Review of the Discrete-Ordinates Method for Particle Transport in Nuclear Energy

Yingchi Yu, Xin He, Maosong Cheng () and Zhimin Dai ()
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Yingchi Yu: Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
Xin He: Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
Maosong Cheng: Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
Zhimin Dai: Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China

Energies, 2025, vol. 18, issue 11, 1-33

Abstract: The advantages and recent advancements of the Discrete-Ordinates (S N ) Method have established its widespread adoption in particle transport calculations for nuclear energy systems. The mathematical foundations and diverse applications of the S N method are comprehensively summarized in this review. Recent advances are critically evaluated, with particular emphasis placed on advanced discretization techniques, high-performance computing implementations, and hybrid coupling strategies with MC, MOC method, and so on. Despite these developments, challenges remain, including the need for high-fidelity simulations, optimization of computational performance, and the complexity introduced by temporal dependencies in dynamic radiation field calculations, which necessitates innovative numerical methods. Future developments of the S N method are anticipated to address these challenges through enhanced high-fidelity numerical simulation, robust high-performance computing frameworks, multi-physics field coupling, and AI integration. These developments advance the industrial-scale implementation of the S N method in nuclear energy applications, enabling efficient and accurate analyses of complex reactor systems.

Keywords: discrete-ordinates method; nuclear energy; particle transport; high-performance computing; numerical calculation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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