Identification of Swift Law Parameters Using FEMU by a Synthetic Image DIC-Based Approach

João Henriques, Mariana Conde, António Andrade-Campos, José Xavier

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)
46 Downloads (Pure)

Abstract

Computer-aided engineering systems rely on constitutive models and their parameters to describe the material behaviour. The calibration of more elaborated material models with a larger number of parameters becomes very time and cost consuming. The development of image-based technology has enhanced the interest in inverse identification methods, which, when coupled with full-field measurements, have the potential to reduce the number of experimental tests required to accurately identify material properties. This work aims to identify the Swift hardening law parameters of a dual-phase steel using a tensile test on a heterogeneous dogbone specimen under uniaxial and quasi-static loading conditions using the finite element model updating (FEMU) technique. The numerical results were used to generate synthetic images, which were then processed by digital image correlation (DIC) and used as the reference in the identification procedure. Two different approaches were tested: (i) directly comparing the numerical results to the reference; (ii) using DIC-levelled numerical data by iteratively generating synthetic images and using the DIC filter with the same settings as were used on the reference (virtual experiment). The identification results obtained from both approaches are compared and discussed.

Original languageEnglish
Title of host publicationAchievements and Trends in Material Forming
Subtitle of host publicationPeer-reviewed extended papers selected from the 25th International Conference on Material Forming, ESAFORM 2022
EditorsGabriela Vincze, Frédéric Barlat
Place of PublicationSwitzerland
PublisherTrans Tech Publications
Pages2211-2221
Number of pages11
ISBN (Electronic)978-303573750-9
ISBN (Print)978-303571759-4
DOIs
Publication statusPublished - 2022
Event25th International Conference on Material Forming, ESAFORM 2022 - Braga, Portugal
Duration: 27 Apr 202229 Apr 2022

Publication series

NameKey Engineering Materials
PublisherTrans Tech Publications Ltd
Volume926
ISSN (Print)1013-9826
ISSN (Electronic)1662-9795

Conference

Conference25th International Conference on Material Forming, ESAFORM 2022
Country/TerritoryPortugal
CityBraga
Period27/04/2229/04/22

Keywords

  • Digital Image Correlation
  • Finite Element Analysis
  • Finite Element Model Updating
  • Inverse Identification
  • Synthetic Image

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