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Open AccessFeature PaperArticle

Notes on Computational Uncertainties in Probabilistic Risk/Safety Assessment

Department of Mechanical and Production Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway
Entropy 2018, 20(3), 162; https://doi.org/10.3390/e20030162
Received: 5 January 2018 / Revised: 9 February 2018 / Accepted: 26 February 2018 / Published: 4 March 2018
(This article belongs to the Special Issue Entropy for Characterization of Uncertainty in Risk and Reliability)
In this article, we study computational uncertainties in probabilistic risk/safety assessment resulting from the computational complexity of calculations of risk indicators. We argue that the risk analyst faces the fundamental epistemic and aleatory uncertainties of risk assessment with a bounded calculation capacity, and that this bounded capacity over-determines both the design of models and the decisions that can be made from models. We sketch a taxonomy of modelling technologies and recall the main computational complexity results. Then, based on a review of state of the art assessment algorithms for fault trees and event trees, we make some methodological proposals aiming at drawing conceptual and practical consequences of bounded calculability. View Full-Text
Keywords: probabilistic risk/safety assessment; uncertainties; assessment algorithms; modeling methodologies probabilistic risk/safety assessment; uncertainties; assessment algorithms; modeling methodologies
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Rauzy, A. Notes on Computational Uncertainties in Probabilistic Risk/Safety Assessment. Entropy 2018, 20, 162.

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