当前位置: X-MOL 学术Comput. Mech. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Self-updated four-node finite element using deep learning
Computational Mechanics ( IF 3.7 ) Pub Date : 2021-08-24 , DOI: 10.1007/s00466-021-02081-7
Jaeho Jung 1, 2 , Phill-Seung Lee 1 , Hyungmin Jun 3
Affiliation  

This paper introduces a new concept called self-updated finite element (SUFE). The finite element (FE) is activated through an iterative procedure to improve the solution accuracy without mesh refinement. A mode-based finite element formulation is devised for a four-node finite element and the assumed modal strain is employed for bending modes. A search procedure for optimal bending directions is implemented through deep learning for a given element deformation to minimize shear locking. The proposed element is called a self-updated four-node finite element, for which an iterative solution procedure is developed. The element passes the patch and zero-energy mode tests. As the number of iterations increases, the finite element solutions become more and more accurate, resulting in significantly accurate solutions with a few iterations. The SUFE concept is very effective, especially when the meshes are coarse and severely distorted. Its excellent performance is demonstrated through various numerical examples.



中文翻译:

使用深度学习的自更新四节点有限元

本文介绍了一种称为自更新有限元 (SUFE) 的新概念。有限元 (FE) 通过迭代程序激活,以提高求解精度,无需网格细化。为四节点有限元设计了基于模式的有限元公式,并为弯曲模式采用了假定的模态应变。通过对给定单元变形的深度学习来实现最佳弯曲方向的搜索程序,以最大限度地减少剪切锁定。所提出的单元称为自更新四节点有限元,为此开发了迭代求解程序。该元件通过了贴片和零能量模式测试。随着迭代次数的增加,有限元解决方案变得越来越准确,通过几次迭代就可以得到非常准确的解决方案。SUFE 概念非常有效,尤其是当网格粗糙且严重扭曲时。其优异的性能通过各种数值例子得到了证明。

更新日期:2021-08-24
down
wechat
bug