Fuselage aerodynamic drag prediction method by cfd

The aim of this work is the development of a new methodology to predict fuselage aerodynamic drag through CFD aerodynamic calculations. The investigation has been focused on typical turboprop fuselage geometry. The geometry has been divided into three main components: nose, cabin, and fuselage tail. Fuselage fineness ratio, windshield angle (Ψ), and upsweep angle (θ), have been used as independent (geometric) variables to derive the drag prediction methodology. These parameters have been varied one by one, keeping the others constant. Several fuselage geometries have been generated and then analysed with Star-CCM+ in viscous, compressible flow regime. Mesh has been carefully set-up looking at mesh solution independency, aerodynamic coefficients, and equation residuals convergence. Particular care has also been posed to the boundary layer, with 20 prismatic layers and a y+ < 1. The flow condition for all the aerodynamic analyses have been typical turboprop cruise condition of M = 0.52, Re = 17.4 million and 0 degree angle of attack and sideslip. Coupled flow, ideal gas, and Spalart-Allmaras turbulence model have been set-up for the simulations. Aerodynamic results have been collected for the analysed fuselages, focusing on the drag coefficient. In particular, from the CFD aerodynamic analyses, nose, cabin, and tail drag coefficient contributions have been isolated and related to the geometric parameters previously defined, in order to get a relation between geometry and drag coefficient for each fuselage component. Reorganizing all the results, a fuselage drag prediction method (focused mainly on skin-friction contribution) has been developed and it is here proposed. The methodology allows the estimation of fuselage drag coefficient as the sum of the contributions of each component (nose, cabin, and tailcone). This approach does not allow the calculation of other sources of drag as leakage, wiper, surface roughness and excrescences. The hypothesis of effect’s superposition has been also verified through the analysis of CFD results, since the geometry modifications of one part of the fuselage only affects the drag coefficient of that part. The generic fuselage drag coefficient can be estimated according to Eq. 1. where: The fuselage shape factors (Kn, Kc, and Kt) are presented graphically (Figure 3) and they include the drag coefficient contribution for each fuselage components. The ratios Swet component/ Swet represent a geometrical weight related to each component whereas the CDfp gives the Mach and Reynolds number effect. Kn shape factor clearly shows the nose effect on drag and it is represented as function of FRn (nose fineness ratio) and windshield angle. The Kn factor increases when fineness ratio decreases (a shorter nose) and it also increases when nose windshield angle increases (steeper nose angle). Kc shape factor is a fuselage fineness ratio (FR) function and it decreases when FR increases, being Kc ≈ 1.0 when FR is higher than 10 (it means a flat plate effect). The last effect is the fuselage tail-cone effect and it is represented by Kt shape factor. This factor increases when both FRt (tail-cone fineness ratio) and upsweep angle increase. It is useful to highlight that for upsweep angles lower than 10 degrees, curves tend asymptotically to a value around 0.7, remarkable sign that no more relevant separation occurs. The proposed fuselage drag prediction method has been applied to the fuselage geometries shown in Figure 4. Results show a very good agreement for test cases 1, 2, and 3. The ATR72 case shows a difference in fuselage drag coefficient of about 6 drag counts. This is mainly due to the windshield protruding geometry of the original ATR72. As conclusions, the fuselage drag prediction methodology can be applied to regional turboprop aircraft with reliable results and it is easily implemented in preliminary design code (or handmade calculations). Further investigations have been scheduled in wind-tunnel to validate CFD results.