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Journal of Shanghai Jiaotong University(Science) >

2024 , Vol. 29 >Issue 5: 845 - 856

DOI: https://doi.org/10.1007/s12204-022-2409-6

Naval Architecture, Ocean and Civil Engineering

Strength Optimization and Prediction of Cemented Tailings Backfill Under Multi-Factor Coupling

  • 胡亚飞，李克庆，韩斌，吉坤
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  • (School of Civil and Resource Engineering; Key Laboratory of Ministry of Education for High-Efficient Mining and Safety of Metal Mines, University of Science and Technology Beijing, Beijing 100083, China)

Accepted date: 2021-03-02

  Online published: 2024-09-28

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Abstract

In order to solve the problem of strength instability of cemented tailings backfill (CTB) under low temperature environment ( 20 ◦C), the strength optimization and prediction of CTB under the influence of multiple factors were carried out. The response surface method (RSM) was used to design the experiment to analyze the development law of backfill strength under the coupling effect of curing temperature, sand-cement ratio and slurry mass fraction, and to optimize the mix proportion; the artificial neural network algorithm (ANN) and particle swarm optimization algorithm (PSO) were used to build the prediction model of backfill strength. According to the experimental results of RSM, the optimal mix proportion under different curing temperatures was obtained. When the curing temperature is 10—15 ◦C, the best mix proportion of sand-cement ratio is 9, and the slurry mass fraction is 71%; when the curing temperature is 15—20 ◦C, the best mix proportion of sandcement ratio is 8, and the slurry mass fraction is 69%. The ANN-PSO intelligent model can accurately predict the strength of CTB, its mean relative estimation error value and correlation coefficient value are only 1.95% and 0.992, and the strength of CTB under different mix proportion can be predicted quickly and accurately by using this model.

Cite this article

胡亚飞，李克庆，韩斌，吉坤 . Strength Optimization and Prediction of Cemented Tailings Backfill Under Multi-Factor Coupling[J]. Journal of Shanghai Jiaotong University(Science), 2024 , 29(5) : 845 -856 . DOI: 10.1007/s12204-022-2409-6

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