Statistical learning model for fuel-cladding heat exchange coefficient evaluation in SFR-Reference-Cited by-同舟云学术

Statistical learning model for fuel-cladding heat exchange coefficient evaluation in SFR

Published:2022-12 Issue: Volume:399 Page:112027
ISSN:0029-5493
Container-title:Nuclear Engineering and Design
language:en
Short-container-title:Nuclear Engineering and Design

Author:

Jeannin Marlène^ORCID,Blanc Victor^ORCID,Dupont Vincent,Pascal Vincent^ORCID,Buiron Laurent,Rubiolo Pablo^ORCID

Publisher

Elsevier BV

Subject

Mechanical Engineering,Waste Management and Disposal,Safety, Risk, Reliability and Quality,General Materials Science,Nuclear Energy and Engineering,Nuclear and High Energy Physics

Reference22 articles.

1. Conception Multi-Physique Et Multi-Objectif Des cœurs de RNR-Na Hétérogènes: Développement D’une Méthode D’optimisation sous incertitudes;Ammar,2014

2. Application OF DEEP LEARNING networks TO SURROGATE modelling OF crud deposition;Andersen,2021

3. Bajard, S., Degezelle, T., Li, S., Conti, A., 2022. Influence of the fuel pellet-clad gap heat exchange coefficient on a loss of flow without scram transient simulated with CATHARE3 in sodium fast reactor. In: Proc. of NURETH-19.

4. Analysis of fabrication and crack-induced porosity migration in mixed oxide fuels for sodium fast reactors by the finite element method;Barani;J. Nucl. Mater.,2022

5. Conceptual design of ASTRID fuel sub-assemblies;Beck;Nucl. Eng. Des.,2017

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MORPHEE a multiphysics tool for control rod withdrawal modeling in SFR;Annals of Nuclear Energy;2024-12

2. Thermal design criteria computation using various statistical approaches – Application to a SFR fuel element;Nuclear Engineering and Design;2024-11