Bridging the Simulation Gap: Physics-Interpretable Machine Learning Framework for In Silico Fatigue Life Prediction of Additively Manufactured Polymers

Research Square 2026 Preprint Open access

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Authors: Rafael Meyer

DOI: 10.21203/rs.3.rs-8735376/v1

Cited by: 0

Fields of Study & Subjects

Additive Manufacturing and 3D Printing Technologies Machine Learning in Materials Science Additive Manufacturing Materials and Processes