Optimised graded metamaterials for mechanical energy confinement and amplification via reinforcement learning

DOI10.1016/J.EUROMECHSOL.2023.104947OpenAlexW4321202048MaRDI QIDQ2692865

Raffaele Ardito, Luca Iorio, Jacopo De Ponti, Luca Rosafalco, Alberto Corigliano

Publication date: 17 March 2023

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

Full work available at URL: https://arxiv.org/abs/2211.09528

zbMATH Keywords

Markov decision processdesign optimisationoptimal resonator arrangementproximal policy optimisation algorithm

Mathematics Subject Classification ID

Composite and mixture properties (74E30) Optimization of other properties in solid mechanics (74P10) Numerical and other methods in solid mechanics (74S99)

Uses Software

• Adam
• GitHub
• Stable Baselines

Cites Work

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• Homogenization of locally resonant acoustic metamaterials towards an emergent enriched continuum
• Interplay between phononic bandgaps and piezoelectric microstructures for energy harvesting
• Structural optimization using evolution strategies and neural networks
• Direct shape optimization through deep reinforcement learning
• Computational homogenization of locally resonant acoustic metamaterial panels towards enriched continuum beam/shell structures
• Phononic crystals. Artificial crystals for sonic, acoustic, and elastic waves
• Towards structural optimization via the genetic algorithm
• Learning representations by back-propagating errors

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