Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment
Author:
Affiliation:
1. Laboratory for Atomistic and Molecular Mechanics (LAMM)
2. Department of Civil and Environmental Engineering
3. Massachusetts Institute of Technology
4. Cambridge
5. USA
Abstract
A new approach to design hierarchical materials using convolutional neural networks is proposed and validated through additive manufacturing and testing.
Funder
Office of Naval Research
Air Force Office of Scientific Research
Publisher
Royal Society of Chemistry (RSC)
Subject
Electrical and Electronic Engineering,Process Chemistry and Technology,Mechanics of Materials,General Materials Science
Link
http://pubs.rsc.org/en/content/articlepdf/2018/MH/C8MH00653A
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