Mechanical properties of GBFS + GVS based geopolymer mortars with different molarities exposed to high temperature: A combined experimental and machine learning approaches

Abstract

This study investigates the effect of high temperatures on mechanical performance of geopolymer mortars (GPMs) produced with the equal proportions of ground blast furnace slag (GBFS) and ground volcanic scoria (GVS) at different molarities of NaOH. Addressing the need for sustainable and heat-resistant building materials, this study combines experimental testing, microstructural analysis, and artificial neural network (ANN) modeling. GPMs are cured under steam and furnace methods at 60 °C, and subsequently exposed to temperatures up to 1050 °C. The results have shown that steam-cured samples exhibit up to 22% higher flexural strength (f_fs) and 11% higher compressive strength (f_cs) than furnace-cured samples. Optimum performance is observed in the GPM produced with 6 mol/L NaOH, with a strength increase exceeding 15% at 450 °C. A feedforward ANN model is developed to predict ultrasonic pulse velocity (U_pv), f_fs, and f_cs. The model demonstrates excellent accuracy with a mean squared error of 2.03 × 10^-5, coefficient of determination of 0.99 and average margin of deviation of less than 0.05%. The novelty of this study lies in the combination of experimental and data-driven methods to accurately forecast performance, offering a reliable tool for optimizing GPMs design in high temperature applications.

Graphical abstract

Keywords

GBFS + GVS based GPM / curing conditions / mechanical properties / high temperature resistance / microstructural properties / ANN

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