Influence of input data uncertainties on failure probability of TRISO-coated particle. (1st December 2021)

• Record Type: Journal Article
• Authors: Li, Jian; Sun, Jun; She, Ding; Shi, Lei
• Is Part Of: Annals of nuclear energy. Volume 163(2021)
• Publication Date: 2021-12-01
• Subjects: TRISO particle fuel performance -- Input data -- Uncertainty -- Failure probability; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 621.4805
• DOI: 10.1016/j.anucene.2021.108561
• Languages: English
• ISSNs: 0306-4549

Abstract

Highlights: The variations of input data for TRISO fuel performance analysis are reasonably determined. Influence of input data uncertainties on particle failure probability is quantified. The importance of including input data uncertainties in TRISO fuel performance analysis is further emphasized. Abstract: 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, fluence 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 perturbation 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.