ANN Backcalculation of Pavement Profiles from the SASW Test

Abstract

The SASW (spectral analysis of surface waves) test is a seismic technique for in situ evaluation of elastic moduli and layer thicknesses for layered systems such as pavements. The objective of the test is to obtain the experimental dispersion curve, and then through an inversion or backcalculation procedure to obtain the classic elastic modulus profile. This paper reports on an artificial neural network (ANN) that was developed to backcalculate accurately in real time pavement profiles from the SASW test collected data. The network was developed using synthetic dispersion curves from a numerical simulation of the SASW test. The most important feature of the developed network is that it consists of several neural network models used in evaluation of the thickness and elastic modulus of each individual layer.