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Research Papers: Energy Conversion/Systems

Large Eddy Simulation for Local Entropy Generation Analysis of Turbulent Flows

[+] Author and Article Information
M. R. H. Sheikhi

Assistant Professor
Mem. ASME
e-mail: sheikhi@neu.edu

Mehdi Safari

Graduate Research Assistant
Mem. ASME

Hameed Metghalchi

Professor
Fellow ASME
Department of Mechanical and Industrial Engineering,
Northeastern University,
Boston, MA 02115

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the Journal of Energy Resources Technology. Manuscript received January 11, 2012; final manuscript received August 13, 2012; published online October 19, 2012. Assoc. Editor: Muhammad M. Rahman.

J. Energy Resour. Technol 134(4), 041603 (Oct 19, 2012) (6 pages) doi:10.1115/1.4007482 History: Received January 11, 2012; Revised August 13, 2012

A new methodology is developed for local entropy generation analysis of turbulent flows using large eddy simulation (LES). The entropy transport equation is considered in LES and is solved along with continuity, momentum, and scalar transport equations. The filtered entropy equation includes several unclosed source terms that contribute to entropy generation. The closure is based on the filtered density function (FDF) methodology, extended to include the transport of entropy. An exact transport equation is derived for the FDF. The unclosed terms in this equation are modeled by considering a system of stochastic differential equations (SDEs). The methodology is employed for LES of a turbulent shear layer involving transport of passive chemical species, energy, and entropy. The local entropy generation effects are obtained from the FDF and are analyzed. It is shown that the dominant contribution to entropy generation in this flow is due to combined effects of energy transfer by heat and mass diffusion. The FDF results are assessed by comparing with those obtained by direct numerical simulation (DNS) of the same layer. The FDF predictions show favorable agreements with the DNS data.

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References

Figures

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Fig. 1

A schematic of the 3D temporally developing mixing layer flow configuration

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Fig. 2

Cross-stream variation of instantaneous filtered temperature field at t = 80, predicted by (a) FDF and (b) DNS

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Fig. 3

Cross-stream variation of Reynolds-averaged filtered entropy at t = 80. The solid line denotes the FDF results and the circles denote the filtered DNS data.

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Fig. 4

Cross-stream variation of Reynolds-averaged filtered total entropy generation at t = 80. The solid line denotes the FDF results and the circles denote the filtered DNS data.

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Fig. 5

The instantaneous volumetric rate of total entropy generation at t = 80 and z = 0.125 L, predicted by the FDF

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