Optimization of Proportioning of Mixed Aggregate Filling Slurry Based on BBD Response Surface Method

GAO Qian, YANG Xiaobing, WEN Zhenjiang, CHEN Dexin, HE Jianyuan


 In view of the mixed aggregate filling mine,in order to determine the optimum proportion of filling slurry, firstly,the physicochemical properties of filling materials were analyzed. Based on the theory of Talbol grading and the theory of maximum bulk density,the ratio of rod grinding sand and waste rock was determined. 13 groups of tests were designed with BBD response surface method(RSM-BBD) to analyze the effects of slurry mass fraction, cement-aggregate ratio and mixture aggregate ratio on the strength of filling body. Finally,the response surface model was constructed with the intensity of each age as the response value to study the correlation between each response parameter and the target response as well as the optimal ratio of the filling slurry under multi-objective conditions. The results show that the strength of the filling body is affected by single factors, and the interaction between the various factors has a great influence on the filling body. The interaction between the mass fraction and aggregate ratio plays a decisive role in the early strength of the filling body. The interaction between the cement-aggregate ratio and aggregate ratio has a significant effect on the medium strength of the filling body. The late strength of the backfill is greatly affected by the interaction of the mass fraction and cement-aggregate ratio. The optimization is based on the lowest unit filling cost, and the optimal ratio is as follow: slurry mass fraction is 80%, cement-aggregate is 1 ∶ 6,the ratio of rod grinding sand and waste rock is 3 ∶ 7,and the test is verified to meet Jinchuan Mine strength requirements.



Keywords: mining engineering,  BBD response surface method(RSM-BBD),  slurry ratio,  aggregates,  compressive strength,  interactions affection,  multi-objective constrained optimization , costs

Full Text:



CHENG H Y, WU A X, HAN B, et al. Stability of safety pillars inopencast-underground combined mining [J] . Journal of Central South University (Science and Technology), 2016, 47 (9) :3183—3192. (In Chinese)

BEN -AWUAH E, RICHTER O, ELKINGTON T, et al. Strategic mining options optimization: open pit mining, underground miningor both [J] . International Journal of Mining Science and Technology, 2016, 26 (6) :1065—1071.

LI X B, ZHOU J, WANG S F, et al. Review and practice of deep mining for solid mineral resources [J] . The Chinese Journal of Nonferrous Metals, 2017, 27 (6) :1236—1262. (In Chinese)

DJURDJEVAC L, IGNJATOVIC D, LJUBOJEV M, et al. Change the uniaxial compressive strength of paste backfill depending on change the parameters[J] . Mining & Metallurgy Engineering Bor, 2016 (1) :17—24.

GHIRIAN A, FALL M. Strength evolution and defor mation behaviour of cemented paste backfill at early ages: effect of curing stress, filling strategy and drainage [J] . International Journal of Mining Science and Technology, 2016, 26 (5) :809—817.

FALL M, BENZAAZOUA M, SAA E G. Mix proportioning of underground cemented tailings backfill [J] . Tunnelling & Underground Space Technology, 2008, 23 (1) :80—90.

SHI C J, WANG D H, AN X P, et al. Method for mixture design of concrete with multiple performancerequirements [ J] . Journal of the Chinese Ceramic Society, 2018, 46 (2) :230—238. (In Chinese)

KESIMAL A, YILMAZ B, ERCIKDI B, et al. Effect of properties of tailings and binder on the short-and long-term strength and stability of cemented paste back fill [ J] . Materials Letters, 2005, 59 (28) :3703—3709.

BHARATKUMAR B H,NARAYANAN R,RAGHUPRASAD B K,Mix proportioning of high performance concrete [J]. Cement & Concrete Composites,2001,23(1):71—80.

ALDHAFEERI Z,FALL M,POKHAREL M,et al. Tem perature dependence of the reactivity of cemented paste backfill [J]. Applied Geochemistry,2016,72(9):10—19.

ZHANG Q L,LI X P,YANG W. Optimization of filling slurry ratio in a mine based on back-propagation neural network[J]. Journal of Central South University(Science and Technology),2013,44(7): 2867—2874.( In Chinese)

LIU Z X,GONG Y C,LI X B. Study on the backfilling material properties based on fractal theory and BP neural network [J]. Gold Science and Technology,2017,25(2):38—44.( In Chinese)


  • There are currently no refbacks.