Artificially Intelligent Manufacturing Paradigm for Composites

The scientific goals will be achieved via three research thrusts as shown in the figure above. Research Thrust I is the DLC representing a suite of seamlessly linked, high-fidelity multiscale models for simulating all stages of a polymer composite’s life cycle, which also integrates uncertainty and environmental-energy-economic (E3) impact quantification. The DLC will enable the generation of a large quantity of high-fidelity data for the development and training of AI models in Research Thrust II. Equipped with the DLC generated data, in Research Thrust II AI modeling and inverse design research thrust, we are developing new AI models to efficiently map the composite materials’ architecture and the manufacturing process to composite components’ performance. Next, we are developing generative neural networks for material and manufacturing process inverse design. In Research Thrust III we are conducting material characterization and testing of mechanical, physical, rheological, and morphological properties at nano-, micro-, and macroscales to inform and validate both DLC and AI models and simulations. We will also implement new/hybrid processes that combine existing or new scalable processing routes to create tailored composite micro and macro structures. Finally, the inverse design is performed by the generative AI models and validated by experimental tests.