Uncertainty analysis based on probability bounds in probabilistic risk assessment of high microgravity science experiment system

Abstract

In order to quantitatively assess the reliability of high microgravity science experiment system in Chinese space stations, a reliability assessment approach based on probabilistic risk assessment (PRA) is proposed. Uncertainty analysis is a core problem in PRA, which must be addressed. There are several methods for analyzing uncertainty such as Monte Carlo simulation, interval analysis, probability bounds, the Dempster-Shafer theory of evidence, and fuzzy set theory. When the probability distributions of random input variables are specified, but the parameters are intervals, probability bounds analysis is an effective way to analyze the uncertainty of PRA. By constructing the probability boxes (p-boxes) of basic events, using the event chain model of PRA, uncertainty can be propagated from basic events to end states. The uncertainty analysis results verify the feasibility of probability bounds analysis of PRA in high microgravity science experiment system, and will provide a reference for the subsequent study of the quantitative risk assessment of space utilization payloads.