scholarly journals Simulation of Rotating Channel Flow With Heat Transfer: Evaluation of Closure Models

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Alan S. Hsieh ◽  
Sedat Biringen ◽  
Alec Kucala
Keyword(s):  
Heat Transfer ◽  
Heat Flux ◽  
Reynolds Stress ◽  
Channel Flow ◽  
Turbulence Models ◽  
Turbulent Channel Flow ◽  
Turbulent Heat ◽  
Stress Distributions ◽  
Mean Velocity ◽  
Closure Models

A direct numerical simulation (DNS) of spanwise-rotating turbulent channel flow was conducted for four rotation numbers: Rob=0, 0.2, 0.5, and 0.9 at a Reynolds number of 8000 based on laminar centerline mean velocity and Prandtl number 0.71. The results obtained from these DNS simulations were utilized to evaluate several turbulence closure models for momentum and heat transfer transport in rotating turbulent channel flow. Four nonlinear eddy viscosity turbulence models were tested and among these, explicit algebraic Reynolds stress models (EARSM) obtained the Reynolds stress distributions in best agreement with DNS data for rotational flows. The modeled pressure–strain functions of EARSM were shown to have strong influence on the Reynolds stress distributions near the wall. Turbulent heat flux distributions obtained from two explicit algebraic heat flux models (EAHFM) consistently displayed increasing disagreement with DNS data with increasing rotation rate.

Heat transfer in a turbulent channel flow with square bars or circular rods on one wall

2015 ◽  
Vol 776 ◽  
pp. 512-530 ◽  
Author(s):  
S. Leonardi ◽  
P. Orlandi ◽  
L. Djenidi ◽  
R. A. Antonia
Keyword(s):  
Heat Transfer ◽  
Heat Flux ◽  
Prandtl Number ◽  
Channel Flow ◽  
Turbulent Channel Flow ◽  
Turbulent Heat ◽  
Turbulent Prandtl Number ◽  
Smooth Wall ◽  
Roughness Elements ◽  
Smooth Channel

Direct numerical simulations (DNS) are carried out to study the passive heat transport in a turbulent channel flow with either square bars or circular rods on one wall. Several values of the pitch (${\it\lambda}$) to height ($k$) ratio and two Reynolds numbers are considered. The roughness increases the heat transfer by inducing ejections at the leading edge of the roughness elements. The amounts of heat transfer and mixing depend on the separation between the roughness elements, an increase in heat transfer accompanying an increase in drag. The ratio of non-dimensional heat flux to the non-dimensional wall shear stress is higher for circular rods than square bars irrespectively of the pitch to height ratio. The turbulent heat flux varies within the cavities and is larger near the roughness elements. Both momentum and thermal eddy diffusivities increase relative to the smooth wall. For square cavities (${\it\lambda}/k=2$) the turbulent Prandtl number is smaller than for a smooth channel near the wall. As ${\it\lambda}/k$ increases, the turbulent Prandtl number increases up to a maximum of 2.5 at the crests plane of the square bars (${\it\lambda}/k=7.5$). With increasing distance from the wall, the differences with respect to the smooth wall vanish and at three roughness heights above the crests plane, the turbulent Prandtl number is essentially the same for smooth and rough walls.

Heat Transfer Modulation by Inertial Particles in Particle-Laden Turbulent Channel Flow

2018 ◽  
Vol 140 (11) ◽  
Author(s):  
Caixi Liu ◽  
Shuai Tang ◽  
Yuhong Dong ◽  
Lian Shen
Keyword(s):  
Heat Transfer ◽  
Numerical Simulation ◽  
Heat Flux ◽  
Channel Flow ◽  
Turbulent Channel Flow ◽  
Turbulent Heat Flux ◽  
Turbulent Heat ◽  
Inertial Particles ◽  
Thermal Feedback ◽  
Heat Transfer Modulation

We study the effects of particle-turbulence interactions on heat transfer in a particle-laden turbulent channel flow using an Eulerian–Lagrangian simulation approach, with direct numerical simulation (DNS) for turbulence and Lagrangian tracking for particles. A two-way coupling model is employed in which the momentum and energy exchange between the discrete particles and the continuous fluid phase is fully taken into account. Our study focuses on the modulations of the temperature field and heat transfer process by inertial particles with different particle momentum Stokes numbers (St), which in a combination of the particle-to-fluid specific heat ratio and the Prandtl number results in different particle heat Stokes numbers. It is found that as St increases, while the turbulent heat flux decreases due to the suppression of wall-normal turbulence velocity fluctuation, the particle feedback heat flux increases significantly and results in an increase in the total heat flux. The particle thermal feedback effect is illustrated using the instantaneous structures and statistics of the flow and temperature fields. The mechanisms of heat transfer modulation by inertial particles are investigated in detail. The budget of turbulent heat flux is examined. Moreover, by taking advantage of the ability of numerical simulation to address different momentum and heat processes separately, we investigate in detail the two processes of particles affecting heat transfer for the first time, namely the direct effect of particle thermal feedback to the fluid (i.e., heat feedback) and the indirect effect of the modulation of turbulent velocity field induced by the particles (i.e., momentum feedback). It is found that the contribution of heat transfer from turbulent convection is reduced by both heat and momentum feedback due to the decrease of the turbulent heat flux. The contribution of heat transfer from particle transport effects is barely influenced by the momentum feedback, even if St is large and is mainly affected by the heat feedback. Our results indicate that both heat and momentum feedback are important when the particle inertia is large, suggesting that both feedback processes need to be taken into account in computation and modeling.

Relationship between the heat transfer law and the scalar dissipation function in a turbulent channel flow

2017 ◽  
Vol 830 ◽  
pp. 300-325 ◽  
Author(s):  
Hiroyuki Abe ◽  
Robert Anthony Antonia
Keyword(s):  
Heat Transfer ◽  
Prandtl Number ◽  
Channel Flow ◽  
Dissipation Rate ◽  
Turbulent Channel Flow ◽  
Scalar Dissipation ◽  
Scalar Dissipation Rate ◽  
Mean Velocity ◽  
The Mean ◽  
Logarithmic Dependence

Integration across a fully developed turbulent channel flow of the transport equations for the mean and turbulent parts of the scalar dissipation rate yields relatively simple relations for the bulk mean scalar and wall heat transfer coefficient. These relations are tested using direct numerical simulation datasets obtained with two isothermal boundary conditions (constant heat flux and constant heating source) and a molecular Prandtl number Pr of 0.71. A logarithmic dependence on the Kármán number $h^{+}$ is established for the integrated mean scalar in the range $h^{+}\geqslant 400$ where the mean part of the total scalar dissipation exhibits near constancy, whilst the integral of the turbulent scalar dissipation rate $\overline{\unicode[STIX]{x1D700}_{\unicode[STIX]{x1D703}}}$ increases logarithmically with $h^{+}$. This logarithmic dependence is similar to that established in a previous paper (Abe & Antonia, J. Fluid Mech., vol. 798, 2016, pp. 140–164) for the bulk mean velocity. However, the slope (2.18) for the integrated mean scalar is smaller than that (2.54) for the bulk mean velocity. The ratio of these two slopes is 0.85, which can be identified with the value of the turbulent Prandtl number in the overlap region. It is shown that the logarithmic $h^{+}$ increase of the integrated mean scalar is intrinsically associated with the overlap region of $\overline{\unicode[STIX]{x1D700}_{\unicode[STIX]{x1D703}}}$, established for $h^{+}$ (${\geqslant}400$). The resulting heat transfer law also holds at a smaller $h^{+}$ (${\geqslant}200$) than that derived by assuming a log law for the mean temperature.

DNS of Heat Transfer Reduction in Viscoelastic Turbulent Channel Flows

2015 ◽  
Author(s):  
Kyoungyoun Kim ◽  
Radhakrishna Sureshkumar
Keyword(s):  
Heat Transfer ◽  
Channel Flow ◽  
Reduction Rate ◽  
Turbulent Channel Flow ◽  
Passive Scalar ◽  
Heat Fluxes ◽  
Turbulent Heat Transfer ◽  
Uniform Heat Flux ◽  
Turbulent Heat ◽  
Turbulent Heat Fluxes

A direct numerical simulation (DNS) of viscoelastic turbulent channel flow with the FENE-P model was carried out to investigate turbulent heat transfer mechanism of polymer drag-reduced flows. The configuration was a fully-developed turbulent channel flow with uniform heat flux imposed on both walls. The temperature was considered as a passive scalar. The Reynolds number based on the friction velocity (uτ) and channel half height (δ) is 125 and Prandtl number is 5. Consistently with the previous experimental observations, the present DNS results show that the heat-transfer coefficient was reduced at a rate faster than the accompanying drag reduction rate. Statistical quantities such as root-mean-square temperature fluctuations and turbulent heat fluxes were obtained and compared with those of a Newtonian fluid flow. Budget terms of the turbulent heat fluxes were also presented.

Logarithmic Expansions for Reynolds Shear Stress and Reynolds Heat Flux in a Turbulent Channel Flow

2008 ◽  
Vol 130 (9) ◽  
Author(s):  
Abu Seena ◽  
A. Bushra ◽  
Noor Afzal
Keyword(s):  
Heat Flux ◽  
Shear Stress ◽  
Channel Flow ◽  
Intermediate Layer ◽  
Reynolds Shear Stress ◽  
Turbulent Channel Flow ◽  
Closure Models ◽  
Fully Developed Turbulent Flow ◽  
Logarithmic Functions ◽  
Heat And Fluid Flow

The heat and fluid flow in a fully developed turbulent channel flow have been investigated. The closure model of Reynolds shear stress and Reynolds heat flux as a function of a series of logarithmic functions in the mesolayer variable have been adopted. The interaction between inner and outer layers in the mesolayer (intermediate layer) arising from the balance of viscous effect, pressure gradient and Reynolds shear stress (containing the maxima of Reynolds shear stress) was first proposed by Afzal (1982, “Fully Developed Turbulent Flow in a Pipe: An Intermediate Layer,” Arch. Appl. Mech., 53, 355–377). The unknown constants in the closure models for Reynolds shear stress and Reynolds heat flux have been estimated from the prescribed boundary conditions near the axis and surface of channel. The predictions are compared with the DNS data Iwamoto et al. and Abe et al. for Reynolds shear stress and velocity profile and Abe et al. data of Reynolds heat flux and temperature profile. The limitations of the closure models are presented.

Application of a Higher Order GGDH Heat Flux Model to Three-Dimensional Turbulent U-Bend Duct Heat Transfer

2003 ◽  
Vol 125 (1) ◽  
pp. 200-203 ◽  
Author(s):  
K. Suga ◽  
M. Nagaoka and ◽  
N. Horinouchi
Keyword(s):  
Heat Transfer ◽  
Heat Flux ◽  
Three Dimensional ◽  
Turbulence Models ◽  
Higher Order ◽  
Moment Closure ◽  
Turbulent Heat ◽  
Generalized Gradient ◽  
Flux Model ◽  
Heat Flux Model

A higher order version of the generalized gradient diffusion hypothesis (HOGGDH) for turbulent heat flux is applied to predict heat transfer in a square-sectioned U-bend duct. The flow field turbulence models coupled with are a cubic nonlinear eddy viscosity model and a full second moment closure. Both of them are low Reynolds number turbulence models. The benefits of using the HOGGDH heat flux model are presented through the comparison with the standard GGDH.

Hybrid RANS-LES Simulation of Turbulent Heat Transfer in a Channel Flow With Imposed Spanwise and Streamwise Mean Temperature Gradient

2019 ◽  
Author(s):  
Olalekan O. Shobayo ◽  
D. Keith Walters
Keyword(s):  
Heat Transfer ◽  
Temperature Gradient ◽  
Channel Flow ◽  
Plane Channel ◽  
Turbulent Heat Transfer ◽  
Turbulent Heat ◽  
Mean Velocity ◽  
Eddy Simulation ◽  
Mean Temperature ◽  
The Mean

Abstract Computational fluid dynamics (CFD) results for turbulent flow and heat transfer in a plane channel are presented. This study presents an idealized fully-developed planar channel flow case for which the mean velocity gradient is non-zero only in the wall-normal direction, and the mean temperature gradient is imposed to be uniform and non-zero in the streamwise or spanwise direction. Previous studies have documented direct numerical simulation results for periodic channel flow with mean temperature gradient in both the streamwise and wall-normal directions, but limited investigations exist documenting the effect of imposed spanwise gradient. The objective of this study is to evaluate turbulent heat flux predictions for three different classes of modeling approach: Reynolds-averaged Navier-Stokes (RANS), large-eddy simulation (LES), and hybrid RANS-LES. Results are compared to available DNS data at Prandtl number of 0.71 and Reynolds number of 180 based on friction velocity and channel half-width. Specific models evaluated include the k-ω SST RANS model, monotonically integrated LES (MILES), improved delayed detached eddy simulation (IDDES), and dynamic hybrid RANS-LES (DHRL). The DHRL model includes both the standard formulation that has been previously documented in the literature as well as a modified version developed specifically to improve predictive capability for flows in which the primary mean velocity and mean temperature gradients are not closely aligned. The modification consists of using separate RANS-to-LES blending parameters in the momentum and energy equations. Results are interrogated to evaluate the performance of the three different model types and specifically to evaluate the performance of the new modified DHRL variant compared with the baseline version.

Influence of Rheological Parameters on Turbulent Heat Transfer in Drag-Reducing Viscoelastic Channel Flow

2010 ◽  
Author(s):  
Takahiro Tsukahara ◽  
Takahiro Ishigami ◽  
Junya Kurano ◽  
Yasuo Kawaguchi
Keyword(s):  
Heat Transfer ◽  
Prandtl Number ◽  
Channel Flow ◽  
Reduction Rate ◽  
Turbulent Channel Flow ◽  
Weissenberg Number ◽  
Turbulent Heat Transfer ◽  
Rheological Parameters ◽  
Uniform Heat Flux ◽  
Turbulent Heat

Direct numerical simulations (DNS) of a drag-reducing viscoelastic turbulent channel flow with heat transfer had been carried out for three kinds of rheologically different fluids (e.g., different values of Weissenberg number). The molecular Prandtl number was set to be 0.1–2.0. A uniform heat-flux condition was employed as the thermal boundary condition. In this paper, we present various statistical turbulence quantities including the mean and fluctuating temperatures, the Nusselt number (Nu), and the cross-correlation coefficients and discuss about their dependence on the rheological parameters and the Prandtl-number dependency of the obtained drag-reduction rate and heat-transfer reduction rate.

Direct Assessment of the Accuracy of Stereo PIV in Turbulent Channel Flow

Volume 1 ◽  
2004 ◽  
Author(s):  
K. T. Christensen ◽  
Y. Wu
Keyword(s):  
Reynolds Number ◽  
Channel Flow ◽  
Single Point ◽  
Outer Region ◽  
Turbulence Models ◽  
Turbulent Channel Flow ◽  
Wall Region ◽  
Mean Velocity ◽  
Velocity Gradients ◽  
The Mean

Stereo particle-image velocimetry (PIV) has become a widely-used method for studying complex flows because it allows one to acquire instantaneous, three-component velocity data on a planar domain with high spatial resolution. However, the accuracy of such measurements must be carefully evaluated before stereo PIV data can be faithfully used in the development of sophisticated turbulence models, assessment of appropriate computational boundary conditions, and in the validation of advanced computations. To this end, the accuracy of stereo PIV is assessed directly in an actual turbulent environment: two-dimensional turbulent channel flow. This flow is a challenging test of stereo PIV because the turbulent velocity fluctuations are quite small compared to the mean (typically less than ten percent of the mean velocity) and strong velocity gradients exist in the near-wall region. Measurements are made in the streamwise–wall-normal plane along the channel’s spanwise centerline using both stereoscopic and conventional 2-D PIV. A large ensemble of statistically independent velocity realizations are acquired with each method at a friction Reynolds number Reτ = u*h/ν = 934. Single-point statistics are computed from the experimental data and compared to statistics determined from a direct numerical simulation (DNS) of turbulent channel flow at a nearly-identical friction Reynolds number of 940 [5]. Excellent agreement is found in the outer region of the flow (y/h > 0.15, where h is the half-height of the channel). For y/h < 0.15, both the conventional and stereo PIV results differ from the DNS data. These differences are most-likely a manifestation of errors associated with strong velocity gradients and intense turbulent events present in this region of the flow.

Understanding the Capability of RANS Based Turbulence Models on Fully Turbulent Channel Flow

2019 ◽  
Author(s):  
Yasin Kaan İlter ◽  
Uğur Oral Ünal
Keyword(s):  
Reynolds Stress ◽  
Channel Flow ◽  
Flow Characteristics ◽  
Turbulence Models ◽  
Turbulent Channel Flow ◽  
Reynolds Numbers ◽  
Fine Tuning ◽  
Mean Flow ◽  
Flat Plates ◽  
Number Range

Abstract Fully turbulent channel flow is a very common and effective way to investigate the boundary layer flow over the flat plates. Mean flow characteristics of the channel flow can be predicted using steady Reynolds Averaged Navier-Stokes (RANS) simulations although the turbulent flow has an unsteady nature. The objective of the present study is to evaluate the predictive capability of the turbulence models, which are based on RANS decomposition, in channel flow involving smooth surfaces. The study covers the application of the Reynolds-stress based second-moment turbulence closure model and the most preferred linear eddy viscosity models to determine the mean flow characteristics. The turbulence properties were compared with the DNS data obtained from the open literature. Also, an iterative study was performed for the fine-tuning of the coefficients appearing in the Reynolds-stress turbulence model. A tuned version of the Reynolds-stress model for two different frictional Reynolds numbers (Reτ) of 180 and 590 is presented. These studies will form a basis for further computations on the channel flow with a higher Reynolds number range and different channel sections. They will also serve as the initial steps for the future experimental and computational studies that will focus on the understanding of the flow mechanism over the dimpled surfaces at Reynolds numbers (based on half channel height and mean bulk velocity) up to 2.105.

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