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Singapore : Springer Singapore Pte. Limited, 2018

1 online resource (199 pages)

ISBN 9789811075483 (electronic bk.)

ISBN 9789811075476

Print version: Wang, Chunlai Evolution, Monitoring and Predicting Models of Rockburst Singapore : Springer Singapore Pte. Limited,c2018 ISBN 9789811075476

Intro -- Preface -- Acknowledgements -- About the Author -- Contents -- 1 Introduction -- 1.1 The Overview of Rockburst -- 1.2 Current Status on Rockburst Induced Conditions -- 1.3 Current Status on the Precursor Characteristics of Rockbursts -- 1.4 Current Status on the Evolution of Rockburst -- 1.5 Current Status on Predicting of Rockburst -- 1.5.1 Study on the Synergetic Monitoring of Rockburst -- 1.5.2 Study on the Predicting Model of Rockburst -- 1.5.3 Study on the Field Predicting of Rockburst Hazard -- References -- 2 Experimental Materials and Equipments -- 2.1 Experimental Materials -- 2.2 Experimental Equipments -- 2.2.1 Laboratory Equipments -- 2.2.2 Field Equipment -- 2.3 SEM and EDS -- Reference -- 3 Mechanism and Predicting Theory-Based of Rockburst Evolution -- 3.1 Introduction -- 3.2 Mechanism of Rockburst -- 3.3 Mechanism of Rockburst Stress-Energy Evolution -- 3.4 Nonlinear Dynamic Theory of Predicting Rockburst -- 3.4.1 Mutation Theory -- 3.4.2 Damage Theory -- 3.4.3 Load/Unload Response Ratio Theory -- 3.4.4 Entropy Theory -- 3.4.5 Fuzzy Matter Element Theory -- 3.4.6 Bayesian Theory and Network Model -- References -- 4 Three-Dimensional Reconstruction Model and Numerical Simulation of Rock Fissures -- 4.1 Introduction -- 4.2 CT Scanning Experiment Under Uniaxial Cyclic Load/Unload -- 4.3 Cracks Extraction and Calculation -- 4.3.1 Processing the CT Images -- 4.3.1.1 Characteristics of CT Images Information -- 4.3.1.2 CT Image Processing Contents and Methods -- 4.3.2 Calculating the Length and Area of Cracks -- 4.3.2.1 Calculating the Length of Cracks -- 4.3.2.2 Calculating the Area of Cracks -- 4.4 Three-Dimensional Reconstruction Model and Numerical Simulation -- 4.4.1 Establishing a Three-Dimensional Finite Element Model -- 4.4.1.1 Establishing the Model of Fissured Rock.

4.4.1.2 Three-Dimensional Reconstruction Model of Failured Sandstone -- 4.4.1.3 Mesh Generation of Reconstructed Model -- 4.4.1.4 Three-Dimensional Model Parameters -- 4.4.2 Numerical Simulation of Fissured Rock -- 4.4.2.1 Selection of Material Parameters -- 4.4.2.2 Numerical Analysis of Model -- References -- 5 Experimental Investigation on Nonlinear Dynamic Evolution Patterns of Cracks in&amp -- blank Rock Failure Process -- 5.1 Introduction -- 5.2 Pattern of Nonlinear Dynamics Evolution of Rock Cracks -- 5.2.1 Fractal Theory -- 5.2.2 Results Analysis on Fractal Dimension of Rock Cracks -- 5.2.2.1 Calculated Procedure of Fractal Box Dimension -- 5.2.2.2 Results Analysis on Fractal Dimension of Sandstone Cracks -- 5.2.3 Entropy Model of Rock System Based on Fractal Dimension -- 5.3 Chaotic Characteristics of Cracks Evolution in Rock Failure Process -- 5.3.1 Chaos Theory -- 5.3.2 Discrimination of Chaotic Characteristics Defined by Li-Yorke -- 5.3.3 Construction of Crack Growth Factor Model -- 5.4 Conclusion -- References -- 6 Experimental Investigation on AE Precursor Information of Rockburst -- 6.1 Introduction -- 6.2 Spatio-temporal Evolution Pattern of Rock Failure -- 6.2.1 AE Experiment -- 6.2.2 Principle of AE Event Location -- 6.2.3 Spatio-temporal Distribution Characteristics of Rock Failure -- 6.3 Characteristics of Relatively Quiet Period for Rock Failure -- 6.3.1 Deformation and Failure Characteristics of Loaded Rock -- 6.3.2 Relationship Between the Constitutive Characteristics and the Accumulative AE Counts -- 6.3.3 Relationship Between AE Rate and Constitutive Characteristics -- 6.3.4 Evolution Characteristics of AE Amplitude in the Time Domain -- 6.3.5 Analyzation of Precursory Characteristics of Rock Failure -- 6.4 Variation Regulation of AE Energy Parameters for Rock Failure -- 6.4.1 Experimental Setup and Procedure.

7.7 b Value Characteristics with MS Activity in Deep Mining -- 7.7.1 The Magnitude-Frequency Relation-b Value -- 7.7.2 Changes of b Value Caused by Rockmass Excavation -- 7.8 Identification of Predicting Key Point Using AE/MS Monitoring System -- 7.9 Model of Multi-means and Synergistic Prediction for Rockburst -- 7.10 Conclusion -- References -- 8 Predicting Model of Rockburst Based on Nondeterministic Theory -- 8.1 Introduction -- 8.2 Predicting Model of Rockburst Based on Bayesian Theory -- 8.2.1 An Overview of Bayesian Theory -- 8.2.1.1 Empirical Probability -- 8.2.1.2 Mean Values and Covariance -- 8.2.1.3 Empirical Discriminant -- 8.2.1.4 Posterior Probability and Verification -- 8.2.2 Key Factors of Rockburst Tendency -- 8.2.2.1 Induced Factors of Rockburst -- 8.2.2.2 Critical Factors -- 8.3 Predicting Model of Rockburst Based on Fuzzy Matter-Element Theory -- 8.3.1 Fuzzy Matter-Element and Composite Fuzzy Matter-Element -- 8.3.2 Standard Fuzzy Matter-Element and Difference Square Composite Fuzzy Matter-Element -- 8.3.3 Weight Coefficients Determined by Entropy Method -- 8.3.4 Closeness Degree and Comprehensive Evaluation -- 8.4 Conclusions -- References -- 9 Field Case -- 9.1 Design of Microseismic Monitoring System in Huize Lead-Zine Mine -- 9.1.1 Main Influence Factor -- 9.1.2 Microseismic Monitoring System -- 9.1.3 Sensor Arrangement Design -- 9.2 Case Verification -- 9.2.1 Predicting Case Based on Displacement Nephogram -- 9.2.2 Predicting Case Based on Apparent Stress -- 9.3 Predicting Key Points Identification of Dynamic Hazard -- 9.3.1 Dynamic Hazard Predicting Using Routine Monitoring -- 9.3.2 Predicting Key Point Identification Using CAV and MS Events Activity -- 9.4 Predicting Model of Rockburst Based on Bayesian Theory -- 9.4.1 Training Samples -- 9.4.2 Predicting Rockburst Tendency Using a Bayesian Model.

4.4.1.2 Three-Dimensional Reconstruction Model of Failured Sandstone -- 4.4.1.3 Mesh Generation of Reconstructed Model -- 4.4.1.4 Three-Dimensional Model Parameters -- 4.4.2 Numerical Simulation of Fissured Rock -- 4.4.2.1 Selection of Material Parameters -- 4.4.2.2 Numerical Analysis of Model -- References -- 5 Experimental Investigation on Nonlinear Dynamic Evolution Patterns of Cracks in& -- blank Rock Failure Process -- 5.1 Introduction -- 5.2 Pattern of Nonlinear Dynamics Evolution of Rock Cracks -- 5.2.1 Fractal Theory -- 5.2.2 Results Analysis on Fractal Dimension of Rock Cracks -- 5.2.2.1 Calculated Procedure of Fractal Box Dimension -- 5.2.2.2 Results Analysis on Fractal Dimension of Sandstone Cracks -- 5.2.3 Entropy Model of Rock System Based on Fractal Dimension -- 5.3 Chaotic Characteristics of Cracks Evolution in Rock Failure Process -- 5.3.1 Chaos Theory -- 5.3.2 Discrimination of Chaotic Characteristics Defined by Li-Yorke -- 5.3.3 Construction of Crack Growth Factor Model -- 5.4 Conclusion -- References -- 6 Experimental Investigation on AE Precursor Information of Rockburst -- 6.1 Introduction -- 6.2 Spatio-temporal Evolution Pattern of Rock Failure -- 6.2.1 AE Experiment -- 6.2.2 Principle of AE Event Location -- 6.2.3 Spatio-temporal Distribution Characteristics of Rock Failure -- 6.3 Characteristics of Relatively Quiet Period for Rock Failure -- 6.3.1 Deformation and Failure Characteristics of Loaded Rock -- 6.3.2 Relationship Between the Constitutive Characteristics and the Accumulative AE Counts -- 6.3.3 Relationship Between AE Rate and Constitutive Characteristics -- 6.3.4 Evolution Characteristics of AE Amplitude in the Time Domain -- 6.3.5 Analyzation of Precursory Characteristics of Rock Failure -- 6.4 Variation Regulation of AE Energy Parameters for Rock Failure -- 6.4.1 Experimental Setup and Procedure.

6.4.2 Energy Parameters Variations in Each Channel -- 6.4.3 Relationship of Energy and Stress-Strain Curve on Time Domain -- 6.4.4 Analysis of Damage Features -- 6.4.5 Energy Release Rate of Rock Damage -- 6.5 Evolution Patterns of Spatial-Temporal-Energy on Rock Fracture Surface -- 6.5.1 Experimental Setup and Procedure -- 6.5.2 Relationship Between Spatial Distribution of AE Events and Rock Fracture -- 6.5.3 Spatial-Temporal Evolution of Strong AE Events on Rock Fracture -- 6.5.4 Spatial-Temporal-Energy Evolution Model of Strong AE Events in Limestone Fracture -- 6.5.5 Spatial Fractal Dimension Evolution Model of AE Events on Fracture -- 6.6 Conclusion -- References -- 7 Experimental Investigations on Multi-means and Synergistic Prediction for Rockburst -- 7.1 Introduction -- 7.2 Predicting Points of Infrared Precursor for Coal Failure -- 7.2.1 Laboratory Test of Coal Failure -- 7.2.2 Theoretical Bases of IRR Detection -- 7.2.3 IRT Characteristics of Coal Samples -- 7.2.4 IRT Prediction for Rock Failure -- 7.3 Experimental Investigation on Predicting Rock Failure Using Load/Unload Energy Response Ratio Theory -- 7.3.1 LURR Characteristics of Coal Samples -- 7.3.2 LURR Prediction of Coal Failure -- 7.4 Experimental Investigation on Predicting Points Using Tangent Damage Factor for Rock Failure -- 7.4.1 Laboratory Test of Rock Failure -- 7.4.2 Define the TDF -- 7.4.3 Damage Characteristic of Limestone Failure -- 7.4.4 Predicting Models of TDF -- 7.5 Experimental Investigation on Predicting Points Using Information Entropy Theory for Rock Failure -- 7.5.1 AE Dominant Frequency -- 7.5.2 AE Dominant Frequency Entropy -- 7.5.3 AE Dominant Frequency and Entropy -- 7.6 Predicting Key Point Identification Using Traditional Monitoring Method -- 7.6.1 Methods for Instrument Installation and Data Collection -- 7.6.2 Recognition Method of Predicting Hazards.

9.4.3 Verifying Accuracy of Bayesian Model -- 9.5 Predicting Model of Rockburst Based on Fuzzy Matter Element Theory -- 9.5.1 Testing and Field Condition -- 9.5.1.1 Mining Conditions and Method -- 9.5.1.2 Laboratory Testing -- 9.5.1.3 Stress Estimation -- 9.5.2 Predicting Rockburst Tendency -- 9.5.2.1 Predicting Rockburst Tendency Using Traditional Method -- 9.5.2.2 Predicting Rockburst Tendency Using the Proposed Model -- 9.5.3 Predicting Model of Fuzzy Matter-Element Theory -- 9.5.3.1 Comparison and Analysis of Predicting Model -- 9.5.3.2 Data Analysis and Discussions -- 9.6 Conclusion -- References.

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