3D Stereo Adaptive Mesh Augmented Lagrangian Digital Image Correlation

Abstract Background: 3D Stereo Digital Image Correlation (3D stereo-DIC) is a powerful experimental tool for measuring full-field, three-dimensional surface deformations, especially for non-planar surfaces or out-of-plane displacements. By capturing and comparing digital images of speckle-patterned samples before and after deformation, stereo-DIC can resolve full-field displacement and strain fields. Objective: However, current post-processing methods in stereo-DIC are less robust compared to 2D DIC, particularly when dealing with heterogeneous deformation fields in complex geometries or with discontinuities. To address these challenges, we recently developed a novel hybrid local subset and global-DIC post-processing algorithm, called the Augmented Lagrangian Digital Image Correlation (ALDIC) method, which ensures global kinematic compatibility while maintaining computational efficiency, and conveniently applies to adaptive meshes. Methods: ALDIC has already demonstrated strong robustness and precision in 2D applications. Building on this progress, here we extend this framework to 3D, presenting the 3D Stereo Augmented Lagrangian Digital Image Correlation (stereo-ALDIC). To further enhance performance, we implemented cumulative and incremental tracking modes to resolve both small and large deformations. Additionally, the integration of an adaptive quadtree mesh allows the method to handle complex geometries with ease. Results: Through various case studies, we demonstrate that stereo-ALDIC outperforms conventional local subset-based stereo-DIC methods in both accuracy and robustness, offering significant advancements for 3D measurement. An open-source MATLAB implementation is freely available.