Statistical modeling and optimization of waste glass-based paver block properties
A significant environmental concern stemming from glass waste is the demand for innovative recycling techniques. This study seeks to provide a sustainable construction option by examining the viability of replacing glass with traditional aggregates in the production of paver blocks. The mix proportions are optimized by Response Surface Methodology (RSM), which examines the impact of major elements on the mechanical properties and durability of the paver blocks. The water absorption capacity decreased by 4.2 % with up to 20 % incorporation of waste glass, while compressive strength increased by 44.93 % compared to conventional concrete with replacement of 30 % of waste glass at 28 days of curing. The study yielded strong coefficients of determination (R²) values of 0.9513, 0.9294, and 0.9766 for compressive strength, water absorption, and UPV (ultrasonic pulse velocity), respectively, by employing RSM to create prediction models for various criteria. The robust R² values signify the models' accuracy in forecasting the performance of paver blocks at different (waste glass aggregates) WGA concentrations. Experimental studies comparing performance with traditional concrete pavers assess compressive strength, water absorption, and abrasion resistance. Research demonstrates that glass recycling enhances strength and durability while mitigating the adverse environmental impacts of glass. RSM facilitated the identification of the optimal composition, ensuring a balance between structural integrity and sustainability. This study discusses the potential eco-friendliness of recycled glass paver blocks for sustainable urban development.
Institutions
- Babasaheb Bhimrao Ambedkar University (IN)
- Chhatrapati Shahu Ji Maharaj University (IN)
- Indian Institute of Technology Kanpur (IN)
Publication Details
- Journal
- Next Materials
- Published
- 2025-09-23
- DOI
- https://doi.org/10.1016/j.nxmate.2025.101236
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00