FRACTURE PROCESSES IN CONCRETE STUDIED WITH SUBREGION SCANNING COMPUTER VISION

Abstract eng:
An understanding of the fracture process is necessary for design and utilization of quasi-brittle materials since cracking characterizes their failure. Subregion Scanning Computer Vision (SSCV) is an effective tool for observing these processes in an experimental setting. SSCV, based on Digital Image Correlation (DIC), is a full-field technique for quantitatively examining the development of cracks, with 0.5 micron resolution. DIC uses correlation matching to measure sub-pixel displacement in a sequence of digital images captured of a specimen undergoing failure. Using this technique, the complete behavior of specimens with multiple cracks at incremented levels of fracture can be investigated. SSCV improves on single-image DIC by dividing the specimen into 56 smaller subregions, each of which is imaged separately and so much improves measurement resolution. In this paper, examples of the results obtained in studies of crack growth in a model concrete under compressive loading and in a fiber-reinforced mortar under tensile loading are presented.

• Export as: BibTeX | MARC | MARCXML | DC | EndNote | NLM | RefWorks
• Add to your basket