Digital Image Correlation (DIC) System for Assessment of Critical Infrastructure and Digital Twin

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Experimental testing provides the ground truth to understand the behavior of different structural components and systems under various dynamic loading conditions. It is a challenging task to identify and understand the governing modes of failure in large, complex structures that are subjected to extreme loads. Well thought-out experiments can be extremely valuable in understanding material/structural behavior. However, the data that can be gathered from a single test is limited mainly due to conventional point-based sensor technology, which only allows measurements at a limited number of discrete points. This can be particularly restrictive when considering unique, complex and costly experiments in which collecting the maximum amount of relevant data is desirable. Digital image correlation (DIC) technique can be a viable alternative for advanced non-contact sensing. As opposed to conventional instruments, DIC gives access to full displacement/strain fields on the entire surface of large-scale structures at various critical stages of loading, from the initiation of damage to its progression until complete failure. The requested DIC system will be used by a group of interdisciplinary researchers in the Schulich School of Engineering at the University of Calgary. The equipment is targeted for pursuing research on new generation structural materials and systems, instrumentation for structural health monitoring of Canadian infrastructure, 3D data registration and feature extraction from point cloud data. The objectives of the proposed research programs are to uncover the coupled complex threats of multi-hazard on civil infrastructure, mechanistic studies of decommissioned pipelines, digital twin and smart monitoring of transportation infrastructure, and measurement of the growth of reindeer antlers. The ongoing and planned research are both timely and beneficial, as the activities proposed by the applicants and their team would support and drastically improve current monitoring and bridge design strategies. The research outcomes will provide valuable input for resilient and sustainable bridge design practice in Canada and advanced tools for digital twin for monitoring of civil infrastructure. Industry partners and bridge code committees are eagerly awaiting the research outcomes from these research studies to generate relevant design provisions. Acquisition of the new 3D-DIC will help move the current research forward, launch new research projects, and enhance opportunities for collaboration. It will permit collection of extensive data for the development of new knowledge and better understanding of structural behavior, advance monitoring of critical infrastructure as well as tracking the growth of wildlife through image processing. Above all, the top priority is advancing the research projects of the applicants' large number of graduate students and trainees by upgrading the existing outdated data acquisition system with the requested DIC system.