Optimization of waste plastic fiber concrete with recycled coarse aggregate using RSM and ANN
Sumant Nivarutti Shinde, Sharon Christa, Rakesh Kumar Grover, Nadeem Pasha, D. Harinder, G. Nakkeeran, George Uwadiegwu Alaneme
Abstract
The disposal of industrial waste, such as ceramic and plastic waste, has led to significant environmental concerns, including greenhouse gas emissions and resource depletion. Recycling these materials is essential for promoting sustainability. Simultaneously, the construction sector contributes heavily to carbon dioxide (CO₂) emissions due to excessive extraction of natural resources. This study explores the potential of ceramic waste as a fine aggregate replacement and plastic waste as fiber reinforcement in mortar to improve mechanical properties and sustainability. The inclusion of plastic fibers enhances crack resistance and reduces brittleness, ensuring better structural performance. Key parameters such as dry density, ultrasonic pulse velocity, rebound hammer strength, and compressive strength were evaluated. The modified mortar exhibited a 30% increase in compressive strength, reaching 38.62 MPa compared to 33.05 MPa in conventional mortar, with an additional 0.6% plastic fiber incorporation. Furthermore, machine learning models, including Response Surface Methodology (RSM) and Artificial Neural Networks (ANN), were used for optimization and prediction, showing high accuracy. This study highlights the feasibility of utilizing waste materials in construction, reducing reliance on natural resources, and advancing eco-friendly, sustainable infrastructure.