Numerical assessment of LES subgrid-scale turbulence models for expandable particles in fire suppression

Owing to the well-established Eulerian–Lagrangian framework on mixture fluids, computational fluid dynamics coupled with discrete element model (CFD–DEM) is an effective while appropriate tool to predict the complex interactive fire behaviours associate with suppression effects. Although suppression behaviours between hydrocarbon-fuelled fire and water-based suppression agents were extensively studied both numerically and experimentally, lack of numerical studies was conducted on fires involving water-reactive chemicals (i.e., Na, Li, and LiH), where extinguishment is barely performed by water-based active suppression system, as violent and explosive decomposition occurred between water and reactive fuel. In this research, a numerical investigation has been conducted on expandable graphite (EG) application for water-reactive fire suppression. Based on the discrete phase model (DPM) framework, a novel EG particle model is proposed to characterise the particle expansion that couples with superior thermal properties and chemical stability. A numerical assessment on large eddy simulation (LES) has been performed to study the temporal fire behaviours and the suppression effect of EG against the flame plume in various subgrid-scale (SGS) models. Four SGS models were adopted, which were namely Smagorinsky–Lilly, WALE, dynamic kinetic energy, and dynamic Smagorinsky–Lilly. As a result, the WALE SGS model was observed to be in a better agreement compared with the experimental data owing to its significant enhancement in flow diffusivity modelling. The WALE SGS model has achieved a more accurate temperature prediction and finer resolved turbulence compared with other SGS models.