Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session W21: Mechanical Metamaterials II
3:00 PM–5:48 PM,
Thursday, March 17, 2022
Room: McCormick Place W-185D
Sponsoring
Unit:
DSOFT
Chair: Lucie Domino, University of Amsterdam
Abstract: W21.00001 : Designing 2D mechanical metamaterials with printability constraints using interpretable machine learning*
3:00 PM–3:12 PM
Presenter:
Mary V Bastawrous
(Department of Mechanical Engineering and Materials Science, Duke University)
Authors:
Mary V Bastawrous
(Department of Mechanical Engineering and Materials Science, Duke University)
Zhi Chen
(Department of Computer Science, Duke University)
L Catherine Brinson
(Department of Mechanical Engineering and Materials Science, Duke University)
We take elastic 2D metamaterials that exhibit band gaps as an example and discuss the application of interpretable machine learning to capture unit-cell features essential for opening band gaps within specified frequency ranges while also incorporating 3D printing considerations. Unlike conventional ‘black box’ machine-learning algorithms, interpretable machine-learning algorithms yield models that can be easily interpreted and checked. Thus, they offer an effective approach towards obtaining interpretable rules spanning the feasible design space (e.g., different unit-cell shapes and topologies) for complex problems, e.g, multi-classification problems or multi-objective problems involving multi-functional metamaterials.
*We gratefully acknowledge funding from the Department of Energy, grant # DE-SC0021358.
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