Modeling emergency evacuation for major hazard industrial sites

Georgiadou, PS; Papazoglou, IA; Kiranoudis, CT; Markatos, NC

dc.contributor.author	Georgiadou, PS	en
dc.contributor.author	Papazoglou, IA	en
dc.contributor.author	Kiranoudis, CT	en
dc.contributor.author	Markatos, NC	en
dc.date.accessioned	2014-03-01T01:26:41Z
dc.date.available	2014-03-01T01:26:41Z
dc.date.issued	2007	en
dc.identifier.issn	0951-8320	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18173
dc.subject	Emergency planning	en
dc.subject	Evacuation model	en
dc.subject	Monte Carlo simulation	en
dc.subject	Stochastic Markov model	en
dc.subject.classification	Engineering, Industrial	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	Computer simulation	en
dc.subject.other	Industrial wastes	en
dc.subject.other	Markov processes	en
dc.subject.other	Monte Carlo methods	en
dc.subject.other	Probability	en
dc.subject.other	Stochastic models	en
dc.subject.other	Emergency planning	en
dc.subject.other	Evacuation models	en
dc.subject.other	Stochastic Markov models	en
dc.subject.other	Hazardous materials	en
dc.title	Modeling emergency evacuation for major hazard industrial sites	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.ress.2006.09.009	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.ress.2006.09.009	en
heal.language	English	en
heal.publicationDate	2007	en
heal.abstract	A model providing the temporal and spatial distribution of the population under evacuation around a major hazard facility is developed. A discrete state stochastic Markov process simulates the movement of the evacuees. The area around the hazardous facility is divided into nodes connected among themselves with links representing the road system of the area. Transition from node-to-node is simulated as a random process where the probability of transition depends on the dynamically changed states of the destination and origin nodes and on the link between them. Solution of the Markov process provides the expected distribution of the evacuees in the nodes of the area as a function of time. A Monte Carlo solution of the model provides in addition a sample of actual trajectories of the evacuees. This information coupled with an accident analysis which provides the spatial and temporal distribution of the extreme phenomenon following an accident, determines a sample of the actual doses received by the evacuees. Both the average dose and the actual distribution of doses are then used as measures in evaluating alternative emergency response strategies. It is shown that in some cases the estimation of the health consequences by the average dose might be either too conservative or too non-conservative relative to the one corresponding to the distribution of the received dose and hence not a suitable measure to evaluate alternative evacuation strategies. (C) 2006 Published by Elsevier Ltd.	en
heal.publisher	ELSEVIER SCI LTD	en
heal.journalName	Reliability Engineering and System Safety	en
dc.identifier.doi	10.1016/j.ress.2006.09.009	en
dc.identifier.isi	ISI:000248628600011	en
dc.identifier.volume	92	en
dc.identifier.issue	10	en
dc.identifier.spage	1388	en
dc.identifier.epage	1402	en