2024 Archive

Abstract: Despite the importance of algorithms and computational methods in research engineer (and fluid dynamics in particular), software development is not taught in most engineering disciplines outside EECS, leaving many of us unaware of or unable to use modern programming languages and software development resources. In this session, Jeff and Gabe will give a high-level overview of open-source software development for fluids researchers.

They will first cover why basically everyone should fall in love with the Julia programming language – a modern language that combines the performance of C/Fortran, with the ease of use and community vitality of Python. Next, they will show how GitHub can help with open-source development; from user issues and proposed updates to bots that automatically test code. Finally, since “publish or perish” is still a thing, they will discuss how to support journal publications with GitHub repositories for fully reproducible papers, as well as using the Journal of Open-Source Software for simple stand-alone software publications.

Abstract: Hydrodynamic interactions among swimming or flying organisms can create complex fluid flows on the scale of the group. These emergent fluid dynamics are often more complex than a linear superposition of individual organism flows, particularly at intermediate Reynolds numbers. In this study, we introduce a method to estimate the flow field generated by the wakes of multiple swimmers in close proximity, using a semi-analytical model that conserves mass and momentum. The key equations were derived analytically, while implementation was carried out numerically. Numerical results using the model found that the induced flow at the front of the aggregation was insensitive to the presence of downstream swimmers, with the induced flow tending towards an asymptote beyond a threshold aggregation length. Closer swimmer spacing led to higher induced flow speeds, in some cases leading to model predictions of induced flow exceeding swimmer speeds required to maintain a stable spatial configuration. This model was informed by and compared with empirical measurements of induced vertical migrations of brine shrimp (Artemia salina) using a recently developed laser scanning system capable of capturing time-resolved, three-dimensional spatial configurations. The results demonstrate that the flows generated at the scale of the aggregation arise from a complex yet predictable interaction among the wake structures of individual organisms, their spacing and configuration, and the overall size of the aggregation.

Abstract: The presence of sidewalls in turbulent duct flows adds complexity to their flow physics, which includes the emergence of mean secondary flow structures in the form of counter-rotating vortices near corners (Prandtl's secondary flow of the second kind). Despite being modest in magnitude, these mean structures can be important for capturing turbulence statistics, but  remain elusive to accurately predict with conventional turbulence models. This research develops reduced-order Galerkin projection models that can predict these mean secondary flows in turbulent duct geometries without relying on prior turbulence knowledge. The models use a basis of eigenmodes obtained from the linearized Navier-Stokes equations around a laminar base flow, with a white noise forcing term applied to account for the effect of unresolved dynamics. We demonstrate that a model of this type obtained using only streamwise-constant modes is sufficient for predicting a physically realistic secondary mean. This approach could provide insight into the origins of secondary mean flow structures.

Abstract: In this study, a novel smart surface-morphing technique is devised that dynamically adjusts roughness parameter with varying flow conditions for a sphere. A comprehensive series of experiments are first performed to systematically study the effect of dimple depth ratios between 0 ≤ 𝑘/𝑑 ≤ 2 × 10−2 across a wide Reynolds number range of 6 × 104 ≤ 𝑅𝑒 ≤ 1.3 × 105. It is observed that 𝑘/𝑑 significantly affects both the onset of the drag crisis and the minimum achievable drag. For a constant 𝑅𝑒, drag monotonically reduces as 𝑘/𝑑 increases. However, there is a critical threshold beyond which drag starts to increase. Particle image velocimetry (PIV) reveals a delay in flow separation on the sphere’s surface with increasing 𝑘/𝑑, causing the flow separation angle to shift downstream. This results in a smaller wake size and reduced drag. However, when 𝑘/𝑑 exceeds the critical threshold, flow separation moves upstream, causing an increase in drag. Using the experimental data, a predictive model is developed relating optimal 𝑘/𝑑 to 𝑅𝑒 for minimizing drag. This control model is then implemented to demonstrate closed-loop drag control of a sphere. The results demonstrate up to a 50% reduction in drag compared to a smooth sphere, across all Reynolds numbers tested.

Abstract: Computing reduced-order models using non-intrusive methods is particularly attractive for systems that are simulated using black-box solvers. However, obtaining accurate data-driven models can be challenging, especially if the underlying systems exhibit large-amplitude transient growth. Although these systems may evolve near a low-dimensional subspace that can be easily identified using standard techniques such as Proper Orthogonal Decomposition (POD), computing accurate models often requires projecting the state onto this subspace via a non-orthogonal projection. While appropriate oblique projection operators can be computed using intrusive techniques that leverage the form of the underlying governing equations, purely data-driven methods currently tend to achieve dimensionality reduction via orthogonal projections, and this can lead to models with poor predictive accuracy. We address this issue by introducing a non-intrusive framework designed to simultaneously identify oblique projection operators and reduced-order dynamics.  In particular, given training trajectories and assuming reduced-order dynamics of polynomial form, we fit a reduced-order model by solving an optimization problem over the product manifold of a Grassmann manifold, a Stiefel manifold, and several linear spaces (as many as the tensors that define the low-order dynamics).  Furthermore, we show that the gradient of the cost function with respect to the optimization parameters can be conveniently written in closed form, so that there is no need for automatic differentiation. We compare our formulation with state-of-the-art methods on three examples: a three-dimensional system of ordinary differential equations, the complex Ginzburg-Landau equation, and a two-dimensional lid-driven cavity flow at Reynolds number Re = 8300.

Abstract: We present a numerical study to characterize nonlinear unsteady aeroelastic interactions of two-dimensional flexible wings at high angles of attack. The coupled fluid-flexible wing system is solved by a body-fitted variational aeroelastic solver based on the fully-coupled Navier-Stokes and nonlinear structural equations. Using the coupled fluid-structure analysis, this study is aimed to provide physical insight and correlations for the aeroelastic behavior of flexible wings in the parameter space of the angle of attack and the aeroelastic number. The phase diagrams of the aerodynamic performance are established to obtain the envelope curves of the optimal performance and determine the transition line of the drag variation. The effects of the angle of attack and the aeroelastic number on the aeroelastic behaviors are systematically examined. The time-averaged membrane deformation is positively correlated with a non-dimensional number, the so-called Weber number. A new scaling relation is proposed based on the dynamic equilibrium between the aerodynamic force fluctuation and the combined inertia-elastic fluctuation. The unsteady aerodynamic force can be adjusted by manipulating the membrane vibration, the mass ratio, the Strouhal number and the aeroelastic number. The numerical investigations provide design guidelines and have the potential to enhance the maneuverability and flight agility of micro air vehicles with flexible wing structures. 

Abstract: Cross-flow turbines (CFT), also commonly called vertical axis turbines, comprise an important type of marine energy converter for fast-moving water currents. Distinct from the more common axial flow turbines, their axis of rotation is perpendicular to the freestream velocity. This feature allows for omnidirectional operation and optimization through strategies that alter the blade-level flow dynamics over one turbine cycle. A wealth of research has investigated CFT dynamics using a constant rotation rate to understand performance. Many optimization methods, either through altering the blade rotation rate or modifying the freestream velocity profile around the turbine, change the relative blade velocity at key points in the cycle to improve power generation. Intracycle velocity control is one such strategy that modulates the angular velocity of the turbine as a function of phase. In unconfined or low blockage scenarios, this control changes blade velocity periodically to cause local cyclic flow speed changes around the turbine blades. In previous investigations, the performance of a single turbine undergoing intracycle velocity control has shown improvements to efficiency. This research explores settings for intracycle control that set the nominal tip speed ratio (TSR) to be close to the optimal for a 2-bladed turbine and compares numerical RANS and experimental results. Then, the parameter space is expanded to include above- and below-optimal TSRs to investigate effects of the velocity variation amplitude on power generation. These simulations uncover the changes in blade dynamics due to different cases of intracycle control. Significant findings include showing that shifts in blade relative velocity and timing of vortex shedding, influenced by intracycle control, impact the CFT power and recovery cycles. Additionally, it is found that intracycle velocity control is most beneficial to turbine power generation when operating at lower-than-optimal TSRs. 

Abstract: Oscillating hydrofoil turbines (OFTs) offer a promising alternative for sustainable energy generation, providing benefits such as high efficiency, adaptability to depth, and low environmental impact. While turbine efficiency is known to be heavily influenced by the angle of attack profile, a key question is how different combinations of heave and pitch waveforms, that produce the same angle of attack profile, affect efficiency. To address this, the efficiencies of oscillating turbines with identical angle of attack, but different kinematic profiles are compared. The profiles are generated using either sinusoidal heave with non-sinusoidal pitch, or non-sinusoidal heave with sinusoidal pitch kinematics. Further investigation explores how current trends in prescribed kinematics translate into more feasible semi-passive systems involving fluid-structure interaction (FSI). In semi-passive systems, the heave motion is governed by the dynamics of a spring-generator setup, and the kinematics are optimized through adjustments to structural parameters, such as the frequency ratio (which is equivalent to adjusting the spring constant) and generator damping coefficients. The aim is to understand how these parameters influence the heave waveform, phase difference, and heave amplitude, finally optimizing OFT efficiency. In both investigations, numerical analyses are performed using an in-house advanced boundary element solver with a leading-edge separation model at Re = 10,000.

Abstract: Bats demonstrate some of the most intricate wing movements found in nature, which grant them the agility required to navigate through tight spaces and complex environments. Their wings are constructed from a membrane that is supported by both elastic and inelastic components. These wings undergo deformation due to muscular, inertial, and aerodynamic forces, which play a crucial role in the development of aerodynamic forces throughout the flapping cycle. Our research delves into the aerodynamics of these flexible wings by employing coupled fluid-structure interaction solvers, assimilating wing joint data derived from experimental measurements. To fully comprehend how these complex flapping wings generate lift, it is essential to understand the interplay of vortices, viscous effects, and the kinematics of bat wings. We utilize the force partitioning method (FPM) to dissect the total lift into these distinct contributing mechanisms. By breaking down the lift generation process, our study aims to deepen the understanding of bat flight mechanics. This knowledge is pivotal for inspiring the design and development of advanced biomimetic micro aerial vehicles that mimic the sophisticated flight capabilities of bats.

Abstract: High-resolution, near-ground wind data is critical for improving the accuracy of weather and climate models, supporting wildfire control efforts, and ensuring safe aircraft takeoffs and landings. However, current wind sensing (anemometry) techniques rely on physical installation at specific locations and only provide single-point or line measurements, which limits their ability to offer the global coverage needed. While traditional methods like the Beaufort scale offer qualitative wind estimates based on visual cues like smoke movement and tree sway, their reliance on subjective interpretation hinders precise data collection, limiting their usefulness for robust predictions. I will present a physics-based single-camera visual anemometry method for quantifying wind speeds observed across an entire camera's field of view. This approach leverages the motion of vegetation, like trees and grasses, as natural wind sensors. Previous methods require a reference anemometer on site, but this new physics-based approach eliminates the need for the reference anemometer at wind speeds under 20 meters per second.  We discover the dominant physics driving the observed vegetation fluctuations, which is used to collapse data from vastly different plants onto a single master curve. The resulting wind speed estimates approach the theoretical accuracy limit imposed by atmospheric turbulence. 

Abstract: This work investigates the porosity effect on the wake past a porous plate normal to the flow, being the porosity β defined as the ratio of open to total area of the plate. As porosity increases, it is well known that the wake shifts from the periodic von Kármán shedding behaviour to a regime where this vortex shedding is absent. This impacts the fluid forces acting on the plate, especially the drag, which is significantly lower for a wake without vortex shedding. We now analyse experimentally the transition between these two regimes using hot-wire anemometry, particle-image velocimetry and force measurements. Results show that the wake exhibits the classical Kármán vortex shedding pattern for β<0.2 but this is absent for β<0.3. In the intermediate range,  0.2<β<0.3, there is a transitional regime characterised by intermittent shedding. The flow alternates randomly between a vortex shedding and a non-shedding pattern and the total proportion of time during which vortex shedding is observed decreases with increasing porosity. Reynolds number varied from 10,000 to 70,000, based on the plate width D.

Abstract: Fluid structure interaction is ubiquitous in nature. For example, fish swim and birds fly by making use of an intricately coupled interaction between their body and the surrounding fluid. In addition, the flexibility in their wings and tails aid in maximizing thrust and enhancing propulsive efficiency in birds and fish. Some marine animals, like tadpoles have a circular head that resembles a bluff body. In addition, they have a flexible tail. They move forward by oscillating both their head and tail. In this work, we approximately model the motion of a ‘tethered tadpole’ by studying the flow past a rotationally oscillating cylinder with an attached flexible filament.

The mechanism of unsteady vortex formation and thrust generation in the flow field of an oscillating cylinder-filament system is studied through detailed flow visualization and particle image velocimetry measurements. The streamwise force and power are estimated through control volume analysis, using an improved expression, which considers the streamwise and transverse velocity fluctuations in the wake. These terms become important in a flow field where asymmetric wakes are observed. An attached filament significantly modifies the flow past an oscillating cylinder from a Bénard–Kármán vortex street to a reverse Bénard–Kármán vortex street and subsequently to an asymmetric vortex street, albeit over a certain range of Strouhal number ∼ 0.25–0.5, encountered in nature in flapping flight/fish locomotion and in the flow past pitching airfoils. The transition from a Kármán vortex street to a reverse Kármán vortex street precedes the drag-to-thrust transition. Most of the momentum and energy addition in the flow field happens near the filament tip, which indicates that filament oscillation is responsible for thrust generation. Maximum thrust is generated at the time instants when vortices are shed in the wake from the filament tip.

Abstract: Actively changing the blade pitch angle of a vertical-axis wind turbine throughout the rotor rotation can increase the power production and reduce the structural vibrations, as demonstrated in previous work. Here, we experimentally explore the potential of pitch control to reduce the turbine’s drag, which is related to the wake deficit and recovery. The pitching kinematics are optimized with double objective Bayesian optimization, to reduce the turbine drag while increasing the power production. The optimized pitching yields a reduction of the turbine drag by 68% while maintaining a power production similar to the unactuated case. This decrease of turbine drag reduces the structural loads and improves the floater stability for offshore wind turbines. Wake flow measurements reveal a wake deficit reduction of 73%, as well as a reduction of the wake unsteadiness. The results confirm the potential of blade pitching to improve the wake recovery and generate smoother conditions for downstream turbines in a wind farm.

Abstract: Many previous works have studied fluid-structure interactions induced by thin flexible bodies. In most of these studies the body is nearly inextensible, with a moderate bending modulus. Here we consider softer materials extensible membranes that have zero bending modulus, and undergo significant stretching in a fluid flow that can lead to flutter. We develop a mathematical model and numerical method to study the large-amplitude flutter of rectangular membranes that shed a trailing vortex-sheet wake in a 3D inviscid flow. We consider 12 distinct boundary conditions at the membrane edges and compute the stability thresholds and the subsequent large-amplitude dynamics across the three-parameter space of membrane mass ratio, pretension, and stretching rigidity. We find that 3D dynamics in the 12 cases naturally form four groups based on the conditions at the leading and trailing edges. The conditions at the side edges are generally less important, but may have qualitative effects on the membrane dynamics e.g. steady versus unsteady, periodic versus chaotic, or the variety of spanwise curvature distributions depending on the group and the physical parameter values.

Abstract: In nature, flexible and porous structures are ubiquitous, aiding plants like dandelions in seed dispersion and reducing structural loads on leaves in strong winds. Natural fliers have compliant wings for thrust and maneuverability, while some bird feathers' porosity reduces noise emissions by suppressing coherent vortex shedding. Despite these natural advantages, poro-elastic structures are rarely used in engineered aerodynamic applications due to complex fluid-structure interactions and numerous design parameters involved.

This study explores the effects of poro-elasticity on thin, circular membrane disks by measuring deformation, unsteady flow fields, and drag forces at varying porosity levels in wind tunnel experiments. Our results show that porosity reduces the magnitude of vortex-induced membrane vibrations by stabilizing a large-scale vortex forming in the wake. The highly porous membranes stretch the vortex in the stream-wise direction, reducing the heavy load fluctuations and the high average drag experienced by the non-porous membranes. We present a poro-elastic scaling to model the aerodynamic loads and provide insights into the unsteady vortex shedding at various porosity levels. Finally, we relate our findings to poro-elastic phenomena observed in nature and offer guidance for the design of engineering devices.

Abstract: Autonomous ocean-exploring vehicles have begun to take advantage of onboard sensor measurements of water properties such as salinity and temperature to locate oceanic features in real time. Such targeted sampling strategies enable more rapid study of ocean environments by actively steering towards areas of high scientific value. Inspired by the ability of aquatic animals to navigate via flow sensing, this work investigates hydrodynamic cues for accomplishing targeted sampling using a palm-sized robotic swimmer. As proof of-concept analogy for tracking hydrothermal vent plumes in the ocean, the robot is tasked with locating the center of turbulent jet flows in a 13,000-liter water tank using data from onboard pressure sensors. To learn a navigation strategy, we first implemented Reinforcement Learning (RL) on a simulated version of the robot navigating in proximity to turbulent jets. After training, the RL algorithm discovered an effective strategy for locating the jets by following transverse velocity gradients sensed by pressure sensors located on opposite sides of the robot. When implemented on the physical robot, this gradient following strategy enabled the robot to successfully locate the turbu1ent plumes at more than twice the rate of random searching. Additionally, we found that navigation performance improved as the distance between the pressure sensors increased, which can inform the design of distributed flow sensors in ocean robots. Our results demonstrate the effectiveness and limits of flow-based navigation for autonomously locating hydrodynamic features of interest.

Abstract: Owing to continuously rising marine vessel traffic, shipping lanes around the world have become a prominent source of ocean noise emissions. One of the major sources of marine noise arises from unsteady cavitation around marine propellers. The current work aims to numerically investigate the dynamics of unsteady partial cavitation around rigid and flexible NACA66 hydrofoils. We elucidate the features of sheet-cavitating flow which enable the transition to cloud cavitation, evaluate the instabilities driving sheet-cavity breakdown and identify the vortex structures which drive cloud cavity collapse, and quantify the frequencies observed over the course of a cavitation cycle. For a rigid hydrofoil, our results demonstrate the emergence of a baroclinic torque instability arising at the vapor-liquid interface, which results in sheet cavity collapse and formation of vortex cavities. In a compliant hydrofoil, the deformation induced velocity fluctuations disturb the sheet cavity's formation, resulting in early cavity collapse. This results in significantly altered vortex dynamics as well as far-field pressure fluctuations. 

Abstract: Simulating fluid flows is a computationally demanding task that can be accelerated by modeling the interactions between point vortices. In this work, we model vortical interactions directly from data using graph neural networks (GNNs). We do this by constructing a hierarchy of GNNs to predict the dynamics of vortex clusters simulated using the Biot-Savart law. This hierarchy consists of a GNN that models the local interactions within a cluster and a GNN that models the global interactions between clusters. Additionally, we design the GNNs such that they enforce equivariance to rotations and translations. We show that this equivariant and hierarchical method is more accurate and faster than constructing a fully connected GNN. Furthermore, the method can predict the dynamics of test data containing a different number of vortices and clusters than exists in our training data, which can not be done with other data-driven methods like dense neural networks.

Abstract: The transient flow dynamics in the highly modulated near-wake region of a cantilevered square cylinder of height to width (h/d) ratio 4, protruding a thin laminar boundary layer, at a Reynolds number of 10600 is investigated using a novel 3D flow reconstruction technique. The technique builds on the multi-time-delay estimation technique of Hosseini et al. (2015) by implementing the finite-impulse-response spectral proper orthogonal decomposition (FIR-SPOD) of Sieber et al. (2016), to synchronize uncorrelated planar PIV measurements using surface pressure measurements. The FIR-SPOD successfully separates turbulent spatio-temporal scales within narrow spectral bandwidths, which in turn results in accurately retaining the correct phase relationships between pressure and velocity modes as is required for synchronizing coherent motions along the height of the obstacle. It is shown that the resultant low-dimensional 3D reconstruction of the flow field captures the cycle-to-cycle variations of the dominant vortex shedding process, which give rise to vortex dislocation events. Thus, the present methodology shows promise in 3D reconstruction of challenging turbulent flows, which exhibit non-periodic behavior or contain multi-scale phenomena.

Abstract: The propulsive characteristics of a foil undergoing a prescribed rotational pitch about its quarter cord in a uniform free stream flow of an incompressible Newtonian fluid are investigated numerically over a wide range of Reynolds and Strouhal numbers. At a fixed Reynolds number, the cycle-averaged thrust is shown to rise monotonically with the Strouhal number. Thus, for sufficiently low Strouhal numbers, the foil experiences a net drag while at a critical transition Strouhal number a self-propelling state in which the foil experiences no net force is attained. For Strouhal numbers larger than the critical Strouhal number, the imposed rotational pitch results in a net thrust. The cycle-averaged power coefficient rises sharply with the Strouhal number.  As a consequence, for a given Reynolds number, the propulsive efficiency for thrust generation attains a maximum at a specific Strouhal number. The dependence of the critical parameters namely the drag-to-thrust transition and maximum efficiency Strouhal numbers, and the peak propulsive efficiency on the Reynolds number will be discussed along with the implications of our findings for undulatory locomotion.

Abstract: The dynamics of wing-gust encounters are governed by the triadic interaction of the wing, its shed vorticity, and the ambient gust vorticity in the flow. Thus, the system state during the interaction is inherently tied to the vorticity field, which cannot be measured directly but only estimated through other measurements and the use of a system model. In this work, we make progress in model-based state estimation of unsteady flows by experimentally measuring the surface pressures, loads, and associated velocity fields of wings encountering transverse gusts, and by developing low-order vortex models that can predict these measured quantities. We find that accurate modelling of the Leading-Edge Vortex (LEV) is required to predict the suction side as well as the pressure side surface pressures and that modelling the deformation of the gust is important in predicting pressure during the gust exit. While these observations reinforce the need for global flow estimation, we also show that local surface pressure measurements aided by unsteady airfoil theory can provide useful information about the system state. 

Abstract: There are many examples in fluid dynamics in which we wish to use a limited amount of information about a flow (e.g., from sensors) to infer its larger behavior. Rather than treat this inverse problem deterministically, it is valuable to embrace its uncertainty, e.g., due to noisy sensor measurements, and work in a probabilistic setting. Even if we think we have non-noisy measurements, we can still learn a lot about the estimated flow by treating it in this setting: Is the estimate unique? What information is available (and not available) in the sensors? In this talk, I will review some basic tools from Bayesian inference and sequential estimation, and demonstrate their application in a vortex estimation problem. Since most of the challenge of applying these tools arises from the non-linearity of fluid dynamic problems, I will devote attention to the techniques we use to overcome those challenges.

Biography: Jeff Eldredge is Professor of Mechanical & Aerospace Engineering at the University of California, Los Angeles, where he has served on the faculty since 2003. Prior to this, he received his Ph.D. from Caltech, followed by post-doctoral research at Cambridge University. His research interests lie in computational and theoretical studies of fluid dynamics, including numerical simulation and low-order modeling of unsteady aerodynamics; investigations of aquatic and aerial locomotion in biological and bioinspired systems; and investigations of biomedical and biomedical device flows. He is the author of numerous papers, as well as the book Mathematical Modeling of Unsteady Inviscid Flows. He is a Fellow of the American Physical Society, an Associate Fellow of AIAA, and a recipient of the NSF CAREER award. He has served on the Editorial Board of Physical Review Fluids and as an Associate Editor for the journal Theoretical and Computational Fluid Dynamics.

Abstract: Metachronal motion is the most common and effective form of motion found in crustaceans to increase efficiency. This study examines the flow dynamics linked with krill's metachronal hovering. Krill, consisting of the five legs distributed along its body, can drive itself by properly coordinating their body and legs (pleopods), called metachronal motion. We will discuss the metachronal paddling motion of these legs and its role in producing two major types of forces: Added mass effects resulting from the inertia of the flow and vortex-induced forces generated from vortices. We will examine how the different kinematic parameters of the metachronal hovering mode affect the contribution of these forces and discuss the consequence of the coordinated opening/closure of the legs in shaping the wake and optimal hydrodynamic force generation at different Reynolds numbers.

Abstract: Wave-assisted propulsion (WAP) systems directly convert wave energy into thrust using elastically mounted hydrofoils. The wave conditions as well as the design of the hydrofoil drives the fluid-structure interaction of the hydrofoil and consequently, its performance. We employ simulations using a sharp-interface immersed boundary method to examine the effect of three key parameters on the flow physics, the fluid-structure interaction, as well as thrust performance of these systems - the stiffness of the torsional spring,  the location of the pitch axis and the Strouhal number. We demonstrate the utility of ‘maps’ of energy exchange between the flow and the hydrofoil system, as a way to understand and predict these characteristics. The force-partitioning method (FPM) is used to decompose the pressure forces into interpretable components and to quantify the mechanisms associated with thrust generation. Next, the multifoil system is investigated where the wake of the leading foil is utilized to enhance the thrust of the trailing foils.

Abstract: The successful deployment of oscillating hydrofoil turbine arrays depends on optimizing array configurations. This relies on understanding how the performance of different foils within an array is affected by the vortex-dominated wake behind each hydrofoil. In this work, an array of oscillating hydrofoil turbines in tandem configuration is experimentally studied to determine the optimal kinematics of the array. By characterizing wake-foil interactions between the leading foil-produced wake and the trailing foil, the kinematic configuration each foil in the array must have to maximize array power extraction is determined. This is done by prescribing leading foil kinematics that produce specific wake regimes and evaluating their effect on the performance of the trailing foil subject to different sets kinematics. Performance is evaluated through the power extracted by the foil over an oscillation cycle through force and torque measurements. Wake-foil interactions that lead to improvements in trailing foil performance are analyzed with time-resolved Particle Image Velocimetry. Constructive and destructive wake-foil interactions are compared, and it was determined that trailing foil performance could be improved either by avoiding interactions with wake vortices or by interacting directly with them. Additional insight is gained from applying the Force and Moment Partitioning Method to the experimental data.

Abstract: Turbulent flows are characterized by the dynamic coupling of widespread spatial and temporal scales. Non-intrusive diagnostic techniques such as Particle Image Velocimetry (PIV) can provide correlated spatiotemporal flow measurements but are often limited by temporal resolution. This work introduces a method for recovering spatiotemporal information from limited flow realizations through novel specification of a local convective velocity. Using the least squares minimization of the linear advection equation, the convective velocity of all scales is estimated. The definition is based on time signals and their local spatial derivatives, making it well-suited towards streamwise heterogeneity and spatially developing flows. Using a simplified semi-Lagrangian numerical technique, the convective velocity is used to estimate unknown velocity fields at intermediate times between successive flow measurements. The technique is assessed using three-dimensional direct numerical simulation (DNS) of a planar jet with Re = 10,000. Spectral analysis revealed that the energy content at frequencies several orders of magnitude beyond the Nyquist rate can be recovered. Furthermore, the results indicate that estimations based on local convective velocities are more accurate than those based on the local mean flow, particularly for recovering energy at the characteristic frequency of shear-dominated flows.

Abstract: Fish can significantly improve their swimming performance if their kinematics and paths are adequately adapted to the incoming flow. When the optimum path is unknown, the first step is to predict the performance that could be obtained for several route candidates. Next, we can select the trajectory that increases the lift or efficiency. We develop several force models with Koopman-based system identification tools to predict the CL evolution of a foil executing transitions in its motion inside an unsteady incoming wake. We test the optimum-path selection capabilities by predicting the CL evolution for a set of route candidates, and rank them based on CL production. We find that adding physically relevant information about the wake in the models helps to find the optimum path, achieving a correlation of 90% with numerical target data. Next, we optimize a more general form of the transition trajectory to minimize power consumption using the previously developed force models and evolution algorithms. We conduct CFD simulations and experiments to asses the performance of the optimiser in finding the most efficient transition inside the wake. 

Abstract: Bioinspired by flapping leaves, splitted-plates mounted on the windward side of a cylinder (inverted configuration) are potentially useful for energy harvesting applications. This work demonstrates the flow-induced rotational vibrations (FIRV) of an inverted rigid cylinder-plate, a simplified model of flexible inverted plates. Such a model is computationally less expensive, and we aim to address some open questions regarding the dynamics of such a class of FSI problems. For instance, whether the large amplitude flapping is VIV or flutter. We observe several regimes in the FIRV response: (i) Initial excitation, (ii) Intermediate symmetry-breaking, (iii) First chaotic regime, (iv) Lock-in, (v) Second chaotic regime, (vi) Final symmetry-breaking. We present a quasi-static aeroelasticity approximation-based mathematical model to understand better the dynamic response and the effects of various parameters, such as the mass ratio. We find that the cylinder-plate’s large-amplitude flapping motion is caused due to VIV, not flutter. A quantification of chaos is presented and the vortex-shedding patterns are discussed eventually.

Abstract: Modern small aircraft are asked to operate under severe atmospheric conditions in urban areas and turbulent wakes behind large structures. While understanding interactions between a strong gust and a wing is important, sweeping over the huge parameter space of extreme aerodynamic flows with expensive simulations and experiments is impractical, calling for data-driven approaches. We discuss how such complex aerodynamics under strong vortex gust-airfoil interactions can be analyzed in a low-order manner with nonlinear machine learning. For this study, we consider wakes over a NACA0012 airfoil at Re = 100 covering a range of angles of attack with a strong disturbance modeled by the Taylor vortex, producing a variety of complex wake patterns due to vortex-airfoil interaction. Such unsteady and violent vortical flows over the parameter space are compressed into merely three variables with a lift-augmented nonlinear autoencoder, revealing a low-rank manifold. Furthermore, the discovered manifold captures the fundamental physics of nonlinear interaction under extreme aerodynamics. Towards the end of the talk, we also show that the present approach can be used for real-time sparse sensor-based state estimation and fast control to significantly mitigate the impact of vortex gusts with local actuation.

Abstract: Natural undulatory swimmers are observed to adapt their waveform kinematics when migrating or when swimming against strong currents. To characterise the effects of waveform kinematics on the swimming performance of undulatory swimmers, we designed a bio-inspired anguilliform robot. We measured the robot’s swimming speed, efficiency, in terms of the cost of transport, and body kinematics in free swimming experiments, for a broad range of kinematic parameters, including joint amplitude, body wavelength, and frequency. We find that speed, in terms of stride length, increases for increasing maximum tail angle, described by the newly proposed specific tail amplitude. Maximum stride length is reached for specific tail amplitudes around unity. Minimum cost of transport requires a lower specific tail amplitude and body undulations close to pure travelling waves. Live anguilliform swimmers display a range of specific tail amplitudes that match our robot’s efficient regime, suggesting similar mechanisms of efficient locomotion. The results improve our understanding of anguilliform swimming and provide guidelines for improved design of undulatory swimming robots.