Home > Research > Publications & Outputs > An ABAQUS® plug-in for generating virtual data ...

Electronic data

  • Manuscript_Final

    Rights statement: The final publication is available at Springer via http://dx.doi.org/10.1007/s00366-021-01525-1

    Accepted author manuscript, 1.77 MB, PDF document

    Available under license: CC BY: Creative Commons Attribution 4.0 International License

Links

Text available via DOI:

View graph of relations

An ABAQUS® plug-in for generating virtual data required for inverse analysis of unidirectional composites using artificial neural networks

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
  • Y. Ismail
  • L. Wan
  • J. Chen
  • J. Ye
  • D. Yang
Close
Article number5
<mark>Journal publication date</mark>31/10/2022
<mark>Journal</mark>Engineering with Computers
Issue number5
Volume38
Number of pages13
Pages (from-to)4323-4335
Publication StatusPublished
Early online date31/10/21
<mark>Original language</mark>English

Abstract

This paper presents a robust ABAQUS® plug-in called Virtual Data Generator (VDGen) for generating virtual data for identifying the uncertain material properties in unidirectional lamina through artificial neural networks (ANNs). The plug-in supports the 3D finite element models of unit cells with square and hexagonal fibre arrays, uses Latin-Hypercube sampling methods and robustly imposes periodic boundary conditions. Using the data generated from the plug-in, ANN is demonstrated to explicitly and accurately parameterise the relationship between fibre mechanical properties and fibre/matrix interphase parameters at microscale and the mechanical properties of a UD lamina at macroscale. The plug-in tool is applicable to general unidirectional lamina and enables easy establishment of high-fidelity micromechanical finite element models with identified material properties.