Waveform simulation and source characterization of acoustic emissions in concrete tensile fracture processes
A lattice modelling approach
Y. Zhou (TU Delft - Concrete Structures)
M.A.N. Hendriks – Promotor (TU Delft - Engineering Structures)
Y. Yang – Promotor (TU Delft - Concrete Structures)
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Abstract
To prevent catastrophic structural failures, it is essential to monitor the condition of aging concrete structures and provide early warnings that enable timely mainte-nance and repair. Structural health monitoring (SHM) of concrete structures has attracted considerable attention in the research community. Among various SHM techniques, acoustic emission (AE) has emerged as a particularly effective method for early fracture detection, owing to its real-time monitoring capabilities and sen-sitivity to early crack formation.
However, a comprehensive review of the mechanisms and models related to AE phenomena in concrete fracture (Chapter 2) reveals ongoing challenges in applying AE reliably. A key difficulty lies in accurately correlating localized fracture events with AE signals recorded after wave propagation through complex structural media. Both experimental inversion and forward modelling approaches have been ex-plored to address this issue. Nevertheless, experimental techniques face inherent limitations due to complex wave propagation effects and sensor responses. Fur-thermore, existing modelling methods are not yet capable of explicitly simulating AE signals generated by concrete fracture.
This dissertation aims to investigate the source mechanisms underlying AE phe-nomena induced by concrete fracture and to establish a quantitative relationship between localized fracture events and the resulting AE signals. The overarching goal is to enhance the reliability of AE-based techniques for early warning applica-tions in concrete structures. Particular attention is given to AE signals generated by tensile cracking, which is the dominant source of AE activity, especially in the early stages of fracture when timely warnings are most critical.