Prediction of footing settlements with geogrid reinforcement and eccentricity

Abstract

This study presents settlement predictions for footings with geogrid reinforcement and biaxial eccentricity using multi-linear regression (MLR) and artificial neural network (ANN) methods. The effects of central, uniaxial and biaxial eccentric loading conditions on embedded and non-embedded square footings in unreinforced and reinforced soils were investigated with laboratory model tests given in the first part of the study. Variations in the bearing capacity were determined through vertical load versus settlement curves drawn after each test. In the second part of this study, MLR and ANN models used to predict settlement were improved using independent variables related with the footings and geogrid. The results showed that fluctuations in the datasets of the settlement were very well reflected by the ANN methods.