Prediction of Anisotropy of the Near-Wall Turbulence With an Anisotropic Low-Reynolds-Number k–ε Turbulence Model

1990 ◽  
Vol 112 (4) ◽  
pp. 521-524 ◽  
Author(s):  
Hyon Kook Myong ◽  
Nobuhide Kasagi
Keyword(s):  
Reynolds Number ◽  
Turbulence Model ◽  
Low Reynolds Number ◽  
Wall Turbulence ◽  
Low Reynolds ◽  
Near Wall Turbulence ◽  
Near Wall

scholarly journals Turbulence model performance for ventilation components pressure losses

2021 ◽  
Author(s):  
Karsten Tawackolian ◽  
Martin Kriegel
Keyword(s):  
Reynolds Number ◽  
Turbulence Model ◽  
Pressure Loss ◽  
Low Reynolds Number ◽  
Turbulence Models ◽  
Reynolds Numbers ◽  
Test Case ◽  
Pressure Losses ◽  
Loss Coefficients ◽  
Near Wall

AbstractThis study looks to find a suitable turbulence model for calculating pressure losses of ventilation components. In building ventilation, the most relevant Reynolds number range is between 3×104 and 6×105, depending on the duct dimensions and airflow rates. Pressure loss coefficients can increase considerably for some components at Reynolds numbers below 2×105. An initial survey of popular turbulence models was conducted for a selected test case of a bend with such a strong Reynolds number dependence. Most of the turbulence models failed in reproducing this dependence and predicted curve progressions that were too flat and only applicable for higher Reynolds numbers. Viscous effects near walls played an important role in the present simulations. In turbulence modelling, near-wall damping functions are used to account for this influence. A model that implements near-wall modelling is the lag elliptic blending k-ε model. This model gave reasonable predictions for pressure loss coefficients at lower Reynolds numbers. Another example is the low Reynolds number k-ε turbulence model of Wilcox (LRN). The modification uses damping functions and was initially developed for simulating profiles such as aircraft wings. It has not been widely used for internal flows such as air duct flows. Based on selected reference cases, the three closure coefficients of the LRN model were adapted in this work to simulate ventilation components. Improved predictions were obtained with new coefficients (LRNM model). This underlined that low Reynolds number effects are relevant in ventilation ductworks and give first insights for suitable turbulence models for this application. Both the lag elliptic blending model and the modified LRNM model predicted the pressure losses relatively well for the test case where the other tested models failed.

Research on improvements of low Reynolds number turbulence model based on flow around automobiles

2020 ◽  
Vol 78 (11) ◽  
pp. 674-695
Author(s):  
Yi Yang ◽  
Guanglin Qiang ◽  
Zhen Chen ◽  
Zhengqi Gu ◽  
Yong Zhang
Keyword(s):  
Reynolds Number ◽  
Turbulence Model ◽  
Low Reynolds Number ◽  
Model Based ◽  
Low Reynolds
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