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.