Deep learning for topology optimization of 2D metamaterials

Deep learning for topology optimization of 2D metamaterials

Data-driven models are rising as an auspicious method for the geometrical design of materials and structural systems. Nevertheless, existing data-driven models customarily address the optimization of structural designs rather than metamaterial designs. Metamaterials are emerging as promising materia...

Full description

Bibliographic Details
Main Authors: Hunter T. Kollmann, Diab W. Abueidda, Seid Koric, Erman Guleryuz, Nahil A. Sobh
Format: Article
Language:English
Published: Elsevier 2020-11-01
Series:Materials & Design
Subjects:
Architected materials
Auxetic materials
Homogenization
Machine learning
Microstructure
Periodic boundary conditions (PBCs)
Online Access:http://www.sciencedirect.com/science/article/pii/S026412752030633X

Internet

http://www.sciencedirect.com/science/article/pii/S026412752030633X

Similar Items