This thesis project examines the drag crisis trigger mechanism for double layer fabrics on cylindrical cross-flow. The primary goal is to discover why the double layer fabric is able to trigger the drag crisis much sooner than conventional surface roughness.

The methodology employed in this research follows an experimental approach, using balance measurements to determine the aerodynamic drag at varying Reynolds numbers for different configurations. Particle Image Velocimetry (PIV) measurements are performed to examine the boundary layer, flow separation point and other flow phenomena occurring near the cylinder surface.

Over the course of this research, eight different double layer configurations have been the subject of study, as well as six single fabric configurations and two reference configurations consisting of a bare cylinder and a cylinder with zigzag trips. Balance measurements have been performed on all of the configurations to determine which configurations are deemed relevant to be studied with PIV techniques. Thus, PIV measurements have been performed on two double layer configurations with a varying underlayer and the same overlayer, as well as the study of the individual fabrics employed to make up the two-fabric construction. That is to say, the two underlayers and one overlayer used have been studied on their own.

The balance results uncover that the minimum drag coefficient across all double layer configurations is achieved with the smallest rib spacing. Conversely, this minimum drag coefficient is located at the highest critical Reynolds number across all configurations. Additionally, a relationship between the critical Reynolds number and the underlayer rib spacing has been determined for the studied configurations. Furthermore, the PIV measurements provide insight into the normalized velocity fields and reconstructed pressure fields. With these results, the development of the boundary layer on the foreside of the cylinder with double layer fabrics can be studied. Examining the flow near the surface, it can be seen that the presence of the ribs results in a localized flow convergence (upstream of the rib) and divergence (downstream of the rib), these geometric effects accelerate and decelerate the flow locally, causing static pressure oscillations on the foreside of the cylinder. With the appearance of localized adverse pressure gradients on the foreside of the cylinder, flow instabilities are seeded eventually trigger the transition of the boundary layer to a turbulent state, thus allowing the flow to remain attached to the cylinder surface for longer, ultimately delaying separation and reducing pressure drag.

While the study has provided valuable insights regarding the trigger mechanism for the drag crisis on double layer fabrics on cylinders, it has also paved the way for further research regarding this topic and the specific effects of rib height, behavior and performance in unsteady flows and whether the two fabric construction is strictly necessary. These considerations are addressed at the end of the conclusions chapter.

Static pressure is a scalar magnitude that expresses the force per unit area exerted by a fluid at rest. As such, it constitutes one of the two mechanisms through which fluid flows generate forces on bodies. Moreover, static pressure is not only relevant in the definition of surface loads, as it plays a key role in a number of fields, such as turbulence research due to its impact on the amplification or damping of turbulent flow instabilities, or medical research, provided its key paper on cardiovascular disease.

Accordingly, different approaches exist that allow to obtain pressure information in Fluid Dynamics applications. Among these, simplified analytical models, Computational Fluid Dynamics and experimental measurements stand out given their extensive use. While each of these comes with its own advantages and limitations, the latter typically offers the advantage of being conducted with real flows, hence providing a reliable source of information if proper similarity parameters and set-up are achieved.

While there exist different techniques to measure pressure experimentally, among which pressure tapping and pressure sensitive paint stand out, these present major limitations, such as the limited spatial resolution that can be achieved without intrusion effects or the challenges encountered during calibration, respectively. Consequently, more recent methods have been developed that allow to reconstruct pressure from velocity fields obtained via Particle Image Velocimetry. An instance of such algorithms is the Poisson Solver, which is based on the application of the incompressible relation to the momentum conservation equations, yielding a boundary-value problem for pressure. Nonetheless, while this approach benefits from the instantaneous and simultaneous nature of PIV measurements, it presents its own challenges, among which the propagation of noise from the velocity field into the reconstructed pressure field stands out.

More recently, with the proliferation of Machine Learning, the number of applications in Fluid Mechanics has grown. In particular, an approach that stands out are Physics-Informed Neural Networks, which optimize Deep NN models minimizing a loss function with contributions from labeled flow data variables and residuals from physical equations, thus learning the flow field variables. While diverse use cases have been reported for PINNs, such as the generation of reduced order models or the direct simulation of flows, especial emphasis has been placed in research on their ability to infer unsteady or mean pressure fields from velocity measurements, via the application of the Navier-Stokes equations.

Even if research has shown PINNs offer key advantages with respect to traditional pressure reconstruction methods, such as robustness to Gaussian noise or lack of discretization errors, analysis of the research available highlights key areas that require further exploration in the establishment of PINNs as a reliable alternative to traditional methods. Specifically, the study of PINNs performance with real experimental data and its comparison with solvers as the Poisson against direct experimental measurements is of paramount relevance, provided that the vast majority of publications concern the use of artificial experimental data from CFD simulations.

In accordance, a PINN framework has been developed and its accuracy in the reconstruction of surface pressure has been tested using time-averaged data from both CFD simulations and experimental tests of the two-dimensional flow around a cylinder. Particularly, comparison of the PINNs and the Poisson surface pressure reconstructions with pressure tap data showed superior performance of the former, with respective MSE reductions of -1% and -21% for the flows around a smooth cylinder and one fitted with zig-zag strips at θ = ±45 º.

Additionally, sensitivity studies to understand the effect of various parameters in the PINN training process has resulted in the identification of various trends. Among these, especial attention is required by the ability of PINNs to add regularization in areas affected by correlated noise such as reflections via the addition of collocation points, where the PDE loss is evaluated. Further noteworthy findings concern the benefit of using physical boundary conditions at solid surfaces in the form of the no-slip, no-penetration and no-fluctuations constraints. In this study, it has been proven that these allow not only to bypass non-physical pressure fluctuations that derive from spatially-correlated noise, but also to reduce surface pressure reconstruction error when data gaps exist close to the surface, achieving reductions of up to -92% for a radial data gap of 75% of the cylinder radius from the cylinder surface. Finally, it has been shown that, provided that the dataset contains points that allow to define a reference pressure value, the provision of sparse pressure tap data to the NN during training results in local, rather than generalized, error reductions.

In conclusion, the sensitivity studies carried out on the smooth cylinder dataset have resulted in pressure MSE reductions as substantial as -50\% with respect to the Poisson solver when both are compared with static pressure tap data, supporting the establishment of PINNs as an alternative method to conventional pressure reconstruction algorithms as the Poisson solver, despite the time penalty that these can represent given the instantaneous nature of the latter. On the qualitative side, it has been proven that PINNs can provide a flexible framework to embed prior knowledge of the solution, such as the positive nature of normal Reynolds Stress components or boundary conditions. Along the same lines, it is shown throughout the thesis how PINNs can be used to perform debugging steps that allow to identify sources of error.

The development of offshore wind farms has demonstrated significant value in harnessing renewable energy sources. However, the offshore wind energy sector faces increasing challenges, making the realization of new wind farms a greater financial risk. This has reached the point where several high-profile offshore wind projects have been halted. A key contributor to these struggles is the aerodynamic effect of wind farm wake losses. As wind turbine sizes increase, costs rise, but the wind farm concept limits energy yield. This is due to slow wake recovery behind turbines, causing downstream turbines to only be able to harvest energy from low-momentum flow. Based on the literature review conducted, the methods to improve wind farm efficiency by reducing wake losses, such as wind farm layout optimization and rotor yawing or tilting, only partially address the problem.

The concept of regenerative wind farming, proposed by Ferreira, seeks to provide a solution. This involves integrating lifting devices into wind energy harvesting systems that can redirect the wake vertically, enabling the flow from higher atmospheric layers to contribute more to the wake recovery process. Such interactions can dramatically enhance the energy that is replenished into the wind farm, offering a promising approach to overcoming these challenges.

This research aims to evaluate the potential of the novel wind farm concept, regenerative wind farm, through a scaled wind farm experiment. In the scaled wind farm, there are nine wind energy harvesting systems, which are aerodynamically modeled by using porous disks and wings. The study focuses on the far wake and the performance of downstream turbines. The experiment was conducted in the Open Jet Facility (OJF) at TU Delft. The flow field was measured using Particle Tracking Velocimetry (PTV) with Helium-Filled Soap Bubbles (HFSB), and load measurements were accompanied.

Load measurements revealed that thrust values for downstream turbines increased by more than three times when lifting devices were attached to the actuator surfaces. Also, flow field data showed significantly higher wake velocities, as potent vertical flows in the wake regions were induced by the tip-vortices of the wings, which enhanced vertical energy entrainment. This vertical motion actively entrains the flow above the wind farm, allowing high-momentum air to enter the wind farm layer, something that does not occur without the wings. Additionally, the lifting devices reduce turbulence intensity in the rotor projection area at the downstream end of the wind farm, helping to lower the fatigue loading of downstream systems. An investigation of a misaligned row confirmed that the concept remains effective even under such conditions.

This work demonstrates that the regenerative wind farm concept holds great potential to enhance wind farm power output while reducing the required wind farm area. With this concept, wind turbine wake losses are effectively mitigated by entraining high-momentum flow into the wind farm.

This thesis presents an innovative approach to investigating automotive underbody aerodynamics through the development and application of an on-site 3D Lagrangian Particle Tracking (LPT) system. Automotive performance, particularly in high-speed racing applications, is significantly influenced by the aerodynamic efficiency of vehicle diffusers. The work addresses the challenges associated with accurately capturing complex three dimensional flow structures beneath a moving vehicle, where traditional flow measurement techniques struggle to capture underbody flows, especially in an experimental setting.

The research builds upon a previous study on a diffuser equipped radio-controlled car, which uses a measurement technique known as the Ring of Fire. By improving the camera setup, as well as creating better seeding and illumination, the setup allowed for successful particle tracking of neutrally buoyant Helium Filled Soap Bubbles underneath a car model, driving at around 7.5 m/s. The particle tracks captured in a measurement domain the size of (300 x 150 x 200) mm3 allow for the reconstruction of a velocity field around three tested car geometries, by combining data from multiple runs of the car driving through the measurement domain. These geometries are a flat floor car model, a car model fitted with a 15◦ planar diffuser, and a car model with the same diffuser, but also an additional strip of vortex generator fins placed ahead of the diffuser leading edge.

Using a pressure gradient integration method, a pressure field around the car models was obtained. Looking at both the velocity and pressure distribution around the models, the setup was able to capture the difference in peak velocity underneath the car, where the diffuser equipped model showed a maximum velocity of around 1.4 times the freestream velocity. Velocity and pressure coefficient profiles measured along the car’s centerline closely match those reported in the literature, confirming that the diffuser primarily impacts the rear region of the vehicle.

Streamwise vortices introduced into the diffuser by the vortex generator strip showed to be primarily moving high momentum flow closer to the diffuser surface, while potentially resolving a laminar separation bubble near the diffuser leading edge, observed for the plain diffuser case. Difference in local velocity magnitude and pressure coefficient measured at the diffuser leading edge between the flat floor and diffuser equipped models proved to be large enough to be statistically significant. An estimated 25 runs was needed to reach a velocity convergence inside the diffuser within 1% of the mean car velocity, where only 4 or 5 runs would be enough for the flat floor regions upstream of the diffuser.

This work shows the improvement made to the Ring of Fire setup developed to measure on-site automotive underbody aerodynamics. It proves the capabilities of applying 3D LPT to quantify underbody flows, and the potential to apply this setup on larger and faster vehicles.

Aerodynamic drag plays a critical role in high-speed sports, including running, where small performance margins can be decisive for victory in elite competitions. Despite its importance, research on running aerodynamics remains underexplored, with most studies relying on stationary mannequins or simulations that do not capture the dynamic behavior of flow around a moving runner. In other words, there is a significant research gap in experimentally visualizing the wake flow and accurately measuring the drag in real-world running scenarios. This study aims to address this research gap.

In recent years, the Ring of Fire measurement technique has emerged as a feasible option to visualise and analyse flow structures of transiting objects based on particle image velocimetry.
The technique has already been proven in sports like cycling and ice skating, but has not yet been applied to running. This study adapts the Ring of Fire measurement method for sprinting athletes, and the raw images are processed by Shake-the-Box (STB) Lagrangian Particle Tracking. This results in a three-dimensional, time-resolved velocity field in the wake of a runner with an uncertainty of less than 5\% of the runner's speed. This velocity field is used for qualitative flow visualisations, as well as for drag estimations, which are computed from a control volume approach by utilising the flow field before and after the passage of the athlete.

The experimental methodology involved nine junior athletes, wearing both standard sprint suits and aerodynamic suits, sprinting at constant speeds through a measurement setup including three high speed cameras, four LED arrays and Helium Filled Soap Bubbles (HFSB).

The results of the investigation include the visualisation of the full wake,
quantification of the velocity deficit, a qualitative vorticity analysis, some lateral velocity findings and the measured values for drag of one of the athletes.

There are multiple interesting findings about the flow around a dynamic runner in this report. One of them is the splitting of the wake into two side-by-side stream tubes in the far wake. The velocity deficit in a relevant region of the dynamic wake has also been quantified, and it is shown to vary with the inverse of the distance behind the runner, which is useful information for trailing runners.
Another interesting observation is that the vorticity field in the near wake generally follows the rules of finite cylinder flow, where the body parts of the athlete are finite cylinders with variable diameter.
The hypothesis that the flow should have a lateral oscillation related to the frequency of the runner's steps has also been confirmed.

This study demonstrates the applicability of the Ring of Fire system to running aerodynamics and offers the full visualisation of the three dimensional flow in the wake of a moving runner, bridging the research gap to pave the way for further advancements in the field.

Understanding atmospheric motion is crucial for analyzing wind-structure interactions, particularly within the Atmospheric Boundary Layer (ABL). Traditionally, wind tunnels have simulated unsteady ABL conditions using active and passive devices. Recently, multi-fan wind generators have emerged as a flexible, cost-effective alternative, allowing independent fan control to replicate wind conditions the wind turbines, airborne devices or civil structures are subjected to.

This thesis investigates the capability of a newly manufactured 3 x 3 multi-fan wind generator to produce idealized uniform flow, linear shear flow profiles, and streamwise sinusoidal gusts. The system consists of off-the-shelf computer fans, controlled via open-source software, offering a low-cost and adaptable approach. Particle Image Velocimetry (PIV) measurements show a 96% uniform core region with 11.5% turbulence intensity 1 m downstream from the system. There, the area of the core is reduced to 1/9 of the system’s area due to the outer shear layer. The system struggles to replicate linear wind shear, but can generate oscillatory gusts at 0.2 Hz, 0.4 Hz and 0.8 Hz, corresponding to the operating frequency of the fans. Further improvements should focus on extending the configuration to maintain a larger core region, and on reducing swirl dynamics and recirculation to enhance flow quality for wind engineering applications.

This thesis proposes techniques to produce wall-shear stress estimates from three-dimensional Lagrangian particle tracking (LPT). Several works have already faced the problem of determining near-wall velocity and in particular skin friction for the case of a flat surface. Here, the problem is translated to generic three-dimensional objects. The work makes use of an experimental database, recently produced, with LPT (Hendriksen et al. 2024), that provides in-situ registration of the object, for three shapes of increasing complexity: a cube, an airfoil and a cyclist. Four techniques are examined and compared, including interpolation method as well as local data regression. The uncertainty is evaluated a-posteriori, comparing the results with a local coin-stacking technique, where applicable. All techniques yield accurate and robust representations of the skin friction lines around three-dimensional objects, allowing for an insightful inspection of the near-surface flow topology. Instead, distinct differences are found when the skin-friction magnitude is estimated.

This report presents the preliminary design process of an aerial drone aimed at exploring the surface of Mars. The aim of this project is to help determine whether the Red Planet ever hosted alien life. Building on recent breakthroughs in the field, the team set out to develop a drone that can sustain 30 minutes of continuous flight, travel up to 20 kilometres, and identify, collect and transport 3 kilograms of rocks to a Martian ground station. The design process involved planning and integration of various subsystems, including propulsion, structural, electrical and payload systems, all tailored to overcome the unique challenges posed by Mars’ environment. This document provides a thorough overview of the design methodology, subsystem integration and performance analysis, underscoring key design decisions and providing recommendations for future development and optimisation of the drone.

Laser light reflection mitigation in Particle Image Velocimetry (PIV) is crucial for accurate flow
field measurements. While numerous methods exist for planar PIV, fewer have been developed for volumetric PIV systems, especially for coaxial setups like Robotic PIV. Light reflections in volumetric PIV experiments result in high-intensity regions that corrupt particle detection and analysis.

This study presents three novel approaches for treating light reflections in Robotic PIV experiments. The first and second methods use image filtering and masking techniques in the
wavenumber space to separate particle images from reflection regions. The first technique called Spatial Fourier Filter involves decomposing the image signal into low- and high-wavenumber components using the 2D discrete Fourier transform (DFT). A high-pass filter is then applied to attenuate the intensity of reflection regions. Then, the second methodology Spatial Fourier Filter + Mask takes the resulting image from the first method and performs a step of automated adaptive masking to remove residual reflection areas that the filtering approach is not able to eliminate. The third methodology named 3D-based Particle Concentration Mask acts in a later stage of the processing pipeline, creating a 3D mask on the instantaneous processed Shake-the-Box data by analysing the particle concentration distribution over the flow domain.

The proposed methods are tested on experimental data obtained from experiments performed with Robotic PIV on three different geometries: a side-view mirror, Formula 1 car and a propeller. The tests were conducted at one of TU Delft Aerospace Engineering Faculty’s facilities, the W-tunnel in the High-Speed Laboratory (HSL). Comparison between raw and pre-processed images, as well as particle tracking results, is presented.

The results from this data comparison show unsatisfactory outcomes from both Spatial
Fourier Filter and 3D-based Particle Concentration Mask, which fail to fully remove the spurious regions. Nevertheless, the results confirm the successful removal of reflection-induced artifacts in instantaneous images by using the spatial Fourier filter automated masking approach. The developed image pre-processing strategy effectively removes reflection regions in Robotic PIV images, preventing the appearance of spurious particle tracks. The method shows promising results mitigating unsteady light reflections in Robotic PIV, improving the accuracy of flow field measurements. Additional attention is required in the PIV sequence creation step to ensure an adequate level of overlap between measurement volumes. This facilitates addressing the spatial gaps introduced by the masking procedure, that have been proven to robustly be filled in by the multi-view advantage offered by Robotic PIV.

Race cars use aerodynamic downforce to reduce the lap times by increasing grip. Diffusers, upswept ramps located at the rear of a vehicle, are often used to enhance downforce. This investigation proposes a novel LPT facility featuring HFSB, LED illumination, and high-speed cameras to characterize the flow inside automotive diffusers. An RC car, fitted with a custom floor and diffuser, traverses a region of seeded air following the Ring of Fire methodology. Underground cameras view the car through a transparent panel, providing unparalleled optical access to the diffuser of the car. The on-site construction of the setup and the intrinsically realistic interaction with the ground, contribute to realism and fidelity while potentially reducing testing costs associated with wind tunnel operation. The setup was shown to be a valid alternative to conventional testing grounds to capture separation, 3D flow evolution and differences in the flow field between the diffusers with varying angles. The 15° diffuser led to the largest velocity (u/U=1.3) under the car, the 10° diffuser produced the most downforce overall while the 20° diffuser showcased the most prominent separation, heavily affecting its ability to sustain low pressures under the car. The results highlighted the impact of the tyres in disrupting the mechanism of downforce generation through mass flow leakage through the sides of the car.

With the increased use of Advanced Driver Assistance Systems (ADAS) in modern cars, the  field of surface contamination saw a resurgence. To keep the various sensors working properly it is of utmost importance to keep them clean and free of contamination. One way to achieve this is to ensure they are mounted in areas where they can be kept free of water droplets that can cause issues themselves, or by depositing contaminants that they are carrying. Current research focuses on the resulting contami- nation pattern after a drive or test on the car, this thesis however aims to see whether state-of-the-art Particle Image Velocimetry (PIV) techniques can be used to track the water droplets themselves, and with it open up new ways of researching surface contamination. To achieve this two experiments were performed. The first one was a simple experiment to see whether the droplets are being able to be imaged with the PIV cameras. The second experiment introduced a car side mirror model to the flow and used the Shake-the-Box (STB) algorithm to track the individual water droplets. Both of these ex-periments were successful, and showed that this combination of water droplets and STB PIV has great potential for being used in surface contamination research. The main issues found were with experi-mental setups, especially in the windtunnel. As the droplets do not follow the airflow accurately, extra care needs to be taken to ensure the droplets are operating at the right conditions, and are present at the measurement domain. The actual behaviour of the droplets as tracked by the STB algorithm, seems to be accurate with respect to the expectations indicating that the tracking of the droplets is accurate. Further research should try to increase the scale of the experiments, and/or introduce contaminants to the droplets to see how, if at all, this affects the traceability of the droplets.

In response to the urgent need for renewable energy amidst the escalating impacts of global warming, this study delves into the forefront of wind energy research, particularly focusing on the innovative Multi-Rotor System (MRS). The MRS concept offers a promising departure from the prevailing trend of scaling up traditional turbines, instead proposing a configuration comprising multiple smaller rotors mounted on a single support frame. This approach, identified for its inherent upscaling advantages, presents an opportunity to reduce costs and weight relative to conventional Horizontal Axis Wind Turbines (HAWTs). While the concept is not entirely novel, its application with Vertical Axis Wind Turbines (VAWTs) is. Recent studies have demonstrated the significant potential of the VAWT-based MRS, showcasing comparable power performance to large HAWTs while enhancing Operations and Maintenance (O&M) aspects. Furthermore, the adaptable support frames of the MRS facilitate the integration of wake control devices, such as external lift-generating wings, which introduce cross-flow loading to rapidly re-energize the wake. However, despite these advancements, understanding the wake dynamics within MRS systems, particularly concerning their implications for wind farm applications, remains limited.

The current work aims to investigate the intricate near-wake dynamics of the VAWT-based MRS and study the effects of external lift-generating wings on the deflection and recovery of the wake. To do so, a scaled wind tunnel model of such a VAWT-based system has been designed together with a set of removable high-lift wings. These, in turn, have been tested in the Open Jet Facility of the Delft University of Technology to gather insight into the behaviour of the near-wake. Tomographic Particle Image Velocimetry using Helium Filled Soap Bubbles has been deployed in combination with load measurements to gather data.

Load measurements revealed that the thrust coefficient behaviour of the MRS closely resembles that of single-rotor VAWTs, with an additional thrust induced when the external lift-generating devices are present, attributed to accelerated flow on the suction side of the wings. Furthermore, the PTV measurements have provided a detailed visualization of the near-wake, showcasing symmetric wake structures and lateral deflection induced by the presence of individual rotors. The introduction of external lift-generating wings significantly altered wake behaviour, inducing lateral contraction and promoting streamwise momentum recovery through enhanced vertical advection. Furthermore, analysis of velocity deficit recovery highlighted substantial improvements in power recovery behind the MRS with external wings.

The findings presented in this work underscore the potential of the VAWT-based MRS, particularly when such a system is equipped with lift-generating devices. The presence of such devices effectively manipulates the near-wake of the turbine, enhancing wind farm efficiency, and thereby advancing innovative wind energy solutions.

This thesis investigates the aerodynamics of two finite wall-mounted cylinders in tandem, focusing on drag reduction as a function of governing parameters.
For the experimental wind tunnel campaign, two measurement techniques were employed: balance measurements and stereoscopic particle image velocimetry. While balance measurements exhibited good repeatability, drag values obtained with PIV saw high uncertainty and only limited conclusions could be made from it.

Cylinders were mounted to the floor of a closed wind tunnel test section. The trailing cylinder was rigidly attached to the balance underneath, while the leading cylinder could move upstream to the de- sired distance. Stereoscopic PIV images of the wake at various distances upstream and downstream were taken through the transparent sides of the wind tunnel. These images, in combination with the control volume approach, were used to determine the drag of a trailing cylinder.

Coefficients of drag, obtained with a balance for isolated cylinders of various aspect ratios, were in line with similar results from the literature, albeit on the higher side. For cylinders in tandem of the same aspect ratio, AR, as the distance between them increased, the CD of a trailing cylinder converged to that of an isolated cylinder. Comparing tandem configurations with different AR and at the same nondi- mensionalized in-between distance, trailing cylinders with larger AR experienced larger drag reduction.

Introducing cylinder diameter ratio as an additional degree of freedom showed that smaller diameter trailing cylinders experienced greater drag reduction at close distances. However, at a certain distance further downstream, this trend reversed.

The drag reduction values obtained with PIV confirmed the findings from balance measurements. How- ever, due to the limited set of usable data, further work would need to be carried out to gain more confidence in the method.

This thesis investigates the influence of Cylindrical Distributed Roughness Elements (polka-dots) on cylinder flow, with a focus on potential applications in sports aerodynamics. The primary goals are twofold: to explore the mechanism behind tripping and to analyse how the dimensions (height, width, spacing) of polka-dots affect flow characteristics. The research employs an experimental approach, utilising balance measurements to quantify drag within the relevant Reynolds number range experienced by the limbs of speed-skaters. Additionally, Particle Image Velocimetry (PIV) measurements are conducted to examine the boundary layer and wake flow, revealing insights into how different polka-dot geometries impact flow characteristics.

11 polka-dot configurations were tested wherein the polka-dot height, diameter and spanwise (flow-normal) spacing was varied. Two PIV domains were imaged: the boundary layer flow before and after the polka-dot (covering an azimuthal range of about 40◦ of the circular profile), and the wake domain of the cylinder (about 2 diameters into the downstream flow). The boundary layer flow images were used to characterise the flow seen by the polka-dot array, and how it is affected by changes in the polka-dot geometry. The wake domain PIV imagery was used to examine the shape and dimensions of the cylinder wake.

Among the 11 tested polka-dot configurations, 10 effectively triggered drag reduction to varying extents within the relevant regime. The minimum drag coefficient was achieved by the configuration with the polka-dots of greatest diameter. It was also seen that increasing polka-dot height is likely to cause premature separation which is further exacerbated by a narrower polka-dot spacing. In general, results indicate that shorter and wider polka-dots cause transition at lower Reynolds numbers, and a greater reduction in drag occurs when transition takes place at higher Reynolds numbers. Polka-dots placed in closer proximity initiate flow tripping earlier, while wider spacing results in more substantial drag reduction. However, it is observed that the polka-dots, when spaced closer together, see a lower flow velocity for the same polka-dot height and may lead to premature separation.

In terms of the wake width, a high linear correlation is seen between the measured wake width and the measured coefficient of drag (r² ≈ 0.9). It is also seen that for drag coefficient values close to the minimum drag coefficient value, the wake width sees minimal change. The change in wake geometry is then seen as a change in the wake tapering (downstream decrease of the wake width) and the streamwise wake length. Therefore, a larger wake imaging domain in the streamwise direction is likely to allow for a more accurate correlation of the wake geometry and the drag coefficient.

While the study offers valuable insights, several recommendations are put forth for further research. Expanding the wake imaging domain is suggested to enhance correlations with the drag coefficient, and investigating spanwise flow variations would provide deeper insight into the tripping mechanism.

In cycling, the presence of drag reduction from drafting, when multiple cyclists ride in tandem, is a considerable area of performance enhancement for a cycling team and the customisation of this tandem group has the potential of maximising the drag reduction for the entire group or a specific cyclist. The flow interactions between two tandem bluff bodies is complex and incorporates several fluctuating variations in flow phenomena which have considerable effects on the drag forces experienced. An experimental campaign for tandem finite cylinders and cyclists of differing sizes and in different spacing configurations is undertaken, including a drag force measurement and PIV flow visualisation campaign. It is observed that differing magnitudes of drag reduction occur for tandem cylinders and cyclists, which are however, caused by similar variations in flow structures. The size and spacing ratios are found to have notable impact on drag reduction for tandem objects.

Understanding and predicting vortex behavior is crucial to maximize performance using aerodynamic design. Vortex breakdown can be induced to benefit the flow field or has to be prevented to avoid losing performance. It is therefore important to study the dynamics of vortex breakdown.

The main objective of this thesis was to assess the feasibility of measuring a free, streamwise vortex and its breakdown from data acquired with robotic volumetric Particle Image Velocimetry (PIV), whilst analyzing the relation between the local flow properties and the location of the breakdown. Experiments were conducted at the W-Tunnel at the TU Delft High-Speed Lab, where vortex breakdown was induced by the adverse pressure gradient field in front of a cylinder. The robotic Coaxial Volumetric Velocimeter (CVV) was used to assess the feasibility of using this system for vortex breakdown identification, in combination with data processing using a Lagrangian Particle Tracking (LPT) technique (Shake-The-Box), to detect and analyze vortices and their breakdown. The results of this experimental campaign were analyzed to identify vortices and their breakdown from the CVV data by characterizing the vortex’s internal structure. The analysis included establishing the relations of the adverse pressure gradient and the Reynolds number with the breakdown location.

The results showed that vortex breakdown is induced by the adverse pressure gradient. However, the breakdown location is not solely dependent on it. Furthermore, the effect of the Reynolds number at the breakdown location is barely measurable with the robotic volumetric PIV system.

This exploratory and experimental study showed that the CVV in combination with LPT can be used to recognize the structure of the vortex in both its pre- and post-breakdown regimes. However, for the analysis of vortex breakdown, it was found that the data was affected by the low spatial resolution. Thus, robotic volumetric PIV cannot provide conclusive results in terms of the relation between the location breakdown and local flow properties. Several recommendations regarding the experimental set-up are given for future research.

As the world grapples with the challenges of global warming, there has been a significant push for the development of new methods of harnessing renewable energy. Energy harvesters have been a new avenue to generate electrical power locally for remote applications. An energy harvester is a device that taps into aeroelastic phenomena to convert vibrational energy into electrical energy. Additional benefits of harvesters include being lower in complexity, ease of maintenance, and the resulting cost-effectiveness.

The splitter plate represents a wake control device that alters the wake to make the energy capture more efficient and practical when attached to a cylinder. However, the flow mechanisms under different conditions have not been fully understood. The motivation of the present work is to bridge this gap by characterizing the mechanisms and wake dynamics of a cylinder with a flexible splitter plate. This will help advance the understanding of the wake behavior of these devices to make safe and efficient devices. To characterize the behavior of the wake, measurements are made at different flow speeds. A preliminary analysis of the splitter plate motion showed that increasing the Reynolds number produced four distinct regimes to be studied further: crossover, baseline, reduced amplitude, and chaotic regimes. The initial analysis also revealed a condition named burst, defined as a period of resonant, two-dimensional, high amplitude oscillations of the splitter plate. All regimes are compared to a bare cylinder with no splitter plate to ascertain differences in wake behavior.

The use Helium Filled Soap Bubbles (HFSB) in flow diagnostic tools such as Particle Image Velocity (PIV) experiments has permitted large-scale measurements. A Lagrangian Particle Tracking (LPT) experiment was performed in which the HFSB is tracked individually with the help of an algorithm. The present study employs Shake-The-Box (STB), a novel LPT tracking algorithm that uses time-resolved experimental data to predict future tracer particle locations. The benefit of such an algorithm includes reduced ghost particle detection and computational efficiency. The details of this experimental method have been covered extensively in this thesis. The raw experimental data was processed to perform statistical analysis, proper orthogonal decomposition, and spectral analysis to provide insights to meet the thesis objective.

This study explores the flowfield around a pusher propeller-wing configuration using Lagrangian Particle Tracking (LPT). It assesses LPT’s capability to characterise propeller-wing interactions, emphasising its ability to resolve complex flow dynamics.

The experiment successfully achieves high particle concentrations downstream of the propeller, with propeller rotation enhancing the uniformity of the particle distribution. Velocity measurements are precise and feature low uncertainty, and vortex dynamics shed by the propeller are effectively resolved.

Furthermore, the study confirms LPT’s robustness in characterising wing-propeller flow characteristics, particularly in thrust and torque calculations, highlighting its non-invasive nature for performance measurements.

The investigation reveals how the wing influences the slipstream’s vortex structure and identifies the pylon’s effects. The method captures the propeller-induced effects on the wing, providing insights into upwash, downwash, and angle of attack variations.

In conclusion, this research demonstrates the utility of LPT in comprehensively characterising propeller-wing interactions, offering valuable insights for aviation and propeller innovations.

The importance of aerodynamic efficiency in the cycling sport is well known. Simple calculations demonstrate the considerable impact of just a few percentages in drag savings on the outcome of a competition where the margins can be incredibly small. Achieving a drag reduction can, however, be challenging as the flow topology of a cyclist is extremely complex. Nonetheless, the manipulation of flow structures in other research areas is proven to be an effective method for reducing aerodynamic resistance. Hence, the potential of achieving a drag reduction for a cyclist in a time trial position through the manipulation of the 3D flow topology is investigated.

Two devices are introduced named the Hip Vortex Control (HVC) and wingsuit aiming to reduce the streamwise vorticity at the hips and upper arms respectively. A reduction of a crosswind-dependent weighted drag area of -1.35% for the HVC and -5.45% for the wingsuit is measured experimentally. Computational Fluid Dynamics (CFD) simulations and robotic volumetric Particle Tracking Velocimetry (PTV) provide the trends in the drag-reducing mechanisms. The HVC promotes separation on the lower back of the cyclist, reducing the presence of the hip vortices leading to an increase of the pressure on the lower back. The wingsuit limits the formation of the streamwise vortices around the upper arms, slightly increasing the wake and increasing the pressure on the upper arms resulting in the drag reduction.

The numerical and experimental results largely agree on the variations in the flow topology for each configuration. The results indicate that a reduction in streamwise vorticity in the wake of a bluff body can reduce the drag considerably. Both devices lead to an expansion of the wake which should be kept to a minimum to effectively reduce the drag. The results motivate the continuation of the research into the reduction of streamwise vortices in the development of cycling equipment and in other high-velocity sports.