Simulating drag reduction phenomenon in turbulent pipe flows
Simulating drag reduction phenomenon in turbulent pipe flows
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DOI：
10.1016/j.mechrescom.2008.06.003
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发表时间：
2008-12
影响因子：
2.4
通讯作者：
M. Mehrabadi;K. Sadeghy
中科院分区：
文献类型：
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作者：
M. Mehrabadi;K. Sadeghy
在湍流管流中，使用聚合物添加剂减阻是一种有趣的现象，它是由汤姆斯首先发现的[汤姆斯，B.A.，1948]。高雷诺数下直管中线性聚合物溶液流动的一些观察。程序第一个Int.丛林。流变液。2,135-141]。由于它的工业重要性，这一现象在过去一直是理论和实验领域的研究课题。至于涉及的机制，一直认为聚合物添加剂通过增加基础流体的拉伸粘度来影响壁面附近的湍流爆发的结构(见[Lumley，J.L.，Blossey，P.，1998]。湍流的控制。安。流体机械牧师。30,311-327])。在实践中，某些高相对分子质量的柔性聚合物的浓度低至20ppm，减阻效果高达90%。过去，预测使用聚合物添加剂获得如此巨大的减阻效果是不可能的，部分原因是计算设备的局限性，也是因为用于模拟的本构方程的不足。最近，Pinho，F.T.，2003。减阻流体湍流模型的广义核函数框架和k-ε类型闭合的建议。J.非牛顿流体机械。114,149-184]对广义牛顿流体(GNF)模型进行了修改，使其除了考虑剪切粘度(流体粘性行为的度量)外，还考虑了拉伸粘度(流体弹性行为的度量)。基于这一思想，Pinho(2003)首次推导出粘弹性流体的时间平均湍流公式。这些配方被Cruz和Pinho使用[Cruz，D.O.A.，Pinho，F.T.，2003]。用低雷诺数k-ε模型预测减阻流体的湍流管流。J.非牛顿流体机械。114,109-148]和Cruz等人。[Cruz，D.O.A.，Pinho，F.T.，Resende，P.R.，2004.对新应力进行建模以改进粘弹性管流的减阻预测。J.非牛顿流体机械。By嵌入Nagano-Hishida的低雷诺湍流模型[Nagano，Y.，Hishida，M.，1987].壁面湍流剪切流k-ε模型的改进形式。J.流体工程。109-156]。他们使用这个众所周知的湍流模型进行了几次模拟，结果表明，它可以很好地预测一些聚合物添加剂在实践中观察到的大幅减阻。但对于某些其他聚合物，预测结果就不那么好了。在这项工作中，将表明，如果使用另一种称为LaUnder-Sharma模型的低雷诺数k-ε湍流模型，则可以对这些聚合物获得更好的预测。湍流能量耗散模型在旋转盘附近流动计算中的应用。让我们来吧。热质传递1,131-138]用于模拟。
Drag reduction using polymeric additives is an interesting phenomenon in turbulent pipe flows which was first discovered by Toms [Toms, B.A., 1948. Some observations on the flow of linear polymer solutions through straight tubes at large Reynolds numbers. Proc. First Int. Cong. Rheol. 2, 135–141]. Due to its industrial importance, the phenomenon has been the subject of much study in the past, in both theoretical and experimental domains alike. As to the mechanisms involved, it has been argued that polymeric additives act through affecting the structure of turbulent bursts near the wall by boosting the extensional viscosity of the base fluid (see [Lumley, J.L., Blossey, P., 1998. Control of turbulence. Ann. Rev. Fluid Mech. 30, 311–327]). In practice, drag reduction as large as 90% has been achieved with concentration as low as 20ppm of certain high-molecular-weight flexible polymers. Prediction of such huge drag reductions obtained using polymeric additives has not been possible in the past partly, because of the limitations of the computational facilities and also because of the inadequacies of the constitutive equations used for the simulations. Recently, Pinho [Pinho, F.T., 2003. A GNF framework for turbulent flow models of drag reducing fluids and proposal for a k–ε type closure. J. Non-Newtonian Fluid Mech. 114, 149–184] modified the generalized Newtonian fluid (GNF) model in such a way that it could take into account the extensional viscosity (a measure of the elastic behavior of a fluid) in addition to the shear viscosity (a measure of the viscous behavior of a fluid). Based on this idea, Pinho (2003) derived the first time-averaged turbulent flow formulations for viscoelastic fluids. These formulations were used by Cruz and Pinho [Cruz, D.O.A., Pinho, F.T., 2003. Turbulent pipe flow predictions with a low-Reynolds number k–ε model for drag reducing fluids. J. Non-Newtonian Fluid Mech. 114, 109–148] and Cruz et al. [Cruz, D.O.A., Pinho, F.T., Resende, P.R., 2004. Modeling the new stress for improved drag reduction predictions of viscoelastic pipe flow. J. Non-Newtonian Fluid Mech. 121, 127–141] by embedding the low-Reynolds turbulence model of Nagano–Hishida [Nagano, Y., Hishida, M., 1987. Improved form of the k–ε model for wall turbulent shear flows. J. Fluid Eng. 109–156]. They performed several simulations using this well-known turbulence model and showed that it can well predict the large drag reduction observed in practice for some polymeric additives. But for certain other polymers the prediction were found not to be so great. In this work, it will be shown that better predictions can be obtained for these polymers if use is made of another low-Reynolds number k–ε turbulence model called Launder–Sharma model [Launder, B.E., Sharma, B.I., 1974. Application of the energy dissipation model of turbulence to the calculation of flow near a spinning disc. Lett. Heat Mass Transfer 1, 131–138] for the simulations.