# Computational Fluid Dynamics of Compartent Fires: A Review of Methods and Applications
## 3 CFD Simulation in Compartment Fires
### Physical Models
#### 3.3.1 Turbulence Modeling
In addition to the approaches mentioned, wall-modeled large-eddy simulation (WM-LES) [50] is another strategy which uses an explicit separate wall model near the walls while the flow far from the walls is resolved using LES. Furthermore, simple very large eddy simulation (SVLES), available on FDS [12], is a more simplified version of VLES which is designed to handle coarser grids compared to VLES and relies on resolving the large-scale turbulent structure and modeling the smaller scales regarding to the coarser grids' size. The computational cost and accuracy of each turbulence modeling approach in CFD depend on the resolution of turbulence scales and level of detail that need to be modeled or resolved. It indicates the time required to model the same reference problem and the validity of CFD modeling compared to a real scenario, respectively. Grid resolution is a relative criterion and is highly dependent on the considered geometry. For example, in a standard ISO 9705 compartment fire test, fine grid size can be in the range of 5 cm [51], while it can be coarse in another case with a lower HRR. DNS and LES are capable of handling both steady and unsteady flow regimes, although the time-averaging process in RANS filters out the unsteady, fluctuating component of the flow. This means that RANS cannot directly capture transient or unsteady flow features. It is especially important in the case of a compartment fire (as is shown in Figures 1 and 3) that the compartment fire has a steady fluid flow and transition behavior between different stages. Therefore, RANS is not a perfect choice for the CFD modeling of a compartment fire. Due to the required number of mesh grids and computational cost, there are turbulence ranges in which the models are more applicable: RANS can be used for high Reynolds number flows (e.g., Re \(>10^{3}\)) because it does not require fine grids and is computationallyefficient. LES is more appropriate to use in high Reynolds number flows where large-scale turbulence structures are dominant, but the computational cost increases with higher Reynolds numbers (e.g., \(10^{7}\) > Re \(>10^{4}\)). DNS is limited to very low Reynolds numbers (e.g., Re \(<10^{4}\)), since an extremely fine grid is required for resolving all turbulent scales. DES behaves like LES and is more for high Reynolds flows (e.g., Re \(>10^{5}\)) where both attached and separated flow regions exist. VLES can be applied across different Reynolds number ranges because it adapts to the local grid resolution, allowing for varying levels of turbulence modeling. According to [PERSON] and [PERSON] [52], quoted by [PERSON] et al. [53], LES provides detailed turbulence effects and is more widely used in fire modeling compared to RANS. It should be noted that DNS needs very fine mesh grids as well as computing time, which make it more difficult and less possible, especially when it comes to larger scales. In a typical fire in an enclosed room, the Reynolds number is around \(10^{5}\), resulting in the \(10^{13}\) required cells to simulate the fire and smoke movement [54]. This can eliminate or at least limit the DNS use in CFD modeling of compartment fires. Therefore, it is better to focus on the application of LES or hybrid methods for CFD simulation of compartment fires (neglecting pure RANS because of unsteady nature of compartment fire and DNS because of high computational costs and detailed resolution). A comparative analysis between different turbulence schemes in CFD is presented in Table 1, providing an overview of the advantages and disadvantages of a simulation of a compartment fire. As mentioned in the discussion regarding turbulence modeling, excluding RANS and DNS due to the limits, the LES approach (and other hybrid methods) tends to be more appropriate in the CFD simulation of a compartment fire. It resolves the large-scale turbulent structures directly while modeling the smaller sub-grid scale (SGS) structures