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Monte Carlo Methods for Particle Transport

Alireza Haghighat

$252

Hardback

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English
CRC Press
10 August 2020
Fully updated with the latest developments in the eigenvalue Monte Carlo calculations and automatic variance reduction techniques and containing an entirely new chapter on fission matrix and alternative hybrid techniques. This second edition explores the uses of the Monte Carlo method for real-world applications, explaining its concepts and limitations. Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, it is an ideal textbook and practical guide for nuclear engineers and scientists looking into the applications of the Monte Carlo method, in addition to students in physics and engineering, and those engaged in the advancement of the Monte Carlo methods.

Describes general and particle-transport-specific automated variance reduction techniques

Presents Monte Carlo particle transport eigenvalue issues and methodologies to address these issues

Presents detailed derivation of existing and advanced formulations and algorithms with real-world examples from the author’s research activities

By:  
Imprint:   CRC Press
Country of Publication:   United Kingdom
Edition:   2nd edition
Dimensions:   Height: 234mm,  Width: 156mm, 
Weight:   576g
ISBN:   9780367188054
ISBN 10:   0367188058
Pages:   310
Publication Date:  
Audience:   College/higher education ,  General/trade ,  Primary ,  ELT Advanced
Format:   Hardback
Publisher's Status:   Active
1 Introduction. 2 Random Variables and Sampling. 3 Random Number Generator (RNG). 4 Fundamentals of Probability and Statistics. 5 Integrals and Associated Variance Reduction Techniques. 6 Fixed-Source Monte Carlo Particle Transport. 7 Variance Reducation Techniques or Fixed-Source Particles. 8 Scoring/ Tallying. 9 Geometry and Particle Tracking. 10 Eigenvalue (Criticality) Monte Carlo Method for Particle Transport. 11 Fission Matrix Methods for Eigenvalue Monte Carlo Simulation. 12 Vector and Parallel Processing of Monte Carlo Particle Transport

Dr. Alireza Haghighat is professor and Director of Nuclear Engineering Program, Virginia Tech. He is a fellow of the American Nuclear Society. He has made pioneering contributions to the development of accurate and efficient deterministic, stochastic, and hybrid particle transport theory methods and their application to complex problems in nuclear reactors, nuclear security and radiation diagnosis and therapy.

Reviews for Monte Carlo Methods for Particle Transport

When we decided to offer a new senior undergraduate level course on Monte Carlo in the nuclear engineering department at North Carolina State University, we easily decided to choose the Monte Carlo book by Dr. Haghighat since it came so highly recommended. One of things we liked most about this book is the way the topics are structured. The first seven chapters mainly cover the fundamental theories of Monte Carlo methods for particle transport. While the last five chapters present more advanced theories, they can be seamlessly coupled with hands-on training with industry standard Monte Carlo codes (in our course we selected MCNP6.2). We easily designed our course following the general outline of this book. Furthermore, the course materials have been refined and improved many times based on Dr. Haghighat's many years of teaching experience, as well as comments from students, practitioners, and reviewers. They are well explained and cover almost all the essential concepts in Monte Carlo. For the first half of the semester that focused on Monte Carlo methods, the course work assignments were mainly programming-based homework problems (mostly taken from the exercises in the book). Dr. Haghighat designed these exercises so well that they can not only strengthen the students' understanding, but also inspire their critical thinking. We highly recommend this textbook for senior undergraduate students, graduate students and researchers who are interested in Monte Carlo applications on radiation transport. - Professors Xu Wu and John Zino, North Carolina State University, USA.


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