# A Power Based Analysis for a Transonic Transport Aircraft Configuration through 3D RANS Simulations
## 2 Methodology
### Segregated Computational Domain and Simulation Conditions  
The computation domain is the key in power-based analysis. The domain includes the half model of DLR-F6 to reduce computational resources. The model locates at the center part of this domain, and it is encompassed by external boundaries, including an inlet, a symmetry plane, a cylinder boundary, and an outlet plane, as depicted in Figure 5. The external boundary, as the far-field boundary, is sufficiently large. According to reference [24], the far-field boundary is about 100 times the mean aerodynamic chord (MAC) away from the aircraft. The radius of the cylinder boundary is about 100 times the MAC, and the length of the domain is 130 times the MAC. This computational domain was used in the two cases of the wing body configuration and the BLI configuration so that the influences of the mesh were eliminated when comparing the simulation results of the two cases. The switch between the two configurations could be realized by changing the boundary condition of the actuator disc plane: the plane was set as an internal plane for the wing body configuration and it could be changed into a pressure jump plane for the BLI configuration. As for the surfaces of wing and body, the boundary condition was set as the wall. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline Mean aerodynamic chord & 141.2 mm \\ Projected half span & 585.6 mm \\ Half-model reference area, \(\mathsf{S}_{\text{ref}}\) & 72,700.0 mm\({}^{2}\) \\ Fuselage diameter & 148.4 mm \\ The diameter of the actuator disc & 100 mm \\ X location of the actuator disc (from fuselage nose) & 1181 mm \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Specifications of DLR-F6 geometry (body wing and BLI configurations). Figure 4: The geometry of the DLR-F6 wing body configuration and the BLI configuration (half model). \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline Mach number & 0.75 \\ Air model & Perfect gas \\ Temp & 18 \({}^{\circ}\)C \\ Free stream velocity, \(\mathsf{V}_{\infty}\) & 260.4 m/s \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Test condition of DLR-F6 model. A key feature of this power-based analysis is the segregation of the computational domain. By dividing the entire domain into individual subdomains, the power terms for each subdomain can be evaluated and the change in power terms is tracked [23]. Moreover, the division of the domain can be associated with the geometry of aircraft components. The mechanical power conversion of an individual component could be examined, enabling us to study the impacts of a specific aircraft component. As for the entire aircraft, the big picture of power conversion was established by combining the power conversions of the subdomains. This study defines 13 internal survey planes that segregated the computational domain into 14 subdomains. These subdomains correspond to the components of wing, body, and propulsor, as illustrated in Figure 6.  
To obtain the 3D flow field of the DLR-F6 model, this study employed ANSYS Fluent software to perform 3D compressible RANS simulations. The spatial discretization of simulations employed the second-order upwind and the third-order MUSCL methods. This study used the SIMPLE scheme for the pressure-velocity coupling. As for turbulent flow, three models were employed, namely the S-A model, the standard k-\(\epsilon\) model, and [PERSON]'s k-\(\omega\) SST model [30]. Figure 5: Boundaries of computation domain. Meshes were generated through IICEMCFD software, trying to follow the guidelines for mesh construction of the AIAA drag prediction workshop committee [24]. Unstructured mesh and multiblock structured mesh were generated in different densities: coarse, medium, and fine. The sizes of these meshes are listed in Table 4. The unstructured mesh consisted of prismatic and tetrahedral elements.