Stimuli‐Responsive Materials: Finite‐Element‐Based Deep‐Learning Model for Deformation Behavior of Digital Materials (Adv. Theory Simul. 7/2020). Issue 7 (3rd July 2020)

• Record Type: Journal Article
• Authors: Zhang, Zhizhou; Gu, Grace X.
• Is Part Of: Advanced theory and simulations. Volume 3:Issue 7(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-07-03
• Subjects: Science -- Simulation methods -- Periodicals; Science -- Methodology -- Periodicals; Engineering -- Simulation methods -- Periodicals; Engineering -- Methodology -- Periodicals; 507.21
• DOI: 10.1002/adts.202070017
• Languages: English
• ISSNs: 2513-0390

Abstract

Abstract : Digital materials are programmable smart composites that exhibit complex deformation when experiencing external stimuli. In article number 2000031, Zhizhou Zhang and Grace X. Gu report work that integrates multi‐physics modeling and machine learning (convolutional neural networks) to accelerate the prediction of the non‐linear deformation behavior of stimuli‐responsive digital materials. Moreover, high‐level design principles can be extracted from the model using sensitivity analysis.