Acoustic Emission (AE) is revealed to be highly adapted to monitor materials and structures in materials research and for site monitoring. AE-features can be either analyzed by means of physical considerations (geophysics/seismology) or through their time/frequency waveform characteristics. However, the multitude of definitions related to the different parameters as well as the processing methods makes it necessary to develop a comparative analysis in the case of a heterogeneous material such as civil engineering concrete. This paper aimed to study the micro-cracking behavior of steel fiber-reinforced reinforced concrete T-beams subjected to mechanical tests. For this purpose, four-points bending tests, carried out at different displacement velocities, were performed in the presence of an acoustic emission sensors network. Besides, a comparison between the sensitivity to damage of three definitions corresponding to the b-value parameter was performed and completed by the evolution of the RA-value and average frequency (AF) as a function of loading time. This work also discussed the use of the support-vector machine (SVM) approach to define different damage zones in the load-displacement curve. This work shows the limits of this approach and proposes the use of an unsupervised learning approach to cluster AE data according to physical and time/frequency parameters. The paper ends with a conclusion on the advantages and limitations of the different methods and parameters used in connection with the micro/macro tensile and shear mechanisms involved in concrete cracking for the purpose of in situ monitoring of concrete structures.

Moisture accumulation and life span in a hydric setting are major concerns for natural fibers used for the reinforcement of bio-based composites. This article discusses the effect of water aging on the mechanical properties of poly-lactic acid composites reinforced with flax fibers produced by 3D printing. Water absorption of composites is measured and it was observed that the bio-based composite seems to be Fick’s model with a percentage of absorption at saturation equal to 1.2%. To determine the effect of water absorption on static and vibration mechanical properties, various immersion periods are chosen. Water aging obviously influences the stiffness and tensile failure; so, a decline in the Young’s modulus from 2.2 to 1.7 GPa and in strength from 36 to 30.5 MPa is seen. Nevertheless, the damping factor shows an increase by about 16% as a function of the immersion period. These results could be explained by the plasticizing effect of water on bio-based composites, stimulated by moisture absorption.

The detection and location of pipeline leakage can be deduced from the time arrival leak signals measured by acoustic sensors placed at the pipe. Ongoing research in this field is primarily focused on refining techniques for accurately estimating the time delays. This enhancement predominantly revolves around the application of advanced signal processing methods. Additionally, researchers are actively immersed in the utilization of machine learning approaches on vibro-acoustic data files, to determine the presence or absence of leaks. Less attention has been given to evaluating the sensitivity, performance, and overall effectiveness of these sensors in leak detection; although acoustic methods have been successfully used for leak detection in metallic pipes, they are less effective in plastic pipes due to the high attenuation of leak noise signals. The primary thrust of this research centers on identifying sensors that not only possess sensitivity but also exhibit high efficiency. To accomplish this goal, we conducted an exhaustive evaluation of the performance of three distinct categories of acoustic sensors employed for detecting water leaks in plastic pipes: specifically, lead zirconate titanate (PZT) sensors, polyvinylidene fluoride (PVDF) sensors, and surface acoustic wave (SAW) sensors. Our evaluation encompassed the performance of PVDF and SAW sensors in leak detection, comparing them to PZT sensors under a variety of conditions, including different leak sizes, flow rates, and distances from the leak. The results showed that all three sensors, when they were placed in the same position, were able to detect water leaks in plastic pipes with different sensitivities. For small leaks (1 mm, 2 mm), the PVDF sensor showed the greatest sensitivity (0.4 dB/L/h, 0.33 dB/L/h), followed by the SAW sensor (0.16 dB/L/h, 0.14 dB/L/h), and finally the PZT (0.13 dB/L/h, 0.12 dB/L/h). Similarly, for larger leaks (4 mm, 10 mm), the PVDF sensor continued to show superior sensitivity (0.2 dB/L/h, 0.17 dB/L/h), followed by the SAW sensor (0.13 dB/L/h, 0.11), and finally the PZT sensor (0.12 dB/L/h, 0.1 dB/L/h), outperforming the PZT sensor. This suggests that SAW and PVDF sensors, have the potential to serve as valuable, cost-effective alternatives to traditional commercial leak noise transducers. The outcomes of this comparative study involving three acoustic sensors hold the potential to advance the development of robust and dependable systems for the detection of water leaks in plastic pipelines.

This work presents the development of an ultrasonic method based on the use of multiple-scattered waves to detect and image microcracks in polymer concrete samples under steady-state bending vibrations. The sensitivity of the multiple-scattered waves to microcracks revealed to be dependent on the plane in which bending vibrations were excited. In order to understand the origin of such a sensitivity, acoustic emission measurements were performed under the same vibration conditions to verify the existence of a structural anisotropy related to microcrack distribution. Results revealed that, depending on the considered plane, acoustic emission signatures are very different and therefore can be used to understand the involved mechanisms and to identify the vibration planes that offer the optimal imaging conditions.

In mechanics of material and material sciences, the early detection of damage, its non destructive characterisation and monitoring is of great importance. In this field, ultrasonic waves can he very helpful especially when nonlinear ultrasonics is considered. In this work, linear and non linear ultrasonics are used for damage characterisation. Concerning linear ultrasonics, we show that velocity and linear elastic constants are good damage indicators for composites materials. For these materials, ultrasonic velocity is measured in situ during a tensile test, at the same time acoustic emission is collected. Ultrasonic velocity decreases with damage. This decrease is very well correlated to the acoustic activity due to damage initiation and development. For other materials as metallic ones, linear ultrasonics is not sensitive enough for damage characterisation. In this case we show that nonlinear ultrasonics through the nonlinearity parameter ß, is very sensitive to evaluate damage and to detect it very early. In this work we show that if linear ultrasonics through velocity measurements is a very good damage indicator especially for composite materials, nonlinear ultrasonics can he a very efficient tool for the early detection of damage and also for health monitoring. So it can greatly contribute to the understanding of damage initiation.