Inverse identification of in-situ curing shrinkage using a method combining 3D digital image correlation and finite-element simulation

Hongfan Yang, Aimin Wang, Huanxiong Xia*, Sihan Wang, Jianhua Liu, Xiaohui Ao, Yaowen Zhang, Jie Shi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Curing shrinkage of adhesives in the bonding process usually leads to deformation and residual stresses. The measurement of curing shrinkage is valuable in providing fundamental information for better understanding, controlling, and optimizing the curing process. This paper developed an efficient hybrid inverse identification method for in-situ measurement of the volume shrinkage. This method associates the artificial fish swarm algorithm (AFSA) with a finite element method (FEM) and 3D digital image correlation (3D-DIC) technology. A homemade apparatus for experimental characterization of curing shrinkage is prepared and tested. The evolution of the volume shrinkage is inversely identified by matching the 3D-DIC and the FEM results using the AFSA algorithm. The results are further validated by a direct-density measurement and the standard physical property of the adhesive. Those experimental results demonstrated that the proposed method is a viable non-contact, non-destructive, and in-situ technique that can be applied to measure the in-situ curing shrinkage.

Original languageEnglish
Article number113760
JournalMeasurement: Journal of the International Measurement Confederation
Volume223
DOIs
Publication statusPublished - Dec 2023

Keywords

  • 3D digital image correlation
  • Adhesive cure
  • Artificial fish swarm algorithm
  • Inverse identification
  • Volume shrinkage

Fingerprint

Dive into the research topics of 'Inverse identification of in-situ curing shrinkage using a method combining 3D digital image correlation and finite-element simulation'. Together they form a unique fingerprint.

Cite this