publication . Other literature type . Article . Conference object . 2019

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

Bruno Chanaron; Victor Sanchez-Espinoza; Christophe Demaziere;
Open Access English
  • Published: 04 Jun 2019
  • Publisher: Zenodo
International audience; 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 Horizon2020 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 advan...
free text keywords: simulation, modelling, CORTEX, MCSAFE, NURESAFE, reactor safety, Technology, Other Physics Topics, simulation, Modelling, mcsafe, cortex, nuresafe, light-water nuclear reactor, [PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex], [PHYS.NUCL]Physics [physics]/Nuclear Theory [nucl-th], Probabilistic logic, Computational fluid dynamics, business.industry, business, Reactor safety, European commission, Neutron transport, Computer simulation, Predictive modelling, Nuclear reactor, law.invention, law, Systems engineering, Computer science, ddc:600, lcsh:Nuclear engineering. Atomic power, lcsh:TK9001-9401
Funded by
Core monitoring techniques and experimental validation and demonstration
  • Funder: European Commission (EC)
  • Project Code: 754316
  • Funding stream: H2020 | RIA
High performance Monte Carlo reactor core analysis
  • Funder: European Commission (EC)
  • Project Code: 295971
  • Funding stream: FP7 | SP5 | Fission
  • Funder: European Commission (EC)
  • Project Code: 323263
  • Funding stream: FP7 | SP5 | Fission
Organizing FISA and EuradWaste Conference under the Romanian Presidency of EU Council
  • Funder: European Commission (EC)
  • Project Code: 826027
  • Funding stream: H2020 | CSA
High-Performance Monte Carlo Methods for SAFEty Demonstration- From Proof of Concept to realistic Safety Analysis and Industry-like Applications
  • Funder: European Commission (EC)
  • Project Code: 755097
  • Funding stream: H2020 | RIA
Energy Research
18 references, page 1 of 2

A complete list of the papers published within the projects can be found on the project respective websites: (for CORTEX), (for HPMC), (McSAFE), (for NURESAFE).

[1] C. Demazière et al., Overview of the CORTEX project, Proc. Int. Conf. Physics of Reactors - Reactor Physics paving the way towards more efficient systems (PHYSOR2018), Cancun, Mexico, April 22-26, 2018 (2018). [OpenAIRE]

[2] V. Sanchez et al., High Performance Monte Carlo Computing Projects: from HPCM to McSAFE, NUGENIA Forum, Ljubljana, Slovenia, April 14, 2015.

[3] L. Mercatali et al., McSAFE projects highlights, International Multi Physics Validation Workshop, North Carolina State University, USA, June 2017.

[4] E. Deville and F. Perdu, Documentation of the Interface for Code Coupling: ICOCO, CEA, Paris (2012).

[5] B. Chanaron et al., Advanced multi-physics simulation for reactor safety in the framework of the NURESAFE Project, Ann. Nucl. Energy, 84, 166-177 (2015).

[6] B. Chanaron, The European NURESAFE simulation project for reactor safety, Proc. Int. Conf. Nuclear Engineering (ICONE22), Prague, Czech Republic, July 7-11, 2014 (2014).

[7] C. Demazière, Multi-physics modelling of nuclear reactors: current practices in a nutshell, Int. J. Nucl. Energy Sci. Technol., 7 (4), 288-318 (2013). [OpenAIRE]

[8] I. Lux and L. Koblinger, Monte Carlo particle transport methods: neutron and photons calculations, CRC Press, Boca Raton, FL, USA (1991).

[9] A. Ivanov et al., Internal multi-scale multi-physics coupled system for high fidelity simulation of light water reactors, Ann. Nucl. Energy, 66, pp. 104-112 (2014).

[10] M. Däubler et al., High-fidelity coupled Monte Carlo neutron transport and thermalhydraulic simulations using Serpent 2/SUBCHANFLOW - Part I: Implementation and solution verification, Ann. Nucl. Energy, 83, pp. 352-375 (2015).

[11] F. Calivà F et al., A deep learning approach to anomaly detection in nuclear reactors. Proc. 2018 Int. Joint Conf. Neural Networks (IJCNN2018), Rio de Janeiro, Brazil, July 8-13, 2018 (2018). [OpenAIRE]

[12] F. De Sousa Ribeiro et al., Towards a deep unified framework for nuclear reactor perturbation analy-sis. Proc. IEEE Symposium Series on Computational Intelligence (SSCI 2018), Bengaluru, India, November 18-21, 2018 (2018).

[13] J. Dufek and J. E. Hoogenboom, Description of a stable scheme for steady-state coupled Monte Carlo-thermal-hydraulic calculations, Ann. Nucl. Energy, 68, pp. 1-3 (2014). [OpenAIRE]

[14] J. E. Hoogenboom, Demonstration of the time-dependence after a control rod movement, HPCM Deliverable D3.10 (2013).

18 references, page 1 of 2
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