Prediction of plume-surface interaction (PSI) effects in lunar environments is critical to the design of current and future landers for human landing system (HLS). Lander plume flows traverse a complex near-vacuum mixed continuum-rarefied-granular flow environment upon exiting the thruster nozzle. Current modeling capabilities for lunar lander PSI analysis fall short of providing the physical modeling and model fidelity required to predict PSI with sufficient efficiency and accuracy. This project will develop and mature a suite of predictive capabilities into a computational architecture for human-scale lunar lander PSI modeling including realistic propellants. This will enable better understanding of PSI in near vacuum conditions for lunar landers and enable design of next-generation propulsion systems. A proof-of-concept was developed and successfully demonstrated during Phase II for mixed continuum-rarefied environments relevant to PSI. Phase II Extended and associated Phase III STMD GCD funding will enable adaptation and maturation of the software simulation technology to deliver production predictive capabilities with advanced molecular gas models to support plume gas and plume-surface interaction predictions for human landing systems and other NASA missions.

Potential NASA Applications include: prediction and analysis of lander plume flows and resulting interactions between liberated lunar regolith with vehicle and ground structures; risk reduction through improved fidelity simulations of liberated regolith reaching sensitive vehicle structures and equipment; spacecraft thruster placement and design support; and simulation of effectiveness of RCS thrusters in reentry capsule rarefied wake region.

Potential Non-NASA government and commercial applications include, assessment of thruster plume induced environments on commercial and military spacecraft, predicting the impact of particles scattered from thruster plumes on ballistic missile and missile interceptor signatures, and optimization of commercial satellite operational life through contamination minimization.