Probabilistic Risk Assessment in Space Launches Using Bayesian Network with Fuzzy Method

Abstract

Space launch projects are extremely risky, and any equipment failure or human error may lead to disastrous consequences. Probabilistic risk assessment (PRA) is beneficial to qualitative analysis of risk, but it has not been paid enough attention in risk analysis for space launch systems (SLSs). Compared with most qualitative risk analysis in this field, this paper proposes a risk analysis framework based on Bayesian network (BN) with fuzzy method, which is suitable for probabilistic risk analysis of SLS. This method establishes a risk analysis model of SLS based on statistics and expert experience and reduces the uncertainty of the model by using fuzzy theory. By predicting the system risk probabilities, diagnosing the key risk causes, determining the risk conduction path, and performing a sensitivity analysis, the proposed risk analysis framework is aimed at alleviating this drawback to deal more effectively with the uncertainties in the field of space launches. A case study of space launches demonstrates and verifies the proposed method, and it also provides guidance for similar engineering projects.

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