One of the most important parameters to evaluate layered systems, like pavements, is the modulus of elasticity. Efforts have been made towards modulus evaluation using in situ nondestructive testing (NDT), in particular using the air-coupled spectral-analysis-of-surface-waves (SASW) method. The air-coupled SASW is an extension of the traditional SASW method, where the leaky surface waves are detected using non-contact sensors, instead of the Rayleigh waves using contact sensors. The main objective of this study is to develop an automated system for pavement modulus profiling using air-coupled acoustic testing. A numerical simulation of the air-coupled SASW test was conducted using finite elements. Several hundred hypothetical pavement configurations were used to develop an extensive database of surface wave dispersion curves. The database was further used to develop an artificial neural network (ANN) for an automated pavement modulus backcalculation. Good performance of the developed ANN in the inversion of surface wave data is demonstrated on several pavement profiles.
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