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Deep learned finite elements
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DOI：10.1016/j.cma.2020.113401.png)
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Abstract
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In this paper, we propose a method that employs deep learning, an artificial intelligence technique, to generate stiffness matrices of finite elements. The proposed method is used to develop 4and 8-node 2D solid finite elements. The deep learned finite elements practically pass the patch tests and the zero energy mode tests. Through various numerical examples, the performance of the developed elements is investigated and compared with those of existing elements. Computation efficiency is also studied. It was confirmed that the deep learned finite elements can potentially outperform existing finite elements. The proposed method can be applied to generate various types of finite elements in the future. (C) 2020 Elsevier B.V. All rights reserved.
Keywords:
Finite element
Solid element
Stiffness matrix
Artificial intelligence
Deep learning
Neural network
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