Using FEM-AI Technique to Predict the Behavior of Strip Footing Rested on Undrained Clay Layer Improved with Replacement and Geo-Grid

The objective of this research is to predict how strip footings behave when rested on an undrained clay layer enhanced using a top replacement with and without geo-grid. study was conducted in several stages, including collecting load-settlement curves from "Finite Element Method" (FEM) models different strengths, thicknesses, axial stiffnesses the These were then idealized hyperbolic model, parameters predicted three AI techniques. According numerical results, ultimate bearing pressure pure found be five times strength clay. findings align most established empirical capacity formulas for clays. results also suggest that initial modulus subgrade reaction solely influenced by thickness. Additionally, enhancement due decreases increasing strength. However, percentage improvement decreased higher Moreover, impact geo-grid significant settlement beyond 50mm, it more impactful soft than stiff Finally, proposed predictive employing "Genetic Programming" (GP), "Artificial Neural Networks" (ANN), "Evolutionary Polynomial Regression" (EPR) techniques, these exhibited accuracy about 88%. Doi: 10.28991/CEJ-2023-09-05-014 Full Text: PDF