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Master’s in Advanced Aerodynamic Development Engineering

Online master's programme of 1,900 hours in advanced aerodynamic development engineering: 12 modules covering the aerodynamic development process, advanced flow physics, high-fidelity simulation, adjoint optimisation, aerodynamic maps, aerodynamics in traffic, machine learning, tool correlation, aeroelasticity and regulations, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Manage the aerodynamic development process under constraints.

02

Analyse complex flow structures.

03

Apply high-fidelity simulations.

04

Optimise shapes using adjoint methods.

05

Generate aerodynamic maps and surrogate models.

06

Apply machine learning to aerodynamics.

07

Correlate tools and manage aeroelastic deformations.

Profile

Who it's for

  • Development aerodynamicists in motorsport or high-performance automotive.
  • High-fidelity CFD engineers working with DES, LES or lattice Boltzmann methods.
  • Optimisation engineers applying adjoint and surrogate methods.
  • Aerodynamic correlation engineers comparing CFD, tunnel and track.
  • Data scientists working with aerodynamic simulation data.
  • Aerodynamic project leads planning development programmes.
  • Engineering or science graduates looking to break into motorsport.
Standards & tools

What you'll work with

  • FIA Formula 1 Technical Regulations (technical rules for F1 cars)
  • Formula 1 Financial Regulations (ATR, aerodynamic testing restrictions)
  • WEC Hypercar Technical Regulations (technical rules for endurance prototypes)
  • SAE J1594 (vehicle aerodynamics terminology)
  • Appendix J to the FIA International Sporting Code (technical rules for competition vehicles)
  • ISO 8855 (vehicle dynamics and road-holding vocabulary)
  • Formula E Technical Regulations (technical rules for electric single-seaters)
  • Simcenter Star-CCM+
  • OpenFOAM
  • ANSYS Fluent
  • PowerFLOW
  • Python
Syllabus

12 modules · 1900 h

  1. 1.1. Development cycle in a racing team
  2. 1.2. Performance and lap time targets
  3. 1.3. Aerodynamic sensitivities
  4. 1.4. Managing CFD and wind tunnel resources
  5. 1.5. ATR restrictions and the cost cap
  6. 1.6. Organisation of the aerodynamics department
  7. 1.7. Design-to-manufacturing workflow
  8. 1.8. Configuration management
  9. 1.9. Introducing upgrades on track
  10. 1.10. Case study: development plan for a season
  1. 2.1. Complex vortex structures
  2. 2.2. Vortex interaction
  3. 2.3. Three-dimensional flow in diffusers
  4. 2.4. Boundary layer transition
  5. 2.5. Separation and reattachment
  6. 2.6. Unsteady flows
  7. 2.7. Wakes and their management
  8. 2.8. Local compressibility effects
  9. 2.9. Topological flow analysis
  10. 2.10. Lab: vortex identification with the Q-criterion
  1. 3.1. DES and DDES simulations
  2. 3.2. LES and mesh requirements
  3. 3.3. Lattice Boltzmann methods
  4. 3.4. Simulation of rotating wheels
  5. 3.5. Moving and deforming meshes
  6. 3.6. Simulation of the vehicle in cornering
  7. 3.7. Simulation in the wake of another car
  8. 3.8. Computational cost
  9. 3.9. Validation
  10. 3.10. Practical: DDES simulation of a wheel
  1. 4.1. Continuous and discrete adjoint methods
  2. 4.2. Surface sensitivities
  3. 4.3. Morphing with free-form parameterisation
  4. 4.4. Automated shape optimisation
  5. 4.5. Flow topology optimisation
  6. 4.6. Multi-point optimisation
  7. 4.7. Regulatory geometric constraints
  8. 4.8. Design robustness
  9. 4.9. Integration with CAD
  10. 4.10. Lab: adjoint optimisation with OpenFOAM
  1. 5.1. Front and rear ride-height maps
  2. 5.2. Sensitivity to pitch and roll
  3. 5.3. Sensitivity to yaw
  4. 5.4. Cornering maps
  5. 5.5. Balance stability
  6. 5.6. Use of maps in lap simulation
  7. 5.7. Efficient map generation
  8. 5.8. Design of experiments
  9. 5.9. Surrogate models
  10. 5.10. Practical: surrogate model of an aerodynamic map
  1. 6.1. Downforce loss in the wake
  2. 6.2. Regulations to facilitate overtaking
  3. 6.3. Two-car simulation
  4. 6.4. Aerodynamics in cornering and yaw
  5. 6.5. Effect of crosswind
  6. 6.6. Aerodynamics of steered wheels
  7. 6.7. Cornering tests in the wind tunnel
  8. 6.8. Following metrics
  9. 6.9. Impact on strategy
  10. 6.10. Case study: assessment of downforce loss in the wake
  1. 7.1. Reduced-order models
  2. 7.2. Neural networks for coefficient prediction
  3. 7.3. Graph neural networks for flow fields
  4. 7.4. Physics-informed models
  5. 7.5. Bayesian optimisation
  6. 7.6. POD dimensionality reduction
  7. 7.7. Simulation data management
  8. 7.8. Model validation
  9. 7.9. Integration into the workflow
  10. 7.10. Lab: coefficient prediction with neural networks
  1. 8.1. CFD–wind tunnel–track differences
  2. 8.2. Scale effect
  3. 8.3. Effect of wheels and moving ground
  4. 8.4. On-track deformations
  5. 8.5. Data correction
  6. 8.6. Correlation metrics
  7. 8.7. Managing discrepancies
  8. 8.8. Map correlation
  9. 8.9. Lessons from teams
  10. 8.10. Practical: correlation analysis of a component
  1. 9.1. Deformation of components under load
  2. 9.2. Regulatory deflection tests
  3. 9.3. Fluid–structure simulation
  4. 9.4. Designing for controlled flexibility
  5. 9.5. Laminates and fibre orientation
  6. 9.6. Aeroelastic vibrations
  7. 9.7. Measuring deformations on track
  8. 9.8. Regulatory risks
  9. 9.9. Reliability
  10. 9.10. Case study: deformation of a rear wing
  1. 10.1. Cooling losses
  2. 10.2. Optimisation of inlets and outlets
  3. 10.3. Trade-offs with vehicle dynamics
  4. 10.4. Aerodynamic platform and suspension
  5. 10.5. Porpoising and its control
  6. 10.6. Balance through the different phases of a corner
  7. 10.7. Integration into the simulator
  8. 10.8. Driver feedback
  9. 10.9. Decision-making
  10. 10.10. Workshop: cooling–downforce trade-off at a hot circuit
  1. 11.1. The 2022 technical regulations
  2. 11.2. The 2026 regulations and active aerodynamics
  3. 11.3. Hypercar and LMDh prototypes
  4. 11.4. Balance of Performance
  5. 11.5. Formula E Gen3 aerodynamics
  6. 11.6. Interpreting regulations
  7. 11.7. Technical queries to the FIA
  8. 11.8. Development strategy across regulation changes
  9. 11.9. Trends
  10. 11.10. Practical: analysis of a regulation change
  1. 12.1. Definition of the development objective
  2. 12.2. Baseline flow analysis
  3. 12.3. Design proposal
  4. 12.4. High-fidelity simulation
  5. 12.5. Optimisation
  6. 12.6. Sensitivity assessment
  7. 12.7. Validation plan
  8. 12.8. Conclusions
  9. 12.9. Master's Thesis report
  10. 12.10. Master's Thesis: defence before a panel
Methodology, software & labs

How you'll learn

The programme is 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so it can be combined with your job.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Simcenter Star-CCM+, OpenFOAM, ANSYS Fluent, PowerFLOW and Python, in free, academic or evaluation versions. Testing is studied through real procedures for high-fidelity DES and LES simulations, adjoint optimisation of components and generation of aerodynamic maps. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: FIA Formula 1 Technical Regulations, Formula 1 Financial Regulations (ATR), WEC Hypercar Technical Regulations, SAE J1594, Appendix J to the FIA International Sporting Code, ISO 8855, Formula E Technical Regulations.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of the FIA Formula 1 Technical Regulations, the Formula 1 Financial Regulations (ATR) and the WEC Hypercar Technical Regulations applied to real cases, not as a theoretical annex.
Industry software:Simcenter Star-CCM+, OpenFOAM, ANSYS Fluent, PowerFLOW and Python, in free, academic or evaluation versions.
Master's Thesis with defence:An aerodynamic development project on a real component, from baseline flow analysis and high-fidelity simulation to optimisation and validation plan, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Baseline flow analysis
Identify vortex structures with the Q-criterion and assess the baseline flow.
High-fidelity simulation
Run a DDES simulation of a rotating wheel and evaluate the wake.
Adjoint optimisation
Optimise a component with the adjoint method in OpenFOAM within regulatory constraints.
Maps and machine learning
Build a surrogate aerodynamic map and predict coefficients with neural networks.
Master's Thesis
Develop and validate an aerodynamic upgrade from objective to validation plan, defended before a panel.
Career opportunities

Where this takes you

Development aerodynamicistHigh-fidelity CFD engineerOptimisation engineerAerodynamic correlation engineerAerodynamic data scientistAerodynamic project lead
Admissions & scholarships

Requirements

  • A university degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • An internet connection and a computer capable of running the programme software.
  • English sufficient to read technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with Simcenter Star-CCM+, OpenFOAM, ANSYS Fluent, PowerFLOW and Python, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.

A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.

A university degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the software and English sufficient to read technical standards.

Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.

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