梁金刚 - 清华大学 - 核能与新能源技术研究院

个人简介

教育背景学士 201007 清华大学核工程与核技术博士 201507 清华大学核科学与技术工作履历 201510 - 201907 美国麻省理工学院（MIT）核科学与工程系博士后 201910 – 202105 清华大学核研院助理教授 202106 – 至今清华大学核研院副教授学术兼职 202103 - 至今学术期刊Frontiers in Energy Research (ISSN: 2296-598X) 客座编辑 202106 - 至今学术期刊Energies (ISSN: 1996-1073) 客座编辑 201809 - 至今美国核学会（American Nuclear Society）会员 201911 - 至今中国核学会（China Nuclear Society）会员 201710 – 201906 国际反应堆物理实验评价项目（IRPhEP）技术评审会成员研究概况 2021 –2024 先进核安全分析与风险评价技术研究国家自然科学基金 2022 –2024 基于直接CAD粒子输运和非结构网格统计的聚变蒙卡方法研究国家自然科学基金（面上项目） 2020 –2023 核电厂智能化故障监测与事故诊断方法研究中核领创-菁英项目 2020 –2025 基于高保真多物理模拟的高温堆核事故分析方法研究启动科研获奖情况 2020 省部级三等奖国家电力投资集团科技进步奖 2015 论文类最佳论文奖 2015亚洲反应堆物理年会最佳论文奖

研究领域

致力于通过核反应堆先进模拟分析方法研究，改进核能系统效率及安全水平。具体研究方向包括：反应堆放射性源项辐射防护与屏蔽分析蒙特卡罗粒子输运模拟核反应堆多尺度、多物理耦合分析核能系统设计及安全分析软件研发智能化核应急决策技术

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

B. Qi, L. Zhang, J. Liang*, J. Tong. Combinatorial Techniques for Fault Diagnosis in Nuclear Power Plants Based on Bayesian Neural Network and Simplified Bayesian Network-Artificial Neural Network. Frontiers in Energy Research. 2022, 10. R. Li, Z. Liu, Z. Feng, J. Liang* , L. Zhang. High-fidelity MC-DEM Modeling and Uncertainty Analysis of HTR-PM First Criticality. Frontiers in Energy Research. 2022. Z. Feng, N. An, J. Liang*, K. Wang. ODR-VS method for high packing fraction of dispersed TRISO particles. Annals of Nuclear Energy. 2022, 166. S. Kumar, J. Liang*, B. Forget, K. Smith. “BEAVRS: An integral full core multi-physics PWR benchmark with measurements and uncertainties”. Progress in Nuclear Energy. 129. 2020. J. Liang*, K. Wang, Y. Qiu, X. Chai, S. Qiang. “Domain decomposition strategy for pin-wise full-core Monte Carlo depletion calculation with the reactor Monte Carlo code”. Nuclear Engineering and Technology. 2016, 48(3): 635-641. J. Liang, X. Peng, et al. “Processing of a Comprehensive Windowed Multipole Library via Vector Fitting”. PHYSOR 2018: Reactor Physics paving the way towards more efficient systems. Cancun, Mexico, April 22-26, 2018. J. Liang, S. Kumar, B. Forget, K. Smith. “Quantifying Uncertainty in the BEAVRS Benchmark”. M&C 2017 - International Conference on Mathematics & Computational Methods Applied to Nuclear Science & Engineering, Jeju, Korea, April 16-20, 2017, on USB (2017). J. Liang, Z. Wu*, H Abdel-Kalik. “Nuclear Data Sensitivity Analysis in OpenMC Using the GPT-Free Method”. Transactions of the American Nuclear Society, 2018, 118: 921-924. J. Liang, P. Ducru, et al, “Target Velocity Sampling for Resonance Elastic Scattering Using Windowed Multipole Cross Section Data”, Transactions of the American Nuclear Society, 2019, 119: 1163-1166. X. Wang, J. Liang, Y. Li, Q. Zhang*. Hybrid Monte Carlo methods for Geant4-based nuclear well logging implementation. Annals of Nuclear Energy. 2022, 169. S. Liu, J. Liang, K. Wang, Y. Chen. “Development of the integrated parallelism strategy for large scale depletion calculation in the Monte Carlo code RMC”. Annals of Nuclear Energy. 135: 106941. 2020. X. Peng, J. Liang, et al. “Calculation of adjoint-weighted reactor kinetics parameters in OpenMC”. Annals of Nuclear Energy. 2019. 128: 231-235. Z. Wu, J. Liang, et al. “GPT-Free Sensitivity Analysis for Monte Carlo Models”. Nuclear Technology. 2019: 1-16. X. Peng*, J. Liang, et al. “Development of continuous-energy sensitivity analysis capability in OpenMC”. Annals of Nuclear Energy. 2017. 110: 362-383. S. Liu, J. Liang, Q. Wu, J. Guo, S. Huang*, X. Tang, Z. Li, K. Wang. “BEAVRS full core burnup calculation in hot full power condition by RMC code”. Annals of Nuclear Energy. 2017. 101: 434-446. 梁金刚, 王侃, 蔡云, 孙嘉龙. 中子输运蒙特卡罗模拟的区域分解方法研究 .原子能科学技术, 2014, 48(12): 2315-2320. 梁金刚, 王侃, 余纲林, 佘顶, 柴晓明, 强胜龙, 姚栋. 基于RMC的计数器数据分解方法研究 .核动力工程, 2014, 35(4): 142-146.