Taguchi-based multi-response statistical optimization and performance assessment of high-strength concrete incorporating weathered crystalline rock fine aggregate

This study presents a detailed statistical optimization methodology for improving the performance of high-strength concrete through the strategic integration of weathered crystalline rock (WCR) fine aggregate. Utilizing Taguchi L5 orthogonal array design, the research assessed the impact of varying WCR replacement levels (0%, 5%, 10%, 15% and 20%) on essential concrete properties, encompassing mechanical strength, fresh properties, durability metrics and impact resistance. The experimental program included 175 specimens tested across seven response variables to find out how they worked together in detail. By using signal-to-noise ratio analysis and grey relational analysis together, the best replacement strategies were found. For example, adding 5% WCR resulted in better multi-objective performance with a grey relational grade of 0.953. Using mechanical property correlations, advanced regression modeling was able to predict compressive strength very well (R² = 0.997). ANOVA statistical validation showed that all response variables had significant factor contributions (> 94%). The optimized mix had a compressive strength of 74.5 MPa, improved workability (66.3 mm slump) and impact resistance (778 blows). The results show that using WCR strategically can help meet both structural performance goals and sustainability goals at the same time. This sets a strong foundation for developing sustainable high-strength concrete for use in infrastructure.