “oxidation” area. The resulting Trickett ratios, smaller than 0.4, also reverify that non-fire activity in the suspected area. Therefore, the elevated CO level observed at break 61 might be an oxidation process of the broken coal left at the bottom of longwall gob at ambient temperature. The small amount of oxygen-rich air pulled toward the gob well 9F-1 as stated previously might have intensified the oxidation process a little, but the event was still not a fire event yet. Relative Intensity (RI) Relative intensity (RI) is used by the power industry to measure the quantity of air available to burn a unit mass of fuel (11.6 lbs of air are required to completely consume 1 lb of coal), the percentage of oxygen consumed, and the effect of combustion on temperature (Mitchell 1990). RI is determined by the following equation:

RI ¼


 1  0:0383O2 ICO  104 N2

ð6:3Þ

Adapting the RI to mine fire analysis, it is used to determine the proximity of the sampling location to the fire or growth trend of a fire. If the RI increases, the fire is either growing or moving closer to the sampling location. Conversely, the decreasing RI indicates a fire is being throttled or moving away from the sampling location. The calculated RI from the gas data obtained at break 61 before the inert gas injection is plotted in Fig. 6.7b. The general trend of RI is decreasing even though it experienced an increase during the time period between June 2 and 4. Therefore,

6.2 Case 1: Identifying Status of Coal Oxidation in a Longwall Gob

221

Fig. 6.7 Fire ratios before and after inert gas injection. (a) ICO and Trickett ratio before inert gas injection. (b) Relative intensity before inert gas injection. (c) Litton ratio after inert gas injection. (d) Hydrocarbon ratio after inert gas injection

the suspicious oxidation event was being throttled in the time period between finding of elevated CO level and the start of inert gas injection. 2. Status of oxidation after inert gas injection As shown in Fig. 6.5f, the oxygen in the openings of the longwall panel has been reduced by the inert gas injection to a level that would not support active fire. What would be the status of the suspicious oxidation event and whether it would revive when ventilation is restarted to the longwall panel are the questions to be answered. The artificial addition of N2 and CO2 in the inert gas injection operation prevented the ICO, TR, and RI methods from being correctly used in assessing the status of the oxidation event. Therefore, the methods avoiding the influences of artificially added CO2 and N2 should be used. Two methods, Litton ratio and hydrocarbon ratio, have been employed in the post inert injection assessment. Litton Ratio (LR) Litton (1986) developed a method to monitor the sealed mine atmosphere. It was designed to reduce the potential for reignition when a mine or a

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6 Interpretation of Mine Atmosphere Monitoring Data

section is reopened and oxygen is reintroduced. In this method, only four gases, O2, CO, CH4, and ethane (C2H6) that are independent of the injected N2 and CO2, are required. It requires a residual gas (Rg) in volume percent be determined first using the following equation: Rg ¼ 100  4:774  O2  CH4  C2 H6

ð6:4Þ

Then the Litton ratio (LR) is determined based on the concentration of oxygen in the atmosphere by Eq. 6.5. In the equation, COs is the CO concentration in ppm: 8 1 > > >

s 2 > > : 3  3=2 R

if O2  1% if O2 < 1%

ð6:5Þ

g

If the Litton ratio is greater than 1, smoldering combustion or above-ambient temperature oxidation is occurring. If it is equal to or less than 1, it is possible that ambient temperature has been reached. Equilibrium exists only if LR stabilizes at a value less than 1. Litton also recommends that the minimum time for the LR to remain stabilized at less than 1 is 30 days. The calculated Litton ratio from the B data at monitoring stations at breaks 61, 62, and 53 is shown in Fig. 6.7c. The A data were not used in the calculations because of the frequent sudden and large charges. It shows that the Litton ratio never exceeds 1 during the process. After June 14, the Litton ratio at all monitoring stations reached a stabilized value less than 0.01. Therefore, the oxidation event, if any, should have been occurring at ambient temperature, and re-ventilating the inert longwall area is unlikely for the broken coal in the longwall gob to cause any thermal runaway event. Hydrocarbon Ratio Hydrocarbon ratio method (Justin and Kim 1988) is developed based on the fact that low molecular weight hydrocarbon gases desorbed from coal in direct proportion to increasing temperature. Among them, methane is readily liberated at ambient temperatures; the progression of gas desorption due to heating is carbon dioxide, carbon monoxide, hydrogen, ethylene (C2H4), propylene (C3H6), and acetylene (C2H2). Hydrocarbon concentrations increase with rising temperatures. The hydrocarbon ratio (R1) is defined by Eq. 6.6. In the equation, THC is the total hydrocarbon concentration including hydrogen in ppm, CH4 is the methane concentration in ppm, and c is a constant of 0.01 ppm: R1 ¼

1:01ðTHCÞ  CH4  1000 THC þ c

ð6:6Þ

The hydrocarbon ratio is 0 when no hydrocarbons are detected, 10 when methane is the only measured hydrocarbon, and about 1010 at the upper limit. For bituminous

6.2 Case 1: Identifying Status of Coal Oxidation in a Longwall Gob

223

coal, R1 values are closely dependent on temperature. Because of this, limits have been derived to aid in determining the temperature of coal being analyzed. R1 values from 0 to 50 indicate that normal oxidation is occurring. Values from 50 to 100 indicate possible elevated temperatures. Above 100, coal is undergoing elevated temperature oxidation. The determined hydrocarbon ratio for the three monitoring stations using B data is shown in Fig. 6.7d. Again, A data were not used in the calculations. The hydrocarbon ratio at breaks 61 and 62 increased some at the beginning of inert gas injection, and the maximum is only 46.5 on June 11. It decreased afterward with a sharp dip between June 12 and 13. The R1 values at breaks 61 and 62 reached their respective minimums at 23.5 and 18.3 on June 21, respectively. Then it increased slightly and found to be 29.4 and 23.8 on July 4. At break 53, the hydrocarbon ratio increased initially and reached its maximum at 40.5 on June 14 and followed a minor decrease. The minimum R1 at break 53 was 34.7 occurring on June 26, and the last reading was 38.9. The resulting R1’s is much lower than the upper limit for normal oxidation 50 for bituminous coal. It should be also noted that the coal is ranked as low volatile bituminous coal with very low potential of spontaneous ignition as determined before. Therefore, any oxidation process, if significant, has been occurring at ambient temperature level.

6.2.6

Summary

A comprehensive study has been conducted to analyze the events as a consequence of an elevated CO level observed on May 19, 2011, at location of break 61 of longwall panel 9F. The gas monitoring data conducted by both A and B companies have been analyzed using various applicable methods. The core logs show that only the un-mineable roof or floor coal will be left in the bottom of the longwall gob and consequently has the opportunity of oxidation. The localized variation of the coal bottom elevation in the area near the gob well was likely the cause of the ineffectiveness of water pumping effort because the pumped water was unable to flow to the potential oxidation zone to perform its cooling function. The elevated CO is likely caused by coal oxidation in a zone near the gob well 9F-1 as shown in Fig. 6.2. However, the oxidation was occurring at higher but still ambient temperature as evidenced by the low ICO and Trickett ratios backed up by decreasing relative intensity before the injection of inert gases of N2 and CO2. After the inert gas injection, the Litton ratio and hydrocarbon ratio methods are used to assess the status of the oxidation situation. The stabilized and very low Litton ratio after the completion of the inert gas inject and the low hydrocarbon ratio also show the oxidation is occurring at ambient temperature. These findings are consistent with the low potential for spontaneous ignition determined using the coal quality analysis data.

224

6.3 6.3.1

6 Interpretation of Mine Atmosphere Monitoring Data

Case 2: Causational Analysis of a Thermal Event in a Longwall Panel Background

A thermal event occurred in an underground coal mine with mining history for a long in the northwestern part of China. Up until the self-heating incident, one longwall face and four development sections are active in production with 1.2 Mt (1.32 million st) of coal per year. The high-quality anthracite produced from the mine is mainly for international export. The mine is high gassy mine with estimated gas content of the retreated coal seam to be 11.03 m3/t (354 ft3/st), absolute methane emission rate of 148.72 m3/min (5251 cfm), and a very high relative emission rate of 57.38 m3/t (1842 ft3/st). Smoldering fire has been found in gob area of the mine, but liability of spontaneous combustion of the coal is evaluated to be low. Bleederless ventilation system is applied for controlling the self-heating issues in the gob. The exhaust fan located at the mine portal operates at a static head of 1550 Pa (6.22 in.– H2O) and draws a flow rate of 9204 m3/min (325,000 cfm). As shown in the partial schematic drawing of the mine in Fig. 6.8, the intake air is drawn into the mine mainly through the belt, man, and accessory slopes at the mine portal. A minor amount of air also enters the mine through safety exit at the west wing. The mine is equipped with a telemetric atmospheric monitoring system with 17 monitoring points throughout the mine. The sensors installed at the monitoring points are able to monitor the concentrations of CH4 and CO, air temperature and pressure, smoke, the status of ventilation doors, main and auxiliary fans, power outage, and methane drainage system in real time. A tube bundle-chromatography gas monitoring system is also installed in the mine to collect and analyze the gas compositions at coal-producing faces and potential spots for mine fire. Some of the gas gathering points in the mine are shown as the numbered red dots in Fig. 6.8. The longwall panel is one of the panels in longwall district that extracts in one of the three adjacent coal seams. The panel was designed to be 642 m (2106 ft) long and 252 m (827 ft) wide, with a mining height of 3.0 m (9.84 ft). Ventilation air enters the longwall face from the headentry at a rate of 2264 m3/min (79,940 cfm). Two return airways are located on the tailgate side. The panel tailentry serves as the primary return airway. The second return serves a role similar to the bleeder entry in US coal mines, allowing a minor amount of gob air to leak in and permitting the methane concentration to be higher than 1%, typically around 2%. Stoppings are used to separate the primary and secondary returns. The overlying coal seam above the current panel has been mined previously. Mined longwall panels in the same coal seam are located on the north and west sides of the panel. Mining started in panel on Aug. 26, 2010. After retreating a distance of about 60 m (197 ft) in the panel, an abnormally high CO event occurred. At 6:20 a.m. on June 4, 2011, when the longwall face was about 230 m (755 ft) away from the panel setup entry, a methane-burning flame fire was observed behind the No. 76 face support, as shown in Fig. 6.9. The fire was extinguished by the face crew with a water hose. However, due to excessively high concentrations of CO (around

6.3 Case 2: Causational Analysis of a Thermal Event in a Longwall Panel

225

+1940m West Main

32z13(1) 2nd Return #24

#21

2

1

Gob

Longwall Face

3

#20

32z13(1) Tailentry

5 4

+1930m West Main

7

+1930m Eest Main

6

Methane Fire 32z13(1) Headentry 32z15(1) Track in Development

12

Main Slope

8

9 10

11

Main Fan

Fig. 6.8 Mine ventilation system and part of the longwall panel in question

400 ppm) in the longwall face and in the return air flows, the longwall panel was sealed by 8:40 p.m. the same day, under order from the mine safety administration. The sealed longwall panel has an area of 59,500 m2 (640,450 ft2) and volume of 178,500 m3 (6,503,700 ft3). Then the entire mine was sealed at portal points by 7:15 a.m. on June 5. The sealed mine area is about 61,256 m2 (659,350 ft2), with a volume of 214,396 m3 (7,571,300 ft3). In preparation for sealing the panel, liquid nitrogen was injected into the longwall gob area through boreholes drilled from the surface. After the sealing of the panel and mine, nitrogen gas was continuously injected into the longwall gob at a rate higher than 8000 m3/h (4708 cfm). Water and mud were also pumped into the longwall gob for cooling purposes. On June 16, 2011, after a thorough check of the mine and the longwall face by mine rescue teams, the reopening operation of the sealed mine started. Dilution of the accumulated methane in the mine outside the sealed longwall panel was accomplished through properly adjusting the explosion doors and the airflow rate of the mine fan. The explosion doors were closed, and normal mine ventilation was resumed after the methane concentration in the return shaft was reduced to 0.75%. At 11:00 p.m. on June 17, reopening of the sealed longwall panel started. The

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6 Interpretation of Mine Atmosphere Monitoring Data

Fig. 6.9 Gas monitoring data from multiple sampling points. (a) Point 1 at tailgate T-junction. (b) Point 4 at tailgate. (c) Point 2 at crosscut 21. (d) Point 5 at second return. (e) Point 3 at crosscut 24. (f) Point 8 at main return

atmospheric condition of the longwall face was resumed to 0.9% CH4 and 19.8% O2 at 2:30 p.m. on June 18. Injection of nitrogen gas to the longwall gob through the surface boreholes continued at a rate greater than 5244 m3/h (3086 cfm). Up to June 20, 2011, when the mining operation was returned to normal, a total of 2966.5 t (3263.2 st) liquid nitrogen and 4,216,187 m3 (148,873,563 ft3) nitrogen gas had been injected to the longwall gob area.

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227

Prior to, during, and after the fire event, a large number of mine gas samples were collected, using the tube bundle system and bag samplers at various points (shown as red dots in Fig. 6.8) throughout the mine. The gas samples were analyzed with a gas chromatography setup to determine the gas volumetric concentrations at the sampling locations. The collected gas data, such as CO and CH4 concentrations, were used in the decision-making process by the mine and state regulators for sealing and reopening the longwall panel and the mine. In this paper, the data are further analyzed to determine the location, size, and status of the fire event directly, using the development patterns of the mine gases, and indirectly, using various derived fire ratios. The explosibility of the mine atmosphere inside the panel and in other parts of the mine is also determined.

6.3.2

Gas Monitoring Data

In this section, all the collected gas monitoring data are carefully analyzed. The development curves of various gas concentrations at five monitoring points in the longwall panel and one point near the mine fan are shown in Fig. 6.9. It should be noted that the air monitoring durations at these points were not the same and the measured gas concentrations are not necessarily plotted in the same time interval as shown in Fig. 6.9. The times of the fire (9/4 6:20 a.m.) and of the mine being sealed (6/5 7:15 a.m.) are also marked in these panels. In these plots, the effects of sealing the longwall panel and the mine, as well as the nitrogen injection into the longwall gob, are more clearly shown, especially along the perimeter of the longwall gob. A sharp decrease in O2 concentration and sharp increase in CH4 at points 1 (tailgate Tjunction), 2 (second return at crosscut #21 on gob side), and 3 (second return at crosscut #24 on gob side) only a few hours after the sealing of the panel are observed. The decrease in O2 and increase in CH4 are more gradual at the tailentry (point 4) and in the second return (point 5), as expected. When the higher concentration gases (i.e., N2, O2, and CH4) are removed from these plots, the oxidation product gases (such as CO, CO2, and C2H6) show sudden increases after the flame fire event occurred on June 4. Figure 6.10a shows the development curves of the CO concentration, which experienced the most significant changes among the three oxidation product gases, at the five monitoring points in the longwall panel. Among the points, the tailgate T-junction, closest to the location of the flame fire, experienced a dangerously high level of CO, 0.69% (6922 ppm), at time 0:06 a.m. of June 5, about 17 h after the flame fire event and about 2 h after sealing the panel. However, it decreased sharply afterward and returned to a relatively low level around 50 ppm at 9:25 a.m. June 5. The peaks of CO concentration at the other four points ranged from 129 ppm at point 2 to 1949 ppm at point 4 and occurred a few hours after the peak at point 1. The durations of relatively high CO concentrations (>50 ppm) at these points lasted much longer than that at point 1. Through the analysis of the CO peak concentrations and the occurring times at these monitoring points in reference to the longwall ventilation system, the flame fire at the

228

6 Interpretation of Mine Atmosphere Monitoring Data

Fig. 6.10 Gas monitoring data from multiple sampling points. (a) CO concentration in the panel. (b) ICO ratio. (c) Trickett’s ratio (TR). (d) RI ratio. (e) Litton ratio. (f) Hydrocarbon ratio

longwall face was unlikely to be ignited from any suspected coal-burning events deep in the gob of the current longwall panel. It also shows that the fire event has been extinguished at the face and did not penetrate further back into the gob area. Between 8 and 11 h after sealing the panel, the methane concentrations at all monitoring points in the panel exceeded the lower explosive limit of 5%. At nearly the same times, increases of C2H6 between 15 and 32 ppm were also observed at

6.3 Case 2: Causational Analysis of a Thermal Event in a Longwall Panel

229

these locations. However, no significant increases were observed on C2H2 and C2H4 during the entire monitoring period. The minor increase of hydrocarbon gases in the panel also indicated that the fire event did not induce any significant temperature increase of the broken coal inside the longwall gob.

6.3.3

Fire Ratios and Indications

In order to confirm the findings from direct analysis, the collected gas composition data were used to derive a number of common fire ratios for analyzing thermal events in coal mines. The derived fire ratios and their implications are discussed in this section. Graham’s Ratio (ICO) Graham’s ratio (ICO) is determined by Eq. 6.1. Figure 6.10b shows the derived ICO ratio from the gas monitoring data in the longwall panel. Three abnormal data points have been deleted from the figure, due to the irrationally sudden and isolated increase in O2 levels after sealing the panel. The irrational spikes of O2 concentration in the sealed panel, about 5–10% higher than neighboring points, are possibly due to machine or human errors in gas analysis. These data points brought the oxygen deficiency term in Eq. 6.1 down considerably and created irrational spikes in the resulting ICO. For the same reasons, these three data points are also deleted in Trickett’s ratio and relative intensity determinations that follow. Based on the derived ICO ratio, the earliest indication of fire was observed at the monitoring point 4 in the tailentry with a short time delay. The other points show that ICO > 0.5 occurred nearly 20 h after the fire event, but with much shorter durations of ICO > 0.5 (