Nuclear Science and Techniques

《核技术》(英文版) ISSN 1001-8042 CN 31-1559/TL     2019 Impact factor 1.556

Nuclear Science and Techniques ›› 2018, Vol. 29 ›› Issue (2): 20 doi: 10.1007/s41365-018-0366-4

• NUCLEAR ENERGY SCIENCE AND ENGINEERING • Previous Articles     Next Articles

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

Hong-Fei Liu, Peng Ge, Sheng-Peng Yu, Jing Song, Xiao-Lei Zheng   

  1. Key Laboratory of Neutronics and Radiation Safety, Institute of Nuclear Energy Safety Technology, Chinese Academy of Sciences, Hefei 230031, China
  • Contact: Xiao-Lei Zheng E-mail:xiaolei.zheng@fds.org.cn
  • Supported by:

    This work was supported by the Innovation Foundation of the Chinese Academy of Sciences (No. CXJJ-16Q231), the National Natural Science Foundation of China (No. 11305203), the Special Program for Informatization of the Chinese Academy of Sciences (No. XXH12504-1-09), the Anhui Provincial Special Project for High Technology Industry, and the Special Project of Youth Innovation Promotion Association of Chinese Academy of Sciences, the Industrialization Fund.

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Hong-Fei Liu, Peng Ge, Sheng-Peng Yu, Jing Song, Xiao-Lei Zheng. Data decomposition method for full-core Monte Carlo transport–burnup calculation.Nuclear Science and Techniques, 2018, 29(2): 20     doi: 10.1007/s41365-018-0366-4
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Abstract:

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.

Key words: Monte Carlo, Burnup calculation, Data decomposition, BEAVRS, SuperMC