Digital Image Correlation (DIC) is an analytical technique that compares images of a specimen’s surface during testing to generate full-field strain maps. This technology gives you more information than a traditional point-to-point extensometer or a strain gauge and allows you to see the complete story of the material’s behavior beyond the stress strain curve.
Scientists and engineers have found dozens of useful applications
for DIC including detecting cracks invisible to the naked eye, visualizing localized
necking and discontinuous yielding, comparing differences in material behavior
between two separate formulations, and analyzing strain on parts or components
where a traditional extensometer is not feasible.
In our lab, we recently performed a test to ASTM standard D5766 for the open-hole tensile strength of polymer matrix composites and used DIC to see exactly where the strain was occurring. Using DIC, we were able to visualize where the strain on the specimen was concentrated and how it propagated through the material.
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I am pursuing Ph.D. degree thesis entitled, “Analysis of failure process of geomaterials using extended digital image correlation technique” at Indian Institute of Technology, Kharagpur, India.
My current research covers on the development of non-contact based system for monitoring of failure mechanism of geomaterials under loading conditions. I have developed a high precision digital image correlation algorithm and checked its accuracy by conducting numerical analysis. I have further extended my work to check the applicability of the developed algorithm in experimental domain. I have developed a complete system for collecting high precision data and solved the problem for generating speckle pattern on the surface of experimental sample. I have developed an automatic damage detection and classification algorithm which will help to measure the deformation/strain produced on the surface of a sample having discontinuities. I have analysed the experimental data and developed an algorithm for generating pre-failure signature of material well before time.
Now I am looking for a collaboration with a company to commercialize our technology.
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