Application of digital image correlation to derive Paris' law constants in granite specimens

Abstract

This study investigates the effectiveness of Digital Image Correlation (DIC) as a powerful tool for deriving Paris' law constants in black granite specimens subjected to cyclic loading. A series of monotonic and cyclic loading tests on rectangular granite specimens yields valuable insights into geological material fatigue behavior, establishing monotonic tests as foundational references for subsequent cyclic loading experiments. Innovative DIC software application enables precise tracking and analysis of Crack Mouth Opening Displacement (CMOD) values, revealing distinct, observable patterns in crack growth during cyclic loading. A notable contribution lies in the implementation of a compliance calibration technique integrating Finite Element Method (FEM), facilitating the direct linkage between CMOD values and effective crack lengths, resulting in highly accurate Paris' law constants. With an average of 1.04 E −7 for C and 8.95 for m, these constants are essential for predicting fatigue crack propagation in granite specimens. This research underscores DIC's efficacy as a pivotal fatigue analysis tool, enhancing predictive capabilities for structural safety and durability assessments in geological materials, while emphasizing the crucial role of advanced imaging and numerical techniques in material science and structural engineering. It lays a robust foundation for future geological material studies and comprehensive structural integrity assessments.