Self-updated four-node finite element using deep learning

  • Jaeho Jung
  • , Hyungmin Jun
  • , Phill Seung Lee*
  • *Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)23-44
Number of pages22
JournalComputational Mechanics
Volume69
Issue number1
DOIs
StatePublished - 2022.01

Keywords

  • Deep learning
  • Finite element method
  • Four-node element
  • Kinematic modes
  • Self-updated element
  • Shear locking

Quacquarelli Symonds(QS) Subject Topics

  • Earth & Marine Sciences
  • Engineering - Mechanical
  • Computer Science & Information Systems
  • Mathematics
  • Geophysics
  • Engineering - Petroleum
  • Engineering - Mineral & Mining

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