Numerical study on the mean velocity distribution law of air backflow and the effective interaction length of airflow in forced ventilated tunnels

2015 ◽  
Vol 46 ◽  
pp. 104-110 ◽  
Author(s):  
Chunzi Nan ◽  
Jiming Ma ◽  
Zhao Luo ◽  
Shuangling Zheng ◽  
Zhengwei Wang
Keyword(s):  
Velocity Distribution ◽  
Numerical Study ◽  
Effective Interaction ◽  
Distribution Law ◽  
Interaction Length ◽  
Mean Velocity ◽  
The Mean

Numerical Study on the Effect of Bend Angle on Turbulent Flow through Oscillating Bend

2009 ◽  
Vol 4 (1) ◽  
Author(s):  
Elham Ameri ◽  
M Nasr Esfahany
Keyword(s):  
Numerical Study ◽  
Bend Angle ◽  
Curvature Radius ◽  
Primary Flow ◽  
Mean Velocity ◽  
Contour Map ◽  
Curved Pipes ◽  
Flow Through ◽  
The Mean ◽  
Turbulent Air Flow

The effect of the bend angle on the unsteady developing turbulent air flow through oscillating circular-sectioned curved pipes with the various angles of 180°, 135° and 90° was investigated numerically. The bends had a diameter of 106 mm and a curvature radius ratio of 6.0 with long, straight upstream and downstream sections. Results of the mean velocity and static pressure were obtained at a Reynolds number of 31200 and at various longitudinal stations. The velocity of the primary flow was illustrated in the form of contour map and vector diagram. From the inlet plane of the three oscillating bends to the angle of 45°, the velocity fields in 180°, 90° and 135° bends are similar. The high velocity regions, however, occur near the upper and lower parts in 90° and 180° bends, respectively.

On Turbulent Flow Between Parallel Plates

1953 ◽  
Vol 20 (1) ◽  
pp. 109-114
Author(s):  
S. I. Pai
Keyword(s):  
Turbulent Flow ◽  
Velocity Distribution ◽  
Poiseuille Flow ◽  
The Other ◽  
Turbulent Velocity ◽  
Parallel Plates ◽  
Mean Velocity ◽  
Reynolds Equations ◽  
Mean Pressure ◽  
The Mean

Abstract The Reynolds equations of motion of turbulent flow of incompressible fluid have been studied for turbulent flow between parallel plates. The number of these equations is finally reduced to two. One of these consists of mean velocity and correlation between transverse and longitudinal turbulent-velocity fluctuations u 1 ′ u 2 ′ ¯ only. The other consists of the mean pressure and transverse turbulent-velocity intensity. Some conclusions about the mean pressure distribution and turbulent fluctuations are drawn. These equations are applied to two special cases: One is Poiseuille flow in which both plates are at rest and the other is Couette flow in which one plate is at rest and the other is moving with constant velocity. The mean velocity distribution and the correlation u 1 ′ u 2 ′ ¯ can be expressed in a form of polynomial of the co-ordinate in the direction perpendicular to the plates, with the ratio of shearing stress on the plate to that of the corresponding laminar flow of the same maximum velocity as a parameter. These expressions hold true all the way across the plates, i.e., both the turbulent region and viscous layer including the laminar sublayer. These expressions for Poiseuille flow have been checked with experimental data of Laufer fairly well. It also shows that the logarithmic mean velocity distribution is not a rigorous solution of Reynolds equations.

Accuracy Investigation of Active Flow Control Using Synthetic Jets

2015 ◽  
Vol 741 ◽  
pp. 475-480
Author(s):  
Na Gao ◽  
Chen Pu ◽  
Bao Chen
Keyword(s):  
Flow Control ◽  
Velocity Distribution ◽  
Active Flow Control ◽  
Flow Fields ◽  
Synthetic Jet ◽  
Synthetic Jets ◽  
Experimental Results ◽  
Center Line ◽  
Mean Velocity ◽  
The Mean

2nd order implicit format is implemented in the Navier-Stokes code to deal with instantaneous item unsteady flows. Three simulations are made to testify the method on flow control. First, the external flow fields of synthetic jets are simulated, the mean velocity on the center line, the jet width and velocity distribution are compared well with experimental results. Secondly, the flow fields of synthetic jet in a crossflow are simulated, orifice slot, the mean velocity on the center line and velocity distribution are compared well with experimental results. Finally, the flow control experiments on separation of airfoil are simulated, control methods include steady suction and synthetic jets. Both methods show their ability to favorably effect the flow separation, shortening the length of separation bubble and improving the pressure levels in separation areas in different degrees.

On the mechanism of wall turbulence

1982 ◽  
Vol 119 ◽  
pp. 173-217 ◽  
Author(s):  
A. E. Perry ◽  
M. S. Chong
Keyword(s):  
Velocity Distribution ◽  
Turbulence Intensity ◽  
Scaling Laws ◽  
Heated Surface ◽  
Broad Band ◽  
Wall Turbulence ◽  
Mean Velocity ◽  
Quantitative Measurements ◽  
Temperature Distributions ◽  
The Mean

In this paper an attempt is made to formulate a model for the mechanism of wall turbulence that links recent flow-visualization observations with the various quantitative measurements and scaling laws established from anemometry studies. Various mechanisms are proposed, all of which use the concept of the horse-shoe, hairpin or ‘A’ vortex. It is shown that these models give a connection between the mean-velocity distribution, the broad-band turbulence-intensity distributions and the turbulence spectra. Temperature distributions above a heated surface are also considered. Although this aspect of the work is not yet complete, the analysis for this shows promise.

Numerical study of turbulent magnetohydrodynamic channel flow

2007 ◽  
Vol 572 ◽  
pp. 179-188 ◽  
Author(s):  
THOMAS BOECK ◽  
DMITRY KRASNOV ◽  
EGBERT ZIENICKE
Keyword(s):  
Channel Flow ◽  
Numerical Study ◽  
Layer Structure ◽  
Momentum Balance ◽  
Mean Flow ◽  
Mean Velocity ◽  
Static Approximation ◽  
The Mean ◽  
Magnetohydrodynamic Channel ◽  
Normal Magnetic Field

Mean flow properties of turbulent magnetohydrodynamic channel flow with electrically insulating channel walls are studied using high-resolution direct numerical simulations. The Lorentz force due to the homogeneous wall-normal magnetic field is computed in the quasi-static approximation. For strong magnetic fields, the mean velocity profile shows a clear three-layer structure consisting of a viscous region near each wall and a plateau in the middle connected by logarithmic layers. This structure reflects the significance of viscous, turbulent, and electromagnetic stresses in the streamwise momentum balance dominating the viscous, logarithmic, and plateau regions, respectively. The width of the logarithmic layers changes with the ratio of Reynolds- and Hartmann numbers. Turbulent stresses typically decay more rapidly away from the walls than predicted by mixing-length models.

VELOCITY DISTRIBUTION IN THE DUKE–RUBINSTEIN MODEL

2002 ◽  
Vol 13 (06) ◽  
pp. 829-835
Author(s):  
P. PAŚCIAK ◽  
M. J. KRAWCZYK ◽  
K. KUŁAKOWSKI
Keyword(s):  
Velocity Distribution ◽  
Electric Fields ◽  
Gel Electrophoresis ◽  
Dna Molecules ◽  
Mean Velocity ◽  
The Mean ◽  
High Fields ◽  
High Electric Fields

The Duke–Rubinstein model of gel electrophoresis is applied to calculate the velocity of DNA molecules. We have found that the velocity distribution becomes flat at high electric fields. Simultaneously, the percentage of immobile molecules increases. Effectively, the mean velocity starts to decrease at high fields. The field value, where the mean velocity is maximal, decreases with the molecule length. The results are compared with those from similar calculations obtained by Heukelum and Beljaars within the cage model.

A Comparison of Techniques for Particle Rebound Measurement in Gas Turbine Applications

2015 ◽  
Author(s):  
Jeffrey P. Bons ◽  
Rory Blunt ◽  
Steven Whitaker
Keyword(s):  
Standard Deviation ◽  
Velocity Distribution ◽  
Gas Turbine ◽  
Correlation Coefficient ◽  
Strong Dependence ◽  
Individual Particle ◽  
Aluminum Surface ◽  
Trajectory Data ◽  
Mean Velocity ◽  
The Mean

The rebound characteristics of 100–500μm quartz particles from an aluminum surface were imaged using the particle shadow velocimetry (PSV) technique. Particle trajectory data were acquired over a range of impact velocity (30–90 m/s) and impact angle (20°–90°) typical for gas turbine applications. The data were then analyzed to obtain coefficients of restitution (CoR) using four different techniques: (1) individual particle rebound velocity divided by the same particle’s inbound velocity (2) individual particle rebound velocity divided by inbound velocity taken from the mean of the inbound distribution of velocities from all particles (3) rebound velocity distribution divided by inbound velocity distribution related using distribution statistics and (4) the same process as (3) with additional precision provided by the correlation coefficient between the two distributions. It was found that the mean and standard deviation of the CoR prediction showed strong dependence on the standard deviation of the inbound velocity distribution. The two methods that employed statistical algorithms to account for the distribution shape [methods (3) and (4)] actually overpredicted mean CoR by up to 6% and CoR standard deviation by up to 100% relative to method (1). The error between the methods is shown to be a strong (and linear) function of correlation coefficient, which is typically 0.2–0.6 for experimental CoR data. Non-Gaussianity of the distributions only accounts for up to 1% of the error in mean CoR, and this largely from the non-zero skewness of the inbound velocity distribution. Particle rebound data acquired using field average techniques that do not provide an estimate of correlation coefficient are most accurately evaluated using method (2). Method (3) can be used with confidence if the standard deviation of the inbound velocity distribution is less than 10% of the mean velocity, or if a linear correction based on an assumed correlation coefficient is applied.

Large eddy simulation of a stratified boundary layer under an oscillatory current

2009 ◽  
Vol 643 ◽  
pp. 233-266 ◽  
Author(s):  
BISHAKHDATTA GAYEN ◽  
SUTANU SARKAR ◽  
JOHN R. TAYLOR
Keyword(s):  
Boundary Layer ◽  
Large Eddy Simulation ◽  
Mixed Layer ◽  
Numerical Study ◽  
Bottom Boundary Layer ◽  
Mean Velocity ◽  
Bottom Boundary ◽  
Eddy Simulation ◽  
Large Eddy ◽  
The Mean

A numerical study based on large eddy simulation is performed to investigate a bottom boundary layer under an oscillating tidal current. The focus is on the boundary layer response to an external stratification. The thermal field shows a mixed layer that is separated from the external stratified fluid by a thermocline. The mixed layer grows slowly in time with an oscillatory modulation by the tidal flow. Stratification strongly affects the mean velocity profiles, boundary layer thickness and turbulence levels in the outer region although the effect on the near-bottom unstratified fluid is relatively mild. The turbulence is asymmetric between the accelerating and decelerating stages. The asymmetry is more pronounced with increasing stratification. There is an overshoot of the mean velocity in the outer layer; this jet is linked to the phase asymmetry of the Reynolds shear stress gradient by using the simulation data to examine the mean momentum equation. Depending on the height above the bottom, there is a lag of the maximum turbulent kinetic energy, dissipation and production with respect to the peak external velocity and the value of the lag is found to be influenced by the stratification. Flow instabilities and turbulence in the bottom boundary layer excite internal gravity waves that propagate away into the ambient. Unlike the steady case, the phase lines of the internal waves change direction during the tidal cycle and also from near to far field. The frequency spectrum of the propagating wave field is analysed and found to span a narrow band of frequencies clustered around 45°.

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