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.