A recent publication from IMDEA Materials Institute and the Technical University of Madrid (UPM) presents a major step forward in bringing real-time simulation capabilities to composite manufacturing processes. By addressing key limitations of current deep learning surrogate models for simulating fluid flow in composite manufacturing processes, these results highlight the potential of data-driven approaches to enhance efficiency, adaptability, and resilience in advanced manufacturing processes.
AI-powered surrogate models bring real-time simulation to composite manufacturing
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