Experimental investigation on the unsteady surface pressure fluctuation patterns over an airfoil

Abstract

This article presents a comprehensive mapping of wall pressure fluctuations over an airfoil under three different inflow conditions to shed light on some basic assumptions taken granted for the recent aeroacoustic and aerodynamics experimental studies and in the noise prediction models. Unsteady and steady pressure measurements were performed over a heavily instrumented airfoil which was exposed to smooth inflow, grid generated turbulent inflow, and a smooth inflow with a tripping tape over the airfoil to explore the unsteady response of the airfoil for a broad range of angles of attack, 0◦ {less than or equal to} ᵯC; {less than or equal to} 20◦. The results are presented in terms of non-dimensional pressure coefficient, root mean square non-dimensional pressure coefficient, frequency-energy content pattern map at isolated frequencies for the entire airfoil,and spectra of frequency-energy content at selected transducer locations. The results show that the unsteady airfoil response patterns for the tripped boundary layer and turbulence ingestion cases show a dramatic difference compared to the airfoil response patterns of the smooth inflow conditions. The response patterns differ across angles of attack, frequency, and between both sides of the airfoil. The results suggest a three region pattern for smooth inflow case, a two region pattern for tripped boundary layer case, and a two region pattern for the turbulence ingestion case. Moreover, the results indicate that the presence of tripping may provide a flow with necessary statistical characteristics for the experimental rigs representing the full-scale application; however, it may misrepresent the frequency-dependent nature of the boundary layer.

Wind Tunnel Bench Test of a Pitch-and-Plunge Aeroelastic Model Undergoing Nonlinear Post-Flutter Oscillations

“…The associated pressure fluctuations create aerodynamic imbalances around the structure and lead to additional pitching moments of aerodynamic nature. The interaction with inertial and elastic moments promotes the onset of stall-induced structural oscillations [12][13][14]. The manifestation of such oscillations is experimentally and numerically addressed in recent studies.…”

The role of porous structure on airfoil turbulence interaction noise reduction

“…The effect of the angle of attack on the turbulence interaction noise has previously been shown to be insignificant, 2 yet there is a profound change in the airfoil response function, which does not have a dramatic effect on noise generation. 3 Furthermore, Celik et al 4,5 demonstrated that the lack of sensitivity to the angle of attack extends to the lift and drag spectra too. Airfoil geometry studies in the context of turbulence interaction noise indicate that airfoil thickness and camber play important roles in noise generation.…”

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

“…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].…”

“…For instance, pressure distribution data is crucial for aerodynamic design optimization [19] and many surrogate models have recently been developed to reduce the computational time involved in predicting aerodynamic forces during the design process [20,21,22,23]. In the context of unsteady aerodynamics, pressure distribution data are used to provide insights on the turbulent structures responsible for the far-field noise generated by unsteady airfoils [4,24,5] and also to estimate the instant at which the flow separates near the leading edge [25,26,27]. This is particularly useful for developing control strategies for dynamic stall [28,29].…”