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Journal of Central South University 2022年第1期29卷 102-115页

作者： Fatemeh Taghavi Mohammad Noaparast Ziaeddin Pourkarimi fardis Nakhaei School of Mining Engineering College of EngineeringUniversity of TehranTehranIran Department of Mineral Processing and Applied Research Iran Mineral Processing Research Center(IMPRC)KarajIran School of Chemical and Minerals Engineering NorthWest UniversityPotchefstroomSouth Africa

细粒浮选一直是许多矿物加工厂面临的主要问题之一。由于细颗粒的气泡粒子碰撞概率很低,因此降低了浮选效率。细粒的存在通常不利于浮选过程,影响了浮选精矿的选择性和质量,而且增加了试剂的消耗量。因此,在大多数加工厂中,会将部分颗... 详细信息

细粒浮选一直是许多矿物加工厂面临的主要问题之一。由于细颗粒的气泡粒子碰撞概率很低,因此降低了浮选效率。细粒的存在通常不利于浮选过程,影响了浮选精矿的选择性和质量,而且增加了试剂的消耗量。因此,在大多数加工厂中,会将部分颗粒输送到尾矿池中,以减少这些问题的影响,并提高浮选过程的选择性。由于d80小于30μm的颗粒的存在,使伊朗的Esfordi磷酸盐厂损失了至少30%的处理能力。将这些P_(2)O_(5)含量为15.9%的细颗粒转移到尾矿坝,从经济和环境两方面来看,细颗粒的加工对磷酸盐工业具有重要意义。本文探讨了通过浮选工艺处理磷酸矿选矿厂的细尾矿的问题,尽管传统观点认为超细颗粒不可浮选。根据冶金工艺性能结果,比较了有无纳米气泡(NBs)时,浮选机和浮选柱两种处理工艺下磷酸盐矿物的浮选行为。由于NBs(由水动力空化作用产生)具有有趣的和独特的性能,如高稳定性、耐久性和高比表面积,提高了其在采矿、冶金和环境领域的应用。本研究结果表明,在没有NBs的情况下,使用浮选机工艺获得了P_(2)O_(5)含量为26.9%、回收率为29.13%的精矿,而使用浮选柱工艺,得到的P_(2)O_(5)含量为31.6%,回收率为32.74%的精矿。在NBs存在的情况下,通过浮选机和浮选柱获得精矿的回收率分别为40.49%和41.26%,P_(2)O_(5)含量分别为28.47%和30.43%。对比研究表明,在NBs存在的情况下,与浮选机相比,浮选柱工艺对磷矿的处理效率更高,泡沫层更厚。

关键词：浮选柱浮选机磷酸盐尾矿黏液纳米气泡 Venturi管水动力空化

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Application and comparison of RNN, RBFNN and MNLR approaches on prediction of flotation column performance

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International Journal of Mining Science and Technology 2015年第6期25卷 983-990页

作者： Nakhaei fardis Irannajad Mehdi Department of Mining & Metallurgical Engineering Amirkabir University of Technology

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.

关键词： RBF神经网络性能预测浮选柱网络应用 LR方法径向基函数神经网络多元非线性回归 MN

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^(1)H NMR tests on damaged and undamaged XLPE and SiR samples

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High Voltage 2019年第3期4卷 203-209页

作者： Lydia Gkoura Taiji Wang Athanasios Anastasiou Noureddine Harid Huw Griffiths Manu Haddad mich.lis fardis Marina Karayianni Institute of Nanoscience&Nanotechnology National Centre for Scientific Research(NCSR)DemokritosAthensGreece School of Chemical Engineering National Technical University of AthensAthensGreece Department of Electrical and Computer Engineering Advanced Power and Energy Research CentreKhalifa UniversityAbu DhabiUnited Arab Emirates School of Engineering Advanced High Voltage Engineering Research CentreCardiff UniversityCardiffUK

Cross-linked polyethylene(XLPE)and silicone rubber(SiR)samples were subjected to a high-voltage AC stress plane-plane configuration and inclined plane test,*** voltage was applied such that discharge was observed across the surface of the XLPE test sample for several hours and for visible damage to occur on SiR samples also after several *** stressed samples together with virgin samples from the same manufactured batch were tested using nuclear magnetic resonance(NMR)***,^(1)H NMR spin-lattice(T_(1))and spin-spin(T_(2))relaxation time measurements were employed to examine potential changes in the chemical bonding of undamaged and damaged XLPE and SiR *** results show that there may be a moderate increase in the T_(1)and T_(2)values of the damaged samples in comparison with the undamaged *** raises the possibility that NMR can be a useful additional experimental tool in characterising material degradation.

关键词： XLPE rubber relaxation

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