Exploration of optimal microstructure and mechanical properties in continuous microstructure space using a variational autoencoder

Exploration of optimal microstructure and mechanical properties in continuous microstructure space using a variational autoencoder

Data-driven approaches enable a deep understanding of microstructure and mechanical properties of materials and greatly promote one's capability in designing new advanced materials. Deep learning-based image processing outperforms conventional image processing techniques with unsupervised learn...

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Bibliographic Details
Main Authors: Yongju Kim, Hyung Keun Park, Jaimyun Jung, Peyman Asghari-Rad, Seungchul Lee, Jin You Kim, Hwan Gyo Jung, Hyoung Seop Kim
Format: Article
Language:English
Published: Elsevier 2021-04-01
Series:Materials & Design
Subjects:
Microstructure-based modeling
Deep learning
Variational autoencoder
Gaussian process regression
Dual-phase steel
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127521000976

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http://www.sciencedirect.com/science/article/pii/S0264127521000976

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