Investigation the synergistic effects in quaternary binder containing red mud, blast furnace slag, steel slag and flue gas desulfurization gypsum based on artificial neural networks

摘要

Using solid wastes to prepare cementitious materials that can replace ordinary Portland cement is an effective way to recycle solid wastes. This present paper investigated the initial setting time and compressive strength of the quaternary binder which consists of ground granulated blast furnace slag, red mud, steel slag and flue gas desulfurization gypsum based on the synergy theory, and the synergetic effect was systematically analyzed by XRD, FTIR, and SEM-EDS. And the artificial neural network was used to predict the initial setting time and compressive strength of the quaternary binder with different raw material proportions. The results showed that the quaternary binder has the highest mechanical strength than that of the ternary binder and the binary binder, which proved the presence of synergetic effect between the raw materials. Sodium silicate, steel slag and flue gas desulfurization gypsum all could accelerate the hydration reaction and increase the compressive strength to some content. The artificial neural network models proved that they are efficient models to predict the initial setting time and compressive strength, and the usage of established ANN prediction models for grouting engineering was provided, and the optimal content for the compressive strength of the quaternary binder was determined by genetic algorithm. (c) 2020 Elsevier Ltd. All rights reserved.