Deep Reinforcement Learning for the Design of Mechanical Metamaterials with Tunable Deformation and Hysteretic Characteristics-Reference-Cited by-同舟云学术

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Deep Reinforcement Learning for the Design of Mechanical Metamaterials with Tunable Deformation and Hysteretic Characteristics

Published:2023 Issue: Volume: Page:
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Author:

Brown Nathan,Deshpande Amit,Garland Anthony P.,Pradeep Sai,Fadel Georges M.,Pilla Srikanth,Li Gang

Publisher

Elsevier BV

Reference71 articles.

1. Temperature-dependent mechanical properties and model of magnetorheological elastomers;W Zhang;Ind. Eng. Chem. Res,2011

2. Fabrication of Highly Expanded thermoplastic Polyurethane Foams Using Microcellular Injection Modling and Gas-Laden Pellets;S Xiaofei;Polym. Eng. Sci,2015

3. Mechanical metamaterials associated with stiffness, rigidity and compressibility: A brief review;X Yu;Prog. Mater. Sci,2018

4. Programmable gear-based mechanical metamaterials;X Fang;Nat. Mater,2022

5. Systematic design of high-strength multicomponent metamaterials;K Momeni;Mater. Des,2019

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