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Statements

Subject Item
n2:RIV%2F60162694%3AG43__%2F13%3A00497197%21RIV14-MV0-G43_____
rdf:type
n5:Vysledek skos:Concept
rdfs:seeAlso
http://vavtest.unob.cz/registr
dcterms:description
Road bridges in accidental situations represent the most vulnerable components of transportation networks. Hazard situations may be caused by natural or manmade hazards such as floods, terrorist attacks or impacts of vehicles. Decisions concerning selection of protective measures can be based on the probabilistic optimisation of expected costs. In general, total structural costs consist of initial cost and consequences due to structural damage and failure. The initial cost comprises of construction cost including cost of protective measures; the failure consequences account for direct costs related to structural failure and indirect costs due to malfunction of transportation network. The paper proposes a general framework for the risk assessment based on Bayesian (causal) networks. The cost optimisation requires data on probability of occurrence and magnitude of selected accidental actions that often need to be based on expert assessments and judgements only. The present study indicates that the probabilistic cost optimisation in conjunction with Bayesian networks provide an effective tool for decisions concerning appropriate protective measures for bridges endangered by various types of hazards. Road bridges in accidental situations represent the most vulnerable components of transportation networks. Hazard situations may be caused by natural or manmade hazards such as floods, terrorist attacks or impacts of vehicles. Decisions concerning selection of protective measures can be based on the probabilistic optimisation of expected costs. In general, total structural costs consist of initial cost and consequences due to structural damage and failure. The initial cost comprises of construction cost including cost of protective measures; the failure consequences account for direct costs related to structural failure and indirect costs due to malfunction of transportation network. The paper proposes a general framework for the risk assessment based on Bayesian (causal) networks. The cost optimisation requires data on probability of occurrence and magnitude of selected accidental actions that often need to be based on expert assessments and judgements only. The present study indicates that the probabilistic cost optimisation in conjunction with Bayesian networks provide an effective tool for decisions concerning appropriate protective measures for bridges endangered by various types of hazards.
dcterms:title
General approach to risk optimisation of road bridges exposed to accidental situation General approach to risk optimisation of road bridges exposed to accidental situation
skos:prefLabel
General approach to risk optimisation of road bridges exposed to accidental situation General approach to risk optimisation of road bridges exposed to accidental situation
skos:notation
RIV/60162694:G43__/13:00497197!RIV14-MV0-G43_____
n3:aktivita
n4:P
n3:aktivity
P(VG20122015089)
n3:dodaniDat
n11:2014
n3:domaciTvurceVysledku
n18:5055385
n3:druhVysledku
n22:D
n3:duvernostUdaju
n12:S
n3:entitaPredkladatele
n16:predkladatel
n3:idSjednocenehoVysledku
76283
n3:idVysledku
RIV/60162694:G43__/13:00497197
n3:jazykVysledku
n19:eng
n3:klicovaSlova
risk optimisation; road bridges; accidental situations
n3:klicoveSlovo
n17:road%20bridges n17:risk%20optimisation n17:accidental%20situations
n3:kontrolniKodProRIV
[8F8EFCDA39E1]
n3:mistoKonaniAkce
Rome, Italy
n3:mistoVydani
Ashurst Lodge
n3:nazevZdroje
Garzia, F. - Brebbia, C.A. - Guarascio, M. (eds.) Proceedings of the 5th International Conference on Safety and Security Engineering SAFE 2013
n3:obor
n9:JM
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
3
n3:projekt
n14:VG20122015089
n3:rokUplatneniVysledku
n11:2013
n3:tvurceVysledku
SÝKORA, Miroslav HOLICKÝ, Milan Maňas, Pavel
n3:typAkce
n20:WRD
n3:zahajeniAkce
2013-01-01+01:00
s:issn
1746-4498
s:numberOfPages
10
n15:hasPublisher
WIT Press
n10:isbn
978-1-84564-744-5
n13:organizacniJednotka
G43