Experimental and Numerical Analysis of the Vibration Behavior of a Bio-Based Sandwich with an Auxetic Core in a Humid Environment
Résumé
Acoustic emission (EA) has proven to be very suitable for detecting and monitoring cracking of materials and structures. EA signals can be analyzedeither based on physical considerations (geophysics/seismology) or using their temporal and frequency characteristics. However, the multitude ofdefinitions related to the different parameters as well as the treatment methods make it necessary to develop a comparative analysis in the case of aheterogeneous material such as civil concrete. To this end, this contribution aims to study the microcracking of reinforced concrete T-beamssubjected to quasi-static mechanical tests. To do this, four-point bending tests, carried out at different travel speeds, were carried out in the presence ofa network of acoustic emission sensors. A comparison between the damage susceptibility of three definitions corresponding to the parameter b-valuewas carried out and supplemented by the evolution of the RA value and the mean frequency (AF) as a function of loading time. This work also showsthe use of the support-vector machine (SVM) method to define different areas of damage in the load-displacement curve. This work shows the limitations of this approach and proposes the use of an unsupervised learning approach to group EA data according to physical parameters as well astime/frequency parameters. Finally, this work discusses the advantages and limitations of the different methods and parameters used in relation to the micro/macro mechanisms at the origin of concrete cracking.