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首页> 外文期刊>International Journal of Mineral Processing >Numerical studies of the influence of particles' size distribution characteristics on the gravity separation performance of Liquid-solid Fluidized Bed Separator
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Numerical studies of the influence of particles' size distribution characteristics on the gravity separation performance of Liquid-solid Fluidized Bed Separator

机译：粒度分布特征对液固流化床分离器重力分离性能影响的数值研究

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A new CFD model for Liquid-solid Fluidized Bed Separator (LSFBS), namely the Eulerian-Eulerian-Lagrangian/RNG k-epsilon approach, was put forward and validated. According to the simulated separation results of two cases, the root-mean-square error (RMSE) between predicted partition numbers of all density fractions and corresponding experimental values were 2.47 and 2.83 respectively, demonstrating the CFD model was able to give accurate simulation results. The Rosin-Rammler model was used to describe the size distribution characteristics (SDC) of the feed, with the parameter D-x and n describing the fineness and particles size variation of the feed respectively. Single-factor tests and central composite design were then developed and simulated using the CFD model to investigate the influence of the two aspects of SDC on the separation performance of LSFBS based on density. The simulated separation results indicate that the finer the feed is, the greater the separation density (delta(50)) and E-p value are; the smaller the particles size variation is, the smaller the delta(50) and E-p value are. According to the response surface analysis, the influence of feed fineness on delta(50) is larger than that of particles size variation while the influence of feed fineness on E-p is smaller than that of particles size variation; the interactive effect between these two factors has a noteworthy influence on E-p but insignificant influence on delta(50). (C) 2016 Elsevier B.V. All rights reserved.
机译：提出并验证了液固流化床分离器（LSFBS）的一种新的CFD模型，即欧拉-欧拉-拉格朗日/ RNGk-ε方法。根据两种情况的模拟分离结果，所有密度分数的预测分配数与相应实验值之间的均方根误差（RMSE）分别为2.47和2.83，证明了CFD模型能够给出准确的模拟结果。使用Rosin-Rammler模型描述饲料的粒度分布特征（SDC），参数D-x和n分别描述饲料的细度和粒度变化。然后使用CFD模型开发和模拟单因素测试和中心复合设计，以研究SDC的两个方面对基于密度的LSFBS分离性能的影响。模拟的分离结果表明，进料越细，分离密度（delta（50））和E-p值越大;粒径变化越小，Δ（50）和E-p值越小。根据响应面分析，进料细度对Δ（50）的影响大于粒径变化的影响，而进料细度对E-p的影响小于粒径变化的影响。这两个因素之间的交互作用对E-p有显着影响，但对delta（50）的影响不显着。 （C）2016 Elsevier B.V.保留所有权利。

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