STATISTICAL OPTIMIZATION AND UNCERTAINTY ANALYSIS OF SUSTAINABLE GEOPOLYMER BINDER SYSTEMS USING TAGUCHI METHODOLOGY AND MONTE CARLO SIMULATION
Keywords:
Geopolymer Concrete, Fly ash, Taguchi, ANOVA, Mix Design, GGBSAbstract
This study presents the parametric optimization of fly ash–GGBS based geopolymer paste using the Taguchi L25 orthogonal array combined with Monte Carlo Simulation (MCS) for performance prediction and reliability assessment. Four key parameters—fly ash content, GGBS percentage, NaOH molarity, and alkaline activator-to-binder ratio—were analyzed at five levels to evaluate their effect on compressive strength. The Taguchi method reduced the experimental trials from 625 to 25 specimens, while MCS assessed variability and reliability through statistical simulation. Experimental analysis using S/N ratio and ANOVA identified GGBS content and NaOH molarity as the most significant factors influencing strength. The optimum mix, consisting of 60% fly ash, 40% GGBS, 12M NaOH, A/B ratio of 0.3, and SS/SH ratio of 2, achieved an average compressive strength of 45.32 MPa. Monte Carlo results confirmed high reliability and low variability, demonstrating that the combined Taguchi–MCS approach is effective for designing sustainable and high- performance geopolymer paste for construction applications.
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