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

Alessandro Mancuso; Michele Compare; Ahti Salo; Enrico Zio

doi:10.1016/j.dib.2019.104243

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

Alessandro Mancuso, Michele Compare, Ahti Salo, Enrico Zio

Tutkimustuotos: Lehtiartikkeli › Data Article › Scientific › vertaisarvioitu

73 Lataukset (Pure)

Abstrakti

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).

Alkuperäiskieli	Englanti
Artikkeli	104243
Sivumäärä	5
Julkaisu	Data in Brief
Vuosikerta	25
Varhainen verkossa julkaisun päivämäärä	2019
DOI - pysyväislinkit	https://doi.org/10.1016/j.dib.2019.104243
Tila	Julkaistu - elok. 2019
OKM-julkaisutyyppi	A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

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10.1016/j.dib.2019.104243Lisenssi: CC BY

1-s2.0-S2352340919305979-mainFinal published version, 178 KBLisenssi: CC BY

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Portfolio optimization of safety measures for the prevention of time-dependent accident scenarios
Mancuso, A., Compare, M., Salo, A. & Zio, E., lokak. 2019, julkaisussa: Reliability Engineering and System Safety. 190, 106500.
Tutkimustuotos: Lehtiartikkeli › Article › Scientific › vertaisarvioitu

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127 Lataukset (Pure)

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title = "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).",

author = "Alessandro Mancuso and Michele Compare and Ahti Salo and Enrico Zio",

year = "2019",

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T1 - Probabilistic model data of time-dependent accident scenarios for a mixing tank mechanical system

AU - Mancuso, Alessandro

AU - Compare, Michele

AU - Salo, Ahti

AU - Zio, Enrico

PY - 2019/8

Y1 - 2019/8

N2 - 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).

AB - 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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DO - 10.1016/j.dib.2019.104243

M3 - Data Article

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

Abstrakti

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Tutkimustuotos

Portfolio optimization of safety measures for the prevention of time-dependent accident scenarios

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