Sustainable mortar into paver block using agricultural waste ash and recycled glass: ANN-based prediction of mechanical properties

In the contemporary context, achieving a balance between construction activities and environmental protection is critically significant. As a result, there exists a significant need to investigate the potential of using waste materials as alternatives to conventional construction materials. The utilisation of recycled glass, rice husk, and sugarcane bagasse ash in concrete production presents a significant area of exploration. This study examines an important void in existing literature regarding the longevity and efficiency of sugarcane bagasse ash (SCBA) and waste glass (WG) as alternatives to cement and fine aggregates. The aim is to evaluate the mechanical characteristics and sustainability of paver blocks that include SCBA and WG, employing experimental testing alongside machine learning methodologies. A two-stage mixing procedure was used to evaluate water absorption, dry density, compressive strength, ultrasonic pulse velocity, and rebound hammer results. An artificial neural network (ANN) model was applied to predict these properties based on experimental datasets. The results showed that increasing SCBA and WG content elevated water absorption but reduced compressive strength, density and workability. Optimal strength and sustainability were achieved with 10% SCBA and 10% WG. Both SCBA and WG demonstrate potential as sustainable alternatives, with ANN providing accurate property predictions.