Clayey soils are often regarded as problematic soil in civil engineering due to their low shear strength, high compressibility and poor drainage capacity. These characteristics limit their suitability for use in roadways, embankments and foundation subgrades unless appropriate stabilization techniques are adopted. In recent years, the use of industrial by-products and geosynthetic materials has gained attention as a sustainable and cost-effective solution. This study presents an experimental investigation into the combined effects of Class C fly ash and Geogrid reinforcement on the geotechnical performance of clayey soil.
A systematic testing program was conducted on untreated clay, clay mixed with varying percentages of fly ash (10% – 30%), and clay–fly ash composites reinforced with Geogrid layers (single and double layers). Standard laboratory experiments, including Atterberg limits, compaction characteristics and California Bearing Ratio (CBR) tests, were conducted to evaluate the strength improvement. The results revealed that untreated clay exhibited a CBR of 5.79%, confirming its weakness in its natural state. The inclusion of fly ash significantly enhanced strength, with the CBR progressively increasing to 15.16% at 30% replacement. Further improvement was obtained when Geogrid was incorporated. The optimum performance was achieved with 20% fly ash combined with two Geogrid layers placed at 0.5 and 0.66 depths from the top, resulting in a maximum CBR value of 16.35%, which is nearly three times higher than that of untreated soil.
The findings highlight that the modification made by flyash and geogrid causes favourable improvements in CBR through enhanced strength and load distribution. In addition, the reuse of fly ash addresses disposal concerns while reducing construction costs. This study confirms that fly ash–Geogrid stabilization is a practical, eco-friendly and technically viable method for improving weak subgrades, making it highly suitable for sustainable road and embankment construction. The study also establishes a predictive model correlating CBR with fly ash content and geogrid configuration, enabling intelligent, data-driven approaches to subgrade design.