# Computational Fluid Dynamics of Compartent Fires: A Review of Methods and Applications
## 3 CFD Simulation in Compartment Fires
### Physical Models
#### 3.3.4 Heat Transfer: Radiation Transport
DOM can handle directional radiation effects and participating media (i.e., soot and gases), although at higher computational cost. DTRM offers directional accuracy like DOM, but it is simpler and less computationally demanding. It is effective in smaller, less complex compartments with minimal scattering and participating media. However, it assumes constant intensity along each ray, which can limit its accuracy in highly dynamic environments, such as those with significant soot or flame radiation. S2S is applicable for compartment boundaries and must be used with another model to include the radiation effect of gases and soot. FDS uses the finite volume method (DOM-based approach) to solve RTE, P1 and finite volume DOM are available in ISIS, while OpenFOAM can adopt P1, DOM, DTRM, and S2S methods. Besides No Radiation Transport, FDS provides three more approaches for the RTE: optically thin, optically thick with specified radiative fraction, and optically thick with predicted radiative fraction (not specified). The optically thin and optically thick approaches for radiation modeling in FDS were compared by [PERSON] and [PERSON] [38] in an open atmosphere free-burning. Their results showed that the optically thin method was more accurate in terms of predicting flame temperature, velocity, and radiative heat flux. But for an enclosed fire, according to [12], the optically thin approach is not appropriate due to its neglect of the re-absorption of thermal radiation by gases in the confined space. Therefore, in CFD simulation of a compartment fire using FDS, the optically thick option is more accurate. However, predicting radiative fraction instead of prescribing required the well-resolved temperature field and absorption coefficient to be calculated directly, as well as fine mesh grids such as in DNS. As a proper method in LES, optically thick with specified radiative fraction can be a better choice for compartment fires, which is a prescriptive method and needs the user to specify the radiative fraction of the fuel. This parameter illustrates the portion of fire energy which is emitted by radiation. The radiative fraction for more common fuels is presented in [12], adopted from _SFPE Handbook of Fire Protection Engineering_[43]. However, the pre-defined values for radiative fraction are typically based on ideal conditions such as complete combustion and a well-ventilated compartment and are not appropriate for under-ventilated fire scenarios, for example. Under-ventilated conditions often lead to incomplete combustion, resulting in a higher proportion of unburned fuel and increased soot production, and changes the radiative properties compared to well-ventilated conditions. It should be noted that considering radiative fraction to be fixed equal to the prescribed value is not always accurate, resulting in over-prediction of the radiative heat flux at the fuel surface [106]. Since the fuel vapor and product gases are accumulated and reduce the radiation, however, this approach can account for soot radiation and is helpful to simplify CFD simulation in a compartment fire [38]. Table 3 presents a summary of different methods for radiation modeling which are available in different CFD tools, presenting their advantages and disadvantages. As mentioned in Equation (5), \(k_{a}\) is the absorption coefficient (for product gases and solid particles such as soot) and needs to be specified for solving RTE. However, the absorption coefficient is not considered in the optically thin approach as it is assumed that the energy emitted by the fire is not absorbed by the surrounding gases or particles (e.g., soot) to a significant extent. \(\mathsf{k}_{\alpha}\) is a critical parameter that quantifies how much radiation is absorbed by a participating medium (such as gases or particles). Several radiative gas property models are available for specifying or approximating the absorption coefficient in CFD [107; 108; 109; 110; 111]:  
1.