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

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 insitu 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.

Automated summary

This study developed an efficient hybrid inverse identification method for in-situ measurement of curing shrinkage of adhesives. By combining artificial fish swarm algorithm, finite element method, and 3D digital image correlation technology, the non-contact and non-destructive measurement of curing shrinkage was achieved.