Integrating experiments, finite element analysis, and interpretable machine learning to evaluate the auxetic response of 3D printed re-entrant metamaterials
Metamaterials have received extensive attention in fundamental and applied research over the past two decades due to their unique mechanical behavior. This paper presents an interpretable machine learning (ML) approach for efficient response prediction of three-dimensional (3D)-printed metamaterials...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2023-07-01
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Series: | Journal of Materials Research and Technology |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2238785423012851 |