Nano letters
Physics-Informed Graph Neural Networks for Predicting Deformation in Disordered Fibrous Materials.
Shuo Yang, Yunhao Yang, Chen Huang, Runnan Bai, Leitao Cao, Jing Ren, Shengjie Ling
Published: 202610.1021/acs.nanolett.5c04895
Abstract
Disordered fibrous networks play vital mechanical roles but are difficult to model due to their sparse connectivity and complex nonaffine deformation. We introduce a physics-informed, graph-learning-based Network Mechanics Prediction (GNMP) that pred…
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