Direct Numerical Simulation of Heat Transfer in Converging–Diverging Wavy Channels

2006 ◽  
Vol 129 (7) ◽  
pp. 769-777 ◽  
Author(s):  
E. Stalio ◽  
M. Piller

Corrugated walls are widely used as passive devices for heat and mass transfer enhancement; they are most effective when operated at transitional and turbulent Reynolds numbers. In the present study, direct numerical simulation is used to investigate the unsteady forced convection in sinusoidal, symmetric wavy channels. A novel numerical method is employed for the simulations; it is meant for fully developed flows in periodic ducts of prescribed wall temperature. The algorithm is free of iterative procedures; it accounts for the effects of streamwise diffusion and can be used for unsteady problems. Results of two simulations in the transitional regime for Reynolds numbers based on average duct height and average velocity of Re=481 and Re=872 are reported. Time averaged and instantaneous velocity and temperature fields together with second-order statistics are interpreted in order to describe the mechanism associated with heat transfer augmentation. Heat flux distributions locate the most active areas in heat transfer and reveal the effects of convective mixing. Slanted traveling waves of high temperature are identified; peak values of Nusselt number are attained when the high-temperature fluid of the waves reaches the converging walls.

2015 ◽  
Vol 764 ◽  
pp. 362-394 ◽  
Author(s):  
T. Dairay ◽  
V. Fortuné ◽  
E. Lamballais ◽  
L.-E. Brizzi

AbstractDirect numerical simulation (DNS) of an impinging jet flow with a nozzle-to-plate distance of two jet diameters and a Reynolds number of 10 000 is carried out at high spatial resolution using high-order numerical methods. The flow configuration is designed to enable the development of a fully turbulent regime with the appearance of a well-marked secondary maximum in the radial distribution of the mean heat transfer. The velocity and temperature statistics are validated with documented experiments. The DNS database is then analysed focusing on the role of unsteady processes to explain the spatial distribution of the heat transfer coefficient at the wall. A phenomenological scenario is proposed on the basis of instantaneous flow visualisations in order to explain the non-monotonic radial evolution of the Nusselt number in the stagnation region. This scenario is then assessed by analysing the wall temperature and the wall shear stress distributions and also through the use of conditional averaging of velocity and temperature fields. On one hand, the heat transfer is primarily driven by the large-scale toroidal primary and secondary vortices emitted periodically. On the other hand, these vortices are subjected to azimuthal distortions associated with the production of radially elongated structures at small scale. These distortions are responsible for the appearance of very high heat transfer zones organised as cold fluid spots on the heated wall. These cold spots are shaped by the radial structures through a filament propagation of the heat transfer. The analysis of probability density functions shows that these strong events are highly intermittent in time and space while contributing essentially to the secondary peak observed in the radial evolution of the Nusselt number.


Author(s):  
Zhi-Gang Feng ◽  
Adam Roig

We have developed a Direct Numerical Simulation combined with the Immersed Boundary method (DNS-IB) to study heat transfer in particulate flows. In this method, fluid velocity and temperature fields are obtained by solving the modified momentum and heat transfer equations, which result from the presence of heated particles in the fluid; particles are tracked individually and their velocities and positions are solved based on the equations of linear and angular motions; particle temperature is assumed to be a constant. The momentum and heat exchanges between a particle and the surrounding fluid at its surface are resolved using the immersed boundary method with the direct forcing scheme. The DNS-IB method has been used to study heat transfer of 1024 of heated spheres in a fluidized bed. By exploring the rich data generated from the DNS-IB simulations, we are able to obtain statistically averaged fluid and particle velocity as well as overall heat transfer rate in a fluidized bed.


2018 ◽  
Vol 845 ◽  
pp. 581-614 ◽  
Author(s):  
M. Georgiou ◽  
M. V. Papalexandris

In this paper we report on a direct numerical simulation (DNS) of turbulent heat transfer in a T-junction. In particular, we study the interaction between two liquid streams, a hot horizontal cross-flow and a cold vertical liquid jet coming from above, in a T-junction of rectangular cross-section. We discuss in detail the instantaneous flow structures and present results for the first- and second-order statistics of the flow quantities, and for the budget of the turbulent kinetic energy. Further, we present results of the power spectral density of the velocity and temperature signals at selected locations of the flow field. Our analysis elucidates the properties of the important features of the flow such as the large recirculation bubble and the secondary separation zones that are formed in the vicinity of the entry of the jet. According to our simulations, thermal mixing is mainly driven by the shear layer between the two streams and, to a lesser extent, by the shear layer between the incoming jet and the large recirculation bubble. Thermal mixing is further enhanced by turbulence generation in the regions of adverse pressure gradients downstream of the large recirculation bubble. Within the framework of our study, we have also conducted a wall-resolved large-eddy simulation (LES) of the flow of interest so as to assess its predictive capacity. Overall, the LES predictions agree satisfactorily with our DNS data; the most noticeable discrepancy is that the LES produces mildly diffused profiles for the second-order statistics in the regions of intense turbulence production.


2021 ◽  
Vol 1877 (1) ◽  
pp. 012035
Author(s):  
Shengxiang Lin ◽  
Huanxiong Xia ◽  
Zhenyu Zhang ◽  
Jianhua Liu ◽  
Honglei Wang

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