Cemented backfill material is an important technical means for improving the safety, efficiency, and environmental sustainability of underground mining. In tailings-free mining conditions, however, suitable aggregates for cemented backfill are often limited, making it necessary to identify alternative aggregates and optimize their mix proportions. To address this issue, clay-bearing crushed stone was selected as the primary aggregate for a tailings-free bauxite mine, and its effects on the mechanical properties, slurry stability, and rheological properties of cemented backfill material were systematically investigated. Crushed stone ratio, mass concentration, and fly ash ratio were used as experimental factors, and 24 experimental mixes were designed to determine the 3-day compressive strength, bleeding rate, and yield stress. Based on the experimental results, response surface regression models were established, and multi-objective optimization was performed using cost analysis, NSGA-II, and entropy-weighted TOPSIS. The results showed that the system containing clay-bearing crushed stone exhibited better stability than the clay-free crushed stone system. The response surface models for 3-day compressive strength, bleeding rate, and yield stress were all significant, with p-values below 0.0001 and R2 values of 0.9658, 0.9306, and 0.8704, respectively. Comprehensive optimization gave the optimal mix proportions as a crushed stone ratio of 6.9721, a mass concentration of 0.82, and a fly ash ratio of 1, corresponding to a predicted 3-day compressive strength of 0.9629 MPa, a bleeding rate of 3.73%, and a cost of 68.225 RMB/t. For engineering application, the recommended mix proportions were adjusted to X1 = 7, X2 = 0.82, and X3 = 1. Parallel tests gave a 3-day compressive strength of 0.99 MPa and a bleeding rate of 3.52%, both within the 95% prediction interval. These results demonstrate that clay-bearing crushed stone can serve as a feasible alternative aggregate for cemented backfill material under tailings-free conditions and that the proposed method combining response surface modeling with multi-objective optimization can effectively balance early strength, slurry stability, and material cost.
Guo et al. (Sun,) studied this question.