In-situ On-demand Digital Image Correlation: A New Data-rich Characterization Paradigm for Deformation and Damage Development in Solids

TL;DR

This work introduces in-situ on-demand (ISOD) DIC, a data-rich deformation characterization paradigm that couples camera frame-rate control with a Lucas–Kanade optical flow core to enable real-time, full-field displacement and strain measurement. The method uses a batch-wise workflow, computing DIC between batch endpoints and adaptively adjusting imaging frame rates based on deformation metrics, which substantially increases data capture during damage events while controlling storage and processing demands. Validation against a commercial DIC system shows high accuracy (mean/max strain agreement with ~0.89% error) and application to nacre-inspired biomimetic specimens demonstrates clear strain localization and enhanced damage insights, with up to ~178% more images captured during crack growth compared to conventional DIC. The approach promises improved constitutive and damage mechanism characterization in solids, with potential extensions to multi-sensor closed-loop systems and real-time digital twins.

Abstract

Digital image correlation (DIC) has become one of the most popular methods for deformation characterization in experimental mechanics. DIC is based on optical images taken during experimentation and post-test image processing. Its advantages include the capability to capture full-field deformation in a non-contact manner, the robustness in characterizing excessive deformation induced by events such as yielding and cracking, and the versatility to integrate optical cameras with a variety of open-source and commercial codes. In this paper, we developed a new paradigm of DIC analysis by integrating camera control into the DIC process flow. The essential idea is to dynamically increase the camera imaging frame rate with excessive deformation or deformation rate, while maintaining a relatively low imaging frame rate with small and slow deformation. We refer to this new DIC paradigm as in-situ on-demand (ISOD) DIC. ISOD DIC enables real-time deformation analysis, visualization, and closed-loop camera control. ISOD DIC has captured approximately 178% more images than conventional DIC for samples undergoing crack growth due to its dynamically adjusted frame rate, with the potential to significantly enhance data richness for damage inspection without consuming excessive storage space and analysis time, thereby benefiting the characterization of intrinsic constitutive behaviors and damage mechanisms

Figures (14)

• Figure 1: Schematic representation for displacement calculation of a pixel.
• Figure 2: Workflow of ISOD DIC.
• Figure 3: Batch-wise feedback-controlled ISOD DIC characterization.
• Figure 4: The experimental setup with the ISOD DIC.
• Figure 5: Aluminum sample with different ROIs: (a) global ROI, (b) ROI 1, (c) ROI 2, (d) ROI 3.