蒙特卡罗粒子输运方法及应用研究

邓力; 李刚; 张宝印; 李瑞; 张玲玉; 付元光; 刘鹏; 马彦; 史敦福; 王鑫; 秦桂明

doi:10.13832/j.jnpe.2025.02.0062

蒙特卡罗粒子输运方法及应用研究

doi: 10.13832/j.jnpe.2025.02.0062

邓力^1,,
李刚^{1, 2, ,},
张宝印^{1, 2},
李瑞²,
张玲玉²,
付元光²,
刘鹏²,
马彦¹,
史敦福²,
王鑫²,
秦桂明¹

1.
北京应用物理与计算数学研究所，北京，100094
2.
中物院高性能数值模拟软件中心，北京，100088

基金项目: 国家自然科学基金（12275030, u23b2067）

详细信息

作者简介:
邓　力（1960—），男，研究员，现主要从事粒子输运及高性能计算研究，E-mail: deng_li@iapcm.ac.cn

通讯作者:
李　刚，E-mail: li_gang@iapcm.ac.cn

中图分类号: TL334；O571.51
计量
- 文章访问数: 24
- HTML全文浏览量: 10
- PDF下载量: 5
- 被引次数: 0
出版历程
- 收稿日期: 2025-02-21
- 修回日期: 2025-03-26
- 网络出版日期: 2025-06-09
- 刊出日期: 2025-06-09

Study on Monte Carlo Particle Transport Method and Application

Deng Li^1
,,
Li Gang^{1, 2
, ,},
Zhang Baoyin^{1, 2},
Li Rui²,
Zhang Lingyu²,
Fu Yuanguang²,
Liu Peng²,
Ma Yan¹,
Shi Dunfu²,
Wang Xin²,
Qin Guiming¹

1.
Institute of Applied Physics and Computational Mathematics, Beijing, 100094, China
2.
CAEP Software Center for High Performance Numerical Simulation, Beijing, 100088, China

摘要

摘要: 蒙特卡罗（MC）粒子输运方法应用概率论随机理论与数理统计知识开发相应程序，并借助计算机工具帮助核领域解决各种粒子输运物理问题。经过70多年的发展，MC粒子输运方法理论和算法已经逐步成熟，先后诞生了多代多个程序软件，在核辐射屏蔽、核反应堆堆芯临界安全分析、核探测及核医学等传统领域广泛应用。本文从MC粒子输运的理论基础介绍开始，给出了MC方法求解积分形式中子输运方程的中子通量密度公式，以及中子通量密度响应量的计算方法，同时概述了求解输运方程的确定论方法分类，介绍了MC粒子输运方法发展历程和计算应用经历的阶段，以及国内外重要的MC粒子输运分析软件，还有近期国际上采用图形处理单元（GPU）技术发展MC粒子输运软件的方向和进展。同时对自主研制的MC粒子输运软件JMCT的功能和特色进行系统性介绍。
- 蒙特卡罗（MC）方法 /
- 粒子输运 /
- 并行计算 /
- JMCT /
- 人工智能
Abstract: Monte Carlo (MC) particle transport methodology incorporates stochastic principles derived from probability theory and mathematical statistics to establish computational frameworks. This approach facilitates the numerical resolution of complex particle transport phenomena in nuclear systems. Over the course of seven decades of development, MC particle transport theory and algorithms have reached a high level of technical maturity. This has resulted in the development of several specialized software packages, which are widely applied in fields such as nuclear radiation shielding, reactor core criticality safety analysis, nuclear detection, and radiation medicine. This study commences by establishing the theoretical framework underlying MC particle transport methodologies. Through rigorous mathematical derivation, we present the neutron flux density formulation developed via MC simulations for addressing integral-form neutron transport equations, coupled with analytical frameworks for determining associated response parameters. It also outlines the classification of deterministic approaches for solving transport equations. The study reviews the historical development and computational application of MC particle transport methods, while summarizing significant software developed domestically and internationally. Furthermore, it examines recent advancements in utilizing graphics processing unit (GPU) technology to develop MC particle transport software, highlighting current research directions and progress in this field. This paper provides a comprehensive review of recent advancements in MC particle transport methodologies and associated software, with a specific focus on key features and capabilities of the independently developed J Monte Carlo transport (JMCT) software.
- Monte Carlo (MC) method /
- Particle transport /
- Parallel computing /
- J Monte Carlo transport (JMCT) /
- Artificial intelligence

HTML全文

图 1 中子输运方程计算方法

Figure 1. Calculated Methods of Neutron Transport Equation

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图 2 JMCT软件架构图

Figure 2. Architecture of JMCT

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图 3 JMCT软件模块图

Figure 3. Modules of JMCT

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图 4 JLAMT软件模块示意图

Figure 4. Modules of JLAMT

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图 5 特殊几何体定制功能

Figure 5. Custom Geometry Modeling Functionality

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图 6 JLAMT用户界面

Figure 6. Input Interface of JLAMT

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图 7 快堆模型局部图

Figure 7. Partial View of Fast Reactor Model

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图 8 TeraVAP绘制的计算结果截面图

Figure 8. Cross-sectional View of Calculation Results Drawn by TeraVAP

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图 9 VENUS-3模型堆芯描述

Figure 9. Description of the Reactor Core of VENUS-3

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图 10 VENUS-3模型图片(JLAMT)

Figure 10. Structure Diagram of VENUS-3 Model (JLAMT)

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图 11 VENUS-3外源计算中子通量密度能谱比较

Figure 11. Neutron Flux Spectrum Calculated from Fixed Source Model of VENUS-3 Model

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图 12 VENUS-3外源计算下光子通量密度能谱比较

Figure 12. Photon Flux Spectrum Calculated from Fixed Source Model of VENUS-3 Model

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图 13 中子(n,n′)反应的通量密度计算值和测量值比值

Figure 13. Ratio of Calculated-to-Measured Neutron Flux Density for (n,n′) Reaction

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图 14 中子(n,p)反应的通量密度计算值和测量值比值

Figure 14. Ratio of Calculated-to-Measured Neutron Flux Density for (n,p) Reaction

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图 15 VERA模型结构图

Figure 15. Structure Diagram of VERA Model

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图 16 JMCT与KENO-VI径向积分功率分布图

Figure 16. Radial Power Distribution of JMCT and KENO-VI

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图 17 JMCT与KENO-VI轴向积分功率分布

Figure 17. Axial Power Distribution of JMCT and KENO-VI

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图 18 Watts Bar D棒组控制棒价值

Figure 18. Bank D Control Rod Worth of Watts Bar

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表 1 VENUS-3临界模型计算结果比较

Table 1. Comparison of Calculation Results of VENUS-3 Critical Model

程序	k_eff	相对偏差/%
MCNP	0.98638(0.00022)	0.24
JMCT	0.98918(0.00022)	0.24
相对偏差=[(JMCT计算结果−MCNP计算结果)/JMCT计算结果]×100%；括号内为统计误差，下同。

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表 2 VENUS-3中子通量密度计算结果

Table 2. Neutron Flux of VENUS-3 Model

计数几何块	中子通量密度/(cm⁻²·s⁻¹)		相对偏差/%
计数几何块	MCNP	JMCT	相对偏差/%
堆芯外中心水通道	6.08083×10⁻⁴(0.0005)	6.11761×10⁻⁴(0.0006)	0.60
堆芯外内层围板	5.81696×10⁻⁴(0.0004)	5.76301×10⁻⁴(0.0004)	0.94
堆芯外热屏蔽层	1.84858×10⁻⁶(0.0027)	1.84418×10⁻⁶(0.0028)	0.24
压力容器下层水区	5.02655×10⁻⁷(0.0020)	5.03376×10⁻⁷(0.0022)	0.14

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表 3 VENUS-3光子通量密度计算结果

Table 3. Photon Flux of VENUS-3 Model

计数几何块	光子通量密度/(cm⁻²·s⁻¹)		相对偏差/%
计数几何块	MCNP	JMCT	相对偏差/%
堆芯外中心水通道	3.85463×10⁻⁴(0.0013)	3.83573×10⁻⁴(0.0014)	0.49
堆芯外内层围板	3.97089×10⁻⁴(0.0008)	3.94740×10⁻⁴(0.0008)	0.59
堆芯外热屏蔽层	5.84187×10⁻⁶(0.0027)	5.84101×10⁻⁶(0.0029)	0.01
压力容器下层水区	1.15948×10⁻⁶(0.0047)	1.15460×10⁻⁶(0.0045)	0.42

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表 4 Watts Bar启堆物理参数计算结果

Table 4. Zero Power Physics Test Results of Watts Bar

参数	测量值	KENO-VI	JMCT	KENO-VI与测量值偏差	JMCT与测量值偏差
A棒组价值/pcm	843	898±2	903±2	55	60
SA棒组价值/pcm	435	447±2	439±2	12	4
硼价值/(pcm·ppm⁻¹)	−10.77	−10.21±0.02	−10.21±0.02	0.56	0.56
温度反应性系数/(pcm·℉⁻¹)	−2.17	−3.19±0.04	−3.26±0.04	−1.02	−1.09
1pcm=10⁻⁵。

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