Assessment of Geopolymer Synthesis Parameters for Strength of Stabilized Fat Clay Using Statistical and Machine Learning Techniques

Calcium-based chemical stabilizers are traditionally used for the stabilization of weak subgrade soils. However, these traditional stabilizers incur significant environmental costs which make them less desirable. As a result, alternative materials based on recycled waste and industrial byproducts are becoming popular. Geopolymers (GP) are a new addition to this list that are gaining traction because of their environmental benefits. GPs improve the soil by precipitation of a polymer gel as a result of mixing an alkaline activator (activator) with an aluminosilicate source (precursor). The effectiveness of GP and the improvement in engineering performance of GP-stabilized soils is contingent on sound GP synthesis parameters. This study investigates the effectiveness of GP-based treatments in improving weak soil and evaluates the significance of various parameters in contributing to the efficacy of GP treatment. As a result, a group of eight GP mixes was designed with a range of values for controlling parameters namely water/solid, activator/precursor, Si/Al and cation/Al ratios. A fat clay was treated by the application of these GP mixes at a dosage of 10% by dry weight. Improvements in mechanical strength were evaluated through unconfined compression strength testing. This was followed by statistical inference on laboratory strength data using analysis of variance (ANOVA) and post hoc tests. Ultimately, parameter importance was quantified by the random forest (RF) regression model. The results indicated that GP-based treatments enhanced the strength of untreated soil. Additionally, GP with higher aluminosilicate content and sufficient activator performed better. Overall, this study provides insight into the relative contribution of various GP synthesis parameters to the performance of GP-stabilized subgrade soils.