Modeling uncertainties when estimating component reliability

The extensive use of probabilistic safely assessment (PSA) methods for various risk-informed applications requires a thorough assessment. of the uncertainties introduced with PSA models. Quantitative assessment is usually focused on an uncertainty analysis of the PSA's input parameters, such as initiating-event frequencies, human-error probabilities, parameters of component-reliability models and some other special parameters. In this paper uncertainties that arise in PSA when building component-reliability models are described. Different approaches can be selected for estimating the input parameters of component-reliability models. Focus is given to the assessment of the so-called modeling uncertainties that arise when different mathematical and calculation-based approaches are used for the parameter of component-reliability model estimation. The assessment of uncertainties is presented using an example of a pump-reliability estimation. The so-called uncertainty bound is defined to assess uncertainties in the parameter estimation due to the use of different mathematical approaches for the parameter calculation. To minimize the modeling uncertainties for the component failure-rate estimation, the numerical calculation of the Bayesian updating procedure and the transformation of the resulting tabular discrete distribution into an analytical distribution seems to be most suitable. (C) 2003 Journal of Mechanical Engineering. All rights reserved.