Sustainable Stabilization of Puducherry Inland Clay using Lime and Quarry Dust: Geotechnical Properties and ANN-Based Predictive Modeling

Objectives: To investigate the effect of lime and quarry dust, both individually and in combination, on the geotechnical properties of Puducherry inland clay using Artificial Neural Network (ANN) modelling. Methods: Clay samples were treated individually with varying proportions of lime and QD (7%, 14%, 21%, and 28% by dry weight) as well as in combination to assess improvements in geotechnical behaviour. Laboratory tests, including Atterberg limits, Free Swell Index (FSI), compaction characteristics, direct shear test, and Unconfined Compressive Strength (UCS), were conducted to evaluate changes in soil properties. To forecast the parameters of stabilized soil, the ANN Simulink model was simulated using a neural network fitting tool after training. Findings: The experimental findings showed that the plasticity index was reduced by 25% and 37% with lime and QD stabilization, respectively. Lime- and QD-stabilized clay reduced the optimum moisture content by 20% and 35%, while maximum dry density increased by 10% and 35%, respectively. Cohesion was reduced by 28% in both cases. Regarding UCS, lime-stabilized clay showed an increase up to 21% addition before declining, whereas QD-stabilized clay showed continuous strength gain. FSI decreased by 35% and 28% in lime- and QD-stabilized clay, respectively. The combination of both lime and QD showed superior performance due to synergistic effects. ANN modelling with statistical indicators (R2: 0.95–0.99, RMSE <30%, MAPE <20%) effectively predicted geotechnical properties with less than 25% error. Novelty: Utilizing QD provides a sustainable alternative to lime while improving the geotechnical performance of clay soil comparable to lime. Using QD as a stabilizer also helps in addressing environmental waste disposal issues. Keywords: Stabilization, Artificial neural network, Lime, Quarry dust, Simulink model