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. This research highlights progress in understanding the parameters that affect the peak heat release rate (HRR) in electrical cabinet fires. A computational fluid dynamics (CFD) model, specifically Fire Dynamics Simulator (FDS), was used to model the ignition source (pre-ignition heating) and flame spread inside of the electrical cabinet (e.g., electrical cables, electrical boards, sensors, transducers, etc.) that influence peak HRR. 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 the peak HRR. A simulation matrix was created using statistical experiment design (SED) and ANOVA based statistical analysis to quantify the relative importance of parameters. This resulted in a series of 51 simulations to quantify the impact of cabinet volume, combustible material surface area, cabinet vent area, ignition source, ignition source elevation, and combustible material burning characteristics (e.g., heat release rate per unit area (HRRPUA), burning duration). Additionally, a series of 12 simulations was also conducted to explore how the combustibles arrangement and the ignition source elevation influence the peak HRR inside the electrical cabinet. The findings revealed that the configuration of combustibles and the placement of the ignition source play a pivotal role in determining the peak HRR. The most impactful parameters were ignition source (HRRb), ignition source elevation (zb), HRRPUA, and surface area of combustible materials (walls and ceilings). Among the factors affecting time-to-peak HRR, ignition source (HRRb) and combustible burning duration (tc) were the most significant. A partition screening analysis was performed to determine the conditions under which the parameter-ventilation area becomes more significant. The results indicate strong predictive capability and reliability in capturing the dynamics of fire HRR, representing a significant advancement in the field of nuclear safety.