Analyses of internal structures and defects in materials using physics-informed neural networks
Characterizing internal structures and defects in materials is a challenging task, often requiring solutions to inverse problems with unknown topology, geometry, material properties, and nonlinear deformation. Here, we present a general framework based on physics-informed neural networks for identif...
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Main Authors: | Zhang, Enrui, Dao, Ming, Karniadakis, George Em, Suresh, Subra |
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其他作者: | School of Materials Science and Engineering |
格式: | Article |
語言: | English |
出版: |
2023
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主題: | |
在線閱讀: | https://hdl.handle.net/10356/164373 |
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機構: | Nanyang Technological University |
語言: | English |
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