A new non-linear lifting line method for 3D analysis of wing/configuration aerodynamic characteristics with application to UAVs

In this work, we develop a new non-linear lifting line method for wings and similar lifting surfaces using the Prandtl’s classical lifting line theory. Specifically, the developed method is able to determine 3D maximum lift coefficient and pre-and post-stall aerodynamic behavior of a wing by using its section’s non-linear 2D lift curve obtained experimentally or numerically. The method also gives induced drag directly, and provides viscous drag and pitching moment coefficients by using two-dimensional airfoil data on the order of seconds using conventional personal computers. Validation of the numerical results in comparison to 3D experimental data show almost 1-1 coincidence with the experimental data in both linear region (including correct prediction of the maximum lift coefficient) and non-linear pre-and post-stall regions. A direct comparison between the results of current method and computationally intense tools such as NASA TetrUSS CFD tool shows a good agreement. One of the key challenges associated with the design of Unmanned Aerial Vehicles (UAVs) is the limited availability of fast and reliable aerodynamic analysis tools that can precisely predict pre-and post-stall aerodynamic behavior at flow regimes marked with viscous effects at low Reynolds numbers. In that respect, we extended our method to include UAV tail and body sections as to do the complete configuration analysis and the aerodynamic characterization of the whole aircraft. Our initial computational comparison of the proposed method with aerodynamic analysis tools such as XFLR5, DATCOM+, Tornado and Fluent show the ability of our method to capture, on the order of a few seconds, critical nonlinear and viscous effects on the whole aircraft with aerodynamic parameter accuracy levels comparable to CFD analysis. As such, our new non-linear lifting line method provides the basis of an aerodynamic analysis tool which can be used for driving UAV design optimization processes and also for providing the aerodynamic parameters for dynamic models which can be used for designing flight control systems for agile maneuvering high performance UAVs operating at extensive flight regimes.