Performance and implementation of the Launder-Sharma low-Reynolds number turbulence model
Performance and implementation of the Launder-Sharma low-Reynolds number turbulence model
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DOI：
10.1016/j.compfluid.2013.02.020
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发表时间：
2013-06-25
影响因子：
2.8
通讯作者：
He, S.
中科院分区：
文献类型：
--
作者：
Mathur, A.;He, S.
Launder-Sharma Launder-Sharma模型（Lett. Heat Mass Transfer 1，1974，131 -138）是最早和最广泛使用的低雷诺数（LRN）模型之一，并且已经被证明对于一系列湍流问题与实验和DNS数据良好地一致，比许多其他LRN k-RNN模型表现得更好。然而，最近的一些研究，包括那些使用商业计算流体动力学求解器报告的模型表现，否则。在本研究中，LS模型已在FLUENT中使用用户自定义函数（UDF），其性能在预测稳定和非稳定的湍流已被测试，并发现与文献中报道的使用“内部”CFD代码密切一致。然而，该FLUENT-UDF LS模型的性能与内置的FLUENT LS模型非常不同。前者与实验和DNS数据吻合良好，而后者则不然。此外，UDF被用来证明，模型预测是非常敏感的模型配方的解释。因此，它的结论是，而LS模型是不敏感的数值方法或编码方法，它是敏感的模型的配方解释的变化。(C)2013爱思唯尔有限公司保留所有权利。
The Launder-Sharma Launder-Sharma model (Lett. Heat Mass Transfer 1,1974,131-138) is one of the earliest and most-widely used low-Reynolds number (LRN) models and has been shown to be in good agreement with experimental and DNS data for a range of turbulent flow problems, performing better than many other LRN k-epsilon models. However, some recent studies including those using commercial CFD solvers report the model to behave otherwise. In the present study, the LS model has been implemented in FLUENT using user-defined functions (UDFs), and its performance in predicting steady and unsteady turbulent flows has been tested and found to agree closely with those reported in the literature using 'in-house' CFD codes. However, this FLUENT-UDF LS model performs very differently from the in-built FLUENT LS model. The former agrees well with experimental and DNS data, whereas the latter does not. In addition, the UDF is used to demonstrate that the model predictions are very sensitive to the interpretation of the model formulation. Consequently, it is concluded that whereas the LS model is not sensitive to numerical method or method of coding, it is sensitive to changes in the interpretation of the formulation of the model. (C) 2013 Elsevier Ltd. All rights reserved.