Quantifying the Influence of Parameters on Heat Release Rate in Electrical Cabinet Fires

Electrical cabinet fire scenarios constitute a significant risk within nuclear facilities, emphasizing the need to mitigate uncertainties in risk evaluations. Owing to the disparate nature of electrical cabinet parameters, only a few factors have been experimentally explored and statistically analyzed to assess their impact on peak HRR. In this study, we conducted both a cabinet parameter study and a combustible configuration study to systematically evaluate their influence on peak HRR and time-to-peak HRR. A series of 51 simulation matrices were created using statistical experiment design (SED) and ANOVA to quantify the influence of cabinet volume, combustible surface area, vent area, ignition characteristics, and burning behavior (e.g., HRRPUA and duration). A computational fluid dynamics (CFD) model, specifically a Fire Dynamics Simulator (FDS), was used to model the ignition source and flame spread inside of the electrical cabinet that influence peak HRR. The most impactful parameters influencing peak HRR and time-to-peak HRR were identified. The findings revealed that the configuration of combustibles and the placement of the ignition source play a pivotal role in determining the peak HRR. A partition screening analysis was conducted to identify the conditions under which the ventilation area becomes a more significant parameter. Additionally, a comparison between experimental results and numerical simulations demonstrated good agreement, further validating the predictive capability of the model.

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Publication Details

Journal
Fire
Published
2025-06-30
DOI
https://doi.org/10.3390/fire8070256
Primary Topic
Fire dynamics and safety research
Type
article
Field-Weighted Citation Impact
0.00

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article

Quantifying the Influence of Parameters on Heat Release Rate in Electrical Cabinet Fires

Mohammad Amer Allaf, Juliana Pacheco Duarte, Urvin Salvi, Brian Y. Lattimer et al.
Fire
Fire dynamics and safety research
article

Quantifying the Influence of Parameters on Heat Release Rate in Electrical Cabinet Fires

Mohammad Amer Allaf, Juliana Pacheco Duarte, Urvin Salvi, Brian Y. Lattimer, Elvan Sahin, Umang Selokar
article en

Abstract

Electrical cabinet fire scenarios constitute a significant risk within nuclear facilities, emphasizing the need to mitigate uncertainties in risk evaluations. Owing to the disparate nature of electrical cabinet parameters, only a few factors have been experimentally explored and statistically analyzed to assess their impact on peak HRR. In this study, we conducted both a cabinet parameter study and a combustible configuration study to systematically evaluate their influence on peak HRR and time-to-peak HRR. A series of 51 simulation matrices were created using statistical experiment design (SED) and ANOVA to quantify the influence of cabinet volume, combustible surface area, vent area, ignition characteristics, and burning behavior (e.g., HRRPUA and duration). A computational fluid dynamics (CFD) model, specifically a Fire Dynamics Simulator (FDS), was used to model the ignition source and flame spread inside of the electrical cabinet that influence peak HRR. The most impactful parameters influencing peak HRR and time-to-peak HRR were identified. The findings revealed that the configuration of combustibles and the placement of the ignition source play a pivotal role in determining the peak HRR. A partition screening analysis was conducted to identify the conditions under which the ventilation area becomes a more significant parameter. Additionally, a comparison between experimental results and numerical simulations demonstrated good agreement, further validating the predictive capability of the model.

FireVol. 8(7)
University of Wisconsin–Madison (US), Virginia Tech (US)
U.S. Department of Energy, Office of Nuclear Energy
Openalex Percentile: Top 82%
Fire dynamics and safety research
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Quantifying the Influence of Parameters on Heat Release Rate in Electrical Cabinet Fires — Mohammad Amer Allaf, Juliana Pacheco Duarte, et al. · Fire (2025) | TGRS Research Map | TGRS