Dalton, D., Gao, H. and Husmeier, D. (2022) Emulation of cardiac mechanics using Graph Neural Networks. Computer Methods in Applied Mechanics and Engineering, 401(B), 115645. (doi: 10.1016/j.cma.2022.115645)
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Abstract
Recent progress in Graph Neural Networks (GNNs) has allowed the creation of new methods for surrogate modelling, or emulation, of complex physical systems to a high level of fidelity. The success of such methods has yet to be explored however in the context of soft-tissue mechanics, an area of research which has itself seen substantial developments in recent years. The present work explicates on this by introducing an emulation framework based on a multi-scale, message-passing GNN, before applying it to the modelling of passive left-ventricle mechanics. Through numerical experiments, it is demonstrated that the proposed method delivers strong predictive accuracy when benchmarked against the results of the nonlinear finite-element method (FEM), and significantly outperforms an alternative emulator based on a fully connected neural network. Furthermore, large computational gains are achieved at prediction time against the FEM.
| Item Type: | Articles |
|---|---|
| Additional Information: | This work as funded by the Engineering and Physical Sciences Research Council (EPSRC) of the United Kingdom, grant reference numbers EP/T017899/1, EP/S030875/1 and EP/S020950/1. |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Dalton, David and Gao, Dr Hao and Husmeier, Professor Dirk |
| Authors: | Dalton, D., Gao, H., and Husmeier, D. |
| College/School: | College of Science and Engineering College of Science and Engineering > School of Mathematics and Statistics > Statistics |
| Journal Name: | Computer Methods in Applied Mechanics and Engineering |
| Publisher: | Elsevier |
| ISSN: | 0045-7825 |
| ISSN (Online): | 1879-2138 |
| Published Online: | 06 October 2022 |
| Copyright Holders: | Copyright © 2022 The Authors |
| First Published: | First published in Computer Methods in Applied Mechanics and Engineering 401(B):115645 |
| Publisher Policy: | Reproduced under a Creative Commons licence |
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