Study on Diffusion Source Cascade Variance Reduction Method for Monte Carlo Deep-penetration Shielding Calculation

Wang Xueqing; Lyu Huanwen; Yang Hongrun

doi:10.13832/j.jnpe.2024.080052

Volume 46 Issue 4

Aug. 2025

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Wang Xueqing, Lyu Huanwen, Yang Hongrun. Study on Diffusion Source Cascade Variance Reduction Method for Monte Carlo Deep-penetration Shielding Calculation[J]. Nuclear Power Engineering, 2025, 46(4): 42-48. doi: 10.13832/j.jnpe.2024.080052

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Wang Xueqing, Lyu Huanwen, Yang Hongrun. Study on Diffusion Source Cascade Variance Reduction Method for Monte Carlo Deep-penetration Shielding Calculation[J]. Nuclear Power Engineering, 2025, 46(4): 42-48. doi: 10.13832/j.jnpe.2024.080052

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Study on Diffusion Source Cascade Variance Reduction Method for Monte Carlo Deep-penetration Shielding Calculation

doi: 10.13832/j.jnpe.2024.080052

State Key Laboratory of Advanced Nuclear Energy Technology, Nuclear Power Institute of China, Chengdu, 610213, China

Received Date: 2024-08-30
Rev Recd Date: 2024-10-22
Publish Date: 2025-08-15

Abstract

Abstract

This paper proposed the diffusion source cascade variance reduction method for Monte Carlo deep-penetration shielding calculation. The core idea of this method is to obtain the global variance-reducing parameter distribution through the cascade of response relations in multi-layer local phase space. The method first calculates the flux response factors related to space and energy between adjacent phase spaces by the dispersion source. Secondly, it cascades outward from the source space to obtain the global estimated flux distribution. Thirdly, it cascades backward from the count space to obtain the importance distribution. Finally it generates the consistent source bias parameters and weight window parameters. This method obtains the variance-reducing parameters through local Monte Carlo pre-calculation, so there is no need for iteration, which can effectively reduce the iteration time cost and improve the calculation efficiency. This method is applied to the single detector problem and the multi-detector problem. The calculated values are in good compliance with the Monte Carlo direct calculation, and the quality factor is improved by about 2~4 orders of magnitude. At the same time, the results are compared with those of the typical variance-reducing methods MAGIC and CADIS. The numerical results show that the overall variance-reducing effect of the diffusion source cascade method is better, and it can meet the requirements of the deep-penetration shielding calculation.
- Monte Carlo method,
- Variance reduction skills,
- Deep-penetration shielding,
- Diffusion source cascade method

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References(18)

References

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