Back to Search Start Over

Realistic performance assessment of FeCrAl-UN/U3Si2 accident tolerant fuel under loss-of-coolant accident scenario.

Authors :
Xiong, Qingwen
Qian, Libo
Song, Gongle
Yang, Jiewei
Liu, Yu
Deng, Jian
Qiu, Zhifang
Source :
Reliability Engineering & System Safety. Mar2024, Vol. 243, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

• Propose of a realistic performance assessment method for nuclear fuel under accident scenario. • Application of the proposed method to HPR-1000 LBLOCA with FeCrAl-UN/U 3 Si 2 fuel. • Uncertainty and sensitivity analysis of the fuel models and related parameters on the PCT. The rigorous safety requirements in the nuclear industry have necessitated the development of accident tolerant fuels, with FeCrAl-UN/U 3 Si 2 being one of the latest innovations in this field. To comprehensively evaluate the performance of this fuel type under accident scenarios, the best estimate plus uncertainty method is employed to conduct a realistic safety assessment of a large break loss-of-coolant accident in the HPR-1000 nuclear power plant using FeCrAl-UN/U 3 Si 2 fuel. The peak cladding temperature and peak pellet temperature are selected as figures of merit, while the uncertainties of key performance models for the FeCrAl cladding and UN/U 3 Si 2 pellet are quantified. The upper tolerance limits of the two figures of merit are determined through uncertainty propagation calculations, and the key influencing parameters are also identified based on the sensitivity analysis. Results demonstrate that the FeCrAl-UN/U 3 Si 2 fuel type owns larger safety margin than the conventional Zr-UO 2 fuel type and effectively reduces the cladding temperature while significantly reducing oxidation and hydrogen production during the accident. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09518320
Volume :
243
Database :
Academic Search Index
Journal :
Reliability Engineering & System Safety
Publication Type :
Academic Journal
Accession number :
174642273
Full Text :
https://doi.org/10.1016/j.ress.2023.109847