Proportion optimization and strength prediction of CGS backfill materials based on GA-ELM mode

Abstract

ABSTRACT The strength of the backfill body is an important aspect of safe production in backfill mining technology. In order to quickly and accurately obtain the strength of coal gasification slag -based cemented backfill materials with different ratios, the orthogonal design of 4 factors and 5 levels and variance analysis method were used to study the mass concentration (A), coal gasification slag (CGS)/cement (B), bone glue ratio (C), activator content (D) on the compressive strength of backfill body and a genetic algorithm with 28-day compressive strength of CGS-based backfill material as the response value was constructed, and verify the applicability of the model. The results show that: the primary and secondary factors affecting the 28-day compressive strength are C > A > B > D, the optimal ratio is 80% mass concentration, CGS/cement ratio 4:1, bone glue ratio 3:7, and activator 3%, according to orthogonal variance analysis; the activity of CGS is gradually stimulated as the curing age grows, the hydration products Ettringite and C-S-H are continually generated, and the compressive strength of the backfill material increases in tandem; In the GA-ELM model test set, the intensity correlation coefficient between the prediction and the measured value reached an average of 0.99, and the prediction accuracy was 71.8% and 43.5% higher than that of ELM and PSO-ELM respectively; Laboratory studies have shown that the GA-ELM prediction model has a prediction accuracy of 98.2% and that it can accurately estimate the strength of CGS cemented backfill.