Data decomposition method for full-core Monte Carlo transport–burnup calculation

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作者
Hong-Fei Liu
Peng Ge
Sheng-Peng Yu
Jing Song
Xiao-Lei Zheng
机构
[1] Chinese Academy of Sciences,Key Laboratory of Neutronics and Radiation Safety, Institute of Nuclear Energy Safety Technology
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Monte Carlo; Burnup calculation; Data decomposition; BEAVRS; SuperMC;
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摘要
Monte Carlo transport simulations of a full-core reactor with a high-fidelity structure have been made possible by modern-day computing capabilities. Performing transport–burnup calculations of a full-core model typically includes millions of burnup areas requiring hundreds of gigabytes of memory for burnup-related tallies. This paper presents the study of a parallel computing method for full-core Monte Carlo transport–burnup calculations and the development of a thread-level data decomposition method. The proposed method decomposes tally accumulators into different threads and improves the parallel communication pattern and memory access efficiency. A typical pressurized water reactor burnup assembly along with the benchmark for evaluation and validation of reactor simulations model was used to test the proposed method. The result indicates that the method effectively reduces memory consumption and maintains high parallel efficiency.
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