Analytic Probabilistic Safety Analysis under Severe Uncertainty

Sadeghi, Jonathan ORCID: 0000-0003-4106-2374, de Angelis, Marco ORCID: 0000-0001-8851-023X and Patelli, Edoardo ORCID: 0000-0002-5007-7247 (2020) Analytic Probabilistic Safety Analysis under Severe Uncertainty. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 6 (1). 04019019-.

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Official URL: http://dx.doi.org/10.1061/ajrua6.0001028

Abstract

Exact analytic expressions are given to evaluate the reliability of systems consisting of components, connected in parallel or series, subject to imprecise failure distributions. We also proposed a simplified version of the first-order reliability method to deal with imprecision. This development allows engineers to evaluate the reliability of systems without having to resort to optimization techniques and/or Monte Carlo simulation. In addition, this framework does not need to assume a distribution for the epistemic uncertainty, which permits a robust analysis even with limited data. In this way, the approach removes a significant barrier to the modeling of epistemic uncertainties in industrial probabilistic safety analysis workflows.

Item Type:	Article
Depositing User:	Symplectic Admin
Date Deposited:	14 May 2019 07:23
Last Modified:	14 Mar 2024 17:47
DOI:	10.1061/AJRUA6.0001028
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3040641