Machine learning assisted approach to design lattice materials with prescribed band gap characteristics

DOI10.1016/j.euromechsol.2023.105125zbMath1529.74080MaRDI QIDQ6073405

Mohammad A. Jaradat, Bassam A. Abu-Nabah, T. A. Venkatesh, Mohamed Shendy, Maen Alkhader

Publication date: 15 September 2023

Published in: European Journal of Mechanics. A. Solids (Search for Journal in Brave)

zbMATH Keywords

finite element methodmetamaterialarchitected materialartificial intelligence-assisted neural networkdouble-walled hexagonal latticesinusoidal periodic perturbation

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Learning and adaptive systems in artificial intelligence (68T05) Vibrations in dynamical problems in solid mechanics (74H45) Finite element methods applied to problems in solid mechanics (74S05) Thin bodies, structures (74K99) Numerical and other methods in solid mechanics (74S99)

Cites Work

• Phononic properties of hexagonal chiral lattices
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