For deep excavations in residual soils that are underlain by highly fissured or fractured rocks, it is common to observe the drawdown of the groundwater table behind the excavation, resulting in seepage-induced ground settlement. In this study, finite element analyses are firstly performed to assess the critical parameters that influence the ground settlement performance in residual soil deposits subjected to groundwater drawdown. The critical parameters that influence the ground settlement performance were identified as the excavation width, the excavation depth, the depth of groundwater drawdown, the thickness of the residual soil, the average SPT N value of the residual soil, the location of the moderately weathered rock, and the wall system stiffness. Subsequently, an artificial neural network (ANN) model was developed to provide estimates of the maximum ground settlement. Validation of the performance of ANN model was carried out using additional data derived from finite element analyses as well as with measured data from a number of excavation sites.
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