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.

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 Numerical Simulation of Passive Scalar Field in a Turbulent Channel Flow

1992 ◽  
Vol 114 (3) ◽  
pp. 598-606 ◽  
Author(s):  
N. Kasagi ◽  
Y. Tomita ◽  
A. Kuroda
Keyword(s):  
Numerical Simulation ◽  
Direct Numerical Simulation ◽  
Channel Flow ◽  
Turbulent Channel Flow ◽  
Passive Scalar ◽  
Streamwise Velocity ◽  
Heat Fluxes ◽  
Wall Region ◽  
Turbulent Heat ◽  
Turbulent Heat Fluxes

A direct numerical simulation (DNS) of the fully developed thermal field in a two-dimensional turbulent channel flow of air was carried out. The isoflux condition was imposed on the two walls so that the local mean temperature increased linearly in the streamwise direction. With any buoyancy effect neglected, temperature was considered as a passive scalar. The computation was executed on 1,589,248 grid points by using a spectral method. The statistics obtained were root-mean-square temperature fluctuations, turbulent heat fluxes, turbulent Prandtl number, and dissipation time scales. They agreed fairly well with existing experimental and numerical simulation data. Each term in the budget equations of temperature variance, its dissipation rate, and turbulent heat fluxes was also calculated. It was found that the temperature fluctuation θ′ was closely correlated with the streamwise velocity fluctuation u′, particularly in the near-wall region. Hence, the distribution of budget terms for the streamwise and wall-normal heat fluxes, u′θ′ and v′θ′, were very similar to those for the two Reynolds stress components, u′u′ and u′v′.

An Explicit Algebraic Model for Turbulent Heat Transfer in Wall-Bounded Flow With Streamline Curvature

2006 ◽  
Vol 129 (4) ◽  
pp. 425-433 ◽  
Author(s):  
B. A. Younis ◽  
B. Weigand ◽  
S. Spring
Keyword(s):  
Heat Transfer ◽  
Boundary Layer ◽  
Heat Flux ◽  
Algebraic Model ◽  
Heat Fluxes ◽  
Turbulent Heat Transfer ◽  
Turbulent Heat ◽  
Streamline Curvature ◽  
Turbulent Heat Fluxes ◽  
The Mean

Fourier’s law, which forms the basis of most engineering prediction methods for the turbulent heat fluxes, is known to fail badly in capturing the effects of streamline curvature on the rate of heat transfer in turbulent shear flows. In this paper, an alternative model, which is both algebraic and explicit in the turbulent heat fluxes and which has been formulated from tensor-representation theory, is presented, and its applicability is extended by incorporating the effects of a wall on the turbulent heat transfer processes in its vicinity. The model’s equations for flows with curvature in the plane of the mean shear are derived and calculations are performed for a heated turbulent boundary layer, which develops over a flat plate before encountering a short region of high convex curvature. The results show that the new model accurately predicts the significant reduction in the wall heat transfer rates wrought by the stabilizing-curvature effects, in sharp contrast to the conventional model predictions, which are shown to seriously underestimate the same effects. Comparisons are also made with results from a complete heat-flux transport model, which involves the solution of differential transport equations for each component of the heat-flux tensor. Downstream of the bend, where the perturbed boundary layer recovers on a flat wall, the comparisons show that the algebraic model yields indistinguishable predictions from those obtained with the differential model in regions where the mean-strain field is in rapid evolution and the turbulence processes are far removed from local equilibrium.

Progress in the Computation of Turbulent Heat Transfer in Massively Separated Flows

2013 ◽  
Author(s):  
B. A. Younis ◽  
B. Arnold ◽  
P. Weihing ◽  
B. Weigand
Keyword(s):  
Heat Transfer ◽  
Heat Fluxes ◽  
Separated Flows ◽  
Turbulent Heat Transfer ◽  
Periodic Flow ◽  
Turbulent Heat ◽  
Fluctuating Pressure ◽  
Massively Separated Flows ◽  
Turbulent Heat Fluxes ◽  
Heated Channel

The paper reports on work in progress aimed at improving the prediction of heat transfer in turbulent separated flows. The cases considered here are the flow over a heated backward-facing step, and the periodic flow in a heated channel with square ribs. The predictions were obtained using two models not hitherto employed in these flows: a Reynolds-stress transport closure in which the model for the fluctuating pressure-strain correlations that satisfies the requirement of model objectivity while not requiring wall-damping functions, and a model for the turbulent heat fluxes that is explicit, algebraic and correctly allows for these fluxes to depend on the gradients of mean temperature and velocity. Both models have previously given good predictions in attached shear flows and the objective of this work was to determine whether this improvement carries over to separated flows. It was found that distinct improvements in the prediction of skin friction and Nusselt number can only be obtained by extending the models so as to allow the computations to extend through the viscous sub-layer directly to the wall.

Near-Wall Turbulent Heat Transfer at Prandtl Numbers 1 to 54

2002 ◽  
Author(s):  
Robert Bergant ◽  
Iztok Tiselj ◽  
Gad Hetsroni
Keyword(s):  
Heat Transfer ◽  
Numerical Simulation ◽  
Reynolds Number ◽  
Heat Fluxes ◽  
Turbulent Heat Transfer ◽  
Turbulent Heat ◽  
Turbulent Heat Fluxes ◽  
Fully Developed Turbulent Flow ◽  
Prandtl Numbers ◽  
Weak Influence

Direct Numerical Simulation (DNS) of fully developed turbulent flow in a flume was used to study the heat transfer near the wall. The Reynolds number has very weak influence on the turbulent heat transfer statistics (mean temperature, RMS-fluctuations, turbulent heat fluxes), therefore our goal was to analyze the influence of the increasing Prandtl number. Three different studies were performed at three different Prandtl numbers (Pr = 1, Pr = 5.4 and Pr = 54) at the same friction Reynolds number Reτ = 171. It should be emphasized that simulation with Pr = 54 cannot be called DNS due to the unresolved smallest thermal scales but results are in expected regions anyway. The obtained results at various Prandtl numbers also allowed us to make some predictions (RMS-fluctuations) for intermediate Prandtl numbers.

DNS of Turbulent Heat Transfer in Channel Flow With Heat Conduction in the Solid Wall

2001 ◽  
Vol 123 (5) ◽  
pp. 849-857 ◽  
Author(s):  
Iztok Tiselj ◽  
Robert Bergant ◽  
Borut Mavko ◽  
Ivan Bajsic´ ◽  
Gad Hetsroni
Keyword(s):  
Heat Transfer ◽  
Boundary Conditions ◽  
Channel Flow ◽  
Temperature Fluctuations ◽  
Heat Fluxes ◽  
Wall Turbulence ◽  
Temperature Fields ◽  
Turbulent Heat Transfer ◽  
Turbulent Heat ◽  
Fluid Temperature

The Direct Numerical Simulation (DNS) of the fully developed velocity and temperature fields in the two-dimensional turbulent channel flow coupled with the unsteady conduction in the heated walls was carried out. Simulations were performed at constant friction Reynolds number 150 and Prandtl numbers between 0.71 and 7 considering the fluid temperature as a passive scalar. The obtained statistical quantities like root-mean-square temperature fluctuations and turbulent heat fluxes were verified with existing DNS studies obtained with ideal thermal boundary conditions. Results of the present study were compared to the findings of Polyakov (1974), who made a similar study with linearization of the fluid equations in the viscous sublayer that allowed analytical approach and results of Kasagi et al. (1989), who performed similar calculation with deterministic near-wall turbulence model and numerical approach. The present DNS results pointed to the main weakness of the previous studies, which underestimated the values of the wall temperature fluctuations for the limiting cases of the ideal-isoflux boundary conditions. With the results of the present DNS it can be decided, which behavior has to be expected in a real fluid-solid system and which one of the limiting boundary conditions is valid for calculation, or whether more expensive conjugate heat transfer calculation is required.

Numerical Simulations of Turbulent Flume Heat Transfer at Pr = 5.4: Impact of the Smallest Temperature Scales

2005 ◽  
Author(s):  
R. Bergant ◽  
I. Tiselj
Keyword(s):  
Heat Transfer ◽  
Temperature Field ◽  
Numerical Simulations ◽  
Passive Scalar ◽  
Temperature Fields ◽  
Turbulent Heat Transfer ◽  
Turbulent Heat ◽  
Temperature Scales ◽  
Highly Correlated

In the present paper a role of the smallest diffusive scales of a passive scalar field in the near-wall turbulent flow was examined with pseudo-spectral numerical simulations. Temperature fields were analyzed at friction Reynolds number Reτ = 170.8 and at Prandtl number, Pr = 5.4. Results of direct numerical simulation (DNS) were compared with the under-resolved simulation where the velocity field was still resolved with the DNS accuracy, while a coarser grid was used to describe the temperature field. Since the smallest temperature scales remained unresolved in this simulation, an appropriate spectral turbulent thermal diffusivity was applied to avoid pileup at higher wave numbers. In spite of coarser numerical grid, the temperature field is still highly correlated with the DNS results, and thus point to practically negligible role of the diffusive temperature scales on the macroscopic behavior of the turbulent heat transfer.

Investigation of MHD RANS Modeling Base on DNS Database Under the Advanced Blanket Design Conditions Utilized Molten Salt

2014 ◽  
Author(s):  
Naoki Osawa ◽  
Yoshinobu Yamamoto ◽  
Tomoaki Kunugi
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Turbulence Model ◽  
Turbulent Channel Flow ◽  
Turbulent Heat Transfer ◽  
Navier Stokes ◽  
Turbulent Heat ◽  
Mhd Turbulence ◽  
Rans Modeling ◽  
Heat Transfer Degradation

In this study, validations of Reynolds Averaged Navier-Stokes Simulation (RANS) based on Kenjeres & Hanjalic MHD turbulence model (Int. J. Heat & Fluid Flow, 21, 2000) coupled with the low-Reynolds number k-epsilon model have been conducted with the usage of Direct Numerical Simulation (DNS) database. DNS database of turbulent channel flow imposed wall-normal magnetic field on, are established in condition of bulk Reynolds number 40000, Hartmann number 24, and Prandtl number 5. As the results, the Nagano & Shimada model (Trans. JSME series B. 59, 1993) coupled with Kenjeres & Hanjalic MHD turbulence model has the better availability compared with Myong & Kasagi model (Int. Fluid Eng, 109, 1990) in estimation of the heat transfer degradation in MHD turbulent heat transfer.

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