Handling epistemic uncertainties in PRA using evidential networks

Abstract

In order to overcome the limitations of traditional methods in uncertainty analysis, a modified Bayesian network (BN), which is called evidence network (EN), was proposed with evidence theory to handle epistemic uncertainty in probabilistic risk assessment (PRA). Fault trees (FTs) and event trees (ETs) were transformed into an EN which is used as a uniform framework to represent accident scenarios. Epistemic uncertainties of basic events in PRA were presented in evidence theory form and propagated through the network. A case study of a highway tunnel risk analysis was discussed to demonstrate the proposed approach. Frequencies of end states are obtained and expressed by belief and plausibility measures. The proposed approach addresses the uncertainties in experts’ knowledge and can be easily applied to uncertainty analysis of FTs/ETs that have dependent events.

Keywords

probabilistic risk assessment / epistemic uncertainty / evidence theory / evidential network

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