Selecting the appropriate turbulence model for high-speed aerodynamic simulations is one of the most critical decisions in computational fluid dynamics. The choice directly impacts accuracy, computational cost, and the reliability of design decisions based on simulation results.
Understanding High-Speed Flow Complexity
At transonic and supersonic speeds, flow phenomena become significantly more complex:
- •Shock waves interact with boundary layers
- •Compressibility effects dominate the physics
- •Turbulence structure changes fundamentally
Standard turbulence models developed for incompressible flows often fail to capture these physics accurately.
The k-ω SST Model: A Workhorse
The k-ω SST (Shear Stress Transport) model remains a workhorse for many aerospace applications. Its ability to blend the advantages of:
- •k-ε in the freestream
- •k-ω near walls
Makes it robust across a wide range of flow conditions. However, for flows with significant separation or strong adverse pressure gradients, even SST can struggle.
When SST Falls Short
Scenarios requiring alternatives:
├── Massive flow separation
├── Highly unsteady phenomena
├── Complex 3D vortical flows
└── Strong shock-boundary layer interactions
Scale-Resolving Simulations (SRS)
Scale-Resolving Simulations like Detached Eddy Simulation (DES) and Large Eddy Simulation (LES) offer improved accuracy for complex separated flows.
These methods:
- •Directly resolve large turbulent structures
- •Model smaller scales
- •Provide time-accurate predictions of unsteady phenomena
The computational cost is higher, but for critical applications, the investment is justified.
Validation is Non-Negotiable
"Validation against experimental data is non-negotiable in high-speed aerodynamics."
We maintain extensive databases of:
- •Wind tunnel results
- •Flight test data
- •Historical simulation benchmarks
This empirical grounding ensures that our CFD predictions translate to real-world performance.
Practical Model Selection Guide
| Design Phase | Recommended Approach | Configurations |
|---|---|---|
| Preliminary | RANS (SST) | Hundreds |
| Detailed | Hybrid RANS-LES | Tens |
| Final Validation | Full LES / Experimental | Single |
Decision Framework
Practical considerations often drive model selection:
- •For preliminary design with hundreds of configurations to evaluate, RANS models provide the necessary throughput
- •For detailed design of critical components, hybrid RANS-LES methods offer the best balance
- •Final validation may require full LES or even direct comparison with experimental programs
Best Practices Summary
- •Start with validated RANS for design space exploration
- •Reserve SRS methods for critical flow features
- •Always validate against experimental data when available
- •Document y+ values and mesh quality metrics
- •Consider uncertainty quantification for critical decisions
Key Takeaways
- •k-ω SST is robust for attached flows but struggles with separation
- •Scale-resolving methods (DES, LES) are essential for complex separated flows
- •Computational cost must be balanced against accuracy requirements
- •Validation against experimental data is mandatory for high-stakes applications
- •Model selection should match the design phase and decision criticality
Need help selecting the right turbulence model for your application? Get in touch with our CFD experts.
