OPEN ACCESS
This paper attempts to determine the optimal proportion of paste filler for a coal mine in China. For this purpose, an orthogonal test was designed with three factors and five levels. Then, the filler strength was measured on the 7th and 28th day of the test. Visual analysis and variance analysis show that the filler strength was mainly affected by cement content and paste concentration on the 7th day, and by cement content and fly ash-gangue ratio on the 28th day. After that, a filler strength prediction model was established through multivariate statistical analysis, and the optimal proportions for the 7th and 29th days were derived through Gaussian elimination: the cement content of 12.705%, the fly ash-gangue ratio of 0.400 and the paste concentration of 77.498%. Finally, these proportions were verified on the 7th and 29th days. The research results shed new light on the preparation of paste filler for engineering purposes
filler strength, orthogonal test, multivariate statistical analysis
NSFC (Natural Science Foundation of China) (51174109, 51074086)
Chang Q. L., Zhou H. Q. Qin J. Y., Fan J., WangY. L. (2009). Using artificial neural network model to determine the prescription of paste filling materials. Journal of Mining & Safety Engineering, Vol. 1, pp. 74-77. https://doi.org/10.3969/j.issn.1673-3363.2009.01.014
Dai L., Xu H. K., Chen T., Qian C., Liang D. P. (2014). Multivariate liner regression forecasting model based on mapreduce. Journal of Computer Applications, Vol. 7, pp. 1862-1866. https://doi.org/10.11772/j.issn.1001-9081.2014.07.1862
Dong J. H., Yang J. H., Yang G. X., Wu F. Q., Liu H. S. (2012). Research on similar material proportioning test of model test based on orthogonal design. Journal of China Coal Society, Vol. 1, pp. 44-49. https://doi.org/10.1007/s11783-011-0280-z
Duan H. F. (2014). Six factors linear prediction model on depth of damage floor. Rock and Soil Mechanics, Vol. 11, pp. 3323-3330.
Duan H. F., Jiang Z. Q., Zhu S. Y., Xiao W. G., Li D. L. (2012). micro-mechanism of water stability and characteristics of strength softening of rock in deep mines. Chinese Journal of Geotechnical Engineering, Vol. 9, pp. 1636-1645.
Liu L. (2013). Research on proportion optimization and flow characteristic of backfill paste in mine sites. Central South University. https://doi.org/10.7666/d.Y2687592
Ti Z. Y., Qin H. Y.,Cao Y. Z. (2014). DM-L optimization model of height of water flowing fractured zone based on sensitivity analysis. Journal of Huazhong Normal University(nat. sci.), Vol. 48, No. 5, pp. 673-676.
Wang H. W., Meng J. (2007). Predictive modeling on multivariate linear regression. Journal of Beijing University of Aeronautics and Astronautics, Vol. 4, pp. 500-504. https://doi.org/10.3969/j.issn.1001-5965.2007.04.028
Wang H. W., Ye M., Saporta G. (2009). Classification for multiple linear regression methods. Journal of System Simulation, Vol. 22, pp. 7048-7050+7056. https://doi.org/10.1360/972009-1650
Wu S. C., Gao Y. T., Yang Z. F. (2006). Random prediction of rockfall of open-pit mine high-steep slope based on orthogonal experiment. Chinese Journal of Rock Mechanics and Engineering, Vol. S1, pp. 2826-2832.
Yang B. G., Han Y. M., Yang P. F., Li Y. (2014). Research on ratio of high concentration cementation stowing materials in coal mine. Coal Science and Technology, Vol. 1, pp. 30-33. https://doi.org/10.13199/j.cnki.cst.2014.01.008
Yao Z. G. (2010). Investigation on the interaction mechanism of backfill and aluminum matrix composites coagulation material for filling mines. Central South University. https://doi.org/10.7666/d.y1918156
Yu H., Jian L. C., Gong M. G., Yang D. D. (2010). Clonal selection function optimization based on orthogonal experiment design. Journal of Software, Vol. 5, pp. 950-967. https://doi.org/10.3724/SP.J.1001.2010.03472
Zhang R. J., Zhang X. G., Bai J. W., Li X. S. (2012). Research on proportion test and hydration mechanism of paste filling material. Journal of Shandong University of Science and Technology (Natural Science), Vol. 6, pp. 62-68.