An Approach for Practical Grid-Resolved Roughness Aerothermodynamic Simulations for Woven Heatshield Surfaces
An approach for simulating the aerothermal environment over a patterned roughness surface within an otherwise axisymmetric flow is developed. The patterned roughness is simplified into a sinusoidal shape that captures the basic features of a charred 3MDCP ablator. Two orientations of this pattern, which are equally flight relevant due to the forming process, enable periodic boundary conditions along the edges of a grid spanning a single roughness element. This simplified three-dimensional grid represents the minimum problem size for a patterned roughness simulation, which enables computationally efficient grid-resolved roughness simulations. This approach is validated by simulating the Langley Mach 6 measurements made on a similar sinusoidal surface, which results in convective heating within 5% of the experimental data. Applying this approach to Mars Sample Return (MSR) Earth Entry System (EES) flight cases, considering simulations with both 11 species air and 30 species air with ablation products, results in heating augmentation that is slightly lower than the widely-used Dahm correlation approach, with the difference being dependent on pattern orientation. This result provides the only insight into the behavior of the roughness augmentation at the high temperature reacting flow conditions present for EES flight cases, which are not captured by available ground test measurements. For shear augmentation, the simulations revealed that the surface-parallel pressure component is dominant. For arc-jet tests targeted to flight values for shear, the higher arc-jet pressures required to match flight values for shear result in up to a 400% increase in the rough wall shear value, which is not captured by the Dahm correlation. This indicates that, to avoid significant over-testing, grid-resolved roughness simulations are required to determine arc-jet conditions that produce flight shear levels in rough-wall scenarios.