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Computational Fluid Dynamics of Advanced Gas Dispersion: Deep Hollow Blade Turbine

机译:先进气体扩散的计算流体动力学:深空心叶片涡轮机

摘要

Stirred tanks are widely used in the chemical and biochemical process industries. Mixing, fermentation, polymerization, crystallization and liquid-liquid extractions are significant examples of industrial operations usually carried out in tanks agitated by one or more impellers. The flow phenomena inside the tank are of great importance in the design, scale-up and optimization of tasks performed by stirred tanks. This work presents of a stirred tank agitated by an advanced gas dispersion impeller namely deep hollow blade turbine (HEDT) using Computational Fluid Dynamic (CFD) method. The standard k-ε, realizable k-ε and shear-stress transport k-ɷ were considered in this study for comparison purposes. Predictions of the impeller-angle-resolved and time-averaged turbulent flow have been evaluated and compared with data from Particle Image Velocimetry (PIV) measurements. Multiple Reference Frame (MRF) used to capture flow features in details and predicts flow for steady state for the impeller blades relative to the tank baffles. Unsteady solver indeed predicts periodic shedding, and leads to much better concurrence with available experimental data than has been achieve with steady computation.
机译:搅拌罐广泛用于化学和生化过程工业。混合,发酵,聚合,结晶和液-液萃取是工业操作的重要实例,通常在一个或多个叶轮搅动的罐中进行。槽内的流动现象对于搅拌槽执行的任务的设计,放大和优化非常重要。这项工作提出了使用先进的气体分散叶轮(即深空叶片涡轮机(HEDT))使用计算流体动力学(CFD)方法搅拌的搅拌釜。为了进行比较,在本研究中考虑了标准k-ε,可实现的k-ε和切应力传递k-ɷ。已经评估了叶轮角度分辨和时间平均湍流的预测,并将其与“粒子图像测速”(PIV)测量的数据进行了比较。多参考框架(MRF)用于详细捕获流量特征并预测叶轮叶片相对于箱体挡板的稳态流量。非稳态求解器确实可以预测周期性的脱落,并且与可用的稳定实验相比,可获得的实验数据的并发性要好得多。

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    Norleen Isa;

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  • 年度 2012
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