Stephen A. Dupree, Stanley K. Fraley

A Monte Carlo Primer (eBook, PDF)

Volume 2

• Format: PDF

Produktbeschreibung

In Volume 1, A Monte Carlo Primer - A Practical Approach to Radiation Transport (the "Primer"), we attempt to provide a simple, convenient, and step-by-step approach to the development, basic understanding, and use of Monte Carlo methods in radiation transport. Using the PC, the Primer begins by developing basic Monte Carlo codes to solve simple transport problems, then introduces a teaching tool, the Probabilistic Framework Code (PFC), as a standard platform for assembling, testing, and executing the various Monte Carlo techniques that are presented. This second volume attempts to continue this approach by using both custom Monte Carlo codes and PFC to apply the concepts explained in the Primer to obtain solutions to the exercises given at the end of each chapter in the Primer. A relatively modest number of exercises is included in the Primer. Some ambiguity is left in the statement of many of the exercises because the intent is not to have the user write a particular, uniquely correct piece of coding that produces a specific number as a result, but rather to encourage the user to think about the problems and develop further the concepts explained in the text. Because in most cases there is more than one way to solve a Monte Carlo transport problem, we believe that working with the concepts illustrated by the exercises is more important than obtaining anyone particular solution.

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Produktdetails

• Verlag: Springer New York
• Seitenzahl: 230
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9781441990365
• Artikelnr.: 44042611

Inhaltsangabe

1. Introduction.- 1.1 The Monte Carlo Method.- 1.2 The Evaluation of Random Processes>.- 1.3 Monte Carlo Evaluation of Definite Integrals.- Exercises.- 2. Monte Carlo Sampling Techniques.- 2.1 Probability Theory and Statistics.- 2.2 Sampling.- 2.3 Means and Variances.- 2.4 Estimations of Means and Variances.- 2.5 Introduction to Variance Reduction Techniques.- Exercises.- 3. Monte Carlo Modeling of Neutron Transport.- 3.1 Introduction.- 3.2 Neutron Interactions and Mean Free Path.- 3.3 Neutron Transport.- 3.4 A Mathematical Basis for Monte Carlo Neutron Transport.- 3.5 Monte Carlo Modeling of Neutron Motion.- 3.6 Particle Flight Path in Complex Geometries.- 3.7 Multi-Region Problems.- Exercises.- 4. Energy-Dependent Neutron Transport.- 4.1 Elastic Scattering of Neutrons.- 4.2 Transformation of Post-Collision Direction to Laboratory System.- 4.3 Energy-Dependent Cross Sections.- Exercises.- 5. A Probabilistic Framework Code.- 5.1 Introduction to PFC.- 5.2 Problem Definition in PFC.- 5.3 The Random Walk in PFC.- 5.4 Computing the Response.- Exercises.- 6. Variance Reduction Techniques.- 6.1 Introduction.- 6.2 Source Biasing.- 6.3 Survival Biasing.- 5.4 Russian Roulette.- 6.5 Splitting.- 6.6 Exponential Transform.- Exercises.- 7. Monte Carlo Detectors.- 7.1 Introduction.- 7.2 The Next-Event Estimator.- 7.3 Volumetric Flux Detectors.- 7.3 Surface-Crossing Flux Estimator.- 7.5 Expectation Surface-Crossing Flux Estimator.- Time-Dependent Detectors.- Exercises.- 8. Nuclear Criticality Calculations with Monte Carlo.- 8.1 Multiplying Assemblies.- 8.2 The Generation Method.- 8.3 The Matrix Method.- 8.4 Combination of Generation and Matrix Methods.- 8.5 Criticality Calculations Using Multigroup Cross Sections.- Exercises.- 9. Advanced Applications of Monte Carlo.- 9.1 Correlated Sampling.- 9.2 Adjoint Monte Carlo.- 9.3 Neutron Thermalization.- Exercises.- Appendix Random Number Generators.