Novel Contamination Control Model Development and Application to the Psyche Asteroid Mission

In this work, we present a state-of-the-art model, developed for JPL's Psyche Mission, which enables direct derivation of contamination control requirements specifically tailored to meet mission science objectives while minimizing cost and schedule impacts to the project. This is accomplished using a method of geometric model processing and analysis as well as a newly developed approach to materials contamination data characterization that enables extrapolation across all mission environments. Spacecraft missions have traditionally followed one of two approaches to contamination control engineering: low-sensitivity missions that rely on non-data-driven heritage practices to meet mission objectives (incurring risks of contamination impacts to the flight system, instruments and science objectives), or flagship-class missions that can afford to implement highly-conservative contamination control programs that may not be optimized to meet mission requirements or accurately quantify contamination impacts. In contrast, the model presented here, enables teams to evaluate the risk of not meeting bakeout requirements, trade contamination degradation budget allotments between spacecraft subsystems, and provide a mission-specific contamination control program suited for missions of all contamination sensitivity levels. This model incorporates instrument contamination requirements, materials information, spacecraft geometry, thermal predictions and mission operations timelines. Both internal and external spacecraft models are developed in order to account for bus venting, and different cases for stowed and deployed configurations and solar array orientations are analyzed to identify the driving mission phases for contamination. The spacecraft is subdivided into subsystem groups to make outgassing rates independently changeable by a table input and parametrically assess the impact of different components on each instrument. JPL's in-house view factor code is used to perform direct and reflected contamination transport modelling, allowing outgassing rate data to be updated without needing to re-run a simulation and enabling real-time analysis iteration compared to the weeks or months-long analysis lifecycle seen on comparable missions. The contamination behavior of the materials is obtained by identifying the contaminant chemical species from a single materials test. The material behavior across all mission environments is subsequently extrapolated from the knowledge of the constituent contamination species. As projects move from detailed design into manufacturing and baking out real hardware, model predictions can be updated with as-measured outgassing data to adjust future bakeouts on-the-fly to meet mission requirements. Results from the Psyche mission are presented, as well as the application of this model to future missions.