Abstract
This study advances turbulence modeling for hypersonic flows by systematically addressing the bidirectional coupling between high-enthalpy thermochemical non-equilibrium and compressible turbulence. Distinct from conventional Reynolds-Averaged Navier-Stokes (RANS) models that rely on constant transport coefficients and decoupled chemistry, we propose a new hierarchy of progressively refined RANS models built on the Compressible turbulent Kinetic energy Dependent Only (CKDO) framework. The innovative contributions include the concurrent integration of re-calibrated Bradshaw coefficients ( Rb ) to account for high-enthalpy stress-strain relations, non-equilibrium corrections to the turbulent kinetic energy equation (NE), and spatially variable turbulent Prandtl ( Prt ) and Schmidt ( Sct ) numbers informed by high-fidelity data. Validated against Direct Numerical Simulation (DNS) data of a Mach 20 boundary layer and experimental measurements for the MP-1 Mars entry vehicle, the models demonstrate distinct trade-offs: while the CKDO- Rb variant marginally improves velocity predictions, it degrades species mass fraction accuracy. The CKDO-NE model enhances global agreement with DNS but amplifies temperature peak deviations. The final holistic CKDO- Sct model—integrating all modifications—achieves superior balanced accuracy across velocity, temperature, density, and species profiles, while significantly reducing MP-1 forebody heat flux prediction errors. These results establish a dedicated modeling paradigm for high-enthalpy flows, demonstrating that accurate predictions necessitate the explicit treatment of multi-scale turbulence-chemistry interactions, which are typically overlooked in existing frameworks.
| Original language | English |
|---|---|
| Article number | 111804 |
| Journal | Aerospace Science and Technology |
| Volume | 174 |
| DOIs | |
| State | Published - Jul 2026 |
Keywords
- Compressibility effects
- High-enthalpy flows
- Turbulence modelling
- Turbulent Prandtl number
- Turbulent Schmidt number
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