Estimating the Flashover Probability of Residential Fires Using Monte Carlo Simulations of the MQH Correlation

Bruns, M.

doi:10.1007/s10694-017-0680-0

Cited by 9 publications

(5 citation statements)

References 19 publications

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“…(the lower the PHRR, the lower the likelihood of flashover and flame spread occurrence). 60,74 B1 and B6 were the best performing barriers in terms of t BI and PHRR 2 (B6 being the best due to the absence of PHRR 1 and lower initial HRR). Interestingly, both B1 and B6 contain hybrid yarns made of regenerated cellulose and polysilicic acid, which are inherently fire resistant.…”

Section: Impact Of Barriers On Fire Riskmentioning

confidence: 98%

“…Such rapid fire growth would most likely lead to flashover conditions in most residential fire scenarios. 60 A HRR of 1000 kW generally leads to flashover in a small bedroom and in dwellings where flaming can spread from RUF to other combustible items in the compartment, independent of the room size. 61 In comparison, all barriers significantly decreased the fire growth by generating a HRR plateau between the appearance of a first peak of heat release rate (PHRR 1 ) and a second, higher peak (PHRR 2 ), which shortly followed the formation of a pool fire.…”

Section: Effects Of Barriers On Fire Growthmentioning

confidence: 99%

“…75 Based on NFPA 1710 and NFPA 1720, 76,77 first responders are expected to intervene within about 12 minutes in urban areas, 13 minutes in suburban areas, and 17 minutes in rural areas. 75 An RUF with similar fire growth as for the chair mock-ups without barrier (ie, PHRR 2 above 2500 kW and t P2 ≈ 3 min) would most likely lead to flashover before responders intervention even in urban areas, 60 whereas, an RUF with a reduced fire growth as for the chair mock-ups with B6 (t BI ≈ 20 min) would most likely allow responders to intervene before flashover even in rural areas because, as previously discussed, flashover is not likely to occur for t < t BI..…”

Section: Impact Of Barriers On Fire Riskmentioning

confidence: 99%

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Performance and failure mechanism of fire barriers in full‐scale chair mock‐ups

et al. 2021

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Section: Impact Of Barriers On Fire Riskmentioning

confidence: 98%

Section: Effects Of Barriers On Fire Growthmentioning

confidence: 99%

Section: Impact Of Barriers On Fire Riskmentioning

confidence: 99%

See 1 more Smart Citation

Performance and failure mechanism of fire barriers in full‐scale chair mock‐ups

et al. 2021

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“…The parameters inputted into this simulation were divided into fixed and random parameters generated via Monte Carlo sampling using CData, as shown in Tables 1 and 2. The selected random parameters incorporated five crucial elements identified in previous studies: opening width, opening height, thermal conductivity, wall thickness, and ceiling thickness [30]. In the next step, more parameter indicators were selected to improve the model's generalization ability.…”

Section: Construction Of Cfast Modelmentioning

confidence: 99%

Fire Source Determination Method for Underground Commercial Streets Based on Perception Data and Machine Learning

Yang,

Zhang,

Zhang

et al. 2024

Fire

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Determining fire source in underground commercial street fires is critical for fire analysis. This paper proposes a method based on temperature and machine learning to determine information about fire source in underground commercial street fires. Data was obtained through consolidated fire and smoke transport (CFAST) software, and a fire database was established based on the sampling to ascertain fire scenarios. Temperature time series were chosen for feature processing, and three machine learning models for fire source determination were established: decision tree, random forest, and LightGBM. The results indicated that the trained models can determine fire source information based on processed features, achieving a precision exceeding 95%. Among these, the LightGBM model exhibited superior performance, with macro averages of precision, recall, and F1 score being 99.01%, 98.45%, and 99.04%, respectively, and a kappa value of 98.81%. The proposed method for determining the fire source provides technical support for grasping the fire situation in underground commercial streets and has good application prospects.

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“…For cost-benefit analysis also probabilistic method was used [14,15]. Some recent research has highlighted probability based quantification of various aspects of fire safety engineering [16][17][18][19][20][21]. Examples of application of comprehensive QPRA on a performancebased designed building are rare in archival journals.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Risk Assessment of Life Safety for a Six-Storey Commercial Building with an Open Stair Interconnecting Four Storeys: A Case Study

Sabapathy¹,

Depetro²,

Moinuddin

2019

Fire Technol

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The gold standard for complying Performance Requirements is based on a Quantitative Probabilistic Risk Assessment (QPRA) method. This case study demonstrates the application of this approach to performance based design of a six-storey commercial building with an open stair interconnecting four storeys. Computational Fluid Dynamics (CFD) based and zone fire as well as evacuation simulations are used to quantify consequences whilst detailed event trees underpinned by statistical data and analysis are utilised to calculate corresponding probabilities. Results are combined in a trade-off analysis tool which calculates the Expected Risk to Life (ERL) based on the trial design features included in each design option. The approach was used to determine a preferred design that achieves an acceptably low ERL and compliance with the Performance Requirements of the Building Code of Australia (BCA). The benchmark ERL was set as 1.36 deaths/1000 fires or a probability of death from a fire of 1.36 x 10-3 based on local statistical data. To obtain an optimum fire safety design (Alternative Solution) a layered approach was adopted in which fire safety systems were added until the risk to occupants in the building due to a fire is the same or less than the benchmark ERL. Eventually three sets of trial design were considered and in all cases the calculated ERL were roughly 22% lower than the benchmark. Eventually the trial design with the least number of fire safety systems were recommended as the Alternative Solution. The trade-off analysis shows the sprinklers and wallwetting sprinklers in the office area resulted in a 20-fold difference in the building wide ERL, each. Schematic Design Fire Specification Event Tree Development Preliminary Risk Assessment and Scenario Generation Data Collection/Analysis Collect and analyse relevant data Determine credible fire scenarios (causes, locations, etc.) Conduct preliminary, qualitative risk analysis Complete risk ranking and short list design fire scenarios Identify all possible statuses of fire safety subsystems Construct event tree and generate possible outcomes Calculate probabilities using relevant data

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Estimating the Flashover Probability of Residential Fires Using Monte Carlo Simulations of the MQH Correlation

Cited by 9 publications

References 19 publications

Performance and failure mechanism of fire barriers in full‐scale chair mock‐ups

Performance and failure mechanism of fire barriers in full‐scale chair mock‐ups

Fire Source Determination Method for Underground Commercial Streets Based on Perception Data and Machine Learning

Probabilistic Risk Assessment of Life Safety for a Six-Storey Commercial Building with an Open Stair Interconnecting Four Storeys: A Case Study

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