Session A07: Aerodynamics: Airfoil

Data-driven analysis of vortex dynamics around a sinusoidally pitching airfoil

Data-driven methods to analyze fluid flows have been recently gaining popularity in many subdomains of fluid dynamics. This has been primarily driven by our improved ability to generate large, high-quality data sets, and efforts to extract patterns from large amounts of data in an efficient manner. This talk will describe our work to understand the dynamics of aeroelastic flutter from one such data set consisting of over 500 simulations of a sinusoidally pitching airfoil under different conditions. In particular, the focus will be on the analysis of the vortex dynamics close to the surface of the airfoil as well as in the wake, which is instrumental in driving flutter. We describe a novel dynamic mode decomposition (DMD) formulation that allows us to decompose the flow in the vicinity of the moving airfoil and also discuss data-driven clustering methods to identify distinct vortex patterns in this complex flow.    

Fluttering, twisting and orbital motions of wall-mounted flexible plates

The dynamics of wall-mounted flexible plates under inclined flows was studied for a variety of Cauchy numbers using theoretical arguments and laboratory experiments. . Particle tracking velocimetry and a high-resolution force sensor were used to characterize the plate dynamics and aerodynamic force. Results show three distinctive modes of tip oscillations, which are modulated by the structure dynamics and flow instability. The first mode is characterized by small-amplitude motions occurring under a critical Cauchy number. Past this condition, the motions are dominated by unsteady twisting patterns. The onset of this mode is characterized by a sharp increase of the force fluctuation intensity. At sufficiently high Cauchy number and flow inclination, the plate may undergo a third mode dominated by large-scale tip orbits about the mean bending. We propose a formulation to estimate the critical Cauchy number as a function of inclination angle, which agrees well with experiments.   

On the multiscale oscillations of a hinged plate under stratified turbulence

Wind-tunnel experiments were conducted to quantify the unsteady motions of a rigid plate under stratified turbulence containing spatially-varied, energetic vortices. The structure was able to oscillate around a vertical axis located at a quarter chord length from the leading edge. Vertically-oriented, von-Karman vortices that varied in frequency and strength along the vertical span of the plate were imposed using a variety of tapered cylinders. Telemetry and hotwire anemometry were used to characterize the motions of the plate, and wake at selected locations. Results show that the plate oscillation is dominated by two distinct modes. One of them, f\textunderscore p, corresponds to the mean flow-induced oscillation frequency; whereas the other, f\textunderscore v, is related to the vortex shedding cells from the non-uniform cylinders. These frequencies exhibited distinct trends with the distance from the cylinders, and the distribution of the coherent motions, which were determined by the tapered ratio of the cylinders. A simple model is proposed to estimate f\textunderscore v.   

Flutter-Enhanced Mixing: Flow-Induced Flutter of Flexible Membranes in Small Scale Mixers

Flow-induced flutter of flexible membranes in small scale mixers is explored. Fully-coupled fluid-structure-scalar interaction (FSI) simulations are used to examine the mixing enhancement in duct-style small scale mixers due to fluttering flags and the sensitivity of the dynamics and the mixing performance to Reynolds number is examined. The fluid and structural dynamics are explored and the resultant mixing enhancement is characterized according to existing performance measures as well as two new analysis techniques. A new performance measure called the Equivalent Mixing Length is developed to examine the connection between increased mixing performance and the corresponding increase in pressure loss which can serve as a measure of performance efficiency of flutter mixers or of any micromixer design. Additionally, a technique is developed to extract an estimate of the interface path length in the flow so as to characterize the impact of increased convection due to the presence of the flutter mixer. Through these measures it is shown that flutter mixers can significantly improve the mixing performance of a small scale mixer over a very short duct length by way of generating vortical structures even at low Reynolds numbers which leads to complex stretching and folding of the interface in the mixer.   

Nonlinear Stability Characteristics of an Elastically Mounted Pitching Wing

We study the nonlinear stability boundaries of an elastically mounted pitching wing in a water flume, with the wing structural dynamics (inertia $I$, stiffness $k$, damping $b$) simulated using a cyber-physical system. We fix $b$ to be small and systematically vary $k$ at different $I$ to test for the onset and extinction of self-sustained oscillations. We find that when $I$ is large, the system bifurcates from a fixed point to small-amplitude oscillations followed by large-amplitude limit cycle oscillations via a subcritical bifurcation, which features hysteretic bistability and an abrupt amplitude jump at the bifurcation. At this $I$, the wing pitching frequency $f_p$ locks onto its structural frequency $f_s$, indicating dominating structural force. Force and PIV measurements reveal the emergence of a secondary leading edge vortex (LEV) after the shedding of the primary LEV. As $I$ decreases, the width of the bistability region shrinks. When $I$ is sufficiently low, the pitching amplitude changes gradually with $k$ without hysteresis, revealing a supercritical bifurcation. At this $I$, $f_p$ is relatively constant and lower than $f_s$, indicating dominating fluid force. The secondary LEV is not present. We also report the effect of sweep angles on the stability boundaries.   

Periodic Loading of a Mach 4 Boundary Layer over a Compliant Surface by an Oscillating Shock Generator

A significant challenge in designing hypersonic vehicles is developing predictive models for aerodynamic loads associated with turbulent boundary layers and shock boundary layer interactions on compliant surfaces. Shock-boundary layer interactions on high-speed vehicles can lead to pressure fluctuations which can couple to structural modes and lead to premature high-cycle fatigue and ultimately component failure. In collaboration with simulations, experimental studies can give insight into the degree of fluid-structure coupling under prescribed load conditions. In this presentation, the flow response over a 0.2 mm thick compliant steel panel under dynamic loading from an oscillating shock generator is investigated in the Caltech Mach 4 Ludwieg tube. Euler simulations were performed to design the geometry and location of the shock generator, predict the amplitude of the oscillation required to drive the pressure wave across the compliant surface, and to calculate the pressure rise on the compliant surface. The flow response is characterized using fast-acting pressure transducers, high-speed schlieren images, and porous fast-response pressure sensitive paint and the panel response using laser doppler vibrometry.   

Anemometry from visual observations of fluid structure interactions

Visual observations of objects interacting with the wind contain information about local wind conditions such as wind speed. These visual encodings can potentially be leveraged to measure wind speeds using videos of pre-existing objects in an environment (e.g. flapping flags or swaying trees). We propose a data driven approach that leverages deep learning methods to predict wind speeds given video recordings of fluid structure interactions. Video clips of flags and trees moving due to naturally occurring wind are used to estimate wind speeds through the application of a convolutional neural network followed by a recurrent neural network. Physical parameters of the observed objects are used to aid in understanding limitations of model performance.