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| 1 | 复杂地应力场反演优化算法及研究新进展显示文摘地应力是采矿工程和岩土工程设计与动力灾害防治的重要依据.地应力场反演是基于现场个别离散点应力测量结果,采用数力方法对目标区域的地应力分布的推算和拓展.本文系统介绍了区域地应力场反演和构建方法,重点阐述了他们的学术思想、应用领域以及优缺点,总结凝练了国内外学者在地应力反演算法和工程运用中作出的改进和创新,特别是非线性数理方法在地应力场反演应用中的新进展.本文提出了一种新的地应力场计算的非线性优化新算法——替代模型加速优化算法,该方法能够保证高精度、快速获得全局最优解.为了适用大规模地应力场反演,发展了能产生降阶和特征提取作用的特征正交分解地应力反演优化算法.最后,提出面向深部岩石工程和地质灾害防治的地应力场研究发展方向. | 王金安 李飞 | 2015 | 中国矿业大学学报2015，44，2： | 64 |
| 2 | Assessment of pH-responsive nanoparticles performance on laboratory column flotation cell applying a real ore feed显示文摘Nanoparticles(NPs)can promote the column flotation process in mining industry.Nanoparticles'effects on column flotation process(copper recovery,grade and flotation rate constant)are assessed in Sarcheshmeh Copper Complex,Iran,through response surface methodology(RSM)optimization technique.The c-Al2O3,a-Fe2O3,SiO2,and TiO2 nanoparticles are selected for these experiments.A flotation rate constant is chosen as a response to assess the effect of nanoparticles on flotation in its kinetic sense.The process p H and nanoparticle dosage are selected as the influential parameters.Results obtained from RSM indicated that the maximum percentage of Cu recovery and grade is obtained at p H of 12 and nanoparticle dosage of 6 kg/t,through a-Fe2O3 and c-Al2O3 nanoparticles,respectively.Applying nanoparticles in particular c-Al2O3 and a-Fe2O3 increases the Cu recovery by 8–10%together with the grade by 3–6%in a significant manner.It is revealed that nanoparticles could effectively be applied in enhancing the flotation performance. | Samiramis Nasirimoghaddam Ali Mohebbi Mohsen Karimi M.Reza Yarahmadi | 2020 | International Journal of Mining Science and Technology2020，30，2： | 19 |
| 3 | 磁化处理全尾砂料浆沉降规律及其参数优化显示文摘为了降低全尾砂料浆的脱水浓缩成本、提高脱水浓缩效果,将磁处理技术引入到全尾砂料浆沉降中,并通过正交试验建立样本数据,运用GA-BP模型确定磁化全尾砂料浆的最佳磁化处理参数.试验研究显示:磁化全尾砂料浆沉降指标随着磁感应强度、磁化时间或料浆速度的增大均呈先增大后减小的趋势,并成非线性变化关系;适宜的磁化处理条件可以提高全尾砂料浆的沉降指标,全尾砂料浆最佳磁化絮凝沉降参数为磁感应强度0.192T、磁处理时间1.85min、料浆速度1.92m/s、PAC(聚合氯化铝)添加量28g/t,最大沉降速度约155cm/h,可节约PAC用量30.0%~42.5%. | 王新民 柯愈贤 张钦礼 杨建 | 2017 | 中国矿业大学学报2017，46，4： | 15 |
| 4 | Application and comparison of RNN, RBFNN and MNLR approaches on prediction of flotation column performance显示文摘Evaluation of grade and recovery plays an important role in process control and plant profitability in mineral processing operations, especially flotation. The accurate measurement or estimation of these two parameters, based on the secondary variables, is a critical issue. Data-driven modeling techniques, which entail comprehensive data analysis and implementation of machine learning methods for system forecast, provide an attractive alternative. In this paper, two types of artificial neural networks(ANNs),namely radial basis function neural network(RBFNN) and layer recurrent neural network(RNN), and also a multivariate nonlinear regression(MNLR) model were employed to predict metallurgical performance of the flotation column. The training capacity and the accuracy of these three above mentioned types of models were compared. In order to acquire data for the simulation, a case study was conducted at Sarcheshmeh copper complex pilot plant. Based on the root mean squared error and correlation coefficient values, at training and testing stages, the RNN forecasted the metallurgical performance of the flotation column better than RBF and MNLR models. The RNN could predict Cu grade and recovery with correlation coefficients of 0.92 and 0.9, respectively in testing process. | Nakhaei Fardis Irannajad Mehdi | 2015 | International Journal of Mining Science and Technology2015，25，6： | 7 |
| 5 | Flotation studies on low grade graphite ore from eastern India显示文摘A low grade graphite ore from eastern India was beneficiated by flotation to improve its quality. The ore was composed of 87.80% ash and 8.59% fixed carbon. Primary coarse wet grinding(d80: 186 lm) followed by rougher flotation in Denver flotation cell using diesel as collector and pine oil as frother yielded a rougher concentrate. Regrinding(d80: 144 lm) of this rougher concentrate was opted for further liberation of graphite. It was followed by cleaning in laboratory flotation column. This combined process of relatively coarse primary grinding followed by regrinding and cleaning in flotation column resulted in final concentrate of 7.44% yield with 89.65% fixed carbon and 6.00% ash. This approach of two-stage grinding to recover the flake graphite at the coarsest possible grind can help to minimize grinding energy costs. A conceptual flow sheet which is cost effective was developed based on this methodology. | Vasumathi N. Vijaya Kumar T.V. Ratchambigai S. Subba Rao S. Bhaskar Raju G. | 2015 | International Journal of Mining Science and Technology2015，25，3： | 6 |
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