| 混合充填骨料胶结充填强度试验与最优配比决策研究 |
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| 引用本文： | 杨 啸,杨志强,高 谦,陈得信.混合充填骨料胶结充填强度试验与最优配比决策研究[J].岩土力学,2016,37(Z2):635-641. |
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| 作者姓名： | 杨 啸 杨志强 高 谦 陈得信 |
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| 作者单位： | 1.北京科技大学 金属矿山高效开采与安全教育部重点实验室，北京 100083；2.金川集团股份有限公司，甘肃 金昌 737100 |
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| 基金项目： | 国家高技术研究发展计划（863）（No. SS2012AA062405） |
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| 摘 要： | 将全尾砂作为充填料进行充填法采矿，不仅可以降低采矿成本，而且还能够实现固体废弃物资源化利用，同时将固体废弃物充填地下保护环境，维护生态平衡。由于尾砂粒径较细，需要与棒磨砂、戈壁砂混合作为充填料应用于充填采矿，有必要开展混合充填骨料的配比优化研究。首先，分别测试了棒磨砂、戈壁砂和尾砂3种骨料的粒径级配和不均匀系数。然后进行了9组配比的胶结充填体强度试验，在该基础上对试验样本进行训练，建立了神经网络预测模型。最后采用该预测模型，进行混合充填骨料正交设计方案的充填体强度预测，并分别采用极差分析和回归分析，揭示了充填体强度与混合充填骨料特征值之间的关系。研究发现，混合骨料平均粒径和不均匀系数不同，充填体早期和后期强度存在显著差异；平均粒径较小的混合骨料早期强度较高，而平均粒径较大者则更利于提高充填体的后期强度。
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| 关 键 词： | 混合充填骨料 平均粒径 充填体强度 粒径级配优化 神经网络 |
| 收稿时间： | 2016-01-14 |
Cemented filling strength test and optimal proportion decision of mixed filling aggregate |
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| YANG Xiao,YANG Zhi-qiang,GAO Qian,CHEN De-xin.Cemented filling strength test and optimal proportion decision of mixed filling aggregate[J].Rock and Soil Mechanics,2016,37(Z2):635-641. |
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| Authors: | YANG Xiao YANG Zhi-qiang GAO Qian CHEN De-xin |
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| Institution: | 1. Key Laboratory of High Efficient Mining and Safety of Metal Mine of Ministry of Education, University of Science and Technology of Beijing,
Beijing 100083, China; 2. Jinchuan Group Co., Ltd., Jinchuan, Gansu 737100, China |
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| Abstract: | Back-filling mining method with whole tailings as material can not only reduce the mining cost, but also recycle solid wastes. At the same time, filling solid waste underground protects environment and maintains ecological balance. Since whole tailing’s particle size is small, whole tailings shall be mix with rod-mill tailings and Gobi sand for mine filling. It is necessary to research the optimal proportion of mixed filling aggregate. First, we tested the particle-size gradation and the nonuniform coefficient of rod-mill tailings, Gobi sand and whole tailings. Then we carried out 9 sets of strength tests of cemented fillings with different mixing ratios. On this base, we built the artificial neural network model for strength predictions and trained it with the experimental samples. Finally, we predicted the strength of mixed filling aggregate of orthogonal design by using the prediction model, and we revealed the relationship between filling body’s strength and characteristic value of mixed filling aggregate by using range analysis and regression analysis. The research results show that, with different mixed aggregate’s average sizes and nonuniform coefficients, the filling body has significant strength differences between early and late stage. Mixed aggregate with smaller average particle size has a higher strength in early stage; while the larger is more inclined to increase the filling body’s strength in late stage. |
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| Keywords: | mixed filling aggregate average particle size filling body’s strength particle size gradation optimization neural network |
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