Digital image correlation analysis of alkali silica reaction in concrete with recycled glass aggregate

Abstract

Digital image correlation (DIC) is an effective tool for measuring the in-plane displacement and full-field strain of the surface of an object. DIC can be implemented as a low-cost non-destructive technique using a time series of images of the object of interest. The advantages of DIC inspires the application in studies of concrete alkali silica reaction (ASR). In this study, a MATLAB DIC code is employed as a strain measurement method to enhance the ASTM C1260 Standard Test Method for Potential Alkali Reactivity of Aggregates (Mortar-Bar Method). Recycled glass is used as the aggregate source in four mortar mixtures used in this study. For each batch, during the 14 days accelerated ASR test, digital images of the surface of the mortar bars are captured every 30 minutes. The images are then processed to measure the in-plane strain field, and the results are compared to physical measurement of length change. This thesis examines the effectiveness of the MATLAB DIC code and the possibility of using the code in studies of ASR based on digital images of the mortar bar surface. This includes a throughout review of the basic algorithm of the MATLAB DIC code. A series of algorithm-induced errors are analyzed. Then, in order to improve accuracy of the strain measurement in the ASR study, the subset size, which is a most critical parameter in terms of accuracy, is optimized through correlating the strain results from the MATLAB code and dial gauge. The optimum subset size is used for the in-plain strain and strain field analysis.