Dynamic Stall Simulations on a Pitching Finite Wing

Abstract

URANS computations were carried out on a pitching finite wing model using the finite volume solver DLR-TAU. The comparison with the experimental data reveals a good agreement, especially in the region of the first occurrence of stall. Discrepancies are observed in the blade tip region, where the flow in the numerical data shows a stronger separation along with larger hysteresis effects in contrast to the experiment. An investigation with different pitching frequencies revealed a change in the sequence of dynamic stall vortex formation in the spanwise direction. For the lowest frequency the propagation of the stall vortex starts at the wing tip and then spreads rootwards, whereas for the higher frequencies the first evolution of the dynamic stall vortex starts further inboard, subsequently propagating in tipward and rootward directions. An investigation using a γ-Re θt approach demonstrated that small differences can be attributed to transition, nevertheless these can give further insight in the physics of dynamic stall and improve the comparability with the experiment. A comparison with two-dimensional simulations shows strong similarities in the sections where the vortex starts to evolve and large differences in the surrounding areas.

Leading-edge vortex dynamics on plunging airfoils and wings

“…For example, surface pressure measurements revealed the three-dimensionality of the leading-edge vortex near the wing tip (Gardner et al 2014). In another study, surface pressure measurements at selected locations were combined with the unsteady Reynolds-averaged Navier-Stokes (N-S) computations (Kaufmann, Merz & Gardner 2017), detailing the differences between the wing-tip region and the inboard sections. It was suggested that multiple dynamic stall cells existed over the span.…”

Influence of Aspect Ratio on Dynamic Stall of a Finite Wing

“…Moreover, the visualization data has demonstrated that, for the same α, the higher AR wings experience a more developed DSV at the root, which explains the performance data behavior. The pressure and PIV data of previous experiments at higher Rec 23 have also been simulated using numerical approaches 27 . However, simulating wing dynamic stall using URANS was found to predict stall early when compared with experiments 27,28 .…”

“…The pressure and PIV data of previous experiments at higher Rec 23 have also been simulated using numerical approaches 27 . However, simulating wing dynamic stall using URANS was found to predict stall early when compared with experiments 27,28 . Furthermore, high-fidelity large-eddy simulations have been applied on pitching finite wings to successfully represent the arch vortex characteristics at transitional Rec 29 , as shown in Fig.…”