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Monte Carlo N-Particle Simulations for Nuclear Detection and Safeguards
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Monte Carlo N-Particle Simulations for Nuclear Detection and Safeguards : An Examples-Based Guide for Students and Practitioners

1st ed. 2022

Book Details

Format Paperback / Softback
ISBN-10 3031041313
ISBN-13 9783031041310
Edition 1st ed. 2022
Publisher Springer International Publishing AG
Imprint Springer International Publishing AG
Country of Manufacture GB
Country of Publication GB
Publication Date Sep 28th, 2022
Print length 307 Pages
Weight 502 grams
Dimensions 15.60 x 23.50 x 2.10 cms
Ksh 6,300.00
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This book fills a gap in the existing MCNP software literature by teaching MCNP software usage through detailed examples that were selected based on both student feedback and the real-world experience of the nuclear safeguards group at Los Alamos National Laboratory.

This  open access book is a pedagogical, examples-based guide to using the Monte Carlo N-Particle (MCNP®) code for nuclear safeguards and non-proliferation applications. The MCNP code, general-purpose software for particle transport simulations, is widely used in the field of nuclear safeguards and non-proliferation for numerous applications including detector design and calibration, and the study of scenarios such as measurement of fresh and spent fuel. This book fills a gap in the existing MCNP software literature by teaching MCNP software usage through detailed examples that were selected based on both student feedback and the real-world experience of the nuclear safeguards group at Los Alamos National Laboratory. MCNP input and output files are explained, and the technical details used in MCNP input file preparation are linked to the MCNP code manual. Benefiting from the authors'' decades of experience in MCNP simulation, this book is essential reading for students, academic researchers, and practitioners whose work in nuclear physics or nuclear engineering is related to non-proliferation or nuclear safeguards. 

Each chapter comes with downloadable input files for the user to easily reproduce the examples in the text.




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