CFD Simulations in Cycling

Computational Fluid Dynamics (CFD) has revolutionized the way cycling teams and manufacturers optimize aerodynamics. These computer-based simulations enable virtual analysis and improvement of airflow around riders and equipment – faster, more cost-effective, and more detailed than ever before.

What are CFD Simulations?

CFD simulations are computer-based computational methods that mathematically model the behavior of fluids and gases. In cycling, they are used to analyze airflow around riders, bicycles, and equipment and minimize air resistance.

Basic Principles of CFD Technology

CFD simulation is based on the numerical solution of the Navier-Stokes equations, which describe the motion of fluids. Modern CFD software divides the space to be analyzed into millions of small cells (mesh) and calculates for each cell:

1. Flow velocity - How fast does the air move at each point?
2. Pressure - What pressure exists at different surfaces?
3. Turbulence - Where do vortices form and how strong are they?
4. Boundary layers - How does the airflow behave directly at the surface?

Difference from Physical Tests

Application Areas in Cycling

Bike Frame Optimization

CFD simulations enable manufacturers to develop frame shapes that reduce air resistance by up to 15-20%. Particularly critical are:

• Tube profiles - Optimization of cross-sectional shape for minimal air resistance
• Tube arrangement - Placement of tubes for optimal flow guidance
• Component integration - Seamless transitions between frame, fork, and accessories
• Cable routing - Internal cable routing to avoid turbulence

Wheel Development

The development of aerodynamic wheels is one of the most important application areas for CFD:

1. Rim depth - Simulation of different profile heights (40mm to 90mm)
2. Spoke configuration - Number, shape, and arrangement of spokes
3. Hub optimization - Minimization of air resistance in the hub area
4. Tire integration - Optimization of the transition from rim to tire

Result: Modern CFD-optimized wheels save approximately 20-30 watts at 40 km/h compared to conventional wheels.

Rider Positions and Clothing

CFD simulations are intensively used to develop optimal rider positions and clothing:

Positioning analysis:

• Upper body angle to horizontal
• Arm position on handlebar or aerobars
• Head position and helmet alignment
• Leg angle during pedaling motion

Clothing optimization:

• Textile structures (smooth vs. structured)
• Seam placement for flow guidance
• Leg endings and sleeve ends
• Jersey fit under different body postures

Helmet Design

Modern aero helmets are completely developed in CFD:

• Front intake zone - Optimization for uniform airflow
• Surface - Balance between aerodynamics and cooling
• Rear trailing edge - Minimization of vortices
• Visor integration - Seamless transition for time trial helmets

The CFD Workflow in Detail

Phase 1: 3D Modeling

The first step is creating a highly precise 3D model:

1. 3D scanning - Capture of real geometries with 3D scanner (accuracy: 0.1mm)
2. CAD modeling - Digital post-processing and optimization
3. Surface preparation - Smoothing and cleaning of the model
4. Define level of detail - Balance between accuracy and computation time

Phase 2: Mesh Generation

The mesh is the computational grid on which the simulation is based:

Mesh quality criteria:

• Cell count: 5-50 million cells (depending on level of detail)
• Cell size: Variable from 0.5mm (surface) to 50mm (far field)
• Cell shape: Hexahedral or tetrahedral
• Boundary layer resolution: At least 10-15 cell layers at surfaces

Phase 3: Define Boundary Conditions

The simulation requires precise input parameters:

Phase 4: Run Simulation

The actual calculation is performed on powerful computer systems:

Hardware requirements:

• CPU: 16-64 cores for parallel computation
• RAM: 64-256 GB memory
• Computation time: 8-48 hours per simulation
• Storage space: 50-500 GB per project

Convergence monitoring:

The simulation runs iteratively until the results stabilize. Monitored are:

• Residuals (deviations between iterations)
• Force coefficients (CD, CL values)
• Pressure and velocity fields

Phase 5: Post-Processing and Analysis

After the simulation, results are visualized and evaluated:

Visualization methods:

1. Streamlines - Flow lines show the air path
2. Pressure distribution - Color-coded pressure differences on surfaces
3. Velocity fields - Air velocity in different areas
4. Vortex visualization - Identification of turbulence zones
5. CD value calculation - Quantification of air resistance
6. Force diagrams - Lift, drag, side forces

Software and Tools

Leading CFD Software in Cycling

Pre- and Post-Processing Tools

Mesh generation:

• ANSYS Meshing
• ICEM CFD
• Pointwise
• SnappyHexMesh (OpenFOAM)

Visualization:

• ParaView (Open Source)
• Tecplot
• FieldView
• EnSight

Validation of CFD Results

CFD simulations must be validated by real measurements:

Validation Methods

001. Wind tunnel correlation

• Comparison of CFD results with wind tunnel tests
• Target accuracy: ±2-3% CD value
• Iterative improvement of simulation parameters

002. On-bike measurements

• Power meter data at constant speed
• Coast-down tests for resistance measurement
• GPS-based velocity profiles

003. Field testing

• Real-world tests under controlled conditions
• Comparison of A/B setups on the same route
• Statistical evaluation over multiple runs

Advantages and Limitations

Advantages of CFD Simulations

• Cost efficiency: 10-20x cheaper than extensive wind tunnel campaigns
• Speed: Multiple variants testable per week
• Level of detail: Complete flow visualization at every point
• Flexibility: Any geometries and conditions can be simulated
• Reproducibility: Identical repetition possible at any time
• Parameter studies: Systematic variation of individual parameters
• Early development phase: Optimization before prototype construction

Limitations and Challenges

• Computation time: High-precision simulations take 24-48 hours
• Hardware requirements: Powerful workstations necessary
• Expertise required: CFD engineers with experience needed
• Modeling accuracy: Small errors in 3D model lead to large deviations
• Turbulence modeling: Complex flows difficult to calculate
• Real-world factors: Wind, temperature, road irregularities not fully representable
• Validation necessary: Results must be confirmed by tests

Best Practices for CFD in Cycling

Checklist for Successful CFD Projects

• Define clear objectives - What exactly should be optimized?
• Create high-quality 3D model - Accuracy is crucial
• Ensure mesh quality - Invest time in good mesh
• Realistic boundary conditions - Represent real riding situations
• Simulate multiple scenarios - 0°, 10°, 20° crosswind
• Mesh independence study - Ensure mesh is fine enough
• Check convergence - Run simulation until stability
• Plausibilize results - Physically meaningful?
• Validate with measurements - Wind tunnel or real test
• Documentation - Record all parameters and assumptions

Avoid Typical Error Sources

001. Mesh too coarse

• Problem: Important flow details are not captured
• Solution: Mesh refinement in critical areas (boundary layer, separation zones)

002. Wrong turbulence models

• Problem: Unrealistic flow prediction
• Solution: Use k-ω SST for external flows

003. Insufficient convergence

• Problem: Unstable, inaccurate results
• Solution: More iterations, smaller time steps

004. Neglecting motion

• Problem: Static simulation vs. real pedaling motion
• Solution: Transient simulations with moving components

Future of CFD in Cycling

Emerging Technologies

AI-supported optimization:

Machine learning accelerates optimization:

• Automatic geometry variation through neural networks
• Prediction of CD values without full simulation
• Trained models based on 1000+ simulations

Real-time CFD:

New algorithms and hardware enable faster calculations:

• GPU-accelerated solvers
• Reduced-order models for fast iteration
• Cloud computing for massive parallelization

Multi-physics simulation:

Integration of various physical phenomena:

• Coupling of CFD with structural mechanics
• Thermal analysis for cooling
• Acoustic simulation for aerodynamic noise

Integration into Development Process

Hybrid Development Approaches

Modern development combines various methods:

• Phase 1 - Concept: CFD simulations for initial ideas (5-10 variants)
• Phase 2 - Detail optimization: Iterative CFD refinement (20-30 variants)
• Phase 3 - Validation: Wind tunnel tests of best 2-3 designs
• Phase 4 - Fine-tuning: CFD for final adjustments
• Phase 5 - Real-world test: On-bike measurements and athlete feedback

ROI Consideration

Investment calculation for CFD setup:

Savings through CFD:

• Wind tunnel tests: -80,000 EUR/year (16 tests at 5,000 EUR saved)
• Prototypes: -50,000 EUR/year (fewer physical prototypes needed)
• Development time: -3 months (faster time-to-market)

Break-even: After approximately 18 months