Acoustic emission (AE) is commonly utilized for the characterization of the damage condition of construction materials and structures. The damage mechanisms generate elastic signals with unique characteristics that enable their identification, a phenomenon observed across various fields like cementitious materials, masonry, polymer composites, and metals. Additionally, AE's sensitivity allows for the detection of indicators even prior to visible signs of damage, thereby providing early data for structural health monitoring. Recent findings have demonstrated that early AE parameters are correlated to the original strain field, enabling projections regarding the final dominant damage or fracture mode. This capability enhances real-time evaluations of material conditions before the load-bearing capacity is compromised and holds promise for in-situ applications. This study emphasizes emerging trends that illustrate the potential of integrating AE with other techniques to effectively monitor and predict the behavior of structural materials. Examples are taken from the complicated behavior of lightweight fiber-reinforced cementitious sandwich panels during bending, as well as fresh concrete curing with a plethora of mechanisms including shrinkage cracking.

This study investigates the evolution of fracture process zone (FPZ) in ultra-high performance fiber reinforced concrete (UHPFRC) using the acoustic emission (AE) technique. An important factor contributing to the fracture energy in concrete is the nucleation of its FPZ. The examination of FPZ helps in understanding the initiation and propagation of cracks in a material. The influence of different toughening mechanisms within the FPZ helps in predicting the structural integrity and performance of a material when subjected to an external loading. Thus, it is essential to investigate the evolution process of FPZ. In order to determine it, three-point bending tests with monotonic loading are performed on three notched beam specimen groups: ultra-high performance concrete (UHPC) without fibers, UHPFRC with 2% (by volume percentage of concrete, (V_f)) straight micro-fiber, and a hybrid UHPFRC with 1% (V_f) straight micro-fibers and 1% (V_f) straight macro-fibers. Straight micro-steel fibers of 13 mm length and 0.2 mm diameter and straight macro-steel fiber of 26 mm length and 1 mm diameter have been used for the study. An AE parameter based on Shannon’s entropy is used to examine the evolution of FPZ. The AE entropy performed more efficiently compared to the other conventional AE parameters on account of it being independent of threshold, and being more sensitive to changes in AE signal irregularities. It is observed that the entropy distribution is greatly influenced by the presence of fibers, indicating a more controlled and distributed cracking process in UHPFRC compared to the brittle behaviour of UHPC without fibers. It is also observed that the FPZ width decreases when straight micro-fibers is partially replaced with straight macro-fibers.

The fracture assessment of concrete and concrete composites using Digital Image Correlation (DIC) and Acoustic Emission (AE) techniques is commonly performed on small-scale laboratory specimens, with findings then extrapolated to large-scale structures. DIC provides detailed surface displacement and macrocrack visualization, while AE offers real-time tracking of micro and macro cracks. However, in real-world scenarios, factors such as structural geometry, variations in loading and background noise can significantly affect AE and DIC data, making interpretation challenging. This study examines small-scale standard notched Steel Fiber Reinforced Concrete (SFRC) beams and large-scale precast SFRC tunnel segments under three-point bending (3PB) to conduct a comparative analysis of fracture behaviour. The influence of tunnel geometry, casting methods, and loading conditions on fracture behaviour is emphasized. The similarities and differences in fracture mechanisms between small-scale beams and large-scale tunnel segments are identified.

The fracture process in concrete is a collaborative process among the micro-cracks originating ahead of the crack tip under the applied load, and influenced by the constituent heterogeneity. To understand this interactive phenomenon, statistical physics-based theories are very applicable, and by treating each micro-crack as an energy source, the whole process can be remodeled into a phase space. This study aims to investigate the sparsity of micro-cracking in concrete subjected to fatigue and monotonic loadings by utilizing the fractal signatures of the phase space constructed from the acoustic emission parameters. The correlation dimension of the acoustic emission energy time series generated from concrete for both types of loading is obtained separately using the Grasserberger-Proccacia algorithm. The results indicate that concrete under fatigue has a lower correlation dimension than the monotonic case, explaining that fatigue is a process where one crack causes failure, unlike the monotonic case, where it is a cooperative phenomenon. The correlation dimension can also capture the influence of cycling frequency on the fatigue life, showing an increment with the increase in frequency. The efficiency of this method can be enhanced by choosing the appropriate dimension of the underlying phase space of the time series and, therefore, can preferably employed to estimate the health of a real-life structure over conventional methods like event source localization.

This article presents the application of natural time analysis of acoustic emission (AE) to detect impending fracture in ultra high performance concrete (UHPC). The UHPC beams with and without coarse aggregate were made and subjected to a three-point bending test. Simultaneously, the generated AE were recorded using an eight channel AE monitoring system. The parameters, namely, variance (κ1), entropy (S), and entropy under time reversal (S ), were studied in natural time domain. All these parameters simultaneously reached their critical values and fluctuated within the time window corresponding to the region of criticality. The critical conditions of the parameters were accompanied by a significant increase in cumulative AE energy, which resembled the Olami-Feder-Christensen earthquake model. Furthermore, change in entropy (ΔS) was minimized before the mainshock event, thus indicating the imminent major event. Therefore, κ1, S, S , and ΔS could be utilized as precursors for detecting impending macroscopic fracture in cementitious composites.