Effects of turbulence modelling on the analysis and optimisation of high-lift configurations

Abstract

Due to the significant effects on the performance and competitiveness of aircraft, high lift devices are of extreme importance in aircraft design. The flow physics of high lift devices is so complex, that traditional one pass and multi-pass design approaches can’t reach the most optimised concept and multi-objective design optimisation (MDO) methods are increasingly explored in relation to this design task. The accuracy of the optimisation, however, depends on the accuracy of the underlying Computational Fluid Dynamics (CFD) solver. The complexity of the flow around high-lift configuration, namely transition and separation effects leads to a substantial uncertainty associated with CFD results. Particularly, the uncertainty related to the turbulence modelling aspect of the CFD becomes important. Furthermore, employing full viscous flow solvers within MDO puts severe limitations on the density of computational meshes in order to achieve a computationally feasible solution, thereby adding to the uncertainty of the outcome. This thesis explores the effect of uncertainties in CFD modelling when detailed aerodynamic analysis is required in computational design of aircraft configurations. For the purposes of this work, we select the benchmark NLR7301 multi-element airfoil (main wing and flap). This flow around this airfoil features all challenges typical for the high-lift configurations, while at the same time there is a wealth of experimental and computational data available in the literature for this case. A benchmark shape bi-objective optimization problem is formed, by trying to reveal the trade-off between lift and drag coefficients at near stall conditions. Following a detailed validation and grid convergence study, three widely used turbulence models are applied within Reynolds-Averaged Navier-Stokes (RANS) approach. K- Realizable, K- SST and Spalart-Allmaras. The results show that different turbulent models behave differently in the optimisation environment, and yield substantially different optimised shapes, while maintaining the overall optimisation trends (e.g. tendency to maximise camber for the increased lift). The differences between the models however exhibit systemic trends irrespective of the criteria for the selection of the target configuration in the Pareto front. A-posteriori error analysis is also conducted for a wide range of configurations of interest resulting from the optimisation process. Whereas Spalart-Allmaras exhibits best accuracy for the datum airfoil, the overall arrangement of the results obtained with different models in the (Lift, Drag) plane is consistent for all optimisation scenarios leading to increased confidence in the MDO/RANS CFD coupling.