Advanced numerical simulation and modelling for reactor safety − contributions from the CORTEX, HPMC, McSAFE and NURESAFE projects

IF 0.9 Q3 NUCLEAR SCIENCE & TECHNOLOGY EPJ Nuclear Sciences & Technologies Pub Date : 2020-06-01 DOI:10.1051/EPJN/2019006

C. Demazière, V. Sánchez-Espinoza, B. Chanaron

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引用次数: 9

Abstract

Predictive modelling capabilities have long represented one of the pillars of reactor safety. In this paper, an account of some projects funded by the European Commission within the seventh Framework Program (HPMC and NURESAFE projects) and Horizon 2020 Program (CORTEX and McSAFE) is given. Such projects aim at, among others, developing improved solution strategies for the modelling of neutronics, thermal-hydraulics, and/or thermo-mechanics during normal operation, reactor transients and/or situations involving stationary perturbations. Although the different projects have different focus areas, they all capitalize on the most recent advancements in deterministic and probabilistic neutron transport, as well as in DNS, LES, CFD and macroscopic thermal-hydraulics modelling. The goal of the simulation strategies is to model complex multi-physics and multi-scale phenomena specific to nuclear reactors. The use of machine learning combined with such advanced simulation tools is also demonstrated to be capable of providing useful information for the detection of anomalies during operation.

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先进的数值模拟和反应堆安全建模-来自CORTEX, HPMC, McSAFE和NURESAFE项目的贡献

预测建模能力长期以来一直是反应堆安全的支柱之一。本文介绍了欧盟委员会在第七个框架计划（HPMC和NURESAFE项目）和地平线2020计划（CORTEX和McSAFE）中资助的一些项目。此类项目旨在开发改进的解决方案策略，用于在正常运行、反应堆瞬态和/或涉及静止扰动的情况下对中子学、热工水力学和/或热力学进行建模。尽管不同的项目有不同的重点领域，但它们都利用了确定性和概率中子输运以及DNS、LES、CFD和宏观热工水力学建模方面的最新进展。模拟策略的目标是对核反应堆特有的复杂多物理和多尺度现象进行建模。机器学习与这种先进的模拟工具相结合的使用也被证明能够为操作期间的异常检测提供有用的信息。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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