Mix design strategy and optimization considering characteristic evaluation of geopolymer concrete

Abstract

In this study, a unique strategy for mix design of geopolymer concrete (GPC) was suggested by integrating fly ash, silica fume, and GGBFS as precursors with varied alkali activator molarities in both ambient and oven curing environments. GPC's crystalline and microscopic qualities were assessed by X-ray diffraction and scanning electron microscopy tests; while its' mechanical properties were assessed using compressive strength test (CST). The experimental results showed a rising trend between the alkali activator (NaOH) concentration and the compressive strength of the GPC. GGBFS precursor based GPC had the highest compressive strength of 87.53 MPa at 14 molarity of NaOH after oven curing at 60°C. Furthermore, Artificial Neural Network (ANN) and Response Surface Method (RSM) were used to evaluate significant correlation and interaction between different parameters considered in mix design. By incorporating six input variables from the experimental test data, namely total precursor content used, secondary precursor content used, curing temperature, number of curing days, total aggregate content, and molarity of NaOH used, and compressive strength as output/response variable. The R-value for ANN found to be 0.99, while the R2 value for the RSM model was 0.98, indicating a satisfactory fit having a good interaction and optimization of GPC parameters. The optimize values of different independent parameters evaluated can obtain maximum CST value of 111.104 MPa.