Machine learning in solid mechanics: Application to acoustic metamaterial design
D. Yago,
G. Sal‐Anglada,
D. Roca
et al.
Abstract:Machine learning (ML) and Deep learning (DL) are increasingly pivotal in the design of advanced metamaterials, seamlessly integrated with material or topology optimization. Their intrinsic capability to predict and interconnect material properties across vast design spaces, often computationally prohibitive for conventional methods, has led to groundbreaking possibilities. This paper introduces an innovative machine learning approach for the optimization of acoustic metamaterials, focusing on Multiresonant Lay… Show more
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