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

被引：8

作者：

Demaziere, Christophe ^{[1
]}

Sanchez-Espinoza, Victor Hugo ^{[2
]}

Chanaron, Bruno ^{[3
]}

机构：

[1] Chalmers Univ Technol, Div Subat & Plasma Phys, Dept Phys, S-41296 Gothenburg, Sweden

[2] Karlsruhe Inst Technol KIT, Inst Neutron Phys & Reactor Technol INR, Hermann vom Helmholtz Pl 1, D-76344 Eggenstein Leopoldshafen, Germany

[3] Commissariat Energie Atom & Energies Alternat, Ctr Saclay, F-91191 Gif Sur Yvette, France

来源：

EPJ NUCLEAR SCIENCES & TECHNOLOGIES | 2020年 / 6卷 / 06期

关键词：

Nuclear reactors;

D O I：

10.1051/epjn/2019006

中图分类号：

TL [原子能技术]; O571 [原子核物理学];

学科分类号：

0827 ; 082701 ;

摘要：

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.

引用

页数：14