A comparison of experimental and computational methods for circular footing response on lime-treated geotextile reinforced silty sand

Civil and geotechnical engineers have tremendous difficulty in addressing soil stability and integrity problems while limiting settlement and building costs. Ground improvement approaches employing geosynthetics as reinforcement has gained popularity in addressing these concerns. The strength and settlement properties of silty sand with a single layer of geotextile were investigated using a series of load-settlement tests with varied geotextile locations and lime concentrations. Furthermore, computational approaches such as artificial neural networks (ANN) and extreme learning machines (ELM) were used, providing an improved and cost-effective way of evaluating the load-bearing capability of circular footings. The computational models were evaluated using accepted statistical indices and validated further using experimental data. Remarkably, the developed ANN model demonstrated exceptional predictive capabilities for determining the circular footing's ultimate bearing capacity (UBC), making it a valuable tool for preliminary design assessments.