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Analysis of Turbulence Models Performance for the Predictions of Flow Yield, Efficiency, and Pressure Drop of a Gas-solid Cyclone Separator

机译:用于预测气固旋风分离器流量,效率和压降的湍流模型性能分析

摘要

This paper presents the results obtained from the application of computational fluid dynamics (CFD) to modelling the flow field of a Lapple cyclone and to optimizing the cyclone based upon its geometrical parameters. A pre-processor software GAMBIT was employed to set up the configuration, discretisation, and boundary conditions of the cyclone. The characteristics of the cyclone being studied was 0.2 m in diameter, receiving a gas flow rate of 0.1 m3/s with a particle mass loading of 0.01 kg/m3. A commercial CFD code FLUENT 6.2.16 was employed to simulate the flow field and particle dynamics in the cyclone. The objective of this research was to investigate the performance of a number of turbulence models on the prediction of the flow field, collection efficiency and pressure drop in the Lapple cyclone. A number of five turbulence models under Reynolds Averaged Navier Stokes (RANS) category, including Spallart-Allmaras, standard k-ε model, RNG k-ε model, standard k-ω model, and Reynolds Stress Model (RSM) were examined in the simulation of the flow field and particle dynamics inside the cyclone. A validation of all calculation was performed by comparing the predicted results in terms of axial and tangential velocities, efficiency and pressure drop against experimental data of a Lapple cyclone taken from literature. The results of the investigation show that out of five turbulence models being tested, the RSM presented the best predicted results. The predictions of axial and tangential velocities as well as cyclone efficiency by this model are in excellent agreement with the experimental data. Although the pressure drop in the cyclone is under-predicted, the RSM predictions are far better than those of other model. Other turbulence models are over-predicted and under-predicted the axial and tangential velocity, respectively. With respect to efficiency and pressure drop of the cyclone, other models are capable of following the trend of the experimental data but they failed to agree with the experimental values. These results suggest that the RSM is the most suitable turbulence model to represent the flow field and particle dynamics inside a cyclone gas-solid separator.
机译:本文介绍了通过应用计算流体力学(CFD)对Lapple旋风分离器的流场进行建模并根据其几何参数优化旋风分离器获得的结果。使用预处理软件GAMBIT来设置旋风分离器的配置,离散化和边界条件。所研究的旋风分离器的直径为0.2 m,气体流量为0.1 m3 / s,颗粒质量负荷为0.01 kg / m3。商业CFD代码FLUENT 6.2.16用于模拟旋风分离器中的流场和粒子动力学。这项研究的目的是研究许多湍流模型在预测Lapple旋风分离器的流场,收集效率和压降方面的性能。在Reynolds平均Navier Stokes(RANS)类别下,检查了五个湍流模型,包括Spallart-Allmaras,标准k-ε模型,RNGk-ε模型,标准k-ω模型和雷诺应力模型(RSM)。旋风分离器内部流场和颗粒动力学的模拟。通过比较轴向和切向速度,效率和压降的预测结果与从文献中获得的Lapple旋风分离器的实验数据,对所有计算进行了验证。调查结果表明,在测试的五个湍流模型中,RSM给出了最佳的预测结果。该模型对轴向和切向速度以及旋风效率的预测与实验数据非常吻合。尽管旋风分离器中的压降预测不足,但RSM预测远优于其他模型。其他湍流模型的轴向和切向速度分别被高估和低估。关于旋风分离器的效率和压降,其他模型也能够跟踪实验数据的趋势,但是它们与实验值不一致。这些结果表明,RSM是最合适的湍流模型,用于表示旋风分离器内的流场和颗粒动力学。

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