Integrated Digital Image Correlation for Micro-Mechanical Parameter Identification in Multiscale Experiments

TL;DR

This paper presents an integrated multiscale experimental and computational approach using Digital Image Correlation to accurately identify micromechanical parameters in heterogeneous materials, addressing challenges of scale, noise, and normalization.

Contribution

It introduces combined multiscale methods with IDIC for parameter normalization, improving accuracy and robustness in microstructural material characterization.

Findings

Effective normalization of microstructural parameters achieved

Enhanced robustness against image noise demonstrated

Relaxed scale separation requirements validated

Abstract

Micromechanical constitutive parameters are important for many engineering materials, typically in microelectronic applications and material design. Their accurate identification poses a three-fold experimental challenge: (i) deformation of the microstructure is observable only at small scales, requiring SEM or other microscopy techniques; (ii) external loadings are applied at a (larger) engineering or device scale; and (iii) material parameters typically depend on the applied manufacturing process, necessitating measurements on material produced with the same process. In this paper, micromechanical parameter identification in heterogeneous solids is addressed through multiscale experiments combined with Integrated Digital Image Correlation (IDIC) in conjunction with various possible computational homogenization schemes. To this end, some basic concepts underlying multiscale approaches available in the literature are first reviewed, discussing their respective advantages and disadvantages from the computational as well as experimental point of view. A link is made with recently introduced uncoupled methods, which allow for identification of material parameter ratios at the microscale, still lacking a proper normalization. Two multiscale methods are analysed, allowing to bridge the gap between microstructural kinematics and macroscopically measured forces, providing the required normalization. It is shown that an integrated experimental--computational scheme provides relaxed requirements on scale separation. The accuracy and performance of the discussed techniques are analysed by means of virtual experimentation under plane strain and large strain assumptions for unidirectional fibre-reinforced composites. The robustness against image noise is also assessed.