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Statements

Subject Item
n2:RIV%2F61989100%3A27740%2F14%3A86089063%21RIV15-MSM-27740___
rdf:type
skos:Concept n20:Vysledek
rdfs:seeAlso
http://www.sciencedirect.com/science/journal/09518320/125
dcterms:description
Risk to safety of personnel in process industries is normally modeled in the application of Event Trees, where the risk is defined as a product of event frequency and its consequences. This method is steady state whilst the actual event is time dependent, comprising, for a gas release, as for example, the size of gas cloud being released, probabilities of ignition, fire or explosion, fatality, escalation to new releases and fire and/or explosion, and the probability of fatality, all varying with time. This Paper presents a method whereby the time-dependent events and the time-dependent probability of fatality are modeled by means of the direct Monte Carlo simulation method. Different accident scenarios are modeled and discussed resulting from Event Trees analysis. Using the simulation method the modeled scenarios change with relevant probabilities at defined times to configurations with appropriate probabilities of fatalities. Simple sensitivity analysis in dependency on most relevant events is also performed. The Paper uses a realistic example from the offshore industry for which the probability of fatality is quantified by the use of simulation method. Risk to safety of personnel in process industries is normally modeled in the application of Event Trees, where the risk is defined as a product of event frequency and its consequences. This method is steady state whilst the actual event is time dependent, comprising, for a gas release, as for example, the size of gas cloud being released, probabilities of ignition, fire or explosion, fatality, escalation to new releases and fire and/or explosion, and the probability of fatality, all varying with time. This Paper presents a method whereby the time-dependent events and the time-dependent probability of fatality are modeled by means of the direct Monte Carlo simulation method. Different accident scenarios are modeled and discussed resulting from Event Trees analysis. Using the simulation method the modeled scenarios change with relevant probabilities at defined times to configurations with appropriate probabilities of fatalities. Simple sensitivity analysis in dependency on most relevant events is also performed. The Paper uses a realistic example from the offshore industry for which the probability of fatality is quantified by the use of simulation method.
dcterms:title
Time-dependent risk modeling of accidental events and responses in process industries Time-dependent risk modeling of accidental events and responses in process industries
skos:prefLabel
Time-dependent risk modeling of accidental events and responses in process industries Time-dependent risk modeling of accidental events and responses in process industries
skos:notation
RIV/61989100:27740/14:86089063!RIV15-MSM-27740___
n3:aktivita
n16:P
n3:aktivity
P(ED1.1.00/02.0070)
n3:cisloPeriodika
2014
n3:dodaniDat
n11:2015
n3:domaciTvurceVysledku
n10:6396038 n10:9414223
n3:druhVysledku
n17:J
n3:duvernostUdaju
n19:S
n3:entitaPredkladatele
n9:predkladatel
n3:idSjednocenehoVysledku
50577
n3:idVysledku
RIV/61989100:27740/14:86089063
n3:jazykVysledku
n14:eng
n3:klicovaSlova
Offshore Industry, Time-Dependent Risk Modeling, Hydrocarbon-Related Fire Risk, Monte Carlo Method
n3:klicoveSlovo
n4:Hydrocarbon-Related%20Fire%20Risk n4:Monte%20Carlo%20Method n4:Offshore%20Industry n4:Time-Dependent%20Risk%20Modeling
n3:kodStatuVydavatele
GB - Spojené království Velké Británie a Severního Irska
n3:kontrolniKodProRIV
[7054E7007953]
n3:nazevZdroje
Reliability engineering and system safety
n3:obor
n15:BB
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
4
n3:projekt
n8:ED1.1.00%2F02.0070
n3:rokUplatneniVysledku
n11:2014
n3:svazekPeriodika
125
n3:tvurceVysledku
Zdráhala, Adam Medonos, Sava Wilkins, Chris Briš, Radim
n3:wos
000333790600007
s:issn
0951-8320
s:numberOfPages
13
n12:doi
10.1016/j.ress.2013.05.010
n18:organizacniJednotka
27740