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Paul Amyotte

Researcher at Dalhousie University

Publications -  225
Citations -  9718

Paul Amyotte is an academic researcher from Dalhousie University. The author has contributed to research in topics: Dust explosion & Poison control. The author has an hindex of 51, co-authored 215 publications receiving 7955 citations. Previous affiliations of Paul Amyotte include St. John's University & Technical University of Nova Scotia.

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Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches

TL;DR: The paper concludes that BN is a superior technique in safety analysis because of its flexible structure, allowing it to fit a wide variety of accident scenarios.
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Dynamic safety analysis of process systems by mapping bow-tie into Bayesian network

TL;DR: This paper introduces the application of probability adapting in dynamic safety analysis rather than probability updating, and illustrates how Bayesian network (BN) helps to overcome limitations in BT.
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Quantitative risk analysis of offshore drilling operations: A Bayesian approach

TL;DR: The Bayesian network method provides greater value than the bow-tie model since it can consider common cause failures and conditional dependencies along with performing probability updating and sequential learning using accident precursors.
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Dynamic risk analysis using bow-tie approach

TL;DR: This work is focused on using bow-tie model approach in a dynamic environment in which the occurrence probability of accident consequences changes, and uses Bayes’ theorem to estimate the posterior probability of the consequences which results in an updated risk profile.
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Domino effect analysis using Bayesian networks.

TL;DR: This study shows how probability updating helps to update the domino effect model either qualitatively or quantitatively, and accentuates the effectiveness of Bayesian network in modeling domino effects in processing facility.