{"id":{"repo_id":"vu-aus","oai_identifier":"oai:eprints.vu.edu.au:15658"},"canonical_url":"https://search.dev.ndltd.org/etd/vu-aus/oai:eprints.vu.edu.au:15658","repository":{"repo_id":"vu-aus","name":"Victoria University (Australia)","base_url":"https://vuir.vu.edu.au/cgi/oai2"},"display":{"title":"The investigation of fire hazards in buildings using stochastic modelling","abstract":"This research investigates the spread of fire and smoke in buildings as well as occupant egress. There are existing deterministic models for these. While deterministic models provide averages of a process, stochastic models give the broad spectrum of all possible scenarios of the process giving the distribution function. The spread of smoke was first modelled by adding a noise component to the equation of an existing deterministic model. Later a deterministic model was developed and stochastic expressions derived using the Markov chain methodology. Though the Markov chain is a discrete process, it was used in approximating smoke spread which is a continuous process. The spread of fire was investigated using network analysis. Various methods of modelling the spread of a phenomenon in a network were compared.","abstract_html":"This research investigates the spread of fire and smoke in buildings as well as occupant egress. There are existing deterministic models for these. While deterministic models provide averages of a process, stochastic models give the broad spectrum of all possible scenarios of the process giving the distribution function. The spread of smoke was first modelled by adding a noise component to the equation of an existing deterministic model. Later a deterministic model was developed and stochastic expressions derived using the Markov chain methodology. Though the Markov chain is a discrete process, it was used in approximating smoke spread which is a continuous process. The spread of fire was investigated using network analysis. 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There are existing deterministic models for these. While deterministic models provide averages of a process, stochastic models give the broad spectrum of all possible scenarios of the process giving the distribution function. The spread of smoke was first modelled by adding a noise component to the equation of an existing deterministic model. Later a deterministic model was developed and stochastic expressions derived using the Markov chain methodology. Though the Markov chain is a discrete process, it was used in approximating smoke spread which is a continuous process. The spread of fire was investigated using network analysis. 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Though the Markov chain is a discrete process, it was used in approximating smoke spread which is a continuous process. The spread of fire was investigated using network analysis. Various methods of modelling the spread of a phenomenon in a network were compared."],"dc:format":["text"],"dc:identifier.uri":["https://vuir.vu.edu.au/15658/1/Odigie_2000compressed.pdf"],"dc:language":["en"],"dc:publisher.department":["Center for Environmental Studies and Risk Engineering"],"dc:publisher.institution":["Victoria University of Technology"],"dc:relation.isreferencedby":["https://vuir.vu.edu.au/15658/"],"dc:subject":["1204 Engineering Design","0401 Atmospheric Sciences","Centre for Environmental Safety and Risk Engineering (CESARE)"],"dc:title":["The investigation of fire hazards in buildings using stochastic modelling"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["phd"]},"updated_at":"2026-07-24T06:33:17Z"}