This study focuses on deformability and damage detection of a concrete masonry wall. It employed point-to-point traditional strain gages and full-field measurement technique using digital image correlation (DIC) to investigate the damage and deformability of a partially grouted (PG) reinforced masonry wall. A set of ungrouted and grouted assemblages and full-scale concrete masonry shear wall were constructed and tested under displacement control loading. The wall was constructed according with masonry standards joint committee (MSJC 2013) and tested under constant vertical compression load and horizontal lateral load using quasi-static displacement procedure. The DIC method was used to determine non-uniform strain contours on the assemblages. This method was verified by comparing strains along the selected directions with traditional TML gage results. After a successful comparison, the method was used to investigate the state of damage and deformability of the wall specimen. Panel deformation, crack pattern, displacement at the top, and the base strain of the wall were captured using full-field measurement and results were in a good agreement with traditional strain gages. It is concluded that full-filed measurements using DIC is promising especially when the test specimens experience inelastic deformation and high degree of damage. The ability to characterize and anticipate failure mechanisms of concrete masonry systems by depicting strain distribution, categorizing structural cracks and investigating their effects on the behavior of the wall were also shown using DIC. In addition to monitoring strains across the gage length, the DIC method provided full-field strain behavior of the test specimens and revealed strain hotspots at locations that corresponded to failure.
This paper represents a hybrid non-destructive testing (HNDT) approach based on infrared thermography (IRT), acoustic emission (AE) and ultrasonic (UT) techniques for effective damage quantification of partially grouted concrete masonry walls (CMW). This integrated approach has the potential to be implemented for the health monitoring of concrete masonry systems. The implementation of this hybrid approach assists the cross validation of in situ recorded information for structural damage assessment. In this context, NDT was performed on a set of partially grouted CMW subjected to cyclic loading. Acoustic emission (AE) signals and Infrared thermography (IRT) images were recorded during each cycle of loading while the ultrasonic (UT) tests were performed in between each loading cycle. Four accelerometers, bonded at the toe of the wall, were used for recording waveforms for both passive (AE) and active (UT) acoustics. For the active approach, high frequency stress waves were generated by an instrumented hammer and the corresponding waveforms were recorded by the accelerometers. The obtained AE, IRT, and UT results were correlated to visually confirm accumulated progressive damage throughout the loading history. Detailed post-processing of these results was performed to characterize the defects at the region of interest. The obtained experimental results demonstrated the potential of the methods to detect flaws on monitored specimens; further experimental investigations are planned towards the quantitative use of these NDT methods.
Reliable damage detection and quantification is a difficult process because of its dynamic and
multi-scale nature, which combined with material complexities and countless other sources of
uncertainty often inhibits a single non-destructive testing (NDT) technique to successfully
evaluate the extension of deterioration in critical structural components. This paper presents an
integrated non-destructive testing approach (INDT) for effective damage identification relying
on the intelligent integration of the Acoustic Emission (AE), Guided Ultrasonic Waves (GUW)
and Digital Image Correlation (DIC) methods. The proposed system has been utilized to identify
wire breaks in seven-wire steel strands and crack initiation and development in masonry concrete
walls and is based on the cross-correlation of heterogeneous damage-related NDT features.
Conventional AE monitoring relies on damage monitoring by evaluating multiple extracted
and/or computed features as a function of load/time. In addition, advanced post-processing
methods including mathematical algorithms for statistical analysis and classification have been
suggested to improve the robustness of AE in damage identification. Unfortunately, such
approaches are often found to be unsuccessful, due to challenging environmental and operational
conditions, as well as when used on actual civil structural components, such as bridge cables and
masonry walls. This paper presents the framework for successful correlation of AE features with
GUW and mechanical parameters such as full field strain maps, which can provide a route
towards actual cross-validated damage assessment, capable to detect the initiation and track the
development of damage in structures. The presented INDT approach could lead to reliable
damage identification approaches in mechanical, aerospace and civil infrastructure applications.