ASSESSMENT OF 2D-DIC STOCHASTIC PATTERNS

Abstract

Cost of experimental testing of materials and structures subjected to mechanical loading often constitutes a significant portion of a project budget. Therefore a collection of data in a maximum possible amount is desirable. Extensometers and strain-gauges attached to the specimen surface often fail and cannot provide full-field information about the development of displacements and strains. Digital Image Correlation (DIC) is capable of providing such information. Unsuitable texture or artificially applied pattern, essential for DIC analysis, can spoil the DIC outcomes completely. An additional investment into preparation of new experimental testing can be avoided with the use of tools employing algorithms for stochastic pattern assessment. The development of such algorithms and their implementation into an open-source DIC software is the goal of the presented research.