An improved tracking method for particle transport Monte Carlo simulations

Tracking methods are used in particle transport Monte Carlo simulations to simulate the particle movements in models with multiple materials. However, as Monte Carlo simulations are becoming increasingly sophisticated, the most widely used tracking method, ray-tracing, exposes serious disadvantages in dealing with continuously varying materials and needs to be improved. Delta-tracking, the most common alternative, is not stable enough as its efficiencystrongly depends on the models. After comparing the two methods, this paper presents an improved tracking method called hybrid-tracking that integrates the advantages of these two tracking methods. Hybrid-tracking significantly improves the computational efficiency by merging cells in complex geometric models. For the model in this paper, the time cost of cross-boundary judgments is significantly lower using hybrid-tracking with the computational efficiency increasing by 20%. Hybrid-tracking is then used in an advanced on-the-fly cross-section temperature treatment-Target Motion Sample (TMS) method, after the biasness of TMS method in ray-tracing is proved. Hybridtracking method extends the application range of the TMS method from a single material to multiple materials. The efficiency and validity of the TMS method in hybrid-tracking are illustrated using the VERA benchmark Problem 3A. These methods are easily implemented in the Monte Carlo codes based on ray-tracing and are compatible with the original functions. (c) 2021 Elsevier Inc. All rights reserved.

Automated summary

This paper introduces an improved tracking method called hybrid-tracking, which enhances the computational efficiency of particle transport Monte Carlo simulations. By integrating the advantages of ray-tracing and Delta-tracking methods, hybrid-tracking extends the application range of the TMS method and significantly improves efficiency.