Homogenization mathematical model of the cemented filling slurry with crushing waste rock and whole tailings

YANG Xiao-bing; YIN Sheng-hua; HAO Shuo; YANG Hang

doi:10.13374/j.issn2095-9389.2021.12.18.004

Volume 44 Issue 7

Jul. 2022

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YANG Xiao-bing, YIN Sheng-hua, HAO Shuo, YANG Hang. Homogenization mathematical model of the cemented filling slurry with crushing waste rock and whole tailings[J]. Chinese Journal of Engineering, 2022, 44(7): 1115-1125. doi: 10.13374/j.issn2095-9389.2021.12.18.004

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YANG Xiao-bing, YIN Sheng-hua, HAO Shuo, YANG Hang. Homogenization mathematical model of the cemented filling slurry with crushing waste rock and whole tailings[J]. Chinese Journal of Engineering, 2022, 44(7): 1115-1125. doi: 10.13374/j.issn2095-9389.2021.12.18.004

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Homogenization mathematical model of the cemented filling slurry with crushing waste rock and whole tailings

doi: 10.13374/j.issn2095-9389.2021.12.18.004

YANG Xiao-bing^{1, 2, 3},
YIN Sheng-hua^{1, 3
,
,},
HAO Shuo^{1, 3},
YANG Hang²

1.
School of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing 100083, China
2.
State Key Laboratory of Mineral Processing, Beijing 102628, China
3.
Key Laboratory of High-Efficient Mining and Safety of Metal Mines (Ministry of Education), University of Science and Technology Beijing, Beijing 100083, China

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Corresponding author: E-mail: ustxsh@163.com
Received Date: 2021-12-18
Available Online: 2022-05-11
Publish Date: 2022-07-01

Abstract

Abstract

Aiming at the problems of pipeline transportation blockage and filling body stratification caused by waste rock–unclassified tailings high-concentration slurry, the effects of superplasticizer and stirring parameters on the slurry homogenization were experimented with, and the quantitative characterization of slurry homogenization was explored. Initially, the polycarboxylate (PC) superplasticizer with the best suitability was screened out based on the bleeding-slump test, and the mathematical correlations of the slump and bleeding rate with the optimal superplasticizer dosage range were obtained by regression. The rheological properties of the slurry and the filling body strength were then determined at different PC superplasticizer dosages, and separate mathematical models for correlations of slurry rheological parameters and mechanical properties with superplasticizer dosage were built. Next, the slurry surface images under different stirring conditions were acquired with the Nikon D350 camera, and their information entropies were calculated. Meanwhile, the OTSU algorithm was used to perform image segmentation thresholding, and the images were binarized via Matlab, followed by a calculation of the proportion of black pixels in the binarized images. Further, the variation trends of image information entropy and black pixels proportion with PC superplasticizer, rock/tailing ratio (mass ratio of waste rock to unclassified tailings), and stirring time were derived. Finally, the homogenization mechanism in the waste rock–unclassified tailings filling slurry was revealed based on the PC superplasticizer’s regulatory role in fine particle absorption and dispersion, which was further validated by the relationship between the zeta potential of cement paste and the dosage of PC superplasticizer. On this basis, a quantitative model of slurry homogenization was developed based on the slump, bleeding rate, rheological properties, strength characteristics, and image information, and the optimal parameters of waste rock–unclassified tailings high-concentration filling slurry were obtained by multi-objective programming. The results show that the PC superplasticizer is highly suitable for the slurry, which can reduce its yield stress and plastic viscosity coefficient and improve its fluidity. When the dosage of PC superplasticizer is 0.50%, the yield stress and plastic viscosity of the slurry is reduced by 34.4% and 21.2%, respectively, in comparison to the case without superplasticizer. The slurry rheological properties conform to the Bingham plastic model. Increasing the PC superplasticizer dosage improves the early strength of the filling body and weakens the 28-d strength. Nonetheless, within the optimal dosage range, all the filling body strengths can meet the mine filling requirements. Slurry surface images with higher information entropy and a smaller proportion of black pixels indicate a higher degree of slurry homogenization. Moreover, the entropy value of slurry surface images tends to increase initially and then decrease with the prolonging of stirring time and the heightening of the rock/tailing ratio. When the rock/tailing ratio is constant, the proportion of black pixels is the largest at a stirring time of 3 min, followed by 5 min, and the smallest at 4 min. According to the quantitative model results of slurry homogenization, the reasonable dosage range of PC superplasticizer is 0.26%–0.5%, and the optimal stirring time is 4.3 min. The degree of homogenization is the best at a 0.5% dosage, at which point the slurry has a plastic viscosity μ of 0.79 Pa·s and a yield stress τ of 202.25 Pa.
- slurry homogenization,
- rheological properties,
- strength properties,
- image information,
- polycarboxylate water reducer

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References(29)

References

[1]	李夕兵, 周健, 王少鋒, 等. 深部固體資源開采評述與探索. 中國有色金屬學報, 2017, 27(6):1236 Li X B, Zhou J, Wang S F, et al. Review and practice of deep mining for solid mineral resources. Chin J Nonferrous Met, 2017, 27(6): 1236
[2]	蔡美峰. 中國金屬礦山21世紀的發展前景評述. 中國礦業, 2001, 10(1):11 doi: 10.3969/j.issn.1004-4051.2001.01.005 Cai M F. Development of China's metal mines in the 21st century. China Min Mag, 2001, 10(1): 11 doi: 10.3969/j.issn.1004-4051.2001.01.005
[3]	程海勇, 吳愛祥, 吳順川, 等. 金屬礦山固廢充填研究現狀與發展趨勢. 工程科學學報, 2022, 44(1):11 Cheng H Y, Wu A X, Wu S C, et al. Research status and development trend of solid waste backfill in metal mines. Chin J Eng, 2022, 44(1): 11
[4]	吳愛祥, 楊瑩, 程海勇, 等. 中國膏體技術發展現狀與趨勢. 工程科學學報, 2018, 40(5):517 Wu A X, Yang Y, Cheng H Y, et al. Status and prospects of paste technology in China. Chin J Eng, 2018, 40(5): 517
[5]	王新民, 趙建文, 張欽禮, 等. 露天轉地下最佳開采模式. 中南大學學報(自然科學版), 2012, 43(4):1434 Wang X M, Zhao J W, Zhang Q L, et al. Optimal mining model of transition from open-pit to underground mining. J Central South Univ (Sci Technol), 2012, 43(4): 1434
[6]	Ben-Awuah E, Richter O, Elkington T, et al. Strategic mining options optimization: Open pit mining, underground mining or both. Int J Min Sci Technol, 2016, 26(6): 1065 doi: 10.1016/j.ijmst.2016.09.015
[7]	吳愛祥, 李紅, 程海勇, 等. 全尾砂膏體流變學研究現狀與展望(下): 流變測量與展望. 工程科學學報, 2021, 43(4):451 Wu A X, Li H, Cheng H Y, et al. Status and prospects of research on the rheology of paste backfill using unclassified tailings (Part 2): Rheological measurement and prospects. Chin J Eng, 2021, 43(4): 451
[8]	阮竹恩, 吳愛祥, 王貽明, 等. 全固廢膏體關鍵性能指標的多目標優化. 工程科學學報, 2022, 44(4):496 Ruan Z E, Wu A X, Wang Y M, et al. Multiple response optimization of key performance indicators of cemented paste backfill of total solid waste. Chin J Eng, 2022, 44(4): 496
[9]	牟宏偉, 呂文生, 楊鵬. 螺旋管在小倍線充填中的應用及充填倍線公式修正. 工程科學學報, 2016, 38(8):1069 Mou H W, Lv W S, Yang P. Application of a spiral pipe in a low stowing gradient backfilling pipeline and amendment of stowing gradient. Chin J Eng, 2016, 38(8): 1069
[10]	祝麗萍, 倪文, 高術杰, 等. 赤泥?礦渣?脫硫石膏?少熟料膠結劑的適應性及早期水化. 工程科學學報, 2015, 37(4):414 Zhu L P, Ni W, Gao S J, et al. Adaptability and early hydration of a cementing agent prepared with red mud, slag, flue gas desulphurization gypsum and a little cement clinker. Chin J Eng, 2015, 37(4): 414
[11]	王建棟, 吳愛祥, 王貽明, 等. 粗骨料膏體抗離析性能評價模型與實驗研究. 中國礦業大學學報, 2016, 45(5):866 Wang J D, Wu A X, Wang Y M, et al. Evaluation model and experimental study for segregation resistance of paste with coarse aggregate. J China Univ Min Technol, 2016, 45(5): 866
[12]	寇云鵬, 齊兆軍, 盛宇航, 等. 運動狀態下全尾砂膠結料漿流變參數時變性研究. 有色金屬(礦山部分), 2019, 71(1):15 Kou Y P, Qi Z J, Sheng Y H, et al. Study on time-dependent rheological parameters of unclassified tailings cemented slurry under motion state. Nonferrous Met Min Sect, 2019, 71(1): 15
[13]	李雪, 李翠平, 顏丙恒, 等. 基于離散元的膏體攪拌影響因素分析. 金屬礦山, 2021(3):19 Li X, Li C P, Yan B H, et al. Analysis of the influence factors of paste stirring based on discrete element method. Met Mine, 2021(3): 19
[14]	閆澤鵬, 尹升華, 嚴榮富, 等. 攪拌時間對粗骨料膏體均質性及早期強度的影響. 中國有色金屬學報,http://kns.cnki.net/kcms/detail/43.1238.TG.20210824.1021.002.html Yan Z P, Yin S H, Yan R F, et al. The effect of mixing time on the homogeneity and early strength of the coarse aggregate paste. Chin J Nonferrous Met,http://kns.cnki.net/kcms/detail/43.1238.TG.20210824.1021.002.html
[15]	王洪江, 楊柳華, 王勇, 等. 全尾砂膏體多尺度物料攪拌均質化技術. 武漢理工大學學報, 2017, 39(12):76 Wang H J, Yang L H, Wang Y, et al. Multi-scale materials’ dispersive mixing technology of unclassified tailings Paste. J Wuhan Univ Technol, 2017, 39(12): 76
[16]	楊志強, 王永前, 高謙, 等. 泵送減水劑對尾砂-棒磨砂膏體料漿和易性與充填體強度影響研究. 福州大學學報(自然科學版), 2015, 43(1):129 Yang Z Q, Wang Y Q, Gao Q, et al. Research on pumping water reducing agent affecting on the strength of backfilling body and workability of paste slurry with tailing and rod grinding sand. J Fuzhou Univ Nat Sci, 2015, 43(1): 129
[17]	曹恩祥. 聚羧酸減水劑對水泥凈漿體系流變性能的作用機理研究[學位論文]. 北京: 清華大學, 2011 Cao E X. Research on Mechanism of Polycarboxylate Superplasticizer on Rheological Properties of Cement Paste [Dissertation]. Beijing: Tsinghua University, 2011
[18]	Jézéquel P H, Collin V. Mixing of concrete or mortars: Dispersive aspects. Cem Concr Res, 2007, 37(9): 1321 doi: 10.1016/j.cemconres.2007.05.007
[19]	Gao J C, Cui X X, Shen Y F, et al. Fabrication of HDPE composites via a novel friction stir processing technology. J Thermoplast Compos Mater, 2019, 32(10): 1305 doi: 10.1177/0892705718796543
[20]	錢珊珊, 姚燕, 王子明, 等. 聚膦酸減水劑的合成、表征及機理. 硅酸鹽學報, 2021, 49(5):910 Qian S S, Yao Y, Wang Z M, et al. Synthesis and mechanism of polyphosphate superplasticizer. J Chin Ceram Soc, 2021, 49(5): 910
[21]	董越. 多固廢資源在金川礦山充填采礦中協同綜合利用研究[學位論文]. 北京: 北京科技大學, 2019 Dong Y. Research on Multi-Solid Waste Collaborative Comprehensive Utilization of Mining Backfill in Jinchuan Mine [Dissertation]. Beijing: University of Science and Technology Beijing, 2019
[22]	Basu P, Thomas B S, Gupta R C, et al. Properties of sustainable self-compacting concrete incorporating discarded sandstone slurry. J Clean Prod, 2021, 281: 125313 doi: 10.1016/j.jclepro.2020.125313
[23]	肖超云, 朱偉興. 基于Otsu準則及圖像熵的閾值分割算法. 計算機工程, 2007, 33(14):188 doi: 10.3969/j.issn.1000-3428.2007.14.066 Xiao C Y, Zhu W X. Threshold selection algorithm for image segmentation based on Otsu rule and image entropy. Comput Eng, 2007, 33(14): 188 doi: 10.3969/j.issn.1000-3428.2007.14.066
[24]	楊柳華, 王洪江, 吳愛祥, 等. 全尾砂膏體攪拌技術現狀及發展趨勢. 金屬礦山, 2016(7):34 doi: 10.3969/j.issn.1001-1250.2016.07.005 Yang L H, Wang H J, Wu A X, et al. Status and development tendency of the full-tailings paste mixing technology. Met Mine, 2016(7): 34 doi: 10.3969/j.issn.1001-1250.2016.07.005
[25]	王春雨, 趙輝, 代正華, 等. 表面活性劑對親水性顆粒懸浮液流變性的影響. 應用化學, 2021, 38(4):398 Wang C Y, Zhao H, Dai Z H, et al. Effect of surfactant on the rheological properties of hydrophilic particle suspension. Chin J Appl Chem, 2021, 38(4): 398
[26]	杜小弟, 劉明, 畢耀, 等. 聚甲基羧酸減水劑對水泥漿體Zeta電位及其流變性影響 // 中國化學外加劑及礦物外加劑研究與應用新進展2016年科隆杯優秀論文匯編. 青島, 2016: 186 Du X D, Liu M, Bi Y, et al. Effect of polymethyl carboxylic acid water reducing agent on zeta potential of cement slurry and its rheological properties// A Compilation of Excellent Papers of Cologne Cup 2016 on New Progress in Research and Application of Chemical Admixtures and Mineral Admixtures in China. Qingdao, 2016: 186
[27]	曹廣勝, 佟樂, 胡儀, 等. 基于污水懸浮顆粒Zeta電位的絮凝劑用量優化. 大慶石油學院學報, 2009, 33(1):17 Cao G S, Tong L, Hu Y, et al. Optimization of flocculant dosage by Zeta potential of the particles in sewage. J Daqing Petroleum Inst, 2009, 33(1): 17
[28]	Wu J Z, Beliakov G. Nonadditive robust ordinal regression with nonadditivity index and multiple goal linear programming. Int J Intell Syst, 2019, 34(7): 1732 doi: 10.1002/int.22119
[29]	Sadeghi H, Moslemi F. A multiple objective programming approach to linear bilevel multi-follower programming. AIMS Math, 2019, 4(3): 763 doi: 10.3934/math.2019.3.763