Abstract 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 4- and 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.

中文翻译：

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深度学习的有限元

摘要 在本文中，我们提出了一种利用深度学习（一种人工智能技术）生成有限元刚度矩阵的方法。所提出的方法用于开发 4 节点和 8 节点二维实体有限元。深度学习的有限元实际上通过了补丁测试和零能量模式测试。通过各种数值例子，研究了开发元件的性能，并与现有元件的性能进行了比较。还研究了计算效率。经证实，深度学习的有限元可能优于现有的有限元。所提出的方法可以应用于将来生成各种类型的有限元。