Monte Carlo Methods and Codes for Nuclear Engineering Analysis provides a comprehensive survey of the state-of-the-art in radiation transport methods used by Monte Carlo (MC) codes. It explores the real-world implementation of these methods in codes used by nuclear scientists and engineers, considering the advantages and disadvantages of the various techniques, design philosophies and algorithm implementations. After a foreword and introduction giving a brief history of Monte Carlo methods, code systems, and their applications in nuclear science and engineering, subsequent chapters describe the fundamentals of Monte Carlo radiation transport methods by dividing the field into a number of topics or focus areas.

Subjects selected include potential geometry and particle tracking, nuclear data, variance reduction, time-dependent analysis and parallel computing. Each chapter presents a comprehensive survey of the state-of-the-art implementations, algorithms, and methodologies used by production-level Monte Carlo codes for the area. A concluding chapter provides a handy summary by briefly listing the methods used by key Monte Carlo codes for each focus area in several tables.

This book is an essential guide to Monte Carlo methods and codes for nuclear scientists, engineers and code developers in academia and industry and students studying this topic.

Monte Carlo Methods and Codes for Nuclear Engineering Analysis provides a comprehensive survey of the state-of-the-art in radiation transport methods used by Monte Carlo (MC) codes. It explores the real-world implementation of these methods in codes used by nuclear scientists and engineers, considering the advantages and disadvantages of the various techniques, design philosophies and algorithm implementations. After a foreword and introduction giving a brief history of Monte Carlo methods, code systems, and their applications in nuclear science and engineering, subsequent chapters describe the fundamentals of Monte Carlo radiation transport methods by dividing the field into a number of topics or focus areas.

Subjects selected include potential geometry and particle tracking, nuclear data, variance reduction, time-dependent analysis and parallel computing. Each chapter presents a comprehensive survey of the state-of-the-art implementations, algorithms, and methodologies used by production-level Monte Carlo codes for the area. A concluding chapter provides a handy summary by briefly listing the methods used by key Monte Carlo codes for each focus area in several tables.

This book is an essential guide to Monte Carlo methods and codes for nuclear scientists, engineers and code developers in academia and industry and students studying this topic.