2017
DOI: 10.1016/j.firesaf.2017.03.068
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The impact of user decision-making in the application of computational compartment fire models

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Cited by 5 publications
(5 citation statements)
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“…Blind modelling studies, such as the work by Rein et al 13 on the Dalmarnock Fire Tests, have highlighted the difficulty in predicting dynamics when there are increasing degrees of freedom. More recently, Baker et al 14 have presented a blind modelling study of furniture fires in an ISO 9705:1993 15 room using B-RISK, concluding that the results provided an illustration of the subjectivity that can occur in everyday performance-based fire safety engineering. 14 In this article, the impact of modelling decisions in the context of analyses with fewer degrees of freedom have been considered, where the experiments have provided an opportunity to simulate a ‘simple’ enclosure and compare to past simulations, with data available for inputs including HRR, geometry, sprinkler characteristics and construction materials.…”
Section: Introductionmentioning
confidence: 99%
“…Blind modelling studies, such as the work by Rein et al 13 on the Dalmarnock Fire Tests, have highlighted the difficulty in predicting dynamics when there are increasing degrees of freedom. More recently, Baker et al 14 have presented a blind modelling study of furniture fires in an ISO 9705:1993 15 room using B-RISK, concluding that the results provided an illustration of the subjectivity that can occur in everyday performance-based fire safety engineering. 14 In this article, the impact of modelling decisions in the context of analyses with fewer degrees of freedom have been considered, where the experiments have provided an opportunity to simulate a ‘simple’ enclosure and compare to past simulations, with data available for inputs including HRR, geometry, sprinkler characteristics and construction materials.…”
Section: Introductionmentioning
confidence: 99%
“…Akin to the FDS tool in Europe, New Zealand has its own tool titled B-RISK (Branz, 2019). According to its official website, it was created to “ allow fire simulation results to be presented in a probabilistic form and allows the variability and uncertainty associated with the predictions of the fire environment to be quantified ” (Wade et al ., 2016). In preparation for its development, Baker et al .…”
Section: Notable Success Stories and Case Studiesmentioning
confidence: 99%
“…The spread rate and mass loss rate of the compartment fire in real-scale with the entire duration of the fire are estimated by expanding the methodology to the use of CFD type fire models [3]. Only when the HRR is well characterized as an input parameter in CFD type fire models, a good agreement with measurements can be obtained [4,5]. Whileas CFD fire simulations typically take large periods of time to complete, and their results would not be available in time to be of use during an emergency.…”
Section: Introductionmentioning
confidence: 99%
“…The consensus provided by these works [2,4,5,15] is that the fire evolution can be evaluated from a certain amount of information as temperature, pressure, speed, chemical composition contained and conveyed in smokes. While as, the detailed diagnostics including these measurements create an insurmountable difficulty during a compartment fire.…”
Section: Introductionmentioning
confidence: 99%