Non-Intrusive Polynomial Chaos for a Realistic Estimation of Accident Frequency

doi:10.23940/ijpe.19.11.p3.28522859

Abstract

Abstract: The pivotal role of frequency analysis in quantitative risk assessments necessitates realistic and efficient prediction of their metrics. Uncertainty analysis, which aims to determine the effects of the involved input uncertainties on the output of interest form a strong basis for all the decisions to be taken based on the results of such assessments. The main purpose of this paper is to employ a non-intrusive polynomial chaos approach to simplify the model relating to the estimation of the frequency of major accidents. Such application facilitates the propagation of the associated parametric uncertainties and makes the whole process less expensive while assuring the desired accuracy when compared with the classical application of the Monte Carlo simulation.

Key words: industrial safety, frequency of major accidents, uncertainty propagation, polynomial chaos expansion, Monte Carlo simulation

Mourad Chebila. Non-Intrusive Polynomial Chaos for a Realistic Estimation of Accident Frequency [J]. Int J Performability Eng, 2019, 15(11): 2852-2859.

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