The implementation of adaptive mesh refinement (AMR) in the spectral-element method code Nek5000 is used for the first time on the well-resolved large-eddy simulation of the turbulent flow over wings. In particular, the flow over a NACA4412 profile with a $$5^\circ$$5 ∘ angle of attack at chord-based Reynolds number $${\text {Re}}_c=200{,}000$$Re c = 200 , 000 is analyzed in the present work and compared with a previous conformal simulation used as baseline. The mesh, starting from a coarse resolution, is progressively and automatically refined by means of AMR, which allows for high resolution near the wall and wake whereas significantly larger elements are used in the far-field. The resulting mesh, which remains unchanged in the production runs (i.e. AMR is used to create the final mesh, which is then fixed), is of higher resolution than those in previous conformal cases, and it allows for the use of larger computational domains, avoiding the use of precursor RANS simulations to determine the boundary conditions. This is achieved with, approximately, 2 times lower total number of grid points if the same spanwise length is used. Turbulence statistics obtained in the AMR simulation show good agreement with the ones obtained with the conformal mesh, and the pressure-coefficient distribution along the wing surface matches pressure-scan experimental data obtained in the MTL wind tunnel at KTH. The use of AMR is therefore expected to enable the simulation of high-Reynolds numbers turbulent flows over complex geometries (such as wings), thus allowing the study of pressure-gradient effects at high Reynolds numbers relevant for practical applications.

Active flow-control techniques have shown promise for achieving high levels of drag reduction. However, these techniques are often complex and involve multiple tunable parameters, making it challenging to optimize their efficiency. Here, we present a Bayesian optimization (BO) approach based on Gaussian process regression to optimize a wall-normal blowing and suction control scheme for a NACA 4412 wing profile at two angles of attack: 5 and 11 $$^\circ$$∘ , corresponding to cruise and high-lift scenarios, respectively. An automated framework is developed by linking the BO code to the CFD solver OpenFOAM. RANS simulations (validated against high-fidelity LES and experimental data) are used in order to evaluate the different flow cases. BO is shown to provide rapid convergence towards a global maximum, even when the complexity of the response function is increased by introducing a model for the cost of the flow control actuation. The importance of considering the actuation cost is highlighted: while some cases yield a net drag reduction (NDR), they may result in an overall power increase. Furthermore, optimizing for NDR or net power reduction (NPR) can lead to significantly different actuation strategies. Finally, by considering losses and efficiencies representative of real-world applications, still a significant NPR is achieved in the 11 $$^\circ$$∘ case, while net power reduction is only marginally positive in the 5 $$^\circ$$∘ case.

Wake analysis plays a significant role in wind-farm planning through the evaluation of losses and energy yield. Wind-tunnel tests for wake studies have high costs and are time-consuming. Therefore, computational fluid dynamics (CFD) emerges as an efficient alternative. An especially attractive approach is based on the solution of the Reynolds-averaged Navier–Stokes (RANS) equations with two-equation turbulence closure models. The validity of this approach and its inherent limitations, however, remain to be fully understood. To this end, detailed wind-tunnel experiments in the wake of a NACA4412 wing section profile are compared with CFD results. Two- and three-dimensional RANS simulations are carried out for a range of angles of attack up to stall conditions at a chord- and inflow-based Reynolds number of $R{e}_c=4\times {10}^5$. Here, we aim to investigate the wake characteristics and self-similar behaviour, both from the experimental and numerical perspectives. The measurements are carried out by means of hot-wire anemometry capturing the wake pattern in several planes. The sensitivity of the CFD model to different configurations of the setup and the considerations required for reliable simulation are discussed. The agreement between CFD, experiments, and the literature is fairly good in many aspects, including the self-similar behaviour and wake parameters, as well as the flow field. Comparison of experiments with URANS/RANS data indicates that the latter is an adequate methodology to characterize wings and their wakes once the CFD setup is designed appropriately and the limitations due to discretization and turbulence modelling are considered.