Integrating Data-Driven and Physics-Based Models for Plume-Surface Interaction Predictions

Rocket propulsion plays a pivotal role in human landings and spacecraft operations near planetary surfaces, yet it introduces substantial risks that can compromise mission success and the safety of surrounding assets. Engine exhaust plumes interact with the surface regolith lifting dust particles that pose threats to visibility, sensor functionality, and the integrity of surface infrastructure through sandblasting. The crater eroded underneath the vehicle can compromise its stability upon touchdown. A key step towards design and risk mitigation strategies, and the ultimate objective of this project, is developing models and engineering relations for plume-surface interactions (PSI) that are guided by data and by an improved understanding of the underlying complex physical mechanisms. Leveraging recent NASA subscale experiments, our methodology employs a multi-stage approach integrating advanced image and data processing tools, statistical models, and state-of-the-art machine learning algorithms. This approach will allow identifying dominant physical mechanisms across erosion regimes, and developing close-form model relations for cratering, erosion and ejecta to facilitate informed decisions driven by PSI risk mitigation.

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