SBIR/STTR Award attributes
Despite the maturity of welding and related joining processes for terrestrial applications, there is limited understanding of the effects of an in-space environment on weld quality. An ICME framework leveraging physics-based process and metallurgical models, anchored by terrestrial data, is desired to predict the effects of in-space, lunar, and Martian environments on the welding process and resulting material properties. To address this need, CFD Research will establish critical elements of such a framework, namely physics-based welding process models to evaluate the relevant environmental effects (microgravity, vacuum, extreme ambient temperature), with phase field models to predict the resulting joint microstructure and properties. A machine learning model component, to enable prediction of process-structure-property relations of alloys derived from lunar and Martian in-situ resource utilization (ISRU), will be developed to provide a path for addressing uncertainty in processing and properties of those materials. The Phase II program will focus on further maturation of the developed framework, particularly simplified data transfer between models, further training and validation of the ML model to address additional trace solutes in ISRU-derived alloys, validation and application studies, and delivery of the resulting software and databases to NASA
