| About this Abstract |
| Meeting |
Materials Science & Technology 2020
|
| Symposium
|
Micro- and Nano-Mechanical Behavior of Materials
|
| Presentation Title |
Computer Vision Approach to Study Surface Deformation of Materials |
| Author(s) |
Chaoyi Zhu, Haoren Wang, Kevin Kaufmann, Kenneth Vecchio |
| On-Site Speaker (Planned) |
Chaoyi Zhu |
| Abstract Scope |
Characterization of the deformation of materials across different length scales has continuously attracted enormous attention from the mechanics and materials communities. In this study, the possibility of utilizing a computer vision algorithm to extract deformation information of materials has been explored, which greatly expands the use of computer vision approaches to studying mechanics of materials and potentially opens new dialogues between the two communities. The computer vision algorithm is first developed and tested on computationally deformed images before evaluating experimentally collected images on speckle painted samples before and after deformation. Experimental validation experiments include evaluating the performance of strain mapping in a uniaxial tensile test and a three-point bending test, compared with extensometer reading and digital image correlation respectively. |