Experimental Investigation of Pressure Drop Characteristics of Viscous Fluid Flow Through Small Diameter Orifices

被引:4
|
作者
Bohra, Lalit Kumar [1 ]
Mincks, Leo M. [2 ]
Garimella, Srinivas [3 ]
机构
[1] ExxonMobil Upstream Res Co, Gas & Facil Div, Houston, TX 77098 USA
[2] Iowa State Univ, Ames, IA 50011 USA
[3] Georgia Inst Technol, George W Woodruff Sch Mech Engn, ASME, Atlanta, GA 30332 USA
来源
JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME | 2021年 / 143卷 / 02期
关键词
orifice flow; pressure drop; Euler number; generalized Reynolds number; viscous flow; non-Newtonian;
D O I
10.1115/1.4048617
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
An experimental study on the flow of a highly viscous fluid through small diameter orifices was conducted. Pressure drops were measured for each of nine orifices, including orifices of nominal diameter 0.5, 1, and 3 mm and three different orifice thicknesses, over wide ranges of flow rates and temperatures. The fluid under consideration exhibits steep dependence of the properties (changes of several orders of magnitude) as a function of temperature and pressure and is also non-Newtonian at the lower temperatures. At small values of Reynolds number, an increase in aspect ratio (length/diameter ratio of the orifice) causes an increase in Euler number. It was also found that at extremely low Reynolds numbers, the Euler number was very strongly influenced by the Reynolds number, while the dependence becomes weaker as the Reynolds number increases toward the turbulent regime, and the Euler number tends to assume a constant value determined by the aspect ratio and the diameter ratio. A two-region (based on Reynolds number) model was developed to predict Euler number as a function of diameter ratio, aspect ratio, viscosity ratio, and generalized Reynolds number. It is shown that for such a highly viscous fluid with some non-Newtonian behavior, accounting for the shear rate through the generalized Reynolds number results in a considerable improvement in the predictive capabilities of the model. Over the laminar, transition, and turbulent regions, the model predicts 86% of the data within +/- 25% for the geometry and operating conditions investigated in this study.
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页数:12
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