Meta-Analysis of Gas Flow Resistance Measurements Through Packed Beds

1995 ◽  
Vol 117 (1) ◽  
pp. 176-180
Author(s):  
Malcolm S. Taylor ◽  
Csaba K. Zoltani
Keyword(s):  
Reynolds Number ◽  
Statistical Methods ◽  
Flow Resistance ◽  
Gas Flow ◽  
Meta Analysis ◽  
Experimental Results ◽  
Packed Beds ◽  
Flow Through ◽  
Effective Representation ◽  
Number Of Authors

Measurements of the resistance to flow through packed beds of inert spheres have been reported by a number of authors through relations expressing the coefficient of drag as a function of Reynolds number. A meta-analysis of the data using improved statistical methods is undertaken to aggregate the available experimental results. For Reynolds number in excess of 103 the relation log Fv = 0.49 + 0.90 log Re′ is shown to be a highly effective representation of all available data.

Experiments on the Resistance Law for Non-Darcy Compressible Gas Flows in Porous Media

1974 ◽  
Vol 96 (4) ◽  
pp. 353-357 ◽  
Author(s):  
B. A. Masha ◽  
G. S. Beavers ◽  
E. M. Sparrow
Keyword(s):  
Reynolds Number ◽  
Porous Material ◽  
Incompressible Flow ◽  
Gas Flow ◽  
Strong Support ◽  
Reynolds Numbers ◽  
Gas Flows ◽  
Pressure Distributions ◽  
Flow Through ◽  
Compressible Gas

Experiments were performed to examine the resistance law for non-Darcy compressible gas flow through a porous material. A particular objective of the investigation was to determine whether a resistance law deduced from incompressible flow experiments could be applied to flows with significant density changes. To this end, the coefficients appearing in the Forchheimer resistance law were first determined from experiments in the incompressible flow regime. These values were then used in an analytical model employing the Forchheimer resistance law to predict streamwise pressure distributions for subsonic compressible flow through the porous material. Corresponding experimental pressure distributions were measured for flow Reynolds numbers up to 81.6. At the highest Reynolds number of the tests the density changed by about a factor of two along the length of the porous medium. The greatest discrepancy between experimental and predicted pressures at any Reynolds number was 2 percent. This agreement lends strong support to the validity of using the incompressible Forchheimer resistance law for subsonic flows in which density changes are significant.

Study for the Gas Flow Through a Critical Nozzle

2003 ◽  
Author(s):  
Heuy Dong Kim ◽  
Jae Hyung Kim ◽  
Kyung Am Park
Keyword(s):  
Reynolds Number ◽  
Mass Flow ◽  
Gas Flow ◽  
Critical Pressure ◽  
Discharge Coefficient ◽  
Pressure Ratio ◽  
Nozzle Throat ◽  
Critical Nozzle ◽  
Flow Through ◽  
Diffuser Angle

The critical nozzle is defined as a device to measure the mass flow with only the nozzle supply conditions, making use of flow choking phenomenon at the nozzle throat. The discharge coefficient and critical pressure ratio of the gas flow through the critical nozzle are strongly dependent on Reynolds number, based on the diameter of nozzle throat and nozzle supply conditions. Recently a critical nozzle with small diameter is being extensively used to measure mass flow in a variety of industrial fields. For low Reynolds numbers, prediction of the discharge coefficient and critical pressure is very important since the viscous effects near walls significantly affect the mass flow through critical nozzle, which is associated with working gas consumption and operation conditions of the critical nozzle. In the present study, computational work using the axisymmetric, compressible, Navier-Stokes equations is carried out to predict the discharge coefficient and critical pressure ratio of gas flow through critical nozzle. In order to investigate the effect of the working gas and turbulence model on the discharge coefficient, several kinds of gases and several turbulence models are employed. The Reynolds number effects are investigated with several nozzles with different throat diameter. Diffuser angle is varied to investigate the effects on the discharge coefficient and critical pressure ratio. The computational results are compared with the previous experimental ones. It is known that the standard k-ε turbulence model with the standard wall function gives a best prediction of the discharge coefficient. The discharge coefficient and critical pressure ratio are given by functions of the Reynolds number and boundary layer integral properties. It is also found that diffuser angle affects the critical pressure ratio.

Characteristics of Porescale Vortical Structures in Random and Arranged Packed Beds of Spheres

2012 ◽  
Author(s):  
Justin R. Finn ◽  
Sourabh V. Apte ◽  
Brian D. Wood
Keyword(s):  
Reynolds Number ◽  
Unsteady Flow ◽  
Reynolds Numbers ◽  
Random Packing ◽  
Packed Beds ◽  
Sphere Diameter ◽  
Vortical Structures ◽  
Simple Cubic ◽  
Principal Axes ◽  
Flow Through

The characteristics of pore scale vortical structures observed in moderate Reynolds number flow through mono-disperse packed beds of spheres are examined. Our results come from direct numerical simulations of flow through (i) a periodic, simple cubic arrangement of 54 spheres, (ii) a wall bounded, close packed arrangement of 216 spheres, and (iii) a realistic randomly packed tube containing 326 spheres with a tube diameter to sphere diameter ratio of 5.96. Pore Reynolds numbers in the steady inertial (10 ≲ Re ≲ 200) and unsteady inertial (Re ≈ 600) regimes are considered. Even at similar Reynolds numbers, the vortical structures observed in flows through these three packings are remarkably different. The interior of the arranged packings are dominated by multi-lobed vortex ring structures which align with the principal axes of the packing. The random packing and the near wall region of the close packed arrangement are dominated by helical vortices, elongated in the mean flow direction. In the simple cubic packing, unsteady flow is marked by periodic vortex shedding which occurs at a single frequency. Conversely, at a similar Reynolds number, the vortical structures in unsteady flow through the random packing oscillate with many characteristic frequencies.

Computational study of the gas flow through a critical nozzle

2003 ◽  
Vol 217 (10) ◽  
pp. 1179-1189 ◽  
Author(s):  
H-D Kim ◽  
J-H Kim ◽  
K-A Park ◽  
T Setoguchi ◽  
S Matsuo
Keyword(s):  
Reynolds Number ◽  
Mass Flow ◽  
Gas Flow ◽  
Critical Pressure ◽  
Discharge Coefficient ◽  
Pressure Ratio ◽  
Nozzle Throat ◽  
Critical Nozzle ◽  
Flow Through ◽  
Diffuser Angle

The critical nozzle is defined as a device to measure the mass flow with only the nozzle supply conditions making use of the flow choking phenomenon at the nozzle throat. The discharge coefficient and critical pressure ratio of the gas flow through the critical nozzle are strongly dependent on the Reynolds number, based on the diameter of the nozzle throat and nozzle supply conditions. Recently a critical nozzle with a small diameter has been extensively used to measure mass flow in a variety of industrial fields. For low Reynolds numbers, prediction of the discharge coefficient and critical pressure is very important since the viscous effects near walls significantly affect the mass flow through the critical nozzle, which is associated with working gas consumption and operation conditions of the critical nozzle. In the present study, computational work using the axisymmetric, compressible, Navier-Stokes equations is carried out to predict the discharge coefficient and critical pressure ratio of gas flow through the critical nozzle. In order to investigate the effect of the working gas and turbulence model on the discharge coefficient, several kinds of gases and several turbulence models are employed. The Reynolds number effects are investigated with several nozzles with different throat diameters. The diffuser angle is varied in order to investigate the effects on the discharge coefficient and critical pressure ratio. The computational results are compared with the previous experimental ones. It is known that the standard k-ε turbulence model with the standard wall function gives the best prediction of the discharge coefficient. The discharge coefficient and critical pressure ratio are given by functions of the Reynolds number and boundary layer integral properties. It is also found that the diffuser angle affects the critical pressure ratio.

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