# 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
Line-by-Line (LBL): This method considers the actual spectral lines of radiatively active gases, resolving absorption coefficients at very high spectral resolution. LBL is used when high accuracy is required. It is the most accurate model for radiative transfer because it considers every spectral line. Due to the intensive computational requirements of resolving individual absorption lines across the entire spectrum, it is not widely implemented in CFD tools like FDS or OpenFOAM. 2. Spectral Band Models: These models divide the spectrum of gas radiation into discrete spectral bands: * Narrow Band Models (NBM): These models divide the spectrum into small narrow bands and treat radiative properties as varying within each band. They offer a more manageable approximation compared to LBL but still retain some spectral detail. * Statistical Narrow Band (SNB): This incorporates statistical methods to represent spectral lines within each narrow band. It is the most accurate model to replicate the LBL method, especially in high temperature gases. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Model** & & **CFD Tool** & **Pros** & **Cons** \\ \hline \multirow{2}{*}{P1} & \(\bullet\) & OpenFOAM & Computationally efficient & Less accurate for non-homogeneous \\  & \(\bullet\) & ISIS & Works well in optically thick media & media Assumes isotropic radiation \\ \hline \multirow{3}{*}{DOM} & \(\bullet\) & FDS & \multirow{3}{*}{Handles complex geometries} & Computationally expensive \\  & \(\bullet\) & OpenFOAM & More accurate than P1 in some cases & Can introduce ray effects (false \\  & \(\bullet\) & ISIS & & directional patterns) \\ \hline \multirow{3}{*}{DTRM} & \(\bullet\) & OpenFOAM & Handles complex geometries & Computationally expensive \\  & & Accurate for optically thin media & Does not inherently include \\  & & Works well with complex geometries & scattering effects \\ \hline \multirow{3}{*}{S2S} & \(\bullet\) & OpenFOAM & Efficient for surface-to-surface & Does not account for gas-phase \\  & & radiation & radiation and soot absorption & \\ \cline{1-1}  & & & or scattering \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of different radiation modeling methods. * Wide Band Model (WBM): This is a simplified version of SNB. It categorizes the radiation spectrum into wider bands rather than treating individual spectral lines. Each band represents a broader wavelength range, where the absorption and emission properties are relatively similar. In other words, the model assumes that within each band, the gas properties, such as absorption coefficients, are constant or vary in a predictable manner. It can result in significantly less computational cost compared to NBM. WBM offers good accuracy, especially for gases like CO\({}_{2}\) and H\({}_{2}\)O which have strong and wide absorption bands. This model is available on FDS (Box Model) [12] and OpenFOAM (WideBandAbsorptionEmission) [112]. * Global Models: These models, including the Gray Gas and Weighted-Sum-of-Gray-Gases (WSGG) models, simplify the radiative transfer by treating the gas as absorbing/emitting uniformly across all wavelengths (or a few representative gray gases with different absorption coefficients). They are commonly available in CFD tools such as FDS, OpenFOAM, and FireFOAM. * Gray Gas Model: To reduce the required computation time for solving RTE, gases are often assumed to be gray. It helps the RTE to be solved more efficiently by treating the gas as having uniform radiative properties and eliminates the need for detailed spectral calculations (i.e., no spectral variation is considered), which involves resolving the radiative transfer across a wide range of wavelengths. By treating the gas as gray, the simulation ignores the fine structure of how different wavelengths are absorbed and emitted by gases like CO\({}_{2}\) and H\({}_{2}\)O, which are computationally expensive to resolve [94].