Analysis of the onset and evolution of a dynamic stall vortex on a periodic plunging aerofoil

Abstract

The onset and evolution of the dynamic stall vortex (DSV) are analysed by means of large eddy simulations of an SD7003 aerofoil undergoing periodic plunging motion in a transitional Reynolds number flow ( $Re =6\times 10^{4}$ ). Interactions between upstream propagating Kelvin–Helmholtz instabilities and a shear layer formed at the leading edge trigger flow separation. The former appear to be related to acoustic waves scattered at the trailing edge due to initial vortex shedding. Two freestream Mach numbers ( $M_{\infty }=0.1$ and $0.4$ ) are employed to examine the flow differences due to compressibility variations. The existence of a common timing for the acoustic perturbations in both flows suggests a possible Mach number invariance for the birth of the Kelvin–Helmholtz instability. Increasing compressibility, however, induces earlier spanwise fluctuations, higher flow three-dimensionality and a weaker and more diffuse DSV, which is formed further downstream of the leading edge and has lower residency time. In order to better characterize the onset of the DSV, two empirical criteria are assessed: the leading edge suction parameter and the chord-normal shear layer height. Results demonstrate a higher robustness of the latter with respect to Mach number variations. Modal decomposition, performed with both the classical dynamic mode decomposition (DMD) and its multi-resolution variant (mrDMD), highlights key trends and demonstrates the capacity of the mrDMD to extract physically meaningful flow structures related to the stall onset. Such detailed characterization of the shear layer can be used for a systematic exploration of flow control strategies for unsteady aerofoils.

Flow imaging as an alternative to pressure transducers through vision transformers and convolutional neural networks

“…The starting point of the method is the input images of flowfields obtained from numerical simulations or experiments, such as those from a 2D cross section. The images are obtained from the high-fidelity simulations of Miotto et al [1,2] in terms of spanwise-averaged flowfields. In these references, the authors were interested in understanding the mechanisms of dynamic stall onset and the conditions for pitch and plunge equivalence to occur.…”

“…These images consider all simulations of dynamic stall cases reported in Refs. [2,1], which include a periodic plunging airfoil and constant ramp pitching and plunging airfoils for Mach numbers 0.1 and 0.4. When generating these images, it is important to keep Data augmentation is used to artificially increase the size of the training set.…”

“…Pressure is a thermodynamic property that plays a key role in fluid mechanics. It is of utmost importance in aerodynamic load prediction [1,2,3], noise generation [4,5], flow instability and turbulence [6,7,8], and flow control [9]. The increase of time resolution in velocity field measurements during the last decade has opened the path to obtaining instantaneous pressure fields by combining experimental data with the flow governing equations [10,11].…”

“…Despite that, the concepts applied herein can be easily extended to other branches of fluid mechanics where a regression task is involved. To this end, we chose CNNs and vision transformers (ViTs) to study the flowfields from our high-fidelity numerical simulations of dynamic stall [1,2] due to their fewer connections and parameters [33,34]. Here, we aim at reusing or transferring information from previously learned tasks to extract quantitative information from available flow visualizations.…”

Switch of tonal noise generation mechanisms in airfoil transitional flows

“…Therefore, they are nondimensionalized by freestream velocity as t = t * U * ∞ /L * and St = f * L * /U * ∞ , respectively. The present numerical tool has been validated for several simulations of compressible flows around turbine blades and airfoils [16,[33][34][35][36][37].…”