Performance Optimization of Eco-Engineered Waterproof Concrete Blocks Using Machine Learning and Industrial By-Products

The construction industry is a significant contributor to environmental degradation, primarily due to the extensive use of conventional concrete, which is associated with high carbon emissions and resource depletion. This study explores the development of sustainable waterproof concrete blocks through the partial replacement of natural aggregates with industrial steel waste and reinforcement using polypropylene fibers and high-density polyethylene (HDPE) sheets. HDPE sheets were integrated as surface linings or embedded layers to serve as an effective barrier against water ingress, thereby enhancing the waterproofing and long-term durability of the blocks. The mechanical properties, including compressive and tensile strength, as well as waterproofing efficiency and durability, were thoroughly evaluated. A comprehensive Life Cycle Assessment (LCA) was conducted to quantify the environmental impact, focusing on global warming potential, energy consumption, water usage, and resource depletion. Results revealed that the use of industrial steel slag and polymer reinforcements not only maintained but also improved structural performance and durability. Furthermore, advanced machine learning models, including Random Forest and XGBoost, were developed and validated to predict performance outcomes, achieving R² values consistently above 0.9. The integration of experimental data, environmental metrics, and predictive modeling establishes a holistic framework for producing eco-efficient, high-performance concrete blocks. This study highlights the potential of incorporating industrial by-products and polymeric reinforcements into concrete production, providing a sustainable approach toward reducing the environmental footprint of the construction sector.