Handling epistemic uncertainties in PRA using evidential networks
来源期刊：中南大学学报(英文版)2014年第11期
论文作者：WANG Dong(王冬) CHEN Jin(陈进) CHENG Zhi-jun(程志君) GUO Bo(郭波)
文章页码：4261 - 4269
Key words：probabilistic risk assessment; epistemic uncertainty; evidence theory; evidential network
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.
WANG Dong(王冬), CHEN Jin(陈进), CHENG Zhi-jun(程志君), GUO Bo(郭波)
(College of Information System and Management, National University of Defense Technology,
Changsha 410073, China)
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.
Key words:probabilistic risk assessment; epistemic uncertainty; evidence theory; evidential network
