(untitled) (Journal of Energy and Safety Technology (JEST), 2026)
This study justifies the application of a Computational Fluid Dynamics (CFD) model, developed using Fire Dynamics Simulator (FDS), for validating and extending the analysis of experimental data from full-scale tunnel fires involving battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs). The model was rigorously calibrated using experimental heat release rate (HRR) data and demonstrated a strong capability to reproduce the where and when temperature trends observed across multiple fire scenarios. Quantitative validation through Root Mean Square Error (RMSE) analysis confirmed acceptable engineering accuracy, with contextualized percentage errors providing clear boundaries of model performance. Notably, the model performed with higher accuracy for ICEV fires ( 12% error) compared to BEV fires ( 20-26% error), highlighting the increased complexity of battery fire dynamics. The CFD model successfully captured critical fire dynamics, including thermal stratification and decay patterns with distance from the fire source. This work establishes that the validated CFD model serves as a reliable and cost-effective tool for supplementing physical experiments, enabling detailed analysis of fire behavior and supporting tunnel safety design where experimental data is limited. The validation is limited to gas temperature predictions in a single tunnel geometry, using experimentally measured HRR as the prescribed fire source together with simplified combustion and material models. The model does not resolve detailed species concentrations or battery degradation chemistry. The reported error ranges (approximately 11–15% for ICEVs and 20–26% for BEVs) should therefore be interpreted as engineering accuracy bounds for similar tunnel configurations, rather than as universal performance indicators.