Taguchi based optimisation of mix design parameters for M60 Grade GGBS-dolomite based geopolymer concrete

Geopolymer concrete (GPC) has emerged as a sustainable alternative to Portland cement concrete with reduced CO 2 emissions per tonne of concrete. However, its mix design is complex due to multiple interrelated factors such as binder content, binder proportion, alkaline activator to binder ratio (AAS/B), sodium silicate to sodium hydroxide ratio (SS/SH), and NaOH molarity, often requiring numerous trial mixes. This complexity makes the process time-consuming and a barrier to its widespread adoption. This study presents a systematic approach to optimise high-strength (M60 grade) GPC using slag and dolomite as binders under ambient curing conditions. The Taguchi method was used to evaluate five mix parameters at four levels each, reducing the number of experimental trials from 1024 (factorial design) to just 16. The results showed that binder proportion, AAS/B ratio, and NaOH molarity significantly affect both compressive strength and workability. AAS/B ratio was most influential on workability, while binder proportion critically influenced strength. The optimised mix—430 kg/m 3 binder, 80:20 GGBS:dolomite, AAS/B = 0.45, SS/SH = 2, and 10 M NaOH—achieved a 28-day compressive strength of 71.10 N/mm 2 . A regression model is developed using standardised data to predict compressive strength for high strength slag-dolomite based geopolymer concrete, which yielded a high predictive accuracy (R 2 = 0.94, RMSE = 2.01 N/mm 2 , MAE = 1.577 N/mm 2 ). The novelty of this work lies in combining GGBS and dolomite in ambient-cured GPC, guided by a robust statistical framework. The Taguchi method is effective in simplifying the optimisation process, offering a cost-efficient, less labour-intensive, and reproducible strategy for mix design in complex geopolymer systems. • GGBS and dolomite used as precursors for sustainable geopolymer concrete. • Employed the Taguchi design of experiments approach to optimise five critical mix parameters. • Achieved M60 grade high-performance GPC with excellent compressive strength and workability, without elevated curing. • Developed regression model (R 2 = 0.94, RMSE = 2.01, MAE = 1.577) to predict compressive strength of slag-dolomite GPC, ensuring reliability. • Validated optimised mix via SEM/EDX and XRD, confirming dense microstructure with silica-rich gel network enhancing strength.