CHARACTERISTICS OF FLOW THROUGH RIGID, EMERGENT AND SPARSE VEGETATION

2016 ◽  
Vol 78 (10) ◽  
Author(s):  
Suraya Sharil ◽  
Wan Hanna Melini Wan Mohtar ◽  
Siti Fatin Mohd Razali
Keyword(s):  
Reynolds Number ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Turbulence Intensity ◽  
Transverse Velocity ◽  
Flow Region ◽  
Vegetation Density ◽  
Flow Depth ◽  
Flow Through ◽  
Fast Flow

This paper looks into the flow profiles in terms of longitudinal and transverse velocities, turbulence intensity and turbulent kinetic energy in relation to the vegetation density, flow depth and stem Reynolds number. An experimental study was conducted in a fully vegetated flume, whereby a control volume was selected for detailed velocity measurement using Acoustic Doppler Velocimeter (ADV). This research considered 0.97%, 3.90% and 7.80% vegetation density or solid volume fractions (SVF) which are categorised as sparse in the lab work. Series of experiments were conducted in uniform flow condition with stem Reynolds number, Red ranging between 1300 and 3000. Experimental results managed to capture the wake area (velocity deficit; < 1) and fast flow region (velocity enhance; > 1). The boundary between the wake area and fast flow region is reflected by the highest magnitude of the normalised longitudinal turbulence intensity and turbulent kinetic energy. Positive normalised transverse velocity represents the flow diversion away from the vegetation and the negative normalised transverse velocity indicates flux towards the centre of the wake. Both turbulence intensity and turbulent kinetic energy display no observable relation with the flow depth. This is probably because the characteristic length for turbulent flow through vegetation is the stem diameter.  

Fluid Flow Analysis in a Pebble Bed Modular Reactor Using RANS Turbulence Models

2008 ◽  
Author(s):  
Margaret Mkhosi ◽  
Richard Denning ◽  
Audeen Fentiman
Keyword(s):  
Reynolds Number ◽  
Fluid Flow ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Turbulence Intensity ◽  
Turbulence Models ◽  
Reynolds Numbers ◽  
Pebble Bed ◽  
Rans Turbulence Models ◽  
Flow Domain

The computational fluid dynamics code FLUENT has been used to analyze turbulent fluid flow over pebbles in a pebble bed modular reactor. The objective of the analysis is to evaluate the capability of the various RANS turbulence models to predict mean velocities, turbulent kinetic energy, and turbulence intensity inside the bed. The code was run using three RANS turbulence models: standard k-ε, standard k-ω and the Reynolds stress turbulence models at turbulent Reynolds numbers, corresponding to normal operation of the reactor. For the k-ε turbulence model, the analyses were performed at a range of Reynolds numbers between 1300 and 22 000 based on the approach velocity and the sphere diameter of 6 cm. Predictions of the mean velocities, turbulent kinetic energy, and turbulence intensity for the three models are compared at the Reynolds number of 5500 for all the RANS models analyzed. A unit-cell approach is used and the fluid flow domain consists of three unit cells. The packing of the pebbles is an orthorhombic arrangement consisting of seven layers of pebbles with the mean flow parallel to the z-axis. For each Reynolds number analyzed, the velocity is observed to accelerate to twice the inlet velocity within the pebble bed. From the velocity contours, it can be seen that the flow appears to have reached an asymptotic behavior by the end of the first unit cell. The velocity vectors for the standard k-ε and the Reynolds stress model show similar patterns for the Reynolds number analyzed. For the standard k-ω, the vectors are different from the other two. Secondary flow structures are observed for the standard k-ω after the flow passes through the gap between spheres. This feature is not observable in the case of both the standard k-ε and the RSM. Analysis of the turbulent kinetic energy contours shows that there is higher turbulence kinetic energy near the inlet than inside the bed. As the Reynolds number increases, kinetic energy inside the bed increases. The turbulent kinetic energy values obtained for the standard k-ε and the RSM are similar, showing maximum turbulence kinetic energy of 7.5 m2·s−2, whereas the standard k-ω shows a maximum of about 20 m2·s−2. Another observation is that the turbulence intensity is spread throughout the flow domain for the k-ε and RSM whereas for the k-ω, the intensity is concentrated at the front of the second sphere. Preliminary analysis performed for the pressure drop using the standard k-ε model for various velocities show that the dependence of pressure on velocity varies as V1.76.

A Model for Simulation of Turbulent Flow With High Free Stream Turbulence Implemented in OpenFOAM®

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Hosein Foroutan ◽  
Savas Yavuzkurt
Keyword(s):  
Reynolds Number ◽  
Friction Coefficient ◽  
Kinetic Energy ◽  
Skin Friction ◽  
Turbulent Kinetic Energy ◽  
Turbulence Intensity ◽  
Free Stream ◽  
Low Reynolds Number ◽  
Skin Friction Coefficient ◽  
Free Stream Turbulence

A low-Reynolds number k-ε model for simulation of turbulent flow with high free stream turbulence is developed which can successfully predict turbulent kinetic energy profiles, skin friction coefficient, and Stanton number under high free stream turbulence. Modifications incorporating the effects of free stream velocity and length scale are applied. These include an additional term in turbulent kinetic energy transport equation, as well as reformulation of the coefficient in turbulent viscosity equation. The present model is implemented in OpenFOAM CFD code and applied together with other well-known versions of low-Reynolds number k-ε model in flow and heat transfer calculations in a flat plate turbulent boundary layer. Three different test cases based on the initial values of the free stream turbulence intensity (1%, 6.53%, and 25.7%) are considered and models predictions are compared with available experimental data. Results indicate that almost all low-Reynolds number k-ε models, including the present model, give reasonably good results for low free stream turbulence intensity case (1%). However, deviations between current k-ε models predictions and data become larger as turbulence intensity increases. Turbulent kinetic energy levels obtained from these models for very high turbulence intensity (25.7%) show as much as 100% underprediction while skin friction coefficient and Stanton number are overpredicted by more than 70%. Applying the present modifications, predictions of skin friction coefficient, and Stanton number improve considerably (only 15% and 8% deviations in average for very high free stream turbulence intensity). Turbulent kinetic energy levels are vastly improved within the boundary layer as well. It seems like the new developed model can capture the physics of the high free stream turbulence effects.

A Model for Simulation of Turbulent Flow With High Free Stream Turbulence Implemented in OpenFOAM

2012 ◽  
Author(s):  
Hosein Foroutan ◽  
Savas Yavuzkurt
Keyword(s):  
Reynolds Number ◽  
Friction Coefficient ◽  
Kinetic Energy ◽  
Skin Friction ◽  
Turbulent Kinetic Energy ◽  
Turbulence Intensity ◽  
Free Stream ◽  
Low Reynolds Number ◽  
Skin Friction Coefficient ◽  
Free Stream Turbulence

A low Reynolds number k-ε model for simulation of turbulent flow with high free stream turbulence is developed which can successfully predict turbulent kinetic energy profiles, skin friction coefficient and Stanton number under high free stream turbulence. Modifications incorporating the effects of free stream velocity and length scale are applied. These include an additional term in turbulent kinetic energy transport equation, as well as reformulation of the coefficient in turbulent viscosity equation. The present model is implemented in OpenFOAM CFD code and applied together with other well-known versions of low Reynolds number k-ε model in flow and heat transfer calculations in a flat plate turbulent boundary layer. Three different test cases based on the initial values of the free stream turbulence intensity (1%, 6.53% and 25.7%) are considered and models predictions are compared with available experimental data. Results indicate that almost all low Reynolds number k-ε models, including the present model, give reasonably good results for low free stream turbulence intensity case (1%). However, deviations between current k-ε models predictions and data become larger as turbulence intensity increases. Turbulent kinetic energy levels obtained from these models for very high turbulence intensity (25.7%) show as much as 100% underprediction while skin friction coefficient and Stanton number are overpredicted by more than 70%. Applying the present modifications, predictions of skin friction coefficient and Stanton number improve considerably (only 15% and 8% deviations in average for very high free stream turbulence intensity). Turbulent kinetic energy levels are vastly improved within the boundary layer as well. It seems like the new developed model can capture the physics of the high free stream turbulence effects.

scholarly journals Influence of pressure on the wake of a hydrophobic circular cylinder for a flow regime with Reynolds number of 2.2×105

2021 ◽  
Vol 2119 (1) ◽  
pp. 012011
Author(s):  
K G Dobroselsky
Keyword(s):  
Reynolds Number ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Vortex Flow ◽  
Flow Region ◽  
Velocity Fields ◽  
Wake Flow ◽  
Flow Structures ◽  
Reynolds Stresses ◽  
Two Dimensional Image

Abstract Vortex flow structures in a turbulent wake behind a circular Teflon cylinder immersed in an incoming flow with a change in pressure for the Reynolds number Re = 2.2×105 have been experimentally studied using a two-dimensional image (2D-PIV) of particles in a closed-circuit water tunnel. The obtained results are presented in the form of time-averaged velocity fields, Reynolds stresses, and distributions of turbulent kinetic energy. The flow data showed that the size of the wake flow region, Reynolds stresses and turbulent kinetic energy change depending on the pressure in the flow. As a result of a 20% reduction in pressure, the size of the vortex zone in the wake increases by about 20%.

Turbulent kinetic energy production and flow structures in flows past smooth and rough walls

2019 ◽  
Vol 866 ◽  
pp. 897-928 ◽  
Author(s):  
P. Orlandi
Keyword(s):  
Reynolds Number ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Turbulent Flows ◽  
Energy Production ◽  
Compressive Strain ◽  
Turnover Time ◽  
Flow Structures ◽  
Wall Region ◽  
Rate Of Dissipation

Data available in the literature from direct numerical simulations of two-dimensional turbulent channels by Lee & Moser (J. Fluid Mech., vol. 774, 2015, pp. 395–415), Bernardini et al. (J. Fluid Mech., 742, 2014, pp. 171–191), Yamamoto & Tsuji (Phys. Rev. Fluids, vol. 3, 2018, 012062) and Orlandi et al. (J. Fluid Mech., 770, 2015, pp. 424–441) in a large range of Reynolds number have been used to find that $S^{\ast }$ the ratio between the eddy turnover time ($q^{2}/\unicode[STIX]{x1D716}$, with $q^{2}$ being twice the turbulent kinetic energy and $\unicode[STIX]{x1D716}$ the isotropic rate of dissipation) and the time scale of the mean deformation ($1/S$), scales very well with the Reynolds number in the wall region. The good scaling is due to the eddy turnover time, although the turbulent kinetic energy and the rate of isotropic dissipation show a Reynolds dependence near the wall; $S^{\ast }$, as well as $-\langle Q\rangle =\langle s_{ij}s_{ji}\rangle -\langle \unicode[STIX]{x1D714}_{i}\unicode[STIX]{x1D714}_{i}/2\rangle$ are linked to the flow structures, and also the latter quantity presents a good scaling near the wall. It has been found that the maximum of turbulent kinetic energy production $P_{k}$ occurs in the layer with $-\langle Q\rangle \approx 0$, that is, where the unstable sheet-like structures roll-up to become rods. The decomposition of $P_{k}$ in the contribution of elongational and compressive strain demonstrates that the two contributions present a good scaling. However, the good scaling holds when the wall and the outer structures are separated. The same statistics have been evaluated by direct simulations of turbulent flows in the presence of different types of corrugations on both walls. The flow physics in the layer near the plane of the crests is strongly linked to the shape of the surface and it has been demonstrated that the $u_{2}$ (normal to the wall) fluctuations are responsible for the modification of the flow structures, for the increase of the resistance and of the turbulent kinetic energy production.

scholarly journals Discussion on improved method of turbulence model for supercritical water flow and heat transfer

2020 ◽  
Vol 24 (5 Part A) ◽  
pp. 2729-2741
Author(s):  
Zhenchuan Wang ◽  
Guoli Qi ◽  
Meijun Li
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Turbulence Model ◽  
Buoyancy Effect ◽  
Improved Method ◽  
Production Term ◽  
Flow And Heat Transfer ◽  
Effect Model

The turbulence model fails in supercritical fluid-flow and heat transfer simulation, owing to the drastic change of thermal properties. The inappropriate buoyancy effect model and the improper turbulent Prandtl number model are several of these factors lead to the original low-Reynolds number turbulence model unable to predict the wall temperature for vertically heated tubes under the deteriorate heat transfer conditions. This paper proposed a simplified improved method to modify the turbulence model, using the generalized gradient diffusion hypothesis approximation model for the production term of the turbulent kinetic energy due to the buoyancy effect, using a turbulence Prandtl number model for the turbulent thermal diffusivity instead of the constant number. A better agreement was accomplished by the improved turbulence model compared with the experimental data. The main reason for the over-predicted wall temperature by the original turbulence model is the misuse of the buoyancy effect model. In the improved model, the production term of the turbulent kinetic energy is much higher than the results calculated by the original turbulence model, especially in the boundary-layer. A more accurate model for the production term of the turbulent kinetic energy is the main direction of further modification for the low Reynolds number turbulence model.

Vortex Detachment and Reverse Flow in Pulsatile Laminar Flow Through Axisymmetric Sudden Expansions

1999 ◽  
Vol 121 (3) ◽  
pp. 574-579 ◽  
Author(s):  
S. Tavoularis ◽  
R. K. Singh
Keyword(s):  
Reynolds Number ◽  
Recirculation Zone ◽  
Reverse Flow ◽  
Flow Region ◽  
Vortex Rings ◽  
Mean Velocity ◽  
Zone Length ◽  
Deceleration Phase ◽  
Pulsatile Flows ◽  
Flow Through

Incompressible, steady and pulsatile flows in axisymmetric sudden expansions with diameter ratios of 1:2.25 and 1:2.00 have been simulated numerically over the ranges of time-averaged bulk Reynolds number 0.1 ≤ Re ≤ 400 and Womersley number 0.1 ≤ W ≤ 50. For steady flow, the calculated recirculation zone length increased linearly with an increase in Re, in good agreement with earlier experiments. For pulsatile flows, particularly at higher values of W, the recirculation zone length correlated strongly with the acceleration of the flow and not with the instantaneous Reynolds number; it increased during the deceleration phase and decreased during the acceleration phase. The computed mean velocity and reattachment length were in general agreement with published experimental data. At relatively low W, the computed near-wall, reverse flow region extended along the full domain over part of the cycle, similarly to that in the experiments. At low values of W, the vortex rings created at the expansion remained attached and oscillated back and forth; for an intermediate range of W, they detached and moved downstream; at relatively high W, these vortices became, once more, attached.

NUMERICAL RESEARCH ON THE EFFECT OF FIBERS ON THE PROPERTY OF TURBULENT FIBER SUSPENSION IN A CHANNEL

2009 ◽  
Vol 23 (03) ◽  
pp. 509-512 ◽  
Author(s):  
SUHUA SHEN ◽  
JIANZHONG LIN
Keyword(s):  
Reynolds Number ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Channel Flow ◽  
Turbulent Channel Flow ◽  
Fiber Suspension ◽  
Additional Stress ◽  
Mean Velocity ◽  
Navier Stokes Equation ◽  
Fiber Concentration

To explore the rheological property in turbulent channel flow of fiber suspensions, the equation of probability distribution function for mean fiber orientation and the Reynolds averaged Navier-Stokes equation with the term of additional stress resulted from fibers were solved with numerical methods to get the distributions of the mean velocity and turbulent kinetic energy. The simulation results show that the effect of fibers on turbulent channel flow is equivalent to an additional viscosity. The turbulent velocity profiles of fiber suspension become gradually sharper by increasing the fiber concentration and/or decreasing the Reynolds number. The turbulent kinetic energy will increase with increasing Reynolds number and fiber concentration.

Influence of the Axisymmetric Contraction Ratio on Free-Stream Turbulence

1976 ◽  
Vol 98 (3) ◽  
pp. 506-515 ◽  
Author(s):  
V. Ramjee ◽  
A. K. M. F. Hussain
Keyword(s):  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Turbulence Intensity ◽  
Free Stream ◽  
Mesh Size ◽  
Turbulence Level ◽  
Free Stream Turbulence ◽  
Contraction Ratio ◽  
The Given ◽  
Screen Mesh

The effect of axisymmetric contractions of a given shape and of contraction ratios c = 11, 22, 44.5, 64, and 100 on the free-stream turbulence of an incompressible flow has been studied experimentally with hot-wires. It is found that the longitudinal and lateral kinetic energies of turbulence increase along the contraction. The monotonic increase of the longitudinal turbulent kinetic energy with increasing c is in contrast with the linear (Batchelor-Proudman-Ribner-Tucker) theory. The variation of the lateral turbulent kinetic energy with c is in qualitative agreement with the theory; however, the increase is much lower than that predicted by the theory. The linear theory overpredicts the decrease in the longitudinal turbulence intensity with increasing c and under-predicts the decrease in the lateral turbulence intensity with increasing c. For the given flow tunnel, it is found that a contraction ratio c greater than about 45 is not greatly effective in reducing longitudinal turbulence levels further; the lateral turbulent intensity continues to decrease with increasing c. In the design of a low turbulence-level tunnel, the panacea for the reduction of the turbulence level does not lie in an indefinite increase of the contraction ratio alone. Studies with various upstream screens and a given contraction of c = 11 suggest that the exit turbulence intensities are essentially independent of the Reynolds number based on the screen-mesh size or screen-wire diameter of the upstream screen.

Sign in / Sign up

Export Citation Format

Share Document