Microstructural characterization, response surface modelling and multi-objective optimization of water hyacinth fibre-reinforced concrete
This study investigates the combined influence of water hyacinth fibre content (wt. % of cement) (0.5–2.0%) and fibre length (10–50 mm) on the water absorption (WA), density, and compressive strength (CS) of concrete using response surface modelling and multi-objective optimization. A replicated full-factorial experimental design was analysed using two-way ANOVA, Tukey post hoc testing, and second-order polynomial regression. Fibre content (wt. % of cement), fibre length, and their interaction significantly affected all response variables (p < 0.05), with compressive strength exhibiting the highest sensitivity. The regression models showed strong predictive capability for compressive strength (R2 = 0.87), moderate performance for density (R2 = 0.62), and limited predictive capability for water absorption (R2 = 0.235), reflecting the inherent heterogeneity of fibre-reinforced concrete. Prediction-error analysis demonstrated satisfactory agreement between experimental and model-predicted responses. Response surface modelling and multi-objective optimization identified a Pareto-efficient design region corresponding to approximately 1.2–1.5% fibre content (wt. % of cement) and 30–40 mm fibre length, providing the best balance between mechanical performance and durability. The study establishes a statistically validated framework for optimizing sustainable water hyacinth fibre-reinforced concrete through integrated modelling and multi-objective optimization.