The goal of developing aircraft that are greener, safer and cheaper can only be maintained through significant innovations in aircraft design. An integrated multidisciplinary design approach can lead to an increase in the performance of future derivative aircraft. Advanced aerodynamics and structural design technologies can be achieved by both passive and active suppression of aeroelastic instabilities. To demonstrate the potential of this approach, the EU-funded project Flutter Free Flight Envelope Expansion for Economical Performance Improvement is developing an unmanned aerial vehicle with a high-aspect-ratio-wing and clearly defined flutter characteristics. The aircraft is used as an experimental test platform. The scope of this work is the investigation of the aeroelastic behaviour of the aircraft and the determination of its flutter limits. The modeling of unsteady aerodynamics is performed by means of the small disturbance CFD approach that provides higher fidelity compared to conventional linear-potential-theory-based methods. The CFD-based and the linear-potential-theory-based results are compared and discussed. Furthermore, the sensitivity of the flutter behaviour to the geometric level of detail of the CFD model is evaluated.

In engineering applications, resolution is often low. In these underresolved regions, the truncation error of the underlying numerical schemes strongly affects the solution. If the truncation error functions as a physically consistent subgrid-scale model (that is, it models the evolution of otherwise resolved scales), resolution may remain low. Thereby, computational efficiency is improved. The sixth-order adaptive central-upwind weighted essentially nonoscillatory scheme with implicit scale separation, denoted as WENO-CU6-M1, potentially allows for physically consistent implicit subgrid-scale modeling, when shaped accordingly. In this work, finding an optimal formulation of WENO-CU6-M1 is considered within a deterministic design optimization framework. Possible surrogate modeling and sampling strategies are considered. Design optimization is based on evaluating the potential of a WENO-CU6-M1 scheme formulation to reproduce Kolmogorov scaling for a Taylor–Green vortex in its quasi-isotropic state. As in the absence of physical viscosity, kinetic energy dissipates exclusively due to the subgrid-scales, the Reynolds number is infinite, and the evolution of the flow is determined by proper subgrid-scale modeling. To complete the work, the effective numerical dissipation rate of the WENO-CU6-M1 model optimized for artificially compressible fluid flows is quantified, and it is compared to the original one. Not only is the zero viscosity limit considered, but the model behavior is benchmarked offdesign, for low to high Reynolds numbers. A comparison to an alternative explicit and implicit subgrid-scale model demonstrates its superior behavior for the chosen test flow.