A Parameter Identification Method for the Rotordynamic Coefficients of a High Reynolds Number Hydrostatic Bearing

1993 ◽  
Vol 115 (3) ◽  
pp. 264-270 ◽  
Author(s):  
C. Rouvas ◽  
D. W. Childs
Keyword(s):  
Reynolds Number ◽  
Fluid Flow ◽  
High Reynolds Number ◽  
Theoretical Development ◽  
Single Frequency ◽  
Unique Problem ◽  
Hydrostatic Bearing ◽  
Rotordynamic Coefficients ◽  
Ratio Speed ◽  
High Reynolds

In identifying the rotordynamic coefficients of a high-Reynolds-number hydrostatic bearing, fluid-flow induced forces present a unique problem, in that they provide an unmeasureable and uncontrollable excitation to the bearing. An analysis method is developed that effectively eliminates the effects of fluid-flow induced excitation on the estimation of the bearing rotordynamic coefficients, by using power spectral densities. In addition to the theoretical development, the method is verified experimentally by single-frequency testing, and repeatability tests. Results obtained for a bearing are the twelve rotordynamic coefficients (stiffness, damping, and inertia coefficients) as functions of eccentricity ratio, speed, and supply pressure.

scholarly journals Stable simulation of fluid flow with high-Reynolds number using Ehrenfests’ steps

2007 ◽  
Vol 45 (1-4) ◽  
pp. 389-408 ◽  
Author(s):  
R. Brownlee ◽  
A. N. Gorban ◽  
J. Levesley
Keyword(s):  
Reynolds Number ◽  
Fluid Flow ◽  
High Reynolds Number ◽  
High Reynolds

scholarly journals Aerodynamic Flow Visualisation Over Surfaces Using Smoke Separation Method from Ansys Fluent

2020 ◽  
Vol 5 (7) ◽  
pp. 32-35
Author(s):  
Virendra Talele ◽  
Niranjan Sonawane ◽  
Omkar Chavan ◽  
Akash Divate ◽  
Niraj Badhe ◽  
...  
Keyword(s):  
Reynolds Number ◽  
Fluid Flow ◽  
High Reynolds Number ◽  
Turbulence Modeling ◽  
Tracking System ◽  
Adverse Pressure Gradient ◽  
Point Particle ◽  
Flow Visualisation ◽  
Ansys Fluent ◽  
High Reynolds

In the present study, three workbench problem for turbulence modeling with high Reynolds number is used to determine the behavior of fluid flow around the surfaces. The cases for simulation is developed using Ansys workbench CFD fluent module. The computational results are obtained using solution sets of high Reynolds number with the LagrangianEulerian (LE) approach of point particle tracking system in Nevers stoke RANS Equation. The effect of flow pattern around the surface and its kinetic behavior of fluid is evaluated in post-process method of results. By observation, it has been tabulated that fluid flow separation is arousal at the corner end of all surfaces which happens due to evoking of a large adverse pressure gradient.

Efficient Generation of High-Reynolds-Number Homogeneous Turbulence by Disturbances Composed of Two Frequency Components

2015 ◽  
Author(s):  
Kotaro Takamure ◽  
Shigehira Ozono
Keyword(s):  
Reynolds Number ◽  
High Reynolds Number ◽  
Random Phase ◽  
Homogeneous Turbulence ◽  
Single Frequency ◽  
Tunnel Length ◽  
Driving Mode ◽  
Spectral Peaks ◽  
Frequency Components ◽  
High Reynolds

We attempted to determine the number of frequency components required for efficient turbulence generation using a multi-fan type wind tunnel where 99 fans were driven to generate turbulence. In a previous study, a random-phase mode was applied, where an input signal composed of forty frequency components was fed to each fan with quasi-random phases. Using this driving mode, we achieved high-Reynolds-number homogeneous turbulence of Reλ ∼ 750 in a relatively short distance. In the present study, in order to understand the elementary process of the evolution, one single frequency or two frequencies were used, instead of forty. When using the single frequency, initial dominant spectral peaks remain at lower frequencies over the tunnel length. In the case of two frequencies, f1 and f2 (f1 = n1f0 and f2 = n2f0; n1 < n2), where n1 and n2 are integers, and f0 is defined as the reciprocal of a basic input data period, the turbulence characteristics depend on the relation between n1 and n2. When n1 and n2 are not coprime (i.e., n2 can be divided by n1), dominant spectral peaks remain over the tunnel length as in the case of using a single frequency, but when coprime (i.e., n2 cannot be divided by n1), the spectral shape becomes relatively smooth with the initial dominant peaks disappearing. However, it was found that the development of turbulence is much slower for the two-frequency case than for the forty-frequency case.

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