Technology on the on-the-fly generation of continuous thermal neutron scattering cross section in MCNP for microreactor multi-physics coupling
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摘要: 微型反应堆在运行过程中具有紧密耦合的核热力响应特征，温度分布具有较强的不均匀性，当堆芯温度发生变化时，需要在线生成不同温度的反应截面，以达到快速模拟截面温度反馈的效果。MCNP的在线多普勒展宽使用较为普遍，但是它只针对可分辨共振区，对于热谱型反应堆，无法在线考虑热中子散射截面受温度的影响，为此，本文进行了基于统计学抽样MCNP连续型热中子散射截面在线计算功能的开发，针对耐高温慢化剂材料ZrHx中的H开展了在线多温度点截面的计算研究，对比了离散和连续型热中子散射截面差异，完成了TRIGA和TOPAZ反应堆有效增值因数（keff）的宏观验证，并将其功能应用到非结构网格MCNP与ABAQUS铀氢锆燃料单栅元核热耦合分析中。结果表明，开发的MCNP在线热中子截面计算产生的keff与采用NJOY离线库计算的keff较为一致，结合MCNP的非结构网格输运功能，可以精细考虑慢化剂材料不同位置的温度反馈效应，为微型固态堆高效的多物理耦合计算奠定重要的基础。Abstract:
Background Microreactors exhibit closely coupled neutronic-thermal-mechanical responses during operation, accompanied by highly non-uniform temperature distributions. Traditional on-the-fly cross-section generation methods, such as Doppler broadening in MCNP, are limited to the resolved resonance region and cannot handle temperature-dependent thermal neutron scattering laws (TSL), which are critical for thermal-spectrum systems.Purpose To address this gap, this study aims to develop an on-the-fly TSL cross-section generation capability within MCNP based on statistical sampling, with a focus on thermal neutron scattering in high-temperature moderators such as ZrHₓ, and to enable high-fidelity neutronic-thermal coupling analysis in microreactor simulations.Methods A statistical sampling approach was implemented for on-the-fly computation of thermal scattering cross-sections. Multi-temperature cross-section evaluations were carried out for hydrogen in ZrHₓ, comparing discrete and continuous TSL treatments. The method was macroscopically validated through keff calculations in TRIGA and TOPAZ reactors. Furthermore, integrated neutronic-thermal coupling simulations were performed using unstructured-mesh MCNP coupled with ABAQUS.Results The developed on-the-fly cross-section method produces keff values in good agreement with those obtained using pre-generated offline libraries. The integration with unstructured particle transport in MCNP allows spatially precise accounting of temperature feedback in the moderator region.Conclusions The new on-the-fly TSL capability enhances the accuracy of temperature-dependent neutronics modeling in thermal-spectrum microreactors. Coupled with unstructured meshing, it provides an essential foundation for high-fidelity multi-physics simulations of solid-state compact microreactors. -
图 1 基于随机抽样原理的在线热化截面计算流程
Figure 1. On-the-fly thermal cross section calculation flow based on random sampling
图 2 ZrHx中H的概率密度函数PDF和累计概率密度函数CDF分布
Figure 2. Probability density function (PDF) and cumulative distribution function (CDF) of H in ZrHx
图 4 次级散射中子的角度余弦分布和极角坐标分布
Figure 4. Angular cosine and polar angle distribution of secondary scattered neutrons
图 7 TOPAZ-II反应堆径向和轴向截面图
Figure 7. Radial and axial cross-sections of the TOPAZ-II reactor
图 9 全反射边界条件的铀氢锆燃料栅元归一化功率分布、统计偏差、实际功率分布和温度分布
Figure 9. Normalized power, std, power, and temperature distribution of uranium zirconium hydride fuel pin model
表 1 基于ENDF/B VIII.0评价库加工的热化ACE格式截面库信息
Table 1. Information of ACE TSL Library Based on ENDF/ B VIII.0
ACE Lib name temperature/K energy/MeV h-zrh.40t 296 2.551E-08 h-zrh.41t 400 3.447E-08 h-zrh.42t 500 4.309E-08 h-zrh.43t 600 5.170E-08 h-zrh.44t 700 6.032E-08 h-zrh.45t 800 6.894E-08 h-zrh.46t 1000 8.617E-08 h-zrh.47t 1200 1.034E-07 
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表 2 TRIGA反应堆MCNP计算keff
Table 2. Calculation of MCNP in TRIGA Reactor
temperature/K offline keff on-the-fly keff deviation//10−5 offline libraries’ temperature/K 400 0.99744 0.99671 73 293, 500 600 0.98422 0.98336 86 500, 700 800 0.96978 0.97060 82 700, 1000 1000 0.95574 0.95649 75 800, 1200
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表 3 TOPAZ-II反应堆MCNP计算keff偏差
Table 3. Calculation of keff Deviation in MCNP of TOPAZ-II Reactor
temperature/K offline keff on-the-fly keff deviation/10−5 offline libraries’ temp/K 400 1.00116 1.00126 10 293、500 600 1.01924 1.01874 50 500、700 800 1.03226 1.03169 57 700、 1000 1000 1.04370 1.04166 204 800、 1200
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表 4 全反射边界条件的铀氢锆燃料栅元模型keff结果
Table 4. keff results of reflective model of uranium zirconium hydrogen fuel pin
model time/min keff deviation/10−5 CSG 1.74 1.46502 — UM（single cell） 17.11 1.46259 243 UM（4 256 hypermesh cell） 65.96 1.46257 245
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表 5 铀氢锆燃料反应性反馈
Table 5. Reactivity Feedback of UZrH Fuel
calculation keff computing time/min Δρ/10−5 cold state (300 K) 1.46257 65.77 − hot state with free gas model 1.46055 65.80 −765 hot sate with on-the-fly TSL xs by statistical sampling 1.45290 68.78 −967
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[1] Mehta V K. Capturing multiphysics effects in hydride moderated microreactors using MCNP and ABAQUS[R]. LA-UR-21-20451, Los Alamos National Laboratory, 2021. [2] Martz R L. The MCNP6 book on unstructured mesh geometry: user’s guide[R]. LA-UR-11-05668 Rev. 8, MCNP6 code release to RSICC, Oak Ridge, TN and general distribution, 2014. [3] 王立鹏, 孔令体, 姜夺玉, 等. 基于经典分子动力学模拟的热中子散射数据产生方法[J]. 现代应用物理, 2025, 16: 020203 doi: 10.12061/j.issn.2095-6223.202407039Wang Lipeng, Kong Lingti, Jiang Duoyu, et al. Thermal neutron scattering data generation method based on classical molecular dynamics simulations[J]. Modern Applied Physics, 2025, 16: 020203 doi: 10.12061/j.issn.2095-6223.202407039 [4] Brown B A, Chadwick M B, Capote R, et al. ENDF/B-VIII. 0: the 8th major release of the nuclear reaction data library with CIELO-project cross sections, new standards and thermal scattering data[J]. Nuclear Data Sheets, 2018, 148: 1-142. doi: 10.1016/j.nds.2018.02.001 [5] Macfarlane R, Muir D W, Boicourt R M, et al. The NJOY nuclear data processing system, Version 2016[R]. Los Alamos: Los Alamos National Laboratory, 2017. [6] Brown F B. The makxsf code with Doppler broadening[R]. Los Alamos: Los Alamos National Laboratory, 2006. [7] Viitanen T, Leppänen J. New interpolation capabilities for thermal scattering data in serpent 2[C]//Proceedings of the PHYSOR 2016: Unifying Theory and Experiments in the 21st Century. 2016. [8] Pavlou A T, Ji Wei. On-the-fly sampling of temperature-dependent thermal neutron scattering data for Monte Carlo simulations[J]. Annals of Nuclear Energy, 2014, 71: 411-426. doi: 10.1016/j.anucene.2014.04.028 [9] 王立鹏, 陈森, 张信一, 等. 基于非结构网格粒子输运的蒙特卡罗模拟计算研究[J]. 核科学与工程, 2024, 44(2): 286-294 doi: 10.3969/j.issn.0258-0918.2024.02.005Wang Lipeng, Chen Sen, Zhang Xinyi, et al. Study on the particle transport calculation with Monte Carlo Method based on unstructured grid[J]. Nuclear Science and Engineering, 2024, 44(2): 286-294 doi: 10.3969/j.issn.0258-0918.2024.02.005 [10] 王立鹏, 曹璐, 余小任, 等. 基于直接CAD几何模型的辐射场生成技术研究及应用[J]. 现代应用物理, 2024, 15: 030201 doi: 10.12061/j.issn.2095-6223.2024.030201Wang Lipeng, Cao Lu, Yu Xiaoren, et al. Research and application of radiation field generation technology based on direct CAD geometric model[J]. Modern Applied Physics, 2024, 15: 030201 doi: 10.12061/j.issn.2095-6223.2024.030201 [11] 王立鹏, 曹璐, 陈森, 等. 基于非结构网格MCNP的KRUSTY热膨胀负反馈计算研究[J]. 核动力工程, 2023, 43(6): 45-53Wang Lipeng, Cao Lu, Chen Sen, et al. Study of KRUSTY thermal expansion negative feedback calculation based on unstructured-mesh MCNP[J]. Nuclear Power Engineering, 2023, 43(6): 45-53 [12] Cullen D E, Hansen L F, Lent E M, et al. Thermal scattering law data: implementation and testing using the Monte Carlo neutron transport codes COG, MCNP and TART[R]. Laboratory: Lawrence Livermore National Laboratory, 2003. -
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