The Evaluation of the Adequacy of PRA Results for Risk-informed Decision Makings With Respect to Incompleteness

PRA(Probabilistic Risk Assessment), as a quantitative tool, has many strengths as well as weaknesses. There are several limitations on the use of PRA techniques for risk modeling and analysis. First, the true values of most model inputs are unknown. Ideally, probability distribution models are well developed and assigned to the unknown input parameters to reflect the analyst's state of knowledge of the values of this input parameter. The problem of overconfidence and lack of confidence in the values of certain model input parameters can lead to inaccurate PRA results. Secondly, the analyst's lack of knowledge of a system's practical application as opposed to its theoretical operation can lead to modeling errors. The quality of PRAs has been addressed by a number of regulatory and industry organizations Some have argued that a good PRA should be a complete, full scope, three level PRA, while others have claimed that the quality of a PRA should be measured with respect to the application and decision supported. we show by way of an example that the adequacy of a PRA results is important to risk-informed decision making process and should be measured with respect to the application and decision supported