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Probabilistic model data of time-dependent accident scenarios for a mixing tank mechanical system

Abstract : This article presents the risk assessment of a mixing tank mechanical system based on the failure probabilities of the components. Possible component failures can cause accidents which evolve over multiple time stages and can lead to system failure. The consequences of these accident scenarios are analyzed by quantifying the failure probabilities and severity of their outcomes. Illustrative costs and updated failure probabilities are provided to evaluate preventive safety measures. Data refers to the results of the Bayesian model presented in our research article (Mancuso et al., 2019).
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https://hal-mines-paristech.archives-ouvertes.fr/hal-02432529
Contributeur : Magalie Prudon <>
Soumis le : mercredi 8 janvier 2020 - 14:46:13
Dernière modification le : jeudi 24 septembre 2020 - 17:20:28

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Alessandro Mancuso, Michele Compare, Ahti Salo, Enrico Zio. Probabilistic model data of time-dependent accident scenarios for a mixing tank mechanical system. Data in Brief, Elsevier, 2019, 25, pp.104243. ⟨10.1016/j.dib.2019.104243⟩. ⟨hal-02432529⟩

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