Influence of input data uncertainties on failure probability of TRISO-coated particle

被引：3

作者：

Li, Jian ^{[1
]}

Sun, Jun ^{[1
]}

She, Ding ^{[1
]}

Shi, Lei ^{[1
]}

机构：

[1] Tsinghua Univ, Minist Educ, Collaborat Innovat Ctr Adv Nucl Energy Technol, Key Lab Adv Reactor Engn & Safety,Inst Nucl & New, Beijing 100084, Peoples R China

来源：

ANNALS OF NUCLEAR ENERGY | 2021年 / 163卷

基金：

中国博士后科学基金;

关键词：

TRISO particle fuel performance; Input data; Uncertainty; Failure probability; FUEL; STRESSES;

D O I：

10.1016/j.anucene.2021.108561

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：

TRISO coated particle fuel exhibits statistical variations and large uncertainties in physical configurations and material properties from particle to particle. Besides, the dependence of mechanical behavior and failure mechanism of the coating layer on multiple variables (such as density, porosity, anisotropy, flu-ence and temperature) further increase the complexity of TRISO fuel performance analysis. Consequently, the particle failure probability would change in a relatively wide range. In this paper, we evaluate the effect of input data uncertainties on particle failure probability. First, uncertainty ranges of input data are determined based on literature review and irradiation conditions. Second, a perturba-tion study on dimensional parameters and material properties is performed. Finally, variation ranges of failure probability upon different input parameters are determined. Results show that the failure rate is sensitive to kernel diameter, SiC thickness and irradiation-induced material properties. (c) 2021 Elsevier Ltd. All rights reserved.

引用

页数：11

共 21 条

[1] Importance of uncertainty quantification in nuclear fuel behaviour modelling and simulation [J].