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

被引:0
|
作者
Mancuso, Alessandro [1 ,2 ]
Compare, Michele [2 ,3 ]
Salo, Ahti [1 ]
Zio, Enrico [2 ,3 ,4 ]
机构
[1] Aalto Univ, Dept Math & Syst Anal, Espoo, Finland
[2] Politecn Milan, Dept Energy Engn, Milan, Italy
[3] Aramis Srl, Milan, Italy
[4] PSL Res Univ, MINES ParisTech, CRC, Sophia Antipolis, France
来源
DATA IN BRIEF | 2019年 / 25卷
基金
芬兰科学院;
关键词
Risk analysis; System reliability; Preventive safety measures; Dynamic bayesian networks; Portfolio optimization;
D O I
10.1016/j.dib.2019.104243
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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). (c) 2019 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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页数:5
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