Efficient Monte Carlo Particle Transport Simulation for Hybrid Geometries Using an Intrusive Approach

Unstructured mesh (UM) is regarded as an attractive alternative to constructive solid geometry (CSG) in Monte Carlo (MC) simulations due to its adaptability to complex geometries and inherent advantages in conducting multiphysics coupling analysis with finite element codes. However, there generally exists a gap between practical solid models and transport-ready geometries due to the omission of background materials such as air and coolant. This necessitates additional effort to create computer-aided design models for background materials and to generate UM representations meeting accuracy requirements. Such limitations can restrict the applicability of MC simulations, particularly when background materials exhibit significant scale variations and narrow slots. Furthermore, the memory requirements and computational costs associated with UM-based MC simulations for large-scale problems may pose feasibility challenges.

To mitigate these issues, this paper presents an intrusive approach to MC simulations within hybrid geometry. In the hybrid geometry, complex solid entities are represented using UM, while background materials or regular-shape geometries are modeled using CSG. This approach allows for arbitrary intersections between these two geometric representations by explicitly processing the topological relationships between CSG and UM objects during geometric initialization and particle tracking.

The hybrid geometry–based particle tracking capability has been implemented in the MC code NECP-MCX. Validation studies were conducted against benchmarks, including the KRUSTY (Kilowatt Reactor Using Stirling Technology) component critical configurations and the ATR (Advanced Test Reactor) critical experiment. Numerical results underscore potential challenges encountered by the pure UM approach while demonstrating that hybrid geometry–based MC simulations can achieve results that closely align with experimental measurements in acceptable efficiencies.