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Self-updated four-node finite element using deep learning

delete2021-08-24
delete18
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OA
AI
J
Jaeho Jung
H
Hyungmin Jun
P
Phill‐Seung Lee *
DOI:10.1007/s00466-021-02081-7delete
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Abstract

Abstract

En 中文
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.
Keywords:
Self-updated element
Finite element method
Four-node element
Shear locking
Kinematic modes
Deep learning
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Journal

Computational Mechanics cover
Computational Mechanics
IF:
3.8
Papers:
3.2K
Citations:
9.0K

Organization

J
Jeonbuk National University
Scholars:
1.3W
Papers: 1.3W
Citations: 1.3W