Aerodynamic drag reduction of heavy-duty vehicles is essential for lowering fuel consumption, with the front wheels contributing significantly to overall drag. Truck aerodynamics is typically investigated using Computational Fluid Dynamics (CFD) and small-scale wind tunnel testing. However, validating CFD results in the highly complex and unsteady front wheel wake region remains challenging. Conventional validation methods, such as wind tunnel measurements or wake-rake techniques, are often limited to simplified models or planar data.

This study addresses this limitation by applying the non-intrusive “Ring of Fire” measurement technique to reconstruct the three-dimensional front wheel wake of a full-scale truck. The objective was to design and implement a Ring of Fire setup capable of resolving the wheel wake region to support CFD validation, while also evaluating the conventional wake-rake method.

The Ring of Fire measurement technique is based on Particle Image Velocimetry (PIV). Helium-Filled Soap Bubbles (HFSBs) served as tracer particles, illuminated by high-power LEDs and recorded by high-speed cameras. A Shake-The-Box (STB) Lagrangian Particle Tracking (LPT) algorithm reconstructed three-dimensional particle trajectories, from which velocity fields were derived. For comparison, a wake-rake equipped with Kiel probes measured a two-dimensional total pressure field in the wheel wake.

Experiments were conducted on a test track using a full-scale European cab-over-engine tractor–trailer combination. Two configurations were tested: a baseline (Variant A) and a reduced-aero configuration (Variant B). Containing the HFSBs in an outdoor environment was a major challenge and was addressed using a foldable dome tent housing three vertically oriented LED units and a seeding rake. Four high speed cameras recorded the motion of the HFSBs within a measurement domain extending 1 meter from the truck surface and up to 1 meter in height, covering the longitudinal distance of 2.2 meter. A dedicated run procedure ensured synchronization between dome opening and data acquisition during truck passage.

A total of 100 runs were performed over two days. 8 valid runs for Variant A and 21 for Variant B were processed after excluding invalid measurements. Crosswind effects were assessed using conditional averaging and were found to be negligible within measurement uncertainty. Convergence analysis indicated that at least 16 combined runs were required to achieve a stable, time-averaged flow field with over 95% spatial data coverage.

For both configurations, the wheel wake region, characterized by significant reduced velocity magnitude, emerged downstream of the footstep and expanded further downstream. Overall, Variant A showed a larger wake region.

Comparison with wake-rake results revealed similar wake topology, but the Ring of Fire provided higher spatial resolution and full three-dimensional reconstruction. The study demonstrates that the Ring of Fire technique successfully captures the complete front wheel wake of a full-scale truck and offers substantial advantages over conventional planar wake-rake measurements.

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.

This thesis presents a novel methodology for investigating the aerodynamics of a competitive racing vehicle through the application of Lagrangian Particle Tracking (LPT) combined with the Shake-the-Box (StB) algorithm. Applied to the DUT24, developed by Formula Student Team Delft (FSTD), the approach enables detailed reconstruction of the three-dimensional velocity field around a fully aerodynamically equipped race car. Particular emphasis is placed on two flow regions of critical aerodynamic importance: the underbody diffuser and the
wakes shed by the rotating tyres. The study addresses the challenges of adapting the experimental set-up to full scale and highlights the advantages of advanced LPT compared with conventional flow measurement techniques.

The experiments were conducted on a 60 m test track at approximately 12 m/s, using Helium-Filled Soap Bubbles (HFSB) as neutrally buoyant tracers. For the diffuser study, three cameras and four LEDs were installed inside a ditch beneath the car, yielding a measurement volume of 300 × 400 × 350 mm. The tyre-wake study employed a lateral arrangement of cameras and LEDs, achieving a volume of 400 × 800 × 450 mm. Statistical convergence was ensured by repeating the tests multiple times, with 40 runs for the underbody and 30 for the tyre wakes.

The results revealed strong flow acceleration beneath the front wing and diffuser, with peak velocities exceeding twice the free-stream (u/U∞ > 2.2) and suction pressures around Cp ≈ −3. Diffuser strakes generated coherent streamwise vortices that promoted flow attachment and contributed to downforce, with no evidence of vortex breakdown. The tyre wakes were shown to be highly three-dimensional and unsteady, with the front tyre producing larger wakes than the rear. Vortical structures shed from the front wing and underbody mitigated and
reshaped these wakes, highlighting the strong coupling between wheel aerodynamics and upstream devices.

Because pressure cannot be directly obtained from LPT, a reconstruction algorithm based on omnidirectional integration with an irrotational boundary condition was applied. The method reproduced physically consistent pressure distributions, such as diffuser recovery and tyre-wake stagnation zones, but absolute discrepancies remained when compared with CFD, particularly in regions of strong adverse gradients or near reflective surfaces.

Comparison with CFD showed good agreement in overall flow topology and acceleration. Both approaches captured the diffuser acceleration and recovery, though CFD underpredicted vortex strength and momentum conservation. In the tyre wakes, CFD resolved similar structures but lacked rotation effects, producing smoother and less energetic vortices. Pressure fields agreed on overall trends but diverged in magnitude.

A convergence analysis indicated that 25 runs were required to reach 1% velocity uncertainty in the diffuser, while the unsteady tyre wakes demanded up to 70 runs for the same threshold, though 30 were sufficient to achieve a convergence of 2% of the velocity flowfield.

In conclusion, the Ring of Fire methodology, scaled to full vehicle dimensions, successfully captured the complex aerodynamic mechanisms of a modern race car. Despite limitations in pressure reconstruction and CFD comparison, the system proved robust and capable of resolving high-velocity underbody flows, coherent diffuser vortices, and unsteady tyre wakes, confirming its value as a powerful tool for experimental vehicle aerodynamics.

The Pulitzer Air Race is an event that originated in the 1920s. The race was organised to promote the development of high-performance aircraft and to experiment with new designs. Similarly, to accelerate the advancement of high-performance, medium-range electric aviation, the National Aviation Authority (NAA) has planned to revive the Pulitzer Air Race for zero-emission electric aircraft. The race spans over four days and covers a distance of 1,000 nautical miles (1,852 km), from Eppley Airfield in Omaha, Nebraska, to Dare County Regional Airport in Manteo, North Carolina. The winner is determined by the fastest speed calculated from cumulative flight time, excluding ground maintenance, charging, or overnight stops.
The Royal Netherlands Aerospace Centre (NLR) saw an opportunity in the upcoming Pulitzer Air Race and wanted to participate in developing a sustainable electric aircraft. Group 26 taking part in the Design Synthesis Exercise (DSE) at Delft University of Technology was approached to deliver a proposal for a design that can participate in this race and win. As a result, the project objective statement for this project is to “Provide a winning design for the Pulitzer Electric Aircraft Air Race within a budget of €900,000, by 10 students in 10 weeks.”
The requirements and constraints were defined after performing a market and a stakeholder analysis, five design concepts were selected over a wide range of potential configurations and a preliminary design for each one was made. Subsequently, a trade-off was performed to select the best design. Two of the design concepts ended up in a tie, those being the conventional aircraft configuration and the Prandtl plane configuration (or box-wing aircraft), both using hydrogen and batteries as energy sources. In the end, the Prandtl plane configuration was selected as the final concept, not only because it embodies a spirit of innovation in line with the ethos of the race, but also because of its potential to be structurally lighter than conventional aircraft configurations.
During the detailed design phase, intense concurrent engineering was performed between departments, with numerous iterations occurring throughout the detailed design process. The designed aircraft has a wingspan of 7.46 m, features two counter-rotating propellers driven by a continuous power of 80 kW each and an MTOM equal to 1,163 kg, of which 115 kg are due to the fuel cell, 30 kg of hydrogen mass and 53.5 kg of batteries. The Prandtl plane has a cruise altitude of 12.5 km, a cruise speed of 163 m/s and can complete the race without any stops in 206 minutes (slightly under 3.5 hours).