Traffic produces vibrations and noise that affect the livability and structural integrity of the built environment. Despite the fact that many studies focused on traffic-induced vibrations and noise, there is a lack of studies linking the vibrations propagating into the road pavement and the related acoustic response (or acoustic signature) as a means to assess the structural health status. Indeed, monitoring this response can lead to an estimation of the road layer structural condition and an identification of cracks that occurred because of the traffic. Consequently, the objectives of this study are to (i) model the involved phenomena through a Finite Element Method (FEM) analysis; (ii) compare data and simulations; and (iii) set up an Extended Finite Element Model (EXFEM) that is able to forecast the change of the road acoustic signature over time because of the presence of occurred cracks. Loads and sound-related phenomena (generation, transmission, interaction with cracks) were simulated through an EXFEM software. In addition, in order to estimate the effectiveness of the study, the aforementioned simulations were compared with real data gathered from a Dense Graded Friction Course road pavement in different and controlled structural conditions through a specially designed, microphone-based electronic system. Even if further studies are needed to better fix the measurement chain and better carry out the FEM analyses, preliminary results show that the EXFEM model is able to reproduce, with good approximation, the measured signals and that this model can be used to forecast the effects of different types of cracks on the propagation of vibration into road pavements

The prediction of road cracks through acoustic signature: Extended finite element modeling and experiments / Fedele, Rosario; Pratico', Filippo Giammaria; Pellicano, Gianfranco. - In: JOURNAL OF TESTING AND EVALUATION. - ISSN 0090-3973. - 49:4(2021), pp. 2942-2963. [10.1520/JTE20190209]

The prediction of road cracks through acoustic signature: Extended finite element modeling and experiments

Rosario Fedele
;
Filippo Giammaria Pratico';
2021-01-01

Abstract

Traffic produces vibrations and noise that affect the livability and structural integrity of the built environment. Despite the fact that many studies focused on traffic-induced vibrations and noise, there is a lack of studies linking the vibrations propagating into the road pavement and the related acoustic response (or acoustic signature) as a means to assess the structural health status. Indeed, monitoring this response can lead to an estimation of the road layer structural condition and an identification of cracks that occurred because of the traffic. Consequently, the objectives of this study are to (i) model the involved phenomena through a Finite Element Method (FEM) analysis; (ii) compare data and simulations; and (iii) set up an Extended Finite Element Model (EXFEM) that is able to forecast the change of the road acoustic signature over time because of the presence of occurred cracks. Loads and sound-related phenomena (generation, transmission, interaction with cracks) were simulated through an EXFEM software. In addition, in order to estimate the effectiveness of the study, the aforementioned simulations were compared with real data gathered from a Dense Graded Friction Course road pavement in different and controlled structural conditions through a specially designed, microphone-based electronic system. Even if further studies are needed to better fix the measurement chain and better carry out the FEM analyses, preliminary results show that the EXFEM model is able to reproduce, with good approximation, the measured signals and that this model can be used to forecast the effects of different types of cracks on the propagation of vibration into road pavements
2021
Acoustic signature, Cracks, Extended Finite Element Model, Noise, Pavement Structural health monitoring, Vibration
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/58188
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