Performance of acoustic emission and digital image correlation for fracture analysis in cementitious mortars under fatigue loading

Abstract

Fatigue loading in brittle materials introduces damage at a micro-scale. These micro-fractures can accumulate and cause a significant reduction in material stiffness or even lead to structural failure. Deformation-based monitoring techniques can be inadequate when detecting damage at a micro-level. Hence, here is where advanced nondestructive testing (NDT) methods such as acoustic emission (AE) and digital image correlation (DIC) can play a great role. The paper aims to combine AE and DIC for advanced fatigue damage analysis on a cylindrical sample subjected to a fatigue Brazilian splitting test. The damage progress quantified from cumulative AE event count, and horizontal displacement measured with DIC showed a very good correlation. The damaged region was identified with an AE localization plot and with a DIC displacement field plot, the damaged area was well represented by both techniques. When a material goes through an irreversible change, part of the released energy will generate an elastic wave. The wave will propagate through the material and the whole phenomenon is termed an acoustic emission. By using AE sensors on the surface of the sample, these waves are captured and analyzed to better understand the source of the emission. Its high sensitivity to micro-changes makes it an ideal technique to use for fatigue damage investigation. Digital image correlation relates sequentially taken images to determine displacement and strain measurements. While DIC analyzes material evolution using surface deformation measurements, AE on the other hand is capable of monitoring damage inside the volume of material. Hence, their combination provides an efficient test setup for monitoring fatigue micro-fracture. The paper aims to combine AE and DIC for advanced fatigue damage analysis on cylindrical samples that are subjected to monotonic and fatigue Brazilian splitting tests. The analysis will use damage progress under monotonic loading as a reference to further understand fatigue fracture. Methods of AE data filtering and AE source localization are discussed and evaluated for their use in fracture analysis. The utilization of DIC to track the material stiffness evolution is investigated. In addition, the paper compares fracture process zones quantified by AE and DIC. From the experimental analysis, it was found that both methods captured the fatigue damage patterns, yet provided complementary information for damage evaluation.