Lightweight Rapid Alloy Development and Fabrication using ICME based Optimization

In order to achieve the best possible performance in additively manufactured components, design of new alloys that are tailored to the unique thermomechanical history of additive manufacturing is necessary. It is well known that the fast cooling rates associated with additive manufacturing can produce unique microstructures not seen in conventional processing of many alloys. Rapid alloy design combining physics based modeling (e.g. CALPHAD) with high throughput production of novel alloy compositions can enable rapid screening of the design space. The addition of machine learning to elucidate complex chemistry-processing-microstructure relationships and multi-objective optimization can provide tailored alloy composition and processing parameters to create structural components with location-specific enhanced properties. This process chain will be demonstrated during the proposed work.