Monte-Carlo Simulation: An Introduction for Engineers and Scientists
- Length: 98 pages
- Edition: 1
- Language: English
- Publisher: CRC Press
- Publication Date: 2022-09-16
- ISBN-10: 1032280778
- ISBN-13: 9781032280776
- Sales Rank: #0 (See Top 100 Books)
Monte-Carlo techniques have increasingly become a key method used in quantitative research. This book introduces engineers and scientists to the basics of using the Monte-Carlo simulation method which is used in Operations Research and other fields to understand the impact of risk and uncertainty in prediction and forecasting models.
Monte-Carlo Simulation: An Introduction for Engineers and Scientists explores several specific applications in addition to illustrating the principles behind the methods. The question of accuracy and efficiency with using the method is addressed thoroughly within each chapter and all program listings are included in the discussion of each application to facilitate further research for the reader using Python programming language.
Beginning engineers and scientists either already in or about to go into industry or commercial and government scientific laboratories will find this book essential. It could also be of interest to undergraduates in engineering science and mathematics, as well as instructors and lecturers who have no prior knowledge of Monte-Carlo simulations.
Cover Half Title Title Page Copyright Page Dedication Contents Preface About the Author Chapter 1: The Basic Idea 1.1. Introduction Chapter 2: Buffon’s Needle 2.1. Background 2.2. Computer Simulation 2.3. Features of the Simulation 2.4. Precision 2.5. Physical Simulation 2.6. Buffon’s Formula 2.7. Exercises Chapter 3: Areas and Integrals 3.1. Temperature Profile 3.2. Simulation 3.3. Sample Mean Method 3.4. Higher Dimensions 3.5. Exercises Chapter 4: Thermal Radiation 4.1. Radiation View Factor 4.2. Simulation 4.3. Precision 4.4. Exercises Chapter 5: Bending Beams 5.1. Neutral Axis Offset 5.2. Simulation 5.3. Precision 5.4. Exercises Chapter 6: Torus Segment 6.1. Volume of a Segment of Torus 6.2. Simulation 6.3. Precision 6.4. Exercises Chapter 7: Radiation Shielding 7.1. Diffusion 7.2. Gamma-Ray Shielding 7.3. Build-up Factor and Energy Distribution 7.4. Simulation 7.5. Build-up Factors 7.6. Exercises Chapter 8: Stressed Cylinder 8.1. Buckling Probability 8.2. Simulation 8.3. Precision 8.4. Wilks’ Method 8.5. Exercises Chapter 9: Linear Resistive Networks 9.1. Circuit Analysis by Random Walk 9.2. Single-Node Simulation 9.3. Unit-Resistance Cube Simulation 9.4. Heat Conduction Simulation 9.5. Exercises Chapter 10: Magnetic Phase Transitions 10.1. Ising Spin Model 10.2. Physical Properties 10.3. The Gibbs and Metropolis Algorithms 10.4. Simulation 10.5. Exercises Chapter 11: Polymer Chains 11.1. Polymers 11.2. Simulation 11.3. Precision 11.4. Exercises Chapter 12: Solutions To Selected Exercises 12.1. Exercise 2.7.4 12.2. Exercise 3.5.2 12.3. Exercise 4.4.1 12.4. Exercise 5.4.2 12.5. Exercise 6.4.2 12.6. Exercise 7.6.2 12.7. Exercise 8.4.2 12.8. Exercise 9.5.1 12.9. Exercise 10.5.3 12.10. Exercise 11.4.3 Appendix A: Random Numbers A.1. Introduction A.2. Uniformly Distributed Random Numbers A.3. Normally Distributed Random Numbers Appendix B: Variance Reduction B.1. Introduction B.2. Importance Weighting B.3. Antithetic Variates B.4. Control Variates Index
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