Machine-learning building-block-flow model for large-eddy simulation of high-speed flows with strong heat transfer and wall roughness

Achieving a successful soft landing on another planet is a challenging endeavor. The Entry, Descent, and Landing (EDL) phase of space vehicles lasts merely a few minutes, yet it encompasses the transition from hypersonic speeds with extreme temperatures to the safe touchdown. Despite the existence of computational methodologies for modeling the fluid dynamics surrounding EDL vehicles, the current approaches lack the capacity to perform accurately across multiple flow phenomena. To enable safe and successful planet exploration by NASA, we propose developing a computational fluid dynamics model that accurately predicts the flow patterns and thermal distributions around EDL vehicles at hypersonic speeds. The improved modeling capabilities will facilitate the development of future missions to Mars, Titan, and the gas giant planets.

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