INTERACTION ANALYSIS AND MECHANICAL PREDICTION MODEL OF COAL GANGUE-BASED GEOPOLYMER

This work analyses interaction factors affecting the preparation of a geopolymer from coal gangue and establishes an accurate mechanical prediction model to efficiently predict the flexural and compressive strength. Coal gangue is the main raw material, and NaOH and water glass are chosen as the activators to synthesise the geopolymer. First, response Surface Methodology (RSM) was applied to analyse the interaction impacts of the water glass modulus, liquid-to-solid ratio, sodium silicate/coal gangue ratio, and curing temperature on the mechanical properties. After that, a modified Support Vector Machine (SVM) and RSM were applied to establish a mechanical prediction model. The results reveal that there are two key interaction factors for the geopolymer properties. First, the water glass modulus and liquid-to-solid ratio could jointly affect the flexural strength. At the same time, the compressive strength is simultaneously influenced by the water glass modulus and curing temperature. Moreover, the analysis of the mechanical prediction models indicates that both the RSM and modified SVM could use little experimental data to predict the mechanical properties of geopolymer. However, the modified SVM has better prediction accuracy. Therefore, this study could efficiently predict the mechanical strength of a coal gangue-based geopolymer, conserve energy, and decrease the environmental pollution resulting from coal gangue.