ISBN-10:
1118117778
ISBN-13:
9781118117774
Pub. Date:
05/08/2012
Publisher:
Wiley
Handbook of Real-World Applications in Modeling and Simulation / Edition 1

Handbook of Real-World Applications in Modeling and Simulation / Edition 1

by John A. Sokolowski, Catherine M. Banks
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Product Details

ISBN-13: 9781118117774
Publisher: Wiley
Publication date: 05/08/2012
Series: Wiley Series in Operations Research and Management Science Series , #2
Pages: 352
Product dimensions: 6.30(w) x 9.30(h) x 1.10(d)

About the Author

John A. Sokolowski, PHD, is Executive Director of the VirginiaModeling, Analysis, and Simulation Center (VMASC) at Old DominionUniversity, where he is also Associate Professor of Modeling andSimulation Engineering. He is the coeditor of Principles ofModeling and Simulation: A Multidisciplinary Approach, Modeling andSimulation Fundamentals: Theoretical Underpinnings and PracticalDomains, and Modeling and Simulation in the Medical and HealthSciences and coauthor of Modeling and Simulation for AnalyzingGlobal Events, all published by Wiley.

Catherine M. Banks, PHD, is Research Associate Professor atVMASC. She is the coeditor of Principles of Modeling andSimulation: A Multidisciplinary Approach, Modeling and SimulationFundamentals: Theoretical Underpinnings and Practical Domains, andModeling and Simulation in the Medical and Health Sciences andcoauthor of Modeling and Simulation for Analyzing Global Events,all published by Wiley.

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Table of Contents

Contributors xiii

Preface xvii

Introduction 1

1 Research and Analysis for Real-World Applications 8
Catherine M. Banks

1.1 Introduction and Learning Objectives  8

1.1.1 Learning Objectives  10

1.2 Background  10

1.3 M&S Theory and Toolbox  13

1.3.1 Simulation Paradigms  15

1.3.2 Types of Modeling  16

1.3.3 Modeling Applications  17

1.4 Research and Analysis Methodologies  18

Case Study: A Methodology for M&S Project Progression 20

Summary  23

Key Terms  24

Exercises  25

References  25

2 Human Behavior Modeling: A Real-World Application 26
John A. Sokolowski

2.1 Introduction and Learning Objectives  26

2.2 Background and Theory  27

2.2.1 Classical Decision Theory  27

2.2.2 Naturalistic Decision Making  31

2.2.3 Recognition-Primed Decision Model  33

2.2.4 Military Decision Making  37

2.2.5 Computational Techniques for Implementing the CJTFDecision Process  40

2.2.6 Summary of the State-of-the-Art  53

Case Studies  54

Summary  81

Key Terms  82

Exercises  83

References  83

Appendix: A Decision Scenario and Associated Data  88

3 Transportation 93
R. Michael Robinson

3.1 Introduction and Learning Objectives  93

3.2 Background  94

3.3 Theory  95

3.3.1 Simulation Levels  95

3.3.2 Traffic Analysis Zones  97

3.3.3 The Four-Step Model  98

3.3.4 Method of Successive Averages  102

3.3.5 Volume Delay Functions  105

3.3.6 Dynamic Traffic Assignment  108

3.4 Transportation Modeling Applications  113

3.4.1 Traffic Demand Models  113

3.4.2 Public Transportation Models  114

3.4.3 Freight Modeling  117

3.4.4 Evacuation Simulations  121

Summary  124

Key Terms  125

Exercises  126

References  126

Further Reading  127

4 Homeland Security Risk Modeling 129
Barry C. Ezell

4.1 Introduction and Learning Objectives  129

4.2 Background  131

4.2.1 Bioterrorism Risk Assessment 2006  132

4.2.2 Estimating Likelihood of Terrorist Events  133

4.2.3 Risk Assessed as a Function of Threat Vulnerability  and Consequence  135

4.3 Theory and Applications in Risk Modeling  136

4.3.1 Philosophical Considerations  137

4.3.2 Ontology and Epistemology  138

4.3.3 Issues and Implications for the Risk Analyst  138

4.3.4 Philosophical Considerations Summary  141

4.3.5 System Principals and Applications for the RiskAnalyst  142

4.3.6 Factors in Developing a Risk Assessment Study Plan 143

4.3.7 Scope and Bound in a Risk Study: Constraints Limitations  and Assumptions  145

4.3.8 Well-Known Challenge in Homeland Security Studies 146

4.4 Elements of a Study Plan  147

4.5 Modeling Paradigms  148

4.5.1 Simple Verses Complex Methodologies  148

4.5.2 Quantitative and Qualitative Designs  148

4.5.3 Modeling Approaches and Examples  150

4.5.4 Verification and Validation for Risk Models  156

Case Studies  157

Summary  161

Key Terms  161

Exercises  161

References  162

Further Reading  164

5 Operations Research 165
Andrew J. Collins and Christine S.M. Currie

5.1 Introduction and Learning Objectives  165

5.2 Background  166

5.2.1 OR Techniques  168

5.3 Theory  169

5.3.1 Problem Structuring Methods  169

5.3.2 Queuing Theory  175

5.3.3 Decision Analysis  179

5.3.4 Game Theory  182

5.3.5 Optimization  186

5.4 Modeling Paradigms  192

Case Studies  193

Summary  199

Key Terms  201

Exercises  202

x Contents

References  204

Further Reading  206

6 Business Process Modeling 207
Rafael Diaz  Joshua G. Behr  and MandarTulpule

6.1 Introduction and Learning Objectives  207

6.2 Background  207

6.3 Discrete-Event Simulation  214

6.3.1 Introduction  214

6.3.2 Fundamentals  215

6.3.3 Queuing System Model Components  218

6.3.4 Time Advance Mechanism  219

6.3.5 Simulation Flowchart  220

6.4 Discrete-Event Simulation Case Study  221

6.4.1 Introduction  222

6.4.2 Background  222

6.4.3 Research Question  223

6.4.4 Overview of Optimization Model  224

6.4.5 The Simulation Model  225

6.4.6 Experimental Setting  225

6.4.7 Simulation Parameterization and Execution  226

6.4.8 Weigh Zones and Product Reassignment  226

6.4.9 Results  226

6.5 System Dynamics Simulation  227

6.5.1 Introduction  227

6.5.2 Fundamentals  228

6.5.3 The Stock and Flow Diagrams  229

6.5.4 Model Calibration  231

6.5.5 Model Testing  233

6.5.6 Population Modeling Exercise  233

6.5.7 Application of System Dynamics  235

6.5.8 Background  235

6.5.9 Research Question  238

6.5.10 Dynamic Hypothesis  238

6.5.11 Causal Loop Diagram  238

6.5.12 Stock and Flow Model  239

6.5.13 Simulation and Results  240

6.5.14 Conclusions  244

6.6 Monte Carlo Simulation  244

6.6.1 Introduction  244

6.6.2 Fundamentals  245

6.6.3 Probability Theory and Monte Carlo  247

6.6.4 Central Limit Theorem  247

6.6.5 Three-Sigma Rule  247

6.6.6 Monte Carlo Case Study  249

6.6.7 Research Question  250

6.6.8 Model Parameters  250

6.6.9 Simulation Procedure  250

6.6.10 Estimating Profit  251

6.6.11 Excel Implementation  253

6.6.12 Outcomes  253

6.6.13 Conclusions  254

Summary  255

Key Terms  255

Review Questions  256

References  257

7 A Review of Mesh Generation for Medical Simulators261
Michel A. Audette  Andrey N. Chernikov  and NikosP. Chrisochoides

7.1 Introduction and Learning Objectives  261

7.2 Background—A Survey of Relevant Biomechanics andOpen-Source Software  263

7.2.1 Architecture of an Interactive Medical Simulator 263

7.2.2 Mechanics of Tissue Manipulation in MedicalSimulation  264

7.2.3 Mechanics of Tissue Cutting and Resection in MedicalSimulation  269

7.2.4 Open-Source Resources in Medical Simulation  269

7.3 Theory—The Impact of Element Quality and Size onSimulation  272

7.4 Modeling Paradigms—Methods for Mesh Generation 276

7.4.1 Structured Tetrahedral Mesh Generation  276

7.4.2 Unstructured Tetrahedral Mesh Generation  276

7.4.3 Octree-Based Unstructured Tetrahedral MeshGeneration  279

7.4.4 Delaunay Unstructured Tetrahedral Mesh Generation 280

7.4.5 Advancing Front Unstructured Tetrahedral MeshGeneration  284

7.4.6 Optimization-Based Unstructured Tetrahedral MeshGeneration  284

7.4.7 Unstructured Surface Mesh Generation  285

Case Studies  289

Summary  291

Key Terms  292

Acknowledgments  293

Exercises  293

References  294

8 Military Interoperability Challenges 298
Saikou Y. Diallo and José J. Padilla

8.1 Introduction and Learning Objectives  298

8.2 Background  299

8.2.1 Overview  300

8.2.2 State of the Art in Interoperability  300

8.2.3 Levels of Interoperability  302

8.2.4 Current Approaches to Interoperation  303

8.3 Theory  305

8.3.1 Data Models  306

8.3.2 A Relational Model of Data in M&S Systems 307

Case Study: Live Virtual Constructive SimulationEnvironments  311

8.4 Live Virtual Constructive  311

8.5 LVC Examples  315

8.6 Distributed Simulation Engineering and Execution Process(DSEEP)  316

8.7 LVC Architecture Framework (LVCAF)  320

8.8 Simulation Systems  322

Summary  323

Key Terms  324

Exercises  325

References  325

Index 329

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