Computational fluid dynamics simulation study on hot spot location in a longwall mine gob

Spontaneous combustion is one of the main sources for mine fires in underground coal mines. Most of these fires are initiated in the longwall gob (caved area) by coal oxidation. Because coal oxidation generates heat, this phenomenon is called the selfheating process. This process will eventually create hot spots under conditions, i.e., oxygen concentrations of at least 5% (by volume) and gob temperatures of 100°C. Coal properties, gob permeability, self-heating characteristics, and the ventilation system are the key variables for the formation of these hot spots. A study was carried out to identify the location of hot spots. The study is based on mine ventilation surveys, laboratory experiments, and gob simulations using Computational Fluid Dynamics (CFD). Ventilation surveys were conducted in an existing longwall mine located in the western United States; the laboratory experiments were performed on a physical gob model to investigate permeability (k) and airflow distribution; and the CFD models were simulated to investigate the flow behavior in the gob, the oxidation of coal, and heat transfer phenomena. Four CFD models were formulated and solved, three utilized a bleeder ventilation system, and the fourth a bleederless ventilation system. For these models, the gob length varied from 912 m to 2,445 m. The gob of each model was divided into 3 zones of different permeability: unconsolidated (k = 4.68 xlO"7 m2), semi-consolidated (k= 3.15 x 10"8 m2), and consolidated (k = 7.98 x 10"9 m2). The simulation results showed that in the models ventilated by a bleeder system, the hot spot was located in the consolidated zone near the return side of the gob. Once initiated, it propagated along the tailgate side as the gob progressed. The leakage flow through the gob played an important role in determining the size and location of the hot spot. In models ventilated by a bleederless system, the hot spot was located in the gob by the face line. This is mainly caused by the air leakage from the headgate T junction (face) and between the shields. It may extend further into the gob depending on the gob permeability and the fan pressure. In addition, these gob simulation exercises have shown that the hot spot areas in all cases can be located accurately. This information can be used to develop suitable control methods. The parametric studies have indicated that the ventilation system and gob permeability are the major contributing factors for the formation of hot spots. Although the gob models were developed for specific dimensions and ventilation system, the results can be applied to other schemes with minor adjustments.

COMPUTATIONAL FLUID DYNAMICS SIMULATION STUDY ON HOT SPOT LOCATION IN A LONGWALL MINE GOB by Samuel Atta Lolon A thesis submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Master of Science Department of Mining Engineering The University of Utah December 2008 Engineering Copyright © Samuel Atta Lolon 2008 All Rights Reserved THE U N I V E R S I T Y OF UTAH G R A D U A T E SCHOOL of a thesis submitted by Samuel Atta Lolon This thesis has been read by each member of the following supervisory committee and by majority vote has been found to be satisfactory. UNIVERSITY GRADUATE SCHOOL SUPERVISORY COMMITTEE APPROVAL ofthe Chair: Felipe Cahzaya Michael K. McCarter D. Kip Solomon THE U N I V E R S I T Y OF UTAH G R A D U A T E SCHOOL APPROVAL To the Graduate Council of the University of Utah: 1 have read the thesis of Samuel Atta Lolon [n [t s f m a i fo rm and have found that (1) its format, citations, and bibliographic style are consistent and acceptable; (2) its illustrative materials including figures, tables, and charts are in place; and (3) the final manuscript is satisfactory to the supervisory committee and is ready for submission to The Graduate School. Date Felipe Calizaya Chair: Supervisory Committee Approved for the Major Department Michael K. McCarter Chair/Dean Approved for the Graduate Council UNIVERSITY GRADUATE SCHOOL FINAL READING APPROVAL ofthe I in its final form ~~ (. C=Q~_..- _ David S. Chapman Dean of The Graduate School ABSTRACT Spontaneous combustion is one of the main sources for mine fires in underground coal mines. Most of these fires are initiated in the longwall gob (caved area) by coal oxidation. Because coal oxidation generates heat, this phenomenon is called the self-heating process. This process will eventually create hot spots under conditions, i.e., oxygen concentrations of at least 5% (by volume) and gob temperatures of 100°C. Coal properties, gob permeability, self-heating characteristics, and the ventilation system are the key variables for the formation of these hot spots. A study was carried out to identify the location of hot spots. The study is based on mine ventilation surveys, laboratory experiments, and gob simulations using Computational Fluid Dynamics (CFD). Ventilation surveys were conducted in an existing longwall mine located in the western United States; the laboratory experiments were performed on a physical gob model to investigate permeability (k) and airflow distribution; and the CFD models were simulated to investigate the flow behavior in the gob, the oxidation of coal, and heat transfer phenomena. Four CFD models were formulated and solved, three utilized a bleeder ventilation system, and the fourth a bleederless ventilation system. For these models, the gob length varied from 912 m to 2,445 m. The gob of each model was divided into 3 zones of different permeability: unconsolidated (k = 4.68 xlO"7 m2), semi-consolidated (k= 3.15 x 10"8 m2), and consolidated (k = 7.98 x 10"9 m2). self­heating (k= xl0-7 m2 ), (k= 10-8 m2 ), (k = 10-9 m2 ). The simulation results showed that in the models ventilated by a bleeder system, the hot spot was located in the consolidated zone near the return side of the gob. Once initiated, it propagated along the tailgate side as the gob progressed. The leakage flow through the gob played an important role in determining the size and location of the hot spot. In models ventilated by a bleederless system, the hot spot was located in the gob by the face line. This is mainly caused by the air leakage from the headgate T junction (face) and between the shields. It may extend further into the gob depending on the gob permeability and the fan pressure. In addition, these gob simulation exercises have shown that the hot spot areas in all cases can be located accurately. This information can be used to develop suitable control methods. The parametric studies have indicated that the ventilation system and gob permeability are the major contributing factors for the formation of hot spots. Although the gob models were developed for specific dimensions and ventilation system, the results can be applied to other schemes with minor adjustments. v v To my parents: Jan and Elisabeth Lolon, for their love and prayers TABLE OF CONTENTS ABSTRACT iv LIST OF TABLES x LIST OF FIGURES xii ACKNOWLEDGMENTS xv CHAPTER 1. INTRODUCTION 1 1.1 Statement of Problems 1 1.2 Thesis Overview 4 2. BACKGROUND AND LITERATURE REVIEW 6 2.1 Longwall Mines in the United States 6 2.2 Ventilation Systems for Longwall Mines 10 2.2.1 U-Tube System 10 2.2.2 Y System 12 2.2.3 Wrap-Around System 14 2.3 Spontaneous Combustion in the Gob 15 2.3.1 Mechanism of Self-Heating Process 16 2.3.2 Requisites for Hot Spot Occurrence 18 2.3.3 Prediction of Spontaneous Combustion Potential 19 2.3.4 Contributing Factors to Self-Heating Process 23 2.3.5 Control Methods 26 2.4 Spontaneous Combustion Studies Using CFD 28 2.5 Porous Medium 2.5.1 Particle Size Distribution 30 2.5.2 Porosity 31 2.5.3 Specific Permeability 32 3. CHARACTERISTICS OF GOB MATERIAL 36 3.1 Longwall Mine Gob 36 3.2 Gob Material and Its Characteristics 40 .. . . . . . .. .. . . . . .. . . .. . .. . ... .. . .. . .. . .. ... ... . .. ... ... . . . .. . .. .... . . .. .. .. .. .. . ..... ... IV . .... .. . .... ...... .. .. .. .. .. . ... . ... .. .. ... .. ... .. .. .... .. ... . ... . .... .. .. . . ... FIGURES... .. ... .. ... . .......... . ... .. . ... .. . ....... ... ..... . . . .... ........ . ........ . XlI ACKNOWLEDGMENTS.... ... . .. .. .. .. . .. . ..... ..... .. ......... ... ........................ INTRODUCTION.................... . ................... . ...... .. .... .. .... .. ..... .......... Problems.... . ....... . .. .. .. .. ........ .. .... . .. . . ... .. .... . .... ...... ..... 1.2 Thesis Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ............ 4 2. BACKGROUND AND LITERATURE REVIEW ....... ....... ... .. ............ . . ... 6 2.1 Longwall Mines in the United States.................. ...... .......... ...... ...... 6 2.2 Ventilation Systems for Longwall Mines .. .. .. .... .. .. .. .. .. .. .. .. .... .. ...... .. . 10 2.2.1 U-Tube System... ... .. . ... ... ... ... ... . .... . ... .. . . . . ... . .. ......... . .. . ..... 10 2.2.2 Y System. ... ......... .. . ... .. .. . .. .. .. ... .... ............... .................. 12 2.2.3 Wrap-Around System.............. .............. .. ......................... 14 2.3 Spontaneous Combustion in the Gob .... . .. .... , .. . . .. ... . . . . .. . . . .. .... . . .. .. . . .. 15 2.3.1 Mechanism of Self-Heating Process .... .... .... ... .. .. ............... ... 16 2.3.2 Requisites for Hot Spot Occurrence. .. . .. .. . . .. ... . .. .. .... . . .. . .... .. .. . 18 2.3.3 Prediction of Spontaneous Combustion Potential. .. ... . .. .. . .. ... ... .. 19 2.3.4 Contributing Factors to Self-Heating Process.............. ........ .. .... 23 2.3.5 Control Methods........ .. ... ... .......... ..... . ... . .... ............. ........ 26 2.4 Spontaneous Combustion Studies Using CFD .. ...... ........ ...... .. .. ......... 28 2.5 Porous Medium. ....... ..... .. . ... ... .. .. . . ... .. . . .......... ... ... ..... . .... ... .. . .. .. 30 2.5.1 Particle Size Distribution. ..... . .......... .... ...... . .. ................. .... 30 2.5.2 Porosity........................ . .. ... . .. .. ..... .. .. .... .... ... .. ... . .. ......... 31 2.5.3 Specific Permeability..................... . ....... .. ...... .. .. ... . .. ........ 32 ............................ ........ ...... Gob....... ...... ............. .. .. .. . . . ... ........................... . Characteristics............................ ........ ........... 3.2.1 Particle Size Selection 40 3.2.2 Packing and Particle Shape 41 3.3 Permeability Tests 42 3.3.1 Sample Preparation 43 3.3.2 Water-Based Method 3.3.3 Air-Based Method 50 3.4 Specific Permeability of Gob Material 55 4. RESEARCH METHODOLOGIES 58 4.1 Physical Model 58 4.1.1 Simulated Airway 60 4.1.2 Fan and Regulator 65 4.2 Computational Fluid Dynamics Model 66 4.2.1 Introduction 66 4.2.2 Airflow Simulation (Without Oxidation) 68 74 4.3.1 Similitude Concept 74 4.3.2 Similitude Validation 4.3.3 Model Calibration 77 5. HOT SPOT LOCATION - CFD SIMULATION EXERCISES 79 Assumptions 5.1.1 Longwall Mine Geometry 80 5.1.2 Input Parameters 83 5.1.3 Flow Distribution - A Base Case 89 5.2 Simulation Exercises 91 5.2.1 Bleeder Ventilation System: Models A, B, and C 91 5.2.2 Bleederless Ventilation System: Model D 100 5.3 Preliminary Conclusions 103 6. DISCUSSION OF GOB SIMULATION STUDIES 106 Model 6.1.1 Limitations Permeability Relationship 110 6.2.2 Hot Spot Locations 114 6.2.3 Effect of Permeability on Hot Spot Formation 118 6.2.4 Effect of Gob Width on Hot Spot Formation 122 6.2.5 Hot Spot Control through Gas Injections 124 viii 3.2.1 Particle Size Selection.................................. ........ ............ 40 3.2.2 Packing and Particle Shape.................................. ............... 3.3 Permeability Tests............................................................ ........ 3.3.1 Sample Preparation........................................ .................. Based Method............................................ ........... 44 Based Method........................................................... Material...... ........ .......... .................... .................................... '" .. . .......... .. 4.l ... '" ........................................................... " .... Airway. .. ... .. .... ....... .. ... .. .. . .... . .. . .. ......... . .... .. .. .... 4.l.2 ............................................................ ............... '" .. . .. .... . .... .. ...... . ... Introduction................................................................... ................................ . 4.3 Model Similitude ................................................................... .. 76 .......................................................... . ....................................................... . ........................................................... . ..................... 5.1 Basic Assumptions................................................................... 80 5.l.1 Geometry.................................................. Parameters............................................................... Case.................. ........................ ................................................................ , ........................ ................................. ............................................................. .................................. 6.1 Physical Model. . . . . . . . . ... . ... ...... .. ... .. .. . .... . . . .. . ... . .. . .. . . . . .. .. . ... . .. ..... 106 6.l.1 Limitations.................................................................... 106 6.1.2 Fluid Effects on Permeability........ .... .. .... ........ ...... .... .. ...... .... 108 6.1.3 Permeability - Particle Size Relationship........... . .... .. . .. ........ .. .. 6.2 Computational Fluid Dynamics Model ............................................ 112 6.2.1 Limitations ................................................................... , 112 ........................................................... Formation........................... Formation............................. .................................. 124 V111 7. CONCLUSIONS AND RECOMMENDATIONS 129 7.1 Conclusions 129 7.2 Recommendations for Future Research 131 APPENDICES A PERMEABILITY TEST DATA 133 B SAMPLE OF PERMEABILITY CALCULATIONS 138 C CALIBRATION OF CFD MODEL 141 D CALCULATION OF COAL INJECTION RATE 147 E PHASES INVOLVED IN SELF-HEATING PROCESS 150 REFERENCES 153 ix .. ... ... ... .. .. . . .................... Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 7.2 Recommendations for Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 131 APPENDICES A PERMEABILITY TEST DATA ... ... .. . .. .. .. ..... . . . . .. .. . . .. .. . . . ... .. .. . .. . ... .. 133 B SAMPLE OF PERMEABILITY CALCULATIONS ............. . .... . ....... ... 138 C CALIBRATION OF CFD MODEL . .. ... . .. . .............. ............ ............. . 141 D CALCULATION OF COAL INJECTION RATE ..... .. ................... .. .. .. 147 E PHASES INVOLVED IN SELF-HEATING PROCESS ... .. . . . . .......... . ..... 150 REFERENCES .. . . .... ... .. ... ... . . .. ..... ........ ... .. .. ......... .... . .. .. ..... .... .. . ......... 153 IX LIST OF TABLES Table Page 2.1. Parameters for SPONCOM Program 22 rocks tests .... crosscuts controls simulations model process studies Al. Water-based test data for 0.28-mm diameter samples 134 A2. Water-based test data for 3.22-mm diameter samples 134 Program........... . .... ......... ..... ... . ... .. . ......... 2.2. Experimental specific permeability of Utah coals . ... . ............ .. ... ........ .. 34 2.3. Experimental specific permeability of broken rocks... ....... ... ... .. ......... .. 35 3.1. Specific permeability for rock and coal samples using water-based tests. ... 50 3.2. Specific permeability for rock samples using air-based tests .. . ...... .. . .... ... . 55 3.3. Specific permeability for simulated gob materials . .... . ..... . .. . . .. . ........... . 57 4.1. Leakage percentage through crosscuts. .. . .. . .. . .. . .. .. . . . . . .. . . . . .. .. ... . ...... . . .. 63 4.2. Type of regulators used for ventilation controls. .. . . . . .. .. . . .. .. . . . . .. .. .... .. ... . 65 4.3. Input parameters used in Fluent for airflow simulations. .. .... ... .. ...... ... . ...... 69 4.4. Ventilation survey data for Mine A and Physical model.. . . . . ..... .. ..... .. ..... . 77 5.1. Input parameters used for a single-phase model .. .. .... .. .. ............ ...... .. ... 84 5.2. Input parameters used for a two-phase model ........ .. .... .......... .. .. .... ...... 86 5.3. Input parameters for the self-heating process.......... ........ .................. . .. 89 6.1 Summary of hot spot locations - Models A through D . . . ....... ........... .. ... 115 6.2 Specific permeabilities used for parametric studies. .. .. . . . . . .. . . . . .. . .. . . . . . ... . 118 6.3 Input parameters for injection simulations . ... . ....... . .......... ... .. ... . . ....... 125 AI. samples.......... .. ............... samples.... .... .. .... ........ ...... A3. Water-based test data for 5.74-mm diameter samples 135 A4. Air-based test data for 5.74-mm diameter rock samples 135 A5. Air-based test data for 7.73-mm diameter rock samples 136 A6. Air-based test data for 8.72-mm diameter rock samples 136 A7. Air-based test data for 9.71-mm diameter rock samples 137 B1. Sample data for permeability calculation 139 CI. Measured data for the physical model 142 C2. Calculated air velocity 144 C3. Reynolds Number (NR) of airflow 144 C4. Parameters used for validation in Fluent 145 C5. CFD modeling results 145 C6. Comparison of results - Physical model versus CFD model 146 Dl. Coal injection parameters 149 El. Primary and mixture phase properties 151 E2. Secondary phase and gob material properties 152 xi samples.......................... . samples........ .. .............. samples.. . ............ . ...... .. samples.. . ....... .. .. ........ .. samples.......... .......... .... B 1. calculation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. Cl. model.................................. ...... ..... velocity....................................... . ....... . ............... airflow.......................................... .... .... Fluent.. ........ ............................ .... ...................................... .. .... .. ...... ............ . model. ... ... . .. ... .. ..... parameters................................ .. .... ..... . ... ............. E 1. ........... . . ..... . .... . .................... . properties................................ ..... Xl LIST OF FIGURES Figure Page 2.1. Typical longwall mine layout used in the United States 7 2.2. Longwall equipment and coal transportation system 9 2.3. Typical U-tube ventilation system 11 2.4. Typical Y ventilation system 13 2.5. Typical Wrap-Around ventilation system 14 2.6. Schematic of fire triangle 16 2.7. SPONCOM result for the sample mine 23 3.1. Gob and strata zones in a longwall mine section 38 method 3.3. Water head-flow rate relationships for coal and rock samples 48 3.4. Longwall mine ventilation model at the University of Utah 51 3.5. The permeameter for air-based test 52 gob 4.1. Mine ventilation model schematic 59 model 4.3. Leakage percentage through four crosscuts 64 4.4. Type of regulator for physical model used in this study 66 4.5. The CFD model created in Gambit 69 2.1 . Typicallongwall ....... . . ...... ......... ... . . . . .. .. . . .. . . . .. . . .. . . .. system............................. .............. ....... system...... ............ .. .. .. .. .. ...... .... .. .... .... .. .... .. system........................................ . triangle.................... .. .................. .. ........ .. ........ . mine...................... .......... ...... ...... ...... ............ .......... ...... 3.2. Permeability test network for water-based method........................... .. .. 45 samples...... ... ... ..... Utah. . . . .... .. . .. .. . .. . . test.. .. .......................................... .. . 3.6. Particle size effect on broken rock sample permeability using air-based tests 56 3.7. Specific permeability distribution in gob. . ...... .. .... ... . . ...... . ... .. ......... .. 57 schematic............................................ ....... 4.2. Pressure gradients for the physical model.... .. .. .... ...... ...... .. .... .... ....... 62 crosscuts...................................... . study. .. .. . . .. ... . .. .. . .. . .. .. Gambit...... .. .. ...... ...................... ........... 4.6. Velocity contours for the sample model 71 4.7. Velocity contours for the U-section 71 4.8. Velocity profiles for two simulated openings 72 4.9. Static pressure contours for the sample model 72 4.10. Static pressure contours for the U-section 73 4.11. Pressure drop through porous medium 74 5.1. Model schematic for a typical longwall mine 81 5.2. Location of injection ports in the simulated mine gob 82 5.3. Base case of airflow distribution 90 5.4. Velocity vectors in gob for a bleeder system 92 5.5. Oxygen concentration contours for model A 93 5.6. Temperature contours for model A 94 5.7. Potential hot spot location for model A 94 5.8. Oxygen concentration contours for model B 96 5.9. Temperature contours for model B 96 5.10. Potential hot spot location for model B 97 5.11. Oxygen concentration contours for model C 98 5.12. Temperature contours for model C 99 5.13. Potential hot spot locations for model C 100 5.14. Velocity vectors in gob for a bleederless system 101 5.15. Oxygen concentration contours for model D 102 5.16. Temperature contours for model D 102 5.17. Potential hot spot location for model D 103 xiii model....................... . .. .. .......... ... .. V-section. . .. .. ....... .. . ......... .... ... ...... .......... openings..................... ........... .... . . .. . .. .. . ...................... .... , V-section.............. ... ... ... . . . .. ... . ..... .... medium.. ... . .. . ... .. . ... .. . . .. . . . . .. .. . .. . ... ... . . typicallongwall .... ...... .... ... ................ .. .. gob........... .. ........... ... distribution.. .. .. . ... .. . ... ................. . ...... .... ........ ......... . .... . .. . . .. ........... ... .. ' ........... . .. . . .... .. . ... . ....... .. . ................................................. .. .. ......... . . .. ..... . ................. . .. ' ...... .. ........... ........ . .. . ... ... ...... ... ............ . .... ... .... .. .... . .. .. .. . .. ..................... . .... . ...... ........... ............................... ... ... ' .......... .. ........ .. .......... . . .. ... .... ... . .. .. .. ... .. ................. .. .... .. . ....... , ................................. .. .. .... ....... .. ... ... .............. ...... ... .. ... ...... ... . .... ... ... ............... ........ .. .. . ... ... ... ..... . .. . . . .......... , Xlll 6.1. Fluid effects on rock sample permeability 108 6.2. Velocity contours through the extended permeameter Ill 6.3. Pressure contours through the extended permeameter Ill 6.4. Particle size effect on broken rock sample permeability 112 6.5. Oxygen concentration contours for case 1 119 6.6. Temperature contours for case 1 120 6.7. Oxygen concentration contours for case 2 121 6.8. Temperature contours for case 2 121 6.9. Oxygen concentration contours for model E 123 6.10. Temperature contours for model E 123 6.11. Temperature contours for model A with a vertical injection 126 6.12. Nitrogen concentration contours for model D with horizontal injection holes 126 6.13. Temperature contours for model D with horizontal injection holes 127 CI. Mine ventilation model schematic 143 Dl. Assumed gob shape and dimensions 148 xiv permeability. .. ... . .. . . . ..... .. .. . . .. .. . ... . ... .... .. .... . ... . .. .... .... . .. . . . .. 111 ...... . ............. ... . . .. 111 permeability. .. ..... . .. .. ...... ..... ...... . .. ... . ....... . .... .. .. ... .... ..... .. ......... ............ . . . . ... .... ... . .... . .. ...... . ... .. ... . .. ... . . .. ... ... .. ......... ...... .... . .. .... ....... . .. . ..... .... .. ... ... . .. . .... .. ... . . .. . . . . ......... ....... .... ...... .. .. ..... .. .............. . . . ...... . . . ... ... . .. . ..... . injection...... ..... ... . .. .. hole1 .. .... .. . .. C1. schematic. .. . .. . .. . ... .. .... . .... ...... .... .. ...... . ... ... D 1. ................................... ......... . .. XIV ACKNOWLEDGMENTS This thesis would not have been possible without the financial support of the William C. Browning Graduate Scholarship. I would like to express my sincere appreciation to my advisor, Dr. Felipe Calizaya, for his constant encouragement throughout this study and his invaluable advices on the research work. I gratefully acknowledge the helpful guidance, advice and comments of my thesis committee members: Dr Michael K. McCarter and Dr. D. Kip Solomon. Recognition is also due to Pamela Hoffman of the Mining Engineering Department for helping me with paperwork and administration, and Robbie for his assistance in performing the experiments. I also sincerely appreciate the assistance and friendship given by all graduate fellows of the Mining Engineering Department, Sonny Suryanto and his family, and Darrel Cameron for reviewing some sections of this thesis. Finally, special thanks are given to my parents, Jan and Elisabeth; my brothers and sisters, Elyezer, Daniel, Olivia, Yunita; and the last but not the least, Zilva. gratefully CHAPTER 1 INTRODUCTION Spontaneous combustion in underground coal mines has become a serious problem, particularly in the caved area (gob). Recent statistics have shown that approximately 17% of a total of 87 underground coal mine fires in the United States are attributed to spontaneous combustion (De Rosa, 2004). Spontaneous combustion results from a self-heating process in exothermic conditions. The accumulated heat, if not removed, is conducive to the rapid increase of temperature and may result in mine fires or explosions. The incidence of such fires is expected to increase in the future as wider panels and deeper coal seams are mined, and increased consumption of low rank coals becomes more prevalent. The effects of spontaneous combustion are often associated with loss of life and damage to property. The crucial step in reducing these effects is locating the ignition point of spontaneous combustion (hot spot). This study is an effort to obtain potential hot spot locations in mine gobs from the best gathered information. 1.1 Statement of Problems In the past decades, much has been written on the subject of spontaneous combustion. The characteristics of coal, including self-heating temperature and rank of coal, have been the subjects of many experiments. In the late 1980s, the Bureau of Mines CHAPTERl 2 performed extensive studies on this matter, developed an empirical expression of coal's self-heating temperature, and identified several contributing factors (Smith and Lazarra, 1987). It is widely accepted that lower rank coals are more susceptible to spontaneous combustion than higher rank coals mainly due to their innate properties. However, such studies merely appear to explain the role of coal properties in spontaneous combustion. Since this combustion often originates in the gob area, then the problem is more complex than just a rank-related phenomenon. The permeability of the gob material is the major contributing factor for the self-heating process. The resistances of the porous media change over time. This is the result of stress changes during the mining process. A better understanding of gob permeability must be developed to simulate the mine gob and determine the possible location of self-heating areas. However, a thorough knowledge of permeability is impossible because the gob is inaccessible. A number of studies have been devoted to determining the characteristics of gob material. Brunner (1985) constructed a model that was correlated to measured field data. Later research by Pappas and Mark (1993) included a photoanalysis approach and laboratory tests on gob material. A more recent study developed by Balusu (2002) used a tracer gas (SF6) to predict gob caving characteristics. However, the results of these studies are crude estimates of gob profiles and the problem calls for further investigation. In foreign countries, limiting the oxygen supply to the gob using a bleederless ventilation system has been chosen as the best alternative to control spontaneous combustion (Koenning, 1989). The regulations in the Unites States require longwall mines to utilize a bleeder system to dilute and remove gases generated in the gob (30 CFR section 75.334). The bleeder system, if not maintained correctly, may cause a perfonned penneability penneability detennine penneability detennining SF6) ifnot 3 substantial volume of coal left in the gob to be exposed to critical conditions under which sufficient quantity of air is supplied to promote oxidation, but inadequate to remove heat. The system may induce the self-heating of coal due to an improper utilization of ventilation air, thus creating favorable conditions to sustain spontaneous combustion. The ventilation practice of coursing air into the gob becomes more complex when the dynamic aspects of longwall mining are considered. The overburden depth and the mining rate determine the gob compaction behind the shields and the entry resistances to the airflow. In the gob, the caved material expands to fill the void and the roof pressure is transferred to the gob, thus reducing the gob porosity and increasing the airway resistances. This dynamic aspect has been barely considered in the past. The self-heating mechanism, the gob permeability, the required bleeder ventilation system, and the dynamic aspects of the longwall mining method have magnified the problem of spontaneous combustion, making it difficult to solve empirically. However, with the advent of supercomputers, the problem can be investigated easily in more detail. The application of numerical methods to simulate these phenomena has produced better and more accurate results. Computational fluid dynamics has been used successfully to model caved areas (Balusu et a l , 2002), gob wells (Ren and Edwards, 2000), and air leakage through stoppings and seals (Calizaya, Duckworth, and Wallace, 2004). Such simulation studies provided a better approximation of certain components of longwall mining but not the self-heating mechanism of coal. The final goal of this study is locating potential self-heating sources within a longwall gob. A series of experiments consisting of physical models, field investigations, and computer simulation exercises have been conducted to determine these locations. An evaluation performed in this study highlights aI., 4 the importance of using the Computational Fluid Dynamics (CFD) program to simulate all the involved phenomena in the self-heating process. 1.2 Thesis Overview This thesis develops a method used to simulate the location of a hot spot in a longwall mine gob ventilated by either a bleeder system or a bleederless system using CFD. Parameters such as gob permeability, panel geometry, self-heating coefficients, and ventilation system are the major factors that affect the development of a hot spot. These parameters are obtained from field surveys of existing mines and laboratory experiments. The effectiveness of both bleeder and bleederless ventilation systems to control hot spot are analyzed. As a reminder, the simulation results presented herein are valid to the conditions stated in this study. To simulate different gob geometries or ventilation systems, the base model should be modified accordingly. After collecting background information and defining the parameters, computer simulations are carried out to show the distribution of airflow inside the gob and to predict the potential locations of hot spot. In this step, four CFD models are built to represent a longwall mine with different gob lengths and ventilation systems. The results of stress redistribution on the gob are simulated by zones of different permeability. The gob zone adjacent to the face, filled with less consolidated material, is characterized by a porous medium of high permeability. This permeability decreases with the distance of the zone from the face; the further the distance, the lower the permeability. The permeability of each zone is determined based on laboratory tests, field surveys, and computer 5 simulations. Based on these data and information, the hot spot location is primarily defined by two parameters: temperature and oxygen concentration. A detailed analysis of the collected data, the geometry of the panel, and the parameters used in the simulations are presented; the locations of potential hot spots in the gob are identified and the effect of ventilation systems and gob characteristics on these locations are discussed. Finally, some conclusions and recommendations for future work in this area are presented. infonnation, CHAPTER 2 BACKGROUND AND LITERATURE REVIEW 2.1 Longwall Mines in the United States Longwall mining is the most efficient method of mining coal. The most recent report issued by the U.S. Energy Information Administration shows that longwall mines accounted for 49% of the 2006 nation's underground coal output. Today, approximately 51 underground coal mines in the United States utilize the longwall method. If the trend for more energy sources prevails, there will be a higher demand for coal, thus calling for a longer and wider panel to increase recovery and decrease the cost. The longwall method is utilized for horizontal or nearly flat seams that have relatively uniform thickness and are fairly free from discontinuities. According to the Code of Federal Regulations in the United States, a three- or four-entry panel in development is used in longwall mines, although a two-entry panel is allowed under special circumstances. A typical longwall layout of a three-entry system is shown in Figure 2.1. The geometry of a panel is generally 330 m (1,000 ft) wide and 3100 m (10,000 ft) long. Development work usually requires 9 months to 1 year, depending on the size of the panel. In contrast to the advancing-type method used in Europe, a retreating method is widely used in the United States. With this method, coal extraction starts from the farthest end of the panel and proceeds toward the main entries. longwalllayout starts from the farthest end of the panel and proceeds toward the main entries. •• •• ••••••••! • • • • • • • • •D • • • • • • Main entries Figure 2.1 Typical longwall mine layout used in the United States Mining ;t----, direction ~ Intake air ...-- Return air ~ Bleeder air Belt conveyor .......- Pennanent stopping D Typicallongwall Seal R Regulator """'* Overcast C Curtain entries The development entries are connected at the back of the panel by another set of The entries are connected in regular intervals by crosscuts and separated by a number of pillars with an average dimension of 24 m (80 ft) wide and 50 m (165 ft) long, depending on seam and cover conditions. The set of entries used for transportation of coal, workers, and equipment is called a "headgate." These entries are also used to deliver intake air. On the opposite side of the panel, a "tailgate" is used for return air. The main equipment used to extract coal from the face is illustrated in Figure 2.2. It includes a shearer going back and forth across the face, a set of shields, and a chain conveyor. For an average panel of 330 m wide, a continuous trip of coal cutting from headgate to tailgate takes about 45 minutes. As the shearer moves along the face, the cutting drums detach coal from the face. The broken fragments are gathered and pushed onto the chain conveyor by a ramp plate as the shields advance forward. A chain conveyor transports the broken coal to a loading point on a stage loader and to a belt conveyor, which delivers coal to surface. The support system, a side-by-side arrangement of hydraulic shields, is used not only to hold the roof during the extraction and push the face conveyor, but also to provide a safe workspace. Today, longwall mines utilize more than 100 shields per panel. After a panel has been mined out completely, the relocation of equipment takes from 3 to 4 weeks. This is the major regular delay to production in longwall mining. With this method, the overlying strata are allowed to cave behind the shield as soon as the coal is extracted. The caved area is later referred to as the "gob." The void due to coal seam extraction produces abutment pressure heaped up around the gob. Under this condition, 8 entries called "bleeder entries." Each entry is about 3 m (10 ft) high and 6 m (20 ft) wide. of24 extraction produces abutment pressure heaped up around the gob. Under this condition, Figure 2.2 Longwall equipment and coal ttrraannssppoorrttaattiioonn ssyysstteemm ((aafftteerr OOiittttoo,, 11997799;; RRaammaannii,, 11998811;; aanndd PPeenngg,, 11998844)) 10 the caved area expands laterally to the nearest entry of outward gob (Peng 1985). The area is mainly filled with coal, caved-in roof, and heaved-up floor materials representing media with different porosities. Its consolidation behavior changes over time as a response to changes in stress pattern. It is accepted that the gob further from the face becomes more consolidated over time and has less porosity than that behind the shields. 2.2 Ventilation Systems for Longwall Mines The ventilation system is described as the lifeblood of underground mines. The system ensures safe working conditions in the mine by providing airflow in sufficient quantity and quality. In addition, ventilation air also dilutes contaminants and hazardous gases to safe levels. Importantly, the mining and geologic conditions need to be examined to determine the proper ventilation system. The primary function of a ventilation system in an underground coal mine is to dilute methane gas to less than 1% by volume and keep the respirable dust levels below 2 mg/m3 in all work areas. For longwall mines, various ventilation systems have been developed. In the United States, three systems are commonly applied: U-tube, Y system, and Wrap-around (McPherson, 1993). It is a common practice to use the same system for the entire panel life. The main features of each system and their layout are presented in this section. The legend shown in Figure 2.1 applies to all longwall mines. 2.2.1 U-Tube System In the U-tube ventilation system, air is brought to the face from the headgate and is exhausted through the tailgate. The airflow schematic is shown in Figure 2.3. This sufficient 1 % mglm3 alliongwall • • • • • • • • • • • 0 0 • • • • • • Figure 2.3 Typical U-tube ventilation system system is preferred to limit the leakage flow to the gob and reduce the number of seals. It is used in Australian and European mines. A modified U-tube ventilation system is used in the United States. This system is sometimes referred to as "bleederless" system. In this modified system, seals are constructed in entries and crosscuts to isolate the gob. Air is directed up the headgate entries, across the face, and back along the return. The entry in the headgate adjacent to the longwall panel can be used either as intake or return. Most mines use this entry as secondary intake since it is also the belt entry. Only two entries in the tailgate are 11 12 available for ventilation since the outer entry is caved during mining of the previous panel. These two entries are used to exhaust the return air. This system is considered simpler and more cost-effective compared to the "Y system" related to the number of utilized seals. It is preferred in mines with the potential problem of spontaneous combustion. The main disadvantage of this system is that in gassy mines, methane could accumulate at the back corner of the gob in the tailgate side. Therefore, this system is more suitable for non-gassy mines. 2.2.2 Y System The Y system, sometimes called a "bleeder" system, utilizes both panel entries outside the face as intakes and a tailgate bleeder as return. Figure 2.4 shows a typical setup of this system. The fresh air flushes the face from the headgate to tailgate, and the contaminated air exits through the outside return entry of the tailgate. This system also allows some portions of fresh air to flow across the gob to dilute gasses generated inside the caved area. It also provides an additional quantity of fresh air to the face near the tailgate. It is used for gassy mines to control the gas concentrations in the tailgate corner. A bleeder fan installed on the surface as exhauster creates the pressure difference to ventilate the panel. Despite the fact that most of the longwall mines employ this system, the Y method is less suitable than other methods to control spontaneous combustion in mine gobs. If the air flushing the gob does not have enough velocity to carry away the heat of the self-heating process, it could be trapped inside the gob, creating "dead-lock" pockets of air that would initiate a continuous oxidation of coal. comer comer. of air that would initiate a continuous oxidation of coal. Bleeder fan on the surface 9 • • ' • • • • • • •• •?r_p n n n rj • Ci • [ f • Ci • [ • C: • [ • [ • [ Li I • D GOB GGG]] ] ] ] a c GOB _=DT[!JC: F^GD D D D D D D Q D • -e Figure 2.4 Typical Y ventilation system Besides the spontaneous combustion problem, another disadvantage of the Y system is that the effectiveness of this method relies on the conditions of bleeder entries. In practice, these entries will become high-resistance airways as the panel retreats. The overburden weight could causes roof and pillar failures. The difficulties to maintaining the initial entry conditions may extend to other entries and increase the airway resistances, thus demanding greater pressure of the bleeder fan. In some cases, additional pillars are set up to keep the return paths open, thus reducing the quantity of air circulated through the face. However, the presence of pillars may increase the overall resistance of the mine, thus decreasing the total flow rate. 13 ~====;DDDDDDDD through the face. However, the presence of pillars may increase the overall resistance of the mine, thus decreasing the total flow rate. 14 Figure 2.5 Typical Wrap-Around ventilation system 2.2.3 Wrap-Around System In the wrap-around system, the bleeder entries are located at the back of the mined-out panels. These entries are used to ventilate the gob. Similar to the Y-type system, a bleeder or exhaust fan is used to create the pressure difference. Figure 2.5 shows a typical layout of this system. Permanent ventilation controls such as stoppings and seals are required to isolate the gob. The entries of the headgate are used as intake and escape paths. The air is then split. Part of it is used to ventilate the face, and the remainder directed through the gob and the bleeder entries. The major advantage of this system is that the distance between the fan and the panel decreases as the panel retreats, Y -thus increasing the quantity at the face. However, the flow rates through the gob and bleeder entries may suffer due to the difficulties of maintaining narrow entries, especially under coal seams of deep cover. The success of all ventilation systems depends on the geologic conditions and mining practices. Well-maintained entries and regularly inspected control devices are essential to provide all workplaces with the required quantities of air. Ventilation simulators such as VnetPC can be used to optimize the design parameters. VnetPC, a commercial program developed between the 1960s and 1990s by McPherson, allows users to evaluate alternatives and select the most efficient one (McPherson, 1993). An evaluation of alternatives is crucial to ventilation planning since longwall mining is a dynamic process. However, the application of such a simulator is restricted to fixed resistance networks. Longwall mine gobs are difficult to simulate, though some efforts of doing so have been reported (Brunner, 1985; Prosser and Oswald, 2006). Finite volume programs such as Fluent are now used to study the flow distribution in the gob. This will be discussed in more detail in the following sections. 2.3 Spontaneous Combustion in the Gob Spontaneous combustion is a major safety concern in underground coal mines. It accounts for approximately 17% of the total number of fires recorded in the United States since 1990. Spontaneous combustion of coal is most likely initiated by a self-heating process. This process is well described as the temperature rise due to oxidation of coal. This process is a complex phenomenon involving a wide range of physical and chemical processes. In longwall mines, the problem becomes complex mainly because the 15 16 Fuel Figure 2.6 Schematic of fire triangle processes take place inside the gob, thus restricting field investigations. The processes, contributing factors, and spontaneous combustion control methods are described below. 2.3.1 Mechanism of Self-Heating Process The spontaneous combustion follows the principle of the fire triangle, as shown in Figure 2.6. The legs of the triangle represent three elements of fire. These are oxygen, fuel, and ignition source. In the self-heating process, carbon, pyrite, and other combustible matters left in the gob represent the fuel. The oxygen element is delivered to the gob by the ventilation system, influenced by mining and geologic conditions. The contact of oxygen and combustible matters initiates the exothermic oxidation of coal. The rapid increase of heat, at last, can ignite the fuel and eventually develop a fire. Today, it is well accepted that the interaction between oxygen and coal substances is the main cause for spontaneous combustion. There has been much diversity of opinion about the tendency of various components of coal to react with oxygen. However, it is agreed that some factors such as pyrite, moisture, and bacteria play a secondary role to the self-heating of coal. Therefore, they are not included in this study. ccmbustion playa Ignition 17 0 2 -> C 0 2 65°- CQ2 C -> 2CO heat (100°- 150°C) (2.1) (2.2) The presence of pyritic sulfur, FeS2 , can initiate the spontaneous heating of coal (Banerjee, 2000). Such a process is represented by: 2FeS2 7 0 2 16H20 ^ 2H2S04 2FeS04 • 7 H 2 0 316 kcal (heat) (2.3) This reaction, however, is not that frequent because the amount of pyritic sulfur in coal is usually less than 1%. As indicated in Equations 2.1 and 2.2, the carbon (C), constituent of coal, reacts with oxygen ( 02 ) within the temperature range of 65 to 94 C producing carbon dioxide (C02 ) and heat. Subsequent reaction of C 0 2 and C at higher temperature generates CO and heat. Both processes occur in exothermic states. The process temperature, once above o 100 Coal oxidation occurs as coal comes into contact with air. The process is suitably explained in terms of heat transfer, chemical surface absorption, and energy balance related to inherent properties of coal. According to Wang et al. (2003), the oxidation process of coal involves oxygen transport to the surface of coal particles, chemical interaction between coal and oxygen, and release of heat and gaseous products. Chamberlain and Hall (1973), and also Cliff and Bofmger (1998) have confirmed the complexity of such phenomena; however, the overall reaction can be simplified using the following reactions as suggested by Mitchell (1996): Bofinger C + O2 -7 CO2 + heat (650 _ 94°C) CO2 + -7 + 1000 _ FeS2, 2FeS2 + 702 + 16H20 -7 2H2S04 + 2FeS04 . 7H20 + 1 %. 02) of65 94°C02) CO2 100°C, begins to accelerate, though the heating can still be interrupted. The reaction 18 process accelerates as temperature climbs beyond 150 C and then a spontaneous ignition ensues. The temperature at which the coal reaches thermal runaway is called the self-heating temperature (SHT) (Smith and Lazarra, 1987; Koenning, 1989). Equations 2.1 and 2.2 clearly imply the dependency of the reaction on temperature. The relationship between reaction rate and temperature obeys Arrhenius' law, which is given by: Rate = A [exp] (-E/RT) (2.4) where A = pre-exponential factor, K s"1 E = activation energy of coal, kJ mol"1 R molar gas constant, 8.314472 JK"1 mol"1 T = temperature, K Wiemann (1985), Smith and Lazarra (1987), and Mitchell (1996) noted that the rate of coal oxidation does not produce a significant rise in temperature, as long as the oxygen concentration in the air mixture is below 5% by volume. This finding, together with SHT values, is used in the following sections to explain the hot spot occurrence. 2.3.2. Requisites for Hot Spot Occurrence The term "hot spot" used in this study refers to a potential location for an ignition source due to spontaneous combustion. Hot spot is a result of the self-heating process. This condition is characterized by a high temperature produced by continuous oxidation. Energy released from this exothermic reaction is in the forms of heat and reaction 150°= S-1 = morl = JKI morl ofthe 19 products. Exothermic reaction implies that the higher the temperature, the more rapid the reaction. Once the reaction temperature climbs above 100 C, it progresses so intensely that it produces spontaneous combustion (Mitchell, 1996). This finding suggests a o minimum temperature of 100 C for hot spot occurrence in the simulation. Several other experiments of thermal runaway beyond coal's SHT in oxidation present a solid foundation for this study. Oxygen, one of the two reactants in Equation 2.2, also represents an important factor to the oxidation process. A minimum supply of oxygen should be available to ensure continuation of oxidation. The oxygen concentration must be at least 5% by volume in the air mixture. Methane, gases from oxidation, and the volume of fresh air supply determine the oxygen concentration in the gob. These two parameters, temperature and oxygen concentration, are used to determine a hot spot. For simulation purposes, the area where temperature and oxygen o concentration are above 100 C and 5%, respectively, obviously becomes a hot spot. Other factors mentioned in section 2.3.4 such as moisture content are included in simulating the hot spot under input variables of CFD. Chapter 5 describes the details of these variables. 2.3.3. Prediction of Spontaneous Combustion Potential The self-heating temperature was proved to have a direct relationship with the rank of coal (Chamberlain, 1973; Smith and Lazarra, 1987; Koenning, 1989). It is widely accepted that spontaneous combustion of coal is a rank-related phenomenon, meaning that young coals such as sub-bituminous or lignite are more susceptible to spontaneous combustion than higher rank coals such as anthracite. 100°minimum temperature of 100°C for hot spot occurrence in the simulation. Several other experiments of thermal runaway beyond coal's SHT in oxidation present a solid foundation for this study. Oxygen, one of the two reactants in Equation 2.2, also represents an important factor to the oxidation process. A minimum supply of oxygen should be available to ensure continuation of oxidation. The oxygen concentration must be at least 5% by volume in the air mixture. Methane, gases from oxidation, and the volume of fresh air supply determine the oxygen concentration in the gob. These two parameters, temperature and oxygen concentration, are used to determine a hot spot. For simulation purposes, the area where temperature and oxygen concentration are above 100°C and 5%, respectively, obviously becomes a hot spot. Other factors mentioned in section 2.3.4 such as moisture content are included in simulating the hot spot under input variables of CFD. Chapter 5 describes the details of these variables. 20 A number of laboratory tests and computer simulation exercises have been developed to predict the propensity of coal to spontaneous combustion. However, none is generally agreed upon and used universally (Cliff and Bofmger, 1998). There are many unanswered questions about the reliability of such tests to represent real conditions because the spontaneous combustion problem is not merely a coal rank problem. It also depends on other factors such as geologic condition, mining method, and mine ventilation. A most recent report on spontaneous combustion justified these facts (Cliff and Bofinger, 1998). However, a global fact shown in these experiments indicates that spontaneous combustion may be a significant cause for mine fires and explosions. 2.3.3.1. Development of SPONCOM Program In the 1990s, the U.S Bureau of Mines developed a ranking method to predict the combustion propensity of coal based on the temperature. The experiment was carried out to determine the minimum temperature at which coal starts generating heat that is 70 considered to have a high propensity to spontaneous combustion; those with temperatures o t o between 70 and 100 C, a medium propensity; and those with temperatures above 100 C, low propensity. In general, the rank of coal is agreed to have a high correlation with this propensity. According to Smith (1992), if the coal is lignite or sub-bituminous, the coal is automatically assigned a high spontaneous combustion potential. If the rank is anthracite, the coal is a low spontaneous combustion potential. For bituminous coal, Smith suggested that the self-heating temperature can be approximated by: Bofinger, ofSPONCOM detennine retained until flaming. Coals with minimum self-heating temperature of below 70°C are between 70 and 100°C, a medium propensity; and those with temperatures above 100°C, low propensity. In general, the rank of coal is agreed to have a high correlation with this propensity. According to Smith (1992), if the coal is lignite or sub-bituminous, the coal is automatically assigned a high spontaneous combustion potential. If the rank is anthracite, the coal is a low spontaneous combustion potential. For bituminous coal, Smith suggested that the self-heating temperature can be approximated by: SHT, °C = 139.7 - [6.6 x 0 2 , %(DAF)] 21 (2.5) where 0 2 is the oxygen percentage in the coal on a dry-ash free basis (DAF). As indicated, the equation shows a correlation between the combustion risk through self-heating temperature and the oxygen content. Based on field and laboratory studies, the former U. S. Bureau of Mines developed an expert system called SPONCOM (Smith et al., 1996). This program, written in ANSI C language, is designed to assess the spontaneous combustion potential of coal based on coal properties, geologic conditions, and mining practices. Since the mining methods used in the United States are longwall and room-and-pillar, this program is limited to those methods. The program output includes the spontaneous combustion potential of the coal, its rank, and its self-heating temperature. The results of this program are crucial for mine operators at the planning and production stages. 2.3.3.2. SPONCOM Program - A Case Study This section demonstrates the application of SPONCOM to assess the spontaneous combustion of coal samples taken from a longwall mine located in the 3 m and a cover annual production is 7.9 Mt of clean coal. For a comprehensive analysis, data are also gathered from references and reports conducted by the third-parties such as USGS core drilling analysis, geologic properties, etc. (www.energy.er.usgs.gov). Several °c = O2, O2 self­heating a1., western U.S. In this mine, the coal seam has an average thickness of ranging between 335 m and 700 m. This mine is in production since 1941, initially as a room-and-pillar coal mine and more recently as a longwall operation. Currently, the coa1. 22 Table 2.1 Parameters for SPONCOM Program 1. Coal Properties (as received): 3. Geologic Properties: Proximate Analysis: Concentration rating of: Moisture (%) 6.32 Joints 50 Volatile Matter (%) 35.43 Channel Deposits 50 Fixed Carbon (%) 45.92 Dikes 0 Ash (%) 12.33 Clay Veins 0 Ultimate Analysis: Coal seam thickness (ft): Hydrogen (%) 5.12 Max. 19.5 Carbon (%) 64.28 Min. 6.7 Nitrogen (%) 1.16 Seam gradient (%): 13.1 Sulfur (%) 0.5 Max. 3.0 Oxygen (%) 16.21 Min. 1.0 Ash (%) 12.33 Average 2.0 BTU/lb 11,302 Overburden range (ft): 1001-1500 Pyritic sulfur 0.13 Presence of rider seam in roof No Coal contains impurities such as resins Yes Presence of rider seam in floor Yes Coal bed show signs of previous oxidation Yes Distance from coal bed (ft) 4 Friability rating (0 - 100) 25 Presence of pyrite in roof No Presence of pyrite in floor No 2. Mining Conditions Face cleats (Number/ft) 10 Rating of floor heave in the mine entries 0 Butt cleats (Number/ft) 10 Rating of rib sloughage in mine entries 25 Presence of geothermal sources No Ambient temperature of mine air ( F) 78 Presence of burn zones Yes Have you encountered self-heating events in: Presence of significant faults Yes Gobs/worked out areas No Entries or gateroads No 4. Mining Practices Pillars No Mining technique used: Longwall Other in-mine areas No Average seam thickness (ft) 8.3 Transport No Longwall production rate 22700 Stockpiles or silos No (ton/day) Quantity of ventilating air Longwall rate of 75.0 on face near headgate (cfm) 50,000 advance/retreat (ft/day) in tailgate return (cfm) 5,000 Longwall panel dimension: Caving height of gob (ft) 15.0 width (ft) 906 length (ft) 18,240 assumptions are also made based on experience and field survey data (Calizaya and Miles, 2006). Table 2.1 lists all parameters used in the program. BTUllb (Number/(Number/bum 23 m Jsl«l Company Name : Company X User Name : SL Date : N/ft Mine : Mine X Coalbed : N/ft < 70 deg C Coal Rank : High v o l a t i l e B EitrntrtTrot*©..;;/^ S e l f - H e a t i n g Temperature :/1>4 deg C "X Spontaneous Combustion P o t e n t i a l : HIGH ) The f o l l o w i n g parameters were i d e n t i f i e d as can i n c r e a s e the r i s k of s e l f - h e a t i n g: f a c t o r s that RATING RISK P r e s s any key Figure 2.7 SPONCOM result for the sample mine The output of the SPONCOM program is shown in Figure 2.7. An evaluation of these data reveals that coal in this mine is highly susceptibility to spontaneous combustion. The coal rank is classified as high volatile B with a self-heating temperature of 54°C (less than the critical temperature of 70°C). This result is crucial to determine the appropriate ventilation system in planning and also evaluating the effectiveness of the current system. 2.3.4. Contributing Factors to Self-Heating Process The problem of spontaneous combustion results from the exothermic oxidation of coal. The oxidation process depends on intrinsic and extrinsic factors. The intrinsic factors are represented by the inherent properties of coal, including self-heating temperature, pyrites and moisture contents, volatile matter, friability, and particle size. 54 DC 70DC). sub-bituminous self-heating temperatures below 70°C. Pyrite content was initially suspected to be a It exposing larger surface area to the air (Banerjee, 2000). of-wetting of moisture. For coals capable of self-heating, the heat of wetting can be greater than of oxidation (Kuchta et a l , 1980). If moisture drains, adsorbed gases will replace the void space. If oxygen is adsorbed, more heat must be 24 These combustible properties influence the oxidation and heat generation process leading to a fire. The extrinsic factors are represented by the ventilation system, geologic conditions, and mining practices. Since the properties of coal are unalterable, the problem of spontaneous combustion may be solved by providing a good ventilation system compatible with the mining practice. The fire triangle, as illustrated in Figure 2.6, requires both intrinsic and extrinsic factors to initiate a fire. The absence of either one may stop the process, at least temporarily. The self-heating is found through experiments to vary with the rank of coal. Coals most susceptible to self-heating are found in the low-rank classification, namely the sub­bituminous and lignite, containing high pyrite, moisture, and oxygen contents which have major constituent to initiate the oxidation. Later, it was found that pyrite only enhances the reaction of the coal by generating heat during the oxidation process. may assist the oxidation of carbonaceous matrix by breaking down coal into smaller fragments and The amount of moisture contained in coal is also a contributing factor to oxidation. Groundwater and extraneous moisture known as adventitious moisture are readily evaporated. Moisture held within the coal itself, known as inherent moisture, is analyzed and shown in Table 2.1 (Ward, 1984). In the oxidation process, the heat-of­wetting stage begins with adsorption evolved heat from moisture can be as much as 2.5 times greater than in dry air, and the aI., al., confirms surface self-heating left in the gob may also increase the oxidation rate. In addition, timber sets and steel often substantial volume of broken coal to be oxidized. In foreign countries, a conventional bleeder system has been recognized as being hazardous in a mine with high spontaneous dissipated (Cliff et aI., 1996) and the system grows to an exothermic condition and induces potential for combustion. 25 The surface area of coal plays an important role in the oxidation process. Winmill (1915-16) observed that the rate of oxidation increased with the fineness of coal. A study conducted by Smith and Lazarra (1987) using an adiabatic heating oven also confirms this statement. The self-heating process potential increases with the increase of surface area or decrease of particle size. Mining practices may contribute to self-heating mainly by extending the production period and increasing the combustible matter left in the gob. The mining rate determines the incubation period for a particular mine gob in which self-heating of coal may develop. A reduction in mining rate, often caused by frequent delays, gives sufficient time for heat buildup in the gob. The location of critical velocity where the self­heating tends to occur is predicted to be near the face (Koenning, 1989). A rapid retreat mining avoids the development of spontaneous combustion. The combustible materials wrecks may cause voids inside the gob, creating paths for airflow. Air leakage is often cited as the cause for initiating the spontaneous combustion process (Koenning, 1989). Another extrinsic factor that contributes to spontaneous combustion is the ventilation air. Current regulations require the use of a bleeder ventilation system for longwall mines. The system allows the ventilation air to travel through the gob and remove harmful gases and the heat of oxidation. This injection of air may cause a self-heating NaCl CaCl. application depends on the borehole depth, injection pressure, and the presence of fissures in the seam. It is then expected that this substance will protect the coal from 26 combustion potential (Oitto, 1979). The bleeder system may prevent the self-heating process if the quantity of air course passing through the gob is large enough to remove the heat of oxidation. However, the difficulty of supplying sufficient airflow quantity to all gob areas may result in preferable local conditions for a continuous self-heating of coal and heat buildup. Air leakage through the stoppings is another factor that contributes to the self-heating process. The leakage flow can be minimized by using heavy duty doors and regulators. In panels with severe geologic structures, faults and joints provide courses for airflow. These also contribute to spontaneous combustion. 2.3.5. Control Methods Early detection of spontaneous combustion is a preventive method. Monitoring combustion products of CO, CO2, and the oxygen deficiency in the gob is carried out to detect a mine fire. However, this practice may not be very effective in early prevention of fire. Time is not a friend in a mine fire (Mitchell, 1996). Currently, there are four control methods to reduce the risk of spontaneous combustion: utilization of an inhibitor, inertization, mining practices, and a ventilation system. An inhibitor is a chemical substance that can be used to prevent the physical contact between oxygen and combustible materials. The inhibitors used in mines include inorganic chlorides such as NaCI and CaC!. Using the same principle of protecting steel products from corrosion, an inhibitor is injected in liquid form into coal seams through a borehole before mining. This substance propagates to the coal seam. The success of this from 27 dioxide for safety reasons (Banerjee, 2000). San Juan Coal mine is the only longwall mine that continues to apply gob inertization in the United States. The mine requires a continuous supply of 0.007 m3 / of nitrogen. Pipes of 100 - 150 mm in diameter are normally used to deliver nitrogen gas into the gob from crosscuts (Bessinger et al., 2005). exponential gives a chance for the development of a hot spot. spontaneous ventilation air to pass through the gob without any chance for heat buildup. The bleederless system should be considered if the resistance to airflow is so high that it can being oxidized during and after the panel extraction. In addition, a cover of limestone or bentonite spread in a foam-liquid solution reduces the surface exposed to air, thus reducing the oxidation of coal (Chamberlain, 1973; Banerjee, 1985). Inertization is the process of injecting an inert gas into the gob to replace the oxygen content in the affected area. Nitrogen and carbon dioxide are the common inert gasses used for this purpose. In longwall mine gobs, nitrogen is preferred to carbon m3/s aI., The development of wider and longer panels increases the mining period, providing more time for coal oxidation. This extension allows for a longer incubation period (Koenning, 1989). Hazardous situations may result due to the exponential relationship between time and temperature rise (Wang and Dlugogorski, 2003). A little increase in time could cause a thermal runaway and result in a fire. A larger panel also An adequate ventilation system can be used to reduce spontaneous combustion in the gob. If bleeder or wrap-around entries are used, oxygen is allowed to percolate through the gob, thus supporting the oxidation of coal. If this condition is allowed to occur for a long period of time, oxidation may result in heat buildup and spontaneous combustion. Therefore, this system should be used only when the gob condition permits self-heating. However, the self-heating of coal can still occur near the face. adequate ventilation design can reduce the number of potential locations of heat buildup without neglecting its al., al., al., from field studies. One of the models showed that the oxygen distribution in the gob ranging from 2% to 2 1 % . A low concentration of up to 2% was detected in the consolidated zone. This zone was characterized by low insitu permeability. Although no explanation was presented on this permeability, the value used was about 1 x 10"1 7m2 28 create critical conditions for self-heating of coal in the gob. In the bleederless systems, the gob is isolated by means of seals and stoppings, thus reducing the risk of self-heating. An main function in providing fresh air to working areas (Hartman et aI., 1997; McPherson, 1993; Banik et aI., 1994; Cliff, Rowlands, and Sleeman, 1996). 2.4 Spontaneous Combustion Studies Using CFD Many studies have been done on spontaneous combustion, but only a few utilize Computational Fluid Dynamics (CFD) software in their investigations. CFD has initially been used in a wide variety of fluid mechanics-related engineering applications. It provides numerous options for modeling laminar and turbulent flows, studying multiphase fluids, representing complex chemical reactions, etc. Often, results are achieved by applying user-defined FORTRAN subroutines. For combustion studies, CFD is a powerful tool to simulate conductive, convective, and radiative processes. In Australia, a CFD modeling investigation was carried out by the Commonwealth Scientific and Industrial Research Organization (CSIRO) to develop airflow patterns for spontaneous combustion control (Balusu et aI., 2002). The studies involved CFD modeling, validation, and calibration of initial models using data obtained 21 %. 10-17 m2 U.10"8 x 10"1 4 m2 . permeabilities for the five zones were determined to be between 1 x 10"9 and 5 x 10"1 2 m2. In this study, the preferable condition for spontaneous combustion was analyzed in terms similar to insitu coal permeability determined for western coals by Hucka (1992). This information is substantial to determine the susceptibility of coal to spontaneous combustion. Yet, the study did not specify areas with potential heat buildup. 29 In the u.K., Lowndes et al. (2002) also used CFD modeling to improve the design of surface gob wells for degasification while minimizing the leakage of air, which may lead to the danger of spontaneous combustion of coal. Importantly, the permeability of gob material was discussed in this study. An experimental method was developed for measuring the permeability of scaled-down rock fragments under increasing stress. FLAC, a two-dimensional finite difference modeling package, was used to simulate strata behavior in association with permeability changes. The permeability used in this simulation ranged from 1 x 10-8 to 1 X 10-14 m2 • Three 0.18-m boreholes spaced 150 m apart with a suction pressure of -4,000 Pa were found to yield the optimum results for the degasification study. Even though they have no direct correlation with spontaneous combustion, these results can be taken into consideration when simulating inert gas injection to reduce oxygen level in the gob. Pressurized air or inert gas can be used to reduce or eliminate the heat buildup in the gob due to oxidation. In the U.S., a recent study conducted at the National Institute for Occupational Safety and Health (NIOSH) utilized CFD to investigate the self-heating process of coal. Yuan et al. (2006 - 2007) studied the ventilation flow paths in the gob and the likelihood of spontaneous heating in longwall gob. Gob permeability, as the important input variable for simulation, was obtained from FLAC. Using the results of the FLAC model, the 10-9 10-12 m2 • confirmed often review of porous medium, including particle-size distribution, porosity, and permeability, of critical velocity. Critical airflow is defined as insufficient airflow to remove the heat due to oxidation, but sufficient to maintain the oxidation process. This study confirmed the existence of a critical velocity zone behind the shields in the gob for a bleederless system. In addition, for a three-entry bleeder system, the critical velocity zone may also occur at the back end of the gob. 30 Although these studies outlined the areas with spontaneous combustion potential, they did not specify the location of the hot spots in the gob. Besides critical velocity, other parameters such as oxygen concentration and temperature should be considered in the simulation study. 2.5 Porous Medium Porous medium simply can be defined as the solid or loose body that contains open cavities. A solid body refers to a packed form of bound material while a loose body consists of granular particles. The interconnected pores in a porous system are often called effective pores. In practice, the effective pores play an important role in fluid flow through porous media. The detailed description of porous medium is sometimes intuitive, so that the exact properties are difficult to describe (Scheidegger, 1957). A statistical as described by Bear (1972), is necessary to understand mine gob characteristics. 2.5.1. Particle Size Distribution Granular materials are best described by their particle-size distribution. It is generally accepted that irregular material particle size cannot be easily defined as a However, using this method, particles with lengths larger than the sieve opening may slip through and alter the particle distribution. Side assessments are necessary to eliminate such a possibility, for example, by screening the material twice with the same sieve. = -z- 100 V n = VV = volume VT = grains, their shape and size distribution (Bear, 1972). Depending on their arrangement, 31 sphere or cube. Each particle shape is unique. The measurement results depend on the particle dimensions and the method of measurement. For particles larger than 0.06 mm, sieve analysis can be used to determine the size distribution (Bear, 1972). In sieve analysis, a pile of material is forced to pass through a sieve of a certain opening size. A number of sieves are used to define the particle distribution graphs. 2.5.2. Porosity The major properties required to simulate a mine gob are porosity and permeability. Porosity is defined as the ratio of void volume to the total volume of a packed body. Mathematically, it is given by: where the porosity Vv the pore volume the total volume n = Vv x 100 % VT (2.6) For consolidated materials, the porosity depends on the degree of cementation, while the porosity of unconsolidated or loose material depends on the packing of the sized Compaction specific darcy millidarcy 10 . Q = C A Ah L m3 /s m/s m Ah 32 non-uniform-sized particles may change the porosity of the total volume. Small particles may occupy the space between the large particles, and reduce the porosity. Compaction and consolidation are other factors that affect porosity. In the case of gob material, compaction is caused by the pressure of overlying strata varying with the depth of overburden and age of the gob. 2.5.3. Specific Permeability Another parameter used to characterize the porous media is the specific permeability, sometimes just called permeability. This parameter indicates the ability of consolidated or unconsolidated material to transmit fluids. Specific permeability is of great importance in determining the airflow behavior in the gob. A common unit for permeability is the (D), or more commonly the (mD), in which 1 darcy equals 9.87 x to- 13 m2 • Darcy's law is expressed by: where Q airflow rate, m3 Is !1h Q=CA C hydraulic conductivity, mls A cross sectional area of porous sample, m2 Llh pressure difference between two points, m L = length of porous sample, m (2.7) k 2.8) 7 k = m2 y = m2 = m modified d2 n3 k* = - (2.9) 180 (1 - n)2 where = m2 dm = uniform-specific 33 Equation 2.7 is restricted for a laminar flow condition. The proportionality constant, C, is also known as Darcy's velocity. Based on this coefficient, the specific permeability is given by: = where specific permeability, m2 f.1 C r specific weight of fluid, N/m2 Il dynamic viscosity of fluid, Ns/m2 (2 .8) Since porosity and specific permeability measure the structure of porous media, they ought to be related. Many investigators have studied the relationship between these two parameters. An empirical correlation was proposed by Carman in 1937. A modified version of this work is known as the Carman-Kozeny equation (Scheidegger, 1957): k* = d; n 3 180 (1 - n) 2 (2.9) k* theoretical specific permeability, m2 dm the mean particle size, m Equation 2.9 clearly indicates that specific permeability is dependent on the mean particle diameter and porosity, and is theoretically obtained by assuming uniform-size particles are arranged in cubic packing. 34 Mine Coal Seam Permeability ( x 10"1 7m2) Parallel to bedding Perpendicular to bedding Castle Gate Sub 3 4.1 3.9 Soldier Creek Rock Canyon 0.5 1.4 Sunnyside 6.3 9.6 Sunnyside L. Sunnyside 1.6 1.1 found specific specific University of Utah. The results are shown in Table 2.3. These values have been adjusted for air as fluid rather than nitrogen. The materials used were the broken rock with various sizes and are tested by X-ray microtomography and constant-head techniques (Gold, Table 2.2 Experimental specific permeability of Utah coals (Hucka, 1992) 10-17 m2 ) Using Darcy's law, Hucka (1992) found the specific permeability values for Utah's coals (Table 2.2). The coal samples used by Hucka were taken from coal mines and tested in the laboratory with nitrogen as a fluid. The permeability values were found to be influenced by the cleat direction and whether the coal sample is parallel or perpendicular to the bedding, fracture, and other geological structures. To characterize the gob material, it is necessary to consider the specific permeability of the broken coal-rock mixture behind the face. Therefore, the gob specific permeability should be much higher than the specific permeability of fresh coal shown in Table 2.2. Investigations of experimental specific permeability were conducted at the adjusted 2004; Lin, 2005; Videla, 2008). These values should be comparable with those used in this simulation. 35 Particle Range Size Mesh Standard (mm) m2) Investigators Method Permeability (No. 200 - 1 in. 0.074-25.40 10"07 Lin et al. (2005) X-Ray Tomography No. 170-3 / 4 i n. 0.088- 19.00 10"11 Gold (2004) Constant-head No. 40 - 1 in. 0.420-25.40 3.450 x 10"11 No. 100-No. 40 0.149-0.420 4.034 x 10"n No. 4 0 - N o . 10 0.420 - 2.000 x 10"10 Videla (2008) Constant-head No. 1 0 - 1 / 8 in. 2.000-3.175 09 Table 2.3 Experimental specific permeability of broken rocks m2 ) 0.074 - 25.40 1.400 x 10,07 No, 170 - 3/4 in. 0,088 - 6.340 x 10,11 0.420 - 25.40 10'" 100 - No. 0.149 - 0.420 10'" 40 No. 3.475 X 10,10 10 118 2.000 - 3.175 2.023 x 10'09 CHAPTER 3 CHARACTERISTICS OF GOB MATERIAL of longwall much work has been done to understand this behavior. Some of these works are used as the foundation of this study. Ventilation air distribution, panel dimensions, and particle size distribution of gob material are important factors in the design of physical and computer-based gob models. For this study, a number of tests have been conducted to better understand the gob material characteristics. Results of these studies, assumptions made and the significance of laboratory experiments are described in this section. size of the broken material. The most important parameter of the gob considered in this Knowledge oflongwall gob conditions is a critical element in the study of spontaneous combustion. Currently, the interpretation of events taking place inside the gob is unclear and, in some cases, merely guesses. Roof caving is one of the major causes impeding investigators to search for further details on air-gas flow, although, recently, oftests 3.1. Longwall Mine Gob The development of the gob in a longwall mine is influenced by several factors, including the geologic conditions of the overlying and underlying strata, panel dimensions, and the depth of the coal seam. The presence of joints, fractures, and any other geologic features will change the characteristics of the gob, the caving time, and the mined-out of the overlying strata will rest upon the gob material, reducing the void spaces in the gob. investigation by the U.S. Mine Safety and Health Administration in 2002 reported that the height of the caved zone may range from 1 to 10 times the mining height, depending on the geologic condition of the roof. Other investigators state that the caved zone may extend from 4 to 6 times the height of the coal bed (Mucho et al., 2000). Above the caved zone, the strata do not detach from each other but are linked by connecting cracks. This is called the dilated zone. This zone extends from 9 to 60 times the mining height and may cause beam deformation. Above this is the fractured zone. Surface fracture of about 50 ft deep may occur due to tension in the subsidence zone. and how they are connected affect the resistance. Research indicates that a significant portion of voids is located in the area behind the shields. The maximum particle size of study is specific permeability. This parameter is strongly affected by gob porosity and particle size. 37 Peng (1984) states that coal extraction using the longwall mine method induces a series of events: abutment pressure and roof-to-floor convergence in the entries and face area, movement of rock strata, and surface subsidence. Figure 3.1 illustrates the typical result of coal extraction in retreat longwall mining. The initial strata response to mining is failure of the immediate roof, thus creating a void over the caved material. As the mined­out span increases, the strata failure continues and the volume of the broken material gradually fills the void space. Eventually the overlying strata rest on the caved material which offers some degree of support. As the longwall face retreats further, the full weight An aI., The gob materials, such as those from caved roof and heaved floor, can cause variable resistance to airflow if a bleeder system is utilized. The amount of void spaces significant surface Shearer/Shields Zone 1 Zone 2 Zone 3 Bleeder Entry Figure 3.1 Gob and strata zones in a longwall mine section (after MSHA, 2002) surface w 00 39 gob material in this area is about 550 mm (Pappas and Mark, 1993). Conversely, smaller particles are found near the bleeder entries. The reduction of void space is due to compaction of the overlying strata; the longer the compaction process, the lower the void space. The shape of the particles depends on the way these are arranged inside the gob. Densely consolidated, blocky material tends to break into large slabs, and creates large porous spaces. Laminated fragments tend to be more compacted than the blocky materials, thus decreasing the void space. The initial shape of the large fragments changes over time due to compaction. Gob permeability depends on the void space distribution in the caved area. With the knowledge of the material size, shape of broken fragments, and packing mode, the gob can be divided into three permeability zones: unconsolidated, semiconsolidated, and consolidated (Figure 3.1). These zones are characterized by their porosity as high, medium, and low, respectively. The size, shape, and packing of gob material may change and become more compact over time due to overburden weight. A number of studies have found that the permeability of the gob material ranges from 1x10" to 1x10" (Brunner, 1985; Ren et al., 1985; Ezterhuizen and Karacan, 2007). The experimental values used in this study are presented in Section 3.4. Although the step of dividing the gob into 3 zones is a fair assumption and supported by several studies, the boundaries of each zone are difficult to define. Longwall mining is a dynamic process. The gob permeability decreases gradually from the face to the bleeder area over time. Therefore, more permeability zones are preferable for simulation to reflect gradual permeability changes. However, iteration time and complexity of the model are the limitations for having unlimited zones. Investigations fragments lxlO -13 lxl0-5 aI., for simulation to reflect gradual permeability changes. However, iteration time and complexity of the model are the limitations for having unlimited zones. Investigations 40 conducted by Balusu et al. in 2002 and 2005 with tracer gas (SF6) and a gas monitoring system presented information to characterize and determine the boundaries of each zone. The unconsolidated zone, characterized by tracer gas, is hypothesized to extend up to 150 m behind the face. A lower concentration zone is assumed to extend from 150 m up to 600 m, and the third zone, almost degassed beyond 600 m. For simulation purposes, zone 1 extends up to 150 m from the face line, zone 2 from 150 m to 600 m, and zone 3 from 600 m up to the bleeder area. The schematic of these zones is presented in Section 5.1. 3.2. Gob Material and Its Characteristics The reliability of physical and computational models in simulating hot spots depends on how closely the simulated gob material emulates the real conditions. Even though there is no simple way to quantify real gob conditions, some studies have been conducted to approximate the air distribution through the gob. The gob is often represented by a zone of fixed volume filled with particles of given size distribution. The particle size and packing mode affect the airflow distribution and the self-heating process of broken coal. For this study, the gob material is represented by crushed rock and coal. Particle size and packing modes are discussed in this section. These properties affect the porosity and permeability of the porous media, and eventually the fluid transport process. 3.2.1 Particle Size Selection In the field, the largest coal-rock particles are more likely to be located in the area behind the shields. This material is freshly broken and unconsolidated. The size of the SF6) from ofthese 41 broken particles in this area is based on a study carried out by analyzing images taken from the area behind the shields in three coal mines in the United States (Pappas and Mark, 1993). The results show that the maximum particle size in the gob area behind the shields is about 550 mm with a mean of 122 mm. This average size is used in the present study to determine the permeability values for the unconsolidated gob material. For other zones, such as those located near the bleeder entries, the size should be assessed through simulations. This is due to the lack of experimental information in these gob zones. Through simulations, the mean particle sizes for the semi-consolidated and consolidated zones were 0.02 and 0.006 m, respectively, smaller than those of the unconsolidated zone. These were determined based on laboratory experiments, permeability tests, and numerical simulations (Section 3.4). 3.2.2 Packing and Particle Shape To understand the relationship between particle structure and porosity, investigators have established the concept of stable packing (Scheidegger, 1957; Bear, 1972; Freeze and Cherry, 1979). Stable packing is approximated by a motionless arrangement of uniform spheres. By studying the various modes of stable packing, a correlation between grain size, structure, and porosity can be determined mathematically. The uniform packing concept has been used by other investigators to generate computer particles whose shape and size differs from that of spheres. They are seldom uniform in simulated porous media (Scheidegger, 1957; Bear, 1972). However, this concept only approximates the natural condition of porous media. The natural condition includes 42 size and shape. This nonuniformity permits the smaller particles to fill the spaces between the larger ones, thus reducing the void space of the porous media. In this study, both crushed coal and rock are used to represent the gob material. Permeability tests have shown that though crushed coal and rock samples have identical particle sizes, they may still have different values of porosity and permeability (Section 3.3). The way each particle is arranged in the porous media plays an important role in defining the permeability of the porous media. The shape of coal particle is usually more angular than that of rock. These factors cause coal particles to have a denser packing than noncoal particles. However, the experiments carried out in this study indicate that, on the average, the difference in permeability between coal and rock samples is within 20%. While longwall gob does not exhibit spherical packing, computational simulators such as Fluent use the spherical packing concept. Therefore, physical measurement and computer modeling results are expected to differ to some degree. A calibration factor can be used to convert physical rock or coal permeability to computer model permeability. Then, this factor can be used to modify the Kozeny-Carman relationship used with Fluent (Section 4.3.2). 3.3. Permeability Tests A series of permeability tests were conducted at the University of Utah using water and air as fluids. The objective of these tests was to determine the specific permeability of simulated gob materials. These tests followed Darcy's concept of fluid flow through porous media. During each test, laminar flow conditions were maintained in the permeameter (container). Fluid flow rates, pressure differences, and room nonunifonnity penn its Penneability penneability penneability penneability penneability penneability. Cannan Penneability ofpenneability detennine penneability penneameter 43 temperatures were recorded systematically. These data were used to calculate specific permeability of the material. This section describes the process of determining permeability of broken coal and rock, data interpretation, and conclusions. 3.3.1 Sample Preparation The granular materials such as crushed rock and coal are best described by their particle-size distribution (Bear, 1972). Six sieve sizes were used to classify the rock and coal samples: 150-um, 425-um, 1.70-mm, 4.75-mm, 6.73-mm, and 12.5-mm sizes. The diameter of permeameter used to hold material defined the largest size. After sieving, the crushed rock and coal samples were divided into 6 size ranges based on the sieves. The mean sizes for each group were 0.28, 3.22, 5.74, 7.73, 8.72, and 9.71 mm, respectively. Tests were conducted circulating either water or air through the permeameter. ASTM Method D2434-68, a water-based standard used to measure the permeability of granular soils, was followed for these tests using the "constant head method." For this method, 30 tests were performed using 3 sample groups with mean sizes of 0.28, 3.22, and 5.74 mm. The permeameter size restricted the tests for larger particles. The air-based tests were carried out using the same constant-head method. Permeameter dimensions used in this test were different than those used in water-based test. Therefore, the sample groups were different. Thirty six tests using 4 sample groups with mean sizes of 5.74, 7.73, 8.72, and 9.71 mm were performed. The first sample group was tested using both fluids (air and water) to explore the effect of fluid to permeability. A detailed description of both experiments is presented in the following sections. I50-l1m, l1m, I2.5-0.28,3.22,5.74, 3.3.2 Water-Based Method The water-based method was used to measure the specific permeability of the simulated gob material by maintaining constant water head (pressure). The pressure drop through the porous medium is measured by the difference in height of two water columns. To determine permeability using Darcy's law, constant flow must be established first. This is achieved by maintaining the water column in the container constant. The ASTM standard states stringent prerequisites for permeability tests: (a) continuity of flow with no material volume change, (b) flow with the material voids saturated with water and no air bubbles, and (c) steady state flow with no changes in hydraulic gradient. These prerequisites are explained in the following sections. 3.3.2.1 Testing Apparatus Figure 3.2 shows the apparatus used for the test. It includes a carbon dioxide gas tank, a water container, a material column (permeameter), a flask, and tubings. At the beginning of each test, carbon dioxide was flushed through the permeameter to eliminate air bubbles trapped in the material voids. This gas was selected due to its inertness and safety. A valve attached to the tank outlet controlled gas flow rate. The maximum gas pressure in the tank was 689 kPa (100 psi). However, only 3.5 kPa (0.5 psi) of gage pressure was used to flush the permeameter. It took from 10 to 15 minutes to flush out the air bubbles from the column. This was monitored visually. The energy source was represented by a water container of fixed head. The container was joined to the permeameter through control valves and tubings. The permeameter was filled with granular samples and saturated with distilled water. The 44 tUbings. Figure 3.2 Permeability test network for water-based method r--~ Gas Pressure Gauge Relief pressure taps Top screen Water Container Permeameter Flask Bottom screen Penneability 46 3.3.2.2 Testing Procedure The permeability of crushed samples (coal and rock) was determined experimentally using the following procedure: 1. Place crushed material in the permeameter and setup the network (Figure 3.2). 2. Flush the specimen with carbon dioxide at a gage pressure of 3.5 kPa (0.5 Psi). 3. Once the air bubbles are removed, close the gas control valve and open the water valve. 4. Maintain the water level in the container constant by feeding it continuously. 5. Collect the fluid overflow in the flask and record the water volume (V). Also, record the collection time (t). 6. Measure the difference in water head (Ah) and sample length in permeameter (L). permeameter cylinder was 60 mm in diameter. This was 8 to 12 times larger than the maximum particle size as prescribed by the ASTM standard. Two porous screens with openings smaller than the particle size were attached to two ends of the specimen. The screen openings were larger than the material voids but smaller than the particle diameter to prevent the movement of particles. The permeameter had two taps to allow water to flow. The specimen height in the permeameter was at least twice the diameter of the cylinder. A metal spring was attached to the top screen to avoid changes in specimen height during the test. Two pressure relief valves in the permeameter lid are used to eliminate pressure buildup between the water level and the permeameter lid. The overflow water collected in the flask was used to determine the flow rate through the specimen. speCImen. of3.5 (~h) 47 7. Record the room temperature and atmospheric pressure. 8. Repeat steps 1 through 7 for different flow rates and particle sizes. Thirty water-based tests were performed using the above procedure. The gathered data from these tests are presented in Appendix A. 3.3.2.3 Testing Results For the water-based method, 30 experiments were considered large enough to produce reliable results. Besides the sample size, another concern was laminar condition requirement for the experiments. Regression analysis was performed to check this condition. Using a standard permeameter, and measuring the water heads, quantity of overflow, and the Darcy's law, the specific permeability (A:) for material samples can be calculated. An example of such a calculation can be found in Appendix A. Figure 3.3 shows the results of 30 permeability tests conducted for the same flow conditions. These were carried out using crushed rock and coal samples of three different particle sizes. This figure also shows the relationship between the water head and flow rates for rock and coal samples. The linear regression analysis on each graph shows an upward trend of head with flow rates showing that the experimental conditions followed the Darcy's concept. Data points that lay outside these regression trends may indicate the presence of turbulent flow. From the observations, such data generally occur at either very low or high flow rates. The R-squared value (R ), called the correlation coefficient, represents how well the regression line matches the original data points and ranges from 0 (no match) to 1 (perfect match). The high R2 values shown on the regression lines implied k) different R2), R2 0.3.5 0.15 - - - • Rock 0.00 4 -t- O.E+00 1..E-07 2.E-07 3.E-07 4.E-07 5.E-07 6.E-07 7.E-07 8.E-07 Flow rate, Q(m3/s) 0.15 r 0.10 0.05 0.00 O.E+00 l.E-06 2.E-06 3.E-06 Flow rate, Q{m3/s) 4.E-5.E-G. 4.75 - 6.73 mm 0.06 <5 0.04 I | m o.o2 0.00 0.E+O0 • Rock m Coal Linear (Rock) Linear (Coal) y= 1733.x RJ = 0 ^ 9 6 1 ^ x • ^ y= 1330.x R2 * 0.902 ^ ^ ^ ^ 5.E-06 l.E-05 2.E-05 2.E-05 3.E-05 Flow rate, Q (m3/s) 3.E-05 4.E-05 4.E-05 Figure 3.3 Water head-flow rate relationships for coal and rock samples A. Sample size: 0.15 - 0.42 mm 0.15 .,---------------------------------------------, • Rock .. Coal I --Linear (Rock) ;§ • 0.10 ~ -- -.-.-.... Linear (Coal) ~ CII :t: ::;; y = 14282x R' = 0.965 ~ 0.05 1-·-·-.... ·--· ..· .. ...... ·.. .................... -·-.. ·.. ....· .. ·-· .. ·.. .... :.. ·.. ............: ;;;;~~,,:.:. ............ -.................... -............ -.... - ................ ---· .. ·.. ·.. ·. ....... -· ...... ·· .... ·.. ·. . ·_ ..- .. ·.. .. · .. 1 :r: +-----.----.,---.........,-. OO l.E-2.E-07 3.E'()7 0 7 E.. E. . 8.E-07 Flow rate, Q (m3/s) B. Sample size: 1.68 - 4.75 mm .. ,.....------------------- --------------------------------, • Rock .. Coal --- Linear (Rock) y = 29705 • R' = 0.906 • ;§ 0.10 .. ~. .......- ........- ....- .-.-. L... .i.n .... e ... _a .r• •( -c .o.. .. a- .I-) .--.-.... --.. ------~:---.... -.-.-~~ .... - .•- ~~<~, ..- -.. --.... -....- -....... I ~ ~ ~ ~ y = 25103x R' = 0.901 "'C""II 0 .05 +-----------------;::>-"""--=--.,,:.:....----·--------·-------------.. - 1 :r: I 0 .. 00 OO • III E'()6 3.£ .. Q (C. Sample size: 4 .75·6.73 mm 0 .06 • Ro ck .. Coal y " 1733 .• --linear (Rock) Rl " 0.961 ...... · .. - .. linear (Coal ) E .. 06 E .. 06 • ;§ 0 .04 ............................................................. ................................. - ........ .-.;.p ~ ............... M ................. ;,., _ :: .......................................... ....... . ... 1 cu' ~ ~ ~ ;g 0 .Q2 't> .'". :r: 0 .00 •• • • O.OO 5 .E .. E·• III E·(m3/y = 1330 .)( R' '" 0 .90 2 3 .E·0 5 4 .E .. E .. 48 49 that the lines can be used to predict values that were not observed within the size ranges. The graphs also illustrate the effect of particle size by showing the slope change of the regression lines. In graph A, the rock and coal particle regression lines almost overlap each other. The gap between the lines is larger with an increase in particle size. This effect is shown in graphs B and C, implying that the smaller the grain size is, the less significant angular shape is on packing mode. In other words, the angularity of particles becomes smaller as the size decreases. This affects the properties of porous media significantly. In the gob, the material directly behind the shields, made up by large-size broken particles, will always have high porosity. In contrast, the gob area adjacent to the bleeder entries due to compaction will have small porosities. During the experiment, the prerequisites for the laminar flow conditions were examined frequently. The test apparatus and its arrangement were checked for any possibility of material volume changes, presence of air bubbles in the voids, and transient state. Several external factors may still affect the results. The critical ones include the following: (1) the permeameter specifications: length, specimen diameter, tap hole diameters, and particle size; (2) presence of invisible air bubbles and tubing; and (3) material placement in the permeameter. For coal, care must be taken to avoid abrading the particles and washing out the fines during the test. Table 3.1 shows a summary of specific permeabilities for crushed rock and coal samples. A comparison of these results shows the specific permeability of coal specimen is consistently higher than that of rock specimen. Band permearneter. 50 (mm) k m2) Rock 0.28 10"09 10"09 1.68-4.75 10"09 x 10~09 4.75-6.73 5.74 10'0 9 8.54 x 10"09 3.3.3 Air-Based Method This method is used to determine the specific permeability of rock particles by passing air through a porous medium in a physical model. These tests were conducted by applying the same principles used with the constant-head method. The prerequisites of laminar flow conditions were also required in these tests. For this purpose, part of an existing longwall model was modified to serve as a permeameter. There are several advantages for conducting these tests: first, since the model resembles a longwall panel, the expected results should better approximate real conditions; second, air is circulated through the porous medium instead of water; third, the permeameter can be used to measure the permeability of larger rock particles. The combined results can predict the gob permeability more accurately. Finally, these results can be compared with those of water-based tests for the same particle size. This comparison can be used to determine the fluid effect on the specific permeability. 3.3.3.1 Testing Apparatus Figure 3.4 shows the ventilation model used for this test. This physical model was constructed of PVC pipes and pressurized by a 1.75-kW blower fan. The maximum fan speed was 60 rpm. The pipes were arranged in a U-shape system (Figure 3.5). It included Table 3.1 Specific permeability for rock and coal samples using water-based tests penneability Particle Size Range Mean size Specific Permeability, (m2 ) (mm) Coal 0.15-0.42 3.34 x lO-uli 3.49 x 10-Uli 1.68 - 4.75 3.22 6.51 x lO-uli 6.62 X 10-09 4.75 - 6.73 7.49 x 10-09 8.54 x 10-u~ detennine penneability penneameter. penneameter penneability oflarger penneability detennine penneability. 1. 75-Figure 33..44 LLoonnggwwaallll mmiinnee vveennttiillaattiioonn mmooddeell aatt tthhee UUnniivveerrssiittyy ooff UUttaahh Figure 3.5 The permeameter for air-based test t o Return Steel Screen Stat 10 A B C D Simulated Gob 55.75 cm Fan Material Stat 1 Stat 2 Stat 4 Stat 5 Intake Steel Screen Pressure tap Crosscut penneameter 53 one intake, one return and four crosscuts (A, B, C and D). There were 10 pressure taps (stat 1 to 10) to measure velocity and static pressures. Each crosscut had one slot where a regulator of fixed resistance (porous medium) could be inserted. For the permeability tests, the first three crosscuts were completely blocked while the last crosscut was regulated. This arrangement represented a longwall panel. A detail description of the model is presented in Chapter 4. Figure 3.5 also shows the modified permeameter. It consists of a cylindrical container 14 cm in diameter and 55.75 cm in length. It was filled with rock particles. Two steel screens of 4.7 mm spacing were attached to the top and bottom ends of the permeameter. The screen size was selected to minimize the resistance to airflow. This limited the particle size that could be tested in the permeameter. The height of the sample-column in the permeameter was at least twice its diameter (31.25 cm). The pressure drop through the porous medium was measured by reading a manometer at Stations 5 and 6. The resistances caused by two elbows were also measured and considered in the calculation. The air quantity was determined based on velocity heads monitored at Stations 4, 5 and 7. 3.3.3.2 Testing Procedure An air-based test was carried out using the following procedure: regulators, and tubings). 2. Disassemble the permeameter from the mine model. Fill it up with particles of predetermined height. 1. Inspect the model and the monitoring instruments (i.e. manometers, pitot tubes, 54 3. Install the top steel screen and reassemble the permeameter. 4. Energize the blower fan and set the initial frequency to 30 Hz. Run the fan for about 2 minutes to reach a steady state condition. 5. Record static and velocity heads at Stations 1, 5, 6, and 7. 6. Measure the room temperature and barometric pressure. 7. Repeat the procedure for different specimen heights (312.5, 468.8, and 557.5 mm) and fan frequencies (45 and 60 Hz). Thirty seven experiments were carried out to determine a relationship between particle size and permeability. Four different particles sizes were tested: 5.74, 7.73, 8.72 and 9.71 mm, respectively. The first experiment was carried out with an empty permeameter to determine the model's resistance to airflow due to frictions and shock losses. The model was inspected carefully for leakage. The remaining tests were carried out with the permeameter filled with dried rock particles. There were nine tests for each particle size (3 sample heights x 3 fan frequencies). 3.3.3.3 Testing Results In these tests, rock particles were used as the porous medium. The particle size ranging from 4.7 to 12.7 mm were divided into four groups. Their mean sizes were 5.74, 7.73, 8.72, and 9.71 mm. A parametric study was conducted by changing one of the three variables at a time: particle size, specimen height, and fan speed. For example, the first test was conducted with a fan frequency of 30 Hz, mean particle size of 5.74 mm, and sample height of 3,125 mm. For the next test, the fan fequency was increased to 45 Hz while maintaining the particle size and the sample height constant. Thirty six experiments 1,5,6, 7.73,8.72, of30 Table 3.2 Specific permeability for rock samples using air-based tests (fan frequency 45 Hz) Mean size (mm) Specific Permeability, k (x 10"8 m2) (half-packed) (3/4-packed) (fully-packed) Average 5.74 1.109 1.011 1.231 1.117 7.73 1.017 1.185 1.281 1.161 8.72 1.229 1.137 1.748 1.371 9.71 1.118 1.261 1.830 1.403 were carried out to complete this study. Out of these, only 12 yielded reasonable results. These were achieved by setting the fan frequency at 45 Hz. At speeds higher than this, the air leakage became a problem and at lower speeds, the instrument accuracy became questionable. Table 3.2 shows the results of this experiment. An evaluation of the figures in this table shows that the permeability increases with the particle size and remains unchanged with the sample height. This follows the Karman-Cozeny concept of permeability and porosity relationship (Bear, 1972). For the sample sizes used in the experiment (5.7 - 9.7 mm), the specific permeability varied between 1.117 x 10"8 and 1.405 x 10"8m2. 3.4. Specific Permeability of Gob Material The specific permeability of gob material is one of the key parameters in the spontaneous combustion study. A number of gob investigations have been carried out to determine the gob permeability, including the use of tracer gas (Koenning, 1989; Lowndes et al., 2002) and photoanalyses (Pappas and Mark, 1993). Such investigations found that the gob permeability varies from 1x10_ 1 3 to lxlO"5 m . This variation in permeability is addressed in this study by using three permeability zones: unconsolidated, semiconsolidated and consolidated, as explained in Section 3.1. 55 10-8 X 10-8 m2 . aI., 1x10 -13 1x10-5 m2 . Permeabilit , 10-8 m2 ) 56 Pappas and Mark (1993) reported that an average particle size of gob material behind the shields is 122 mm. The permeability of the unconsolidated zone was determined based on this information. For other zones, semiconsolidated and consolidated, their permeabilities were determined by CFD simulations (Section 5.1.3). The permeability experiments carried out in this study were used to determine the particle size - permeability relationship. This relationship, once adjusted for packing effect, was then used to generate input parameters for CFD modeling. Figure 3.6 shows this modified relationship for air-based permeability tests. Based on this relationship, for the unconsolidated zone (particles size: 0.122 m), the specific permeability was estimated at 4.203 x 10-7 m2. Due to limited information on material characteristics in zones 2 and 3, the permeabilities for these zones were estimated using CFD simulations. Section 5.1.3 0.0E+00 - - - - 0 0.01 0.02 0.03 0.04 0.05 0.06 Particle mean size (m) Figure 3.6 Particle size effect on broken rock permeability for air-based tests 1.4E-07 1.2E-07 .§. 1.05-07 .lI: § 8.0E-08 I 6.0E-08 .g 40E-08 1 I/) 2.0E-08 O.OE+OO o y= 2E-OSJ<'! + 1 E-06x + 6E-10 R2 = 0 .9993 --_. . _ .... _--_._ .... __ ._._---_ ... __ ._ ... _-----_.. _-------_._-----_._._._. ... _---- 0 .01 0 .02 0 .03 0 .04 0 .05 0 .06 57 Table 3.3 Specific permeability for simulated gob materials Specific Permeability, k (m ) Unconsolidated Semi-consolidated Consolidated Reference values 4.203 x 10"7 2.83 x10"8 7.17 x 10"9 1 x 10~5 to 1 x 10~13 Figure 3.7 Specific permeability distribution in gob describes this work in more detail. Using this approach, the specific permeabilities for zones 2 and 3 were estimated at 2.83 x 10"8 and 7.17 x 10"9 , respectively. Particle sizes in these zones were 0.02 and 0.006 m, respectively. Table 3.3 summarizes the permeability for the three zones: unconsolidated, semiconsolidated, and consolidated. Figure 3.7 illustrates the permeability contour lines for the simulated mine gob. As shown in Table 3.3, the highest permeability is found in the unconsolidated zone (behind the faceline) and gob perimeter. 10-8 10-9 m2 , 2 ) 10.7 X 10-8 X 10-9 X 10-5 X 10-13 Unconsolidated zone Semi consolidated zone Consolidated zone CHAPTER 4 RESEARCH METHODOLOGIES Two laboratory-scale methodologies are used to study the development of hot spots in a mine gob: physical modeling and modeling using Computational Fluid Dynamic. The physical model is a small-scale longwall mine representation. The CFD model is a numerical representation of a longwall mine. It is presented in the latter section of this chapter. To simulate a real case, both models are designed to resemble a longwall panel, which includes intake and return entries, crosscuts, and a gob. This chapter discusses the details of each model, the similitude principles, and ventilation systems. Validation tests for both models reflecting the similitude principles are also presented. Laboratory tests and simulation exercises are described to better understand the air-gas behavior in the gob. 4.1 Physical Model A ventilation model was expanded to include a longwall mine gob at the University of Utah. Figure 4.1 shows the main components of the model, including a blower fan, intake and return ducts, crosscuts, and a simulated mine gob. This model was built to resemble an existing longwall mine panel in geometry and airflow characteristics, and was equipped with high precision instruments to conduct ventilation surveys. METHODOLOGIES ofthis the air-gas behavior in the gob. Fan Stat. 1 Stat. 3 Figure 4.1 Mine ventilation model schematic Return Stat. 10 Stat. 2 Stat. 4 Stat. 5 (1.5 kW) Intake 60 4.1.1 Simulated Airway The physical model was initially designed to simulate the airflow behavior in a longwall mine and determine experimental values for friction factors, shock losses, and the resistance of ventilation controls such as stoppings and regulators. The longwall mine model resembles a U-tube shape and includes: two entries (intake and return) and four crosscuts (A, B, C, and D). Crosscuts A, B, and C are used to simulate stoppings and seals; crosscut D is used for the face, and the U-section is used for the simulated mine gob. The monitored parameters during a test were air velocity and pressure. Ten pressure taps distributed along the pipes are used to measure these parameters. The physical model is made of PVC pipes of about 10.63 m long and 1.2 m high. The inside diameter of the pipes used for main airways is 14 cm, and 7 cm is used for the crosscuts. In this model, a variable speed fan is used to pressurize the air and simulate different ventilation scenarios. The head losses are determined through measurements and cross­checked by applying the steady-state energy equation. This equation is expressed by: Y 2S + Z, = ^ ^ 2 +7 (4.1) where P = absolute air pressure, Pa = air velocity, m/s y = specific weight of the air, kg/m Z = measuring point elevation, m ofthe different cross-checked steady-state energy equation. V2 V2 !!..l + _1_ + Z = P2 + _2_ + Z + H Y 2g 1 Y 2g 2 L p V mls y m3 61 Hs = - = RQ2 (4.3) r v2 Hv=- 2g where Hs = static head, m Hv - velocity head, m R = duct resistance, Ns /m Q = airflow rate, V A, s In Equation 4.2, the measuring point elevations are omitted. This version is correct as long as all head measurements are made on a gage-pressure basis (Hartman, 1997). Figure 4.2 shows the pressure gradient along a single circuit (from fan to discharge) of this model. The pressures are obtained by multiplying the corresponding heads with specific weight of air. In this figure, the total pressure is the sum of velocity and static pressures. The head loss shown in Equation 4.2 consists of two components: friction loss, Hf, and shock loss, Hx. Frictional head losses are caused by the surface Hi = head loss, m The subscripts 1 and 2 denote two individual measurement stations. Accepting the energy conservation principle, Equation 4.1 can also be written using gage-pressure basis (McPherson 1993) as follows: HsJ + HvJ=Hs2 + Hv2+HL (4.2) HL = 2g (4.4) Hs Hv 28 m3/HI, Hx. 62 -500 j- -1000 - Figure 4.2 Pressure gradients for the physical model resistance (gradual decrease in total pressure lines) whereas the shock losses are due to changes in flow direction or air velocity in the duct. This figure shows a pressure reduction at a distance of about 9.5 m. This is caused by two 90° elbows (Stations 5 and 6). The shock losses represent more than 80% of the total head loss in this section. The difference between the total and static pressure is the velocity pressure. In this graph, this parameter remains fairly constant, indicating near zero leakage. To simulate the airflow behavior in mine entries and leakage paths, all crosscuts were blocked by a set of identical regulators. Regulators of predefined size were inserted into slots at four crosscuts. Air quantities and head losses were determined using a pitot tube and a manometer at 11 pressure taps. The collected data were also used to determine 2500 - -+- Total 2000 - 1500 - ,-... ro 'P-o"<" 1000 Q) I-< ::s CJ) 500 CJ) Q) I-< Po< 0 2 4 6 8 10 12 14 16 18 20 Distance from Fan (m) 900 63 Table 4.1 Leakage percentage through crosscuts Regulator Leakage percenta^ yd at crosscut: Type A B C D # 1 14.63 11.79 8.14 4.19 #2 7.57 4.17 3.59 2.42 #3 2.97 0.75 0.33 0.16 the leakage flow through each crosscut, which is a common problem in longwall mines. A common practice to determine leakage flow through a stopping is to measure two flow quantities: upstream and downstream of the stopping. For example, the leakage at crosscut A was calculated by subtracting the air quantity at Station 2 from that at Station 1. The result was cross-checked with readings at Stations 9 and 10. Then, the leakage rate is obtained by (Calizaya & Miles 2006): % L = Q ~®2 .xlOO (4.5) Gi where Qj and Q2 are the upstream and downstream flow rate from the split. Table 4.1 shows the summary of leakage percentages calculated using Equation 4.5 for a fan frequency of 60 Hz. The leakage rates were determined for 3 different regulators. Regulator #1 is more porous than that of either regulator #2 or #3. Figure 4.3 shows the changes in leakage percentage with the location of crosscuts from the fan. It shows that the closer the crosscut is to the pressure source, the higher the leakage percent. For any given circuit, the air will always choose the path of the least resistance. This behavior yields a higher leakage rate at crosscut A than at any other crosscut. QJ Q2 ofleakage Leakage percentage at crosscut: A 64 20 15 Q) 3S> 10 CO 0 • Reg #1 0 R e g #2 • Reg #3 B C Crosscut Figure 4.3 Leakage percentage through four crosscuts By modifying the U-section to become a permeameter (gob), permeability tests can be performed. The modified model is featured in Figure 3.5. During a test, the first three crosscuts, A, B, and C, were blocked while D was kept open. This arrangement resembles a longwall panel with crosscut D as the working face and the U-section as the mine gob. A precise reading of head loss due to porous medium is very important. The pressure drop was determined from gage readings at Stations 5 a and 6. An initial test without the gob material was conducted to determine the shock losses due to two elbows and four joints. These losses are crucial to assess the pressure drop through a porous 2 8 medium. However, the calculated resistance due to elbows was only 5.46 x 10"'Ns7m°, which is negligible in this study compared to that of rock particles (10" to 10" Ns /m ). ......... ~ 0- -Q) 0> 10 ~ ctl Q) ....I 5 o A c D penneameter penneability perfonned. detennined 5a detennine medium. However, the calculated resistance due to elbows was only 5.46 x 10-7 Ns2/m8 , which is negligible in this study compared to that ofrock particles (10-2 to 10-1 Ns2/m8 ). 65 Table 4.2 Type of regulators used for ventilation controls Regulator Holes Porosity Resistance Type Number Diameter (cm) (%) (Ns2/m8) #0 1 7 100 8.44 x 10-06 #1 37 0.6 27.18 6.59 100 4 #2 21 0.6 15.43 1.89 10'03 #3 21 0.3 3.86 2.43 10"02 #4 21 0.15 0.96 8.11 x 10"02 #5 0 0 0 3.90 x 10"01 4.1.2 Fan and Regulator In a ventilation system, airflow occurs due to a pressure difference between two points. A blower fan is used to raise the air pressure in a duct, thus creating a pressure difference. The 1.5-kW fan can produce a gage pressure of up to 1, 245 Pa (5" water gage), and is driven by an AC electric motor. The motor can supply power of up to 2.24 kW (3 HP). It is equipped with a digital inverter to vary the fan speed. The maximum fan speed is 3600 Rpm (60 Hz). On the average, the fan can circulate as much as 0.45 (945 cfm) of air through the system. Several experiments were conducted to verify this quantity. Regulators were used to control the airflow in the model. They were used to simulate mine stoppings, doors, and curtains. Physically, a regulator is a perforated plate of 7.62 cm wide and 0.3 cm thick. It is designed to closely fit a prefabricated slot. The number of holes on each plate determines the equivalent size of a regulator. There were 6 different regulators available for this study. These were labeled as Regulator #0 for fully open, #5 for a solid plate, and the remainder (#1 through #4) for perforated plates with various numbers of holes and diameters of holes. Table 4.2 describes these regulators. 1,245 m 3/s (%) m8 ) X 06 x 10-04 x 10-03 x 10-02 10-02 X 10-01 7.62 cm #0 #l-#4 #5 Figure 4.4 Type of regulator for physical model used in this study Figure 4.4 shows three sample regulators: fully open (0), partially open (#1- #4) and fully closed (#5). These regulators were used to simulate the leakage flow through stopping and doors. They were also used to determine a parameter to characterize these control devices. This parameter is called regulator resistance. This resistance was determined experimentally (Table 4.2). These were determined from pressure-quantity measurements applying Atkinson's relationship (Equation 4.3). 4.2 Computational Fluid Dynamics Model 4.2.1 Introduction Computational fluid dynamics (CFD) is a branch of fluid mechanics that uses numerical methods and algorithms to solve and analyze problems that involve fluid flows. Computers are used to perform millions of calculations required to simulate the interaction of fluids and gases within complex systems. 66 em I }, #0 #1- #4 67 Fluent version 6.1, the most widely used CFD software (Fluent Inc. 2003) was chosen to simulate the air-gas and heat flow in a ventilation model. Fluent uses a numerical method to discretize the spatial domain into small cells to form a volume mesh or grid, and then apply a suitable algorithm to solve the equations of motion. Three governing equations are solved using this software: conservation of mass, conversation of momentum, and conservation of energy. The conservation of mass states that mass of fluid remains constant when moving from one location to another. The conservation of momentum states that the magnitude of momentum (the mass of an object multiplied by the velocity of the object) remains constant but changes only through the action of forces. The conservation of energy states that within a domain, the amount of energy remains constant. Energy can be converted from one form to another but the total energy within the domain remains the same (Versteeg, 1955; Adler, 1992; Thomas, 1992). In CFD, the solution to a problem is found in two steps: (1) defining the geometries and boundary conditions of the problem, and (2) solving the governing equations iteratively. The first stage involves the use of Gambit software. Gambit allows the users to create the geometry of the problem or import it from a CAD package. The geometry is then divided into small elements. This process is called meshing. It is performed using a menu-driven routine. Defining the boundary conditions completes this stage. The second stage involves exporting the geometries created by Gambit into Fluent software. This stage also involves defining the fluid properties and boundary conditions, and solving the fluid flow problem through iteration. The CFD modeling procedure consists of the following steps: 1. Create geometry of the model. and solving the fluid flow problem through iteration. The CFD modeling procedure consists of the following steps: 68 2. Divide the volume occupied by the fluid into discrete cells. The meshing may be uniform or nonuniform. There are various mesh types available in Gambit. 3. Define the fluid properties and input parameters. 4. Define boundary conditions. This involves specifying the fluid properties at the boundaries of the model. 5. Solve the continuity equations iteratively either at steady-state or transient conditions. In the postprocessing stage, the simulation results can be visualized as contour lines, vector graphs, velocity profile, etc. Currently, CFD is used to solve different types of problems, including gas and particles flow problems under both turbulent and laminar conditions, and heat flow transfer. In this study, this tool is used to investigate the airflow behavior in a mine gob, oxidation heat, and heat transfer through conduction, convection, and radiation. 4.2.2 Airflow Simulation (Without Oxidation) A complete airflow study has been conducted on the physical model (duct diameter: 16 cm). Based on this, a CFD model was created and simulated using Gambit and Fluent. The CFD model included a porous medium at the end of the U-section. This section was assigned with a permeability of a represented mine gob material. This permeability was determined based on the laboratory tests (section 3.3.3) and field measurements. Figure 4.5 shows the geometry of a 2-D gob model created in Gambit. Gambit is a preprocessor that is used to build the model geometry and mesh the cells. A map type meshing with an interval size of 4 cm was selected. In Gambit, the permeameter was defined as a "face" characterized by a porous jump. Other relevant parameters include pressure inlet for inlet duct, porous jump for crosscuts, and pressure outlet for return. The model was calibrated using laboratory data to account for duct roughness (Section 4.3.2). All input parameters and boundary conditions were quantified before running the Fluent program. Table 4.3 shows the input parameters used for this sample model. In Fluent, the permeameter, representing the porous medium, is characterized by 3 major parameters: viscous resistance (Ci), inertial resistance (C2), and porosity (£). These parameters were obtained through physical experiments and field data. These parameters Table 4.3 Input parameters used in Fluent for airflow simulations Label Boundary Boundary Condition Remarks RIentluertn pprreessssuurree oiuntlleett 11405 Pa Gage pressure A, B, C wall Blocked Face porous jump 0 Open Gob face C^T^le+OTm"2 Viscous resistance C2 14700 m'1 Inertia resistance 8 0.240389 Porosity wall wall 00.0.00912928 mm RRoouugghhnneesss sc hoenisgtahnt t 69 Return A B C Face Gob Inlet Figure 4.5 The CFD model created in Gambit C l), Inlet pressure inlet 1145 Return pressure outlet 0 - C, = 7.91e+07 m-2 C2 = m-' € = 0.0922 m Roughness constant 0.00198 m Roughness height 70 are interrelated by the following equations: C = 1 1 (4.5) 3.5 (1-g) d s3 m (4.6) where k 9 = specific permeability, m = porosity, dimensionless d•,m the mean particle size, m Fluent is equipped with different postprocessing tools. For qualitative analysis, the tools available are contoured plots and vector plots, which can be used to display parameters such as static pressure, velocity, species concentration, etc. For quantitative analysis, Fluent offers XY-plots in the plane of choice. Figures 4.6 through 4.11 show some of these results. Figures 4.6 and 4.7 show the air velocity profiles through the system and at the U- section. For the sample model, the first three crosscuts are blocked near zero flow, the fourth is open to represent the face, and the U-section represents a porous medium. Figure 4.8 shows velocity plot for two settings: face (crosscut D) and gob. Figures 4.9 and 4.10 show the static pressure profile for the sample model. The zone with the lowest velocity has the highest static pressure. This finding is explained by the energy conservation law. The pressure drop due to the porous medium is shown by the gradual color change in the U-section (Figure 4.10). This can be quantified by a longitudinal cut along the porous medium (line 1-2). For the sample case conditions, the C1 -1 (m -2) k C - (1- £) (m-1 2- ) d", £3 specific penneability, m2 E dm XY -1 - 2). 71 I 34.5 32.6 30.8 29 27.2 25.4 23.6 21.8 19.9 18.1 16.3 14.5 12.7 10.9 9.07 7.25 5.44 3.63 1.81 0 I I I Dec 04, 2007 FLUENT 6.2 (2d, segregated, ske) Figure 4.6 Velocity contours for the sample model 34.5 32.6 30.8 29 27.2 25.4 23.6 21.8 19.9 18.1 16.3 14.5 12.7 10.9 9.07 7.25 5.44 3.63 1.81 0 Dec 04, 2007 FLUENT 6.2 (2d, segregated, ske) Figure 4.7 Velocity contours for the U-section 27.2 25.4 23.6 21 .8 19.9 18.1 16.3 14.5 12.7 10.9 9 .07 7 .25 5.44 3.63 1.81 o Contours of Velocity Magnitude (m/s) 6 .2 25.4 23.6 21 .8 19.9 18.1 16.3 14.5 12.7 10.9 9 .07 7 .25 5.44 3 .63 1 .81 o Contours of Velocity Magnitude (m/s) 6 .2 72 2.25e+01 2.00e+01 1.75e+01 1.50e+01 1.25e+01 V e l o c i t y M a g n i t u d e i. o o e + 01 m / s ) 7 . 5 0 e + 0 0 5.00e+00 2.50e+00 0.00e+00 Face i • • 1 ' i • ' ' - ' i ' ' - ' ' i 16.8 Gob 17 17.3 17.5 17.8 18 18.3 18.5 18.8 19 19.3 P o s i t i o n ( m) Velocity Magnitude Dec 04, 2007 FLUENT 6.2 (2d, segregated, ske) Figure 4.8 Velocity profiles for two simulated openings 1.01e+03 772 713 654 FLUENT 6.2 (2d, segregated, ske) Figure 4.9 Static pressure contours for the sample model 22..0205ee++0011 (: I I • • • • • • • Velocity • • Magnitude 1.00e+01 • • ( m/s) • • 7.50e+00 • • • • • ~ 2. 50e+• • • • O.OOe+OO - Position (m) 6 .2 ske) 948 889 831 713 654 595 536 477 419 360 301 I 242 183 124 65.6 6 .75 -52.1 -111 ~ Contours of Static Pressure (pascal) Dec 04, 2007 FLUENT 6 .2 (2d, segregated, ske) 73 Figure 4.10 Static pressure contours for the U-section static pressure in this section decreases from 1,011 to 598 Pa (Figure 4.11). An evaluation of the above results shows that Fluent software can be used to study the airflow behavior in a longwall mine. The air pressure-quantity distributions in the system can be detected qualitatively and quantitatively. If field or laboratory data were available, these can be used to calibrate the CFD models and improve the accuracy of the results. More complex scenarios involving oxidation of coal, heat transfer, and multigas phenomena can also be investigated. However, this requires changes in the modeling process. These simulations are presented in Chapter 5. 1 .01e+03 948 889 831 772 713 654 595 536 477 419 360 301 242 183 124 65.6 6 .75 -52.1 -111 Contours of Static Pressure (pascal) Dec 04, 2007 FLUENT 6.2 (2d, segregated, ske) multi gas 74 1.05e+03 1.00e+03 H 9.50e+02 9.00e+02 -\ 8.50e+02 Static 8.00e+02 7 - 5 0 e + 0 2 H 7.00e+02 6.50e+02 6.00e+02 H 5.50e+02 Position (m) Static Pressure Dec 04, 2007 FLUENT 6.2 (2d, segregated, ske) 4.3 Model Similitude streamline properties for similar time rates. The dynamic similarity requires constant ratios for all forces acting on corresponding fluid particles and boundary conditions. 1 • • • • • • • Pressure (pascal) 7.50e+02 7.00e+02 6.50e+02 6.00e+02 5.50e+02 10.2 10.3 10.4 Pressure • • • • • • • • • • • • • 2 10.5 10.6 10.7 10.8 10.9 11 FLUENT 6.2 (2d, segregated, ske) Figure 4.11 Pressure drop through porous medium 4.3.1 Similitude Concept Similitude is an important application of a nondimen