Hugues Perrin

Head of Aero-Design for Éclipse 13

• Designed and optimized the design of Éclipse 13, the 2026-2027 car.
• In charge of generating parametric design surfaces on CATIA V5.
• Developped CFD models and optimization algorithms towards the design of the aeroshell, and ran them on supercomputer cluster nodes
• Implemented less-conventional design targets (solar pannel area, manufacturing).
• Worked on the implementation of wheel covers to reduce interference drag.

Head of Wind Tunnel and Experimental Testing

• Led the 2026 wind-tunnel campaign on the previous prototype, Éclipse 12, at Ford's Driveability Test Facility in Detroit, Michigan
• Designed a pitot sensor rake to correlate fine wake vortices to CFD data.
• Correlated the wind tunnel data to numerical predictions to a standard of 92%.
• Validated the impact of 'sharkskin' wrap on aerodynamic forces of a solar car.

Head of Engine CFD Modelization

• Founded the CFD department of the ÉTS student rocketry team.
• Simulated and correlated the engine's combustion mechanisms against field data.
• Predicted supersonic flight conditions for stability and flame-expansion studies.
• Designed and ran live-fire test plans, later used for CFD validation.
• Analyzed in-flight and test-bench data for fuel regression rate, oxidizer flow rate and pressure drop within the chamber to model the rocket more accurately.

Engine Optimization Engineer

• Optimized critical components of a paraffin–N2O hybrid rocket engine using the new CFD models.
• Designed injector plate and nozzle concepts that increased engine specific thrust.
• Created a new methodology for the paraffin-based fuel cartridge.

2025 – 2026

Aerodynamics Researcher

• Owned CFD validation, wind-tunnel correlation and on-track correlation.
• Automated the mesh and aeromap generation pipeline for cluster integration.
• Automated data collection and analysis through plug-and-play Python scripts.
• Ran all on-cluster CFD operations and their optimization.
• Worked on air-cooled in-hub EV motors for DELTA-26.
• Ran knowledge transfer to new members of the aerodynamics department.

Vehicle Dynamics Engineer

• Developed a full tyre model based on Pacejka's Magic Formula for cornering vehicle dynamics.
• Coded a lap-time simulation script for a DSSV suspension geometry and proprietary vehicle characteristics.

Cornering Aerodynamics Simulation Expert

• Developed a fully parameterized, optimized CFD template for steady-state cornering, built on the vehicle dynamics model.
• Validated it against the verified straight-line model at high cornering radii, and against on-track data.

2024 – 2025

Team Co-Captain

• Co-managed a team of 20–40 engineering students.
• Ran school relationships, partnerships, recruitment, training, HR and department coordination.

Head of Aerodynamics

• Managed a team of four to design the DELTA-25 aero package.
• Oversaw a sidepod design for motor and inverter heat management.
• Designed a new front wing and a wing-based undertray, worth a 20% increase in downforce.

Co-Lead Chassis & SES

• Designed and simulated the second-generation carbon-fibre monocoque for EV prototypes.
• Ran aerodynamics-driven optimization of the chassis shape.
• Manufactured the monocoque in-house with pre-preg carbon fibre.
• Ensured rule compliance of the assembly through the Structural Equivalency Spreadsheet.

Welding Operations Manager

• Verified welding-related designs and rule compliance, and ran pre- and post-processing logistics.
• TIG welded safety roll cages and suspension components.
• Trained new welders and ran quality control after heat and black-zinc treatment.

2023 – 2024

Junior Aerodynamicist

• Analyzed data from the first wind-tunnel validation ever run by Formule ETS.
• Studied and calibrated the CFD model against wind-tunnel data.
• Developed a new undertray and bargeboard assembly for MANIC-24.
• Improved motor and inverter heat management by 40%.

Team Management

• Welcomed and trained 12 interns over 1 year.
• Managed a high-turnover workforce to sustain research productivity, data production and analysis.
• Introduced soon-to-be engineers to high-level CFD modelling techniques.

Adjoint-driven optimization of tubercle leading edges for morphing

• Optimized tubercled leading-edge wings for in-flight deformation, targeting fuel consumption reduction and overall increase in performance.
• Used the adjoint solver to derive optimal shapes per flight condition and objective function, constraining displacement to theoretical use cases.
• Presented a paper at the AIAA SciTech 2025 Forum in Florida.

AI-based prediction model for tubercle performance

• Built an AI surrogate predicting tubercle wing performance from its key parameters, amplitude and wavelength.
• Reached predictions within a thousandth of a percent of CFD results.
• Generated the training dataset through SolidWorks automation macros.
• Studied pre and post-stall tubercle effect across turbulence and CFD packages.