Engineering properties of concrete incorporating waste glass as natural sand substitution with tin can fiber: experimental and ANN application

Abstract

Abstract Disposal of waste material is causing environmental issues all around the world. Waste glass and tin can are two such products that impose detrimental effects on the environment. One feasible approach is to utilize these discarded materials as constituents of concrete. This study investigates the performance of concrete prepared with glass waste as fine aggregate (GWA) and tin can fiber (TCF) in terms of workability, fresh density, compressive, and splitting tensile strength as desired concrete properties. An Artificial Neural Network (ANN) approach has been adopted for developing predictive models to simulate the impact of these waste materials on concrete properties. Experimental findings demonstrate that the worability of concrete mix decreases with increasing GWA and TCF contents in the mix. Increasing TCF percentages results in an increase in fresh density of concrete; however, a declining pattern in fresh density has been observed with increasing GWA percentage in the concrete mix. Compressive strength at all curing ages shows positive trends till 20% GWA and 1% TCF incorporation in concrete. Similar pattern has been observed for splitting tensile strength up to 10% GWA and 0.5% TCF. Constructed models are feasible for prediction of the desired concrete properties as verified by various statistical parameters. Sensitivity analysis reports that TCF has a greater influence on concrete properties than GWA.

Keywords

• Waste glass
• Tin can fiber
• Artificial neural network
• Workability
• Density
• Compressive strength