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Research Papers: Alternative Energy Sources

Computational Fluid Dynamics Study for Improvement of Prediction of Various Thermally Stratified Turbulent Boundary Layers

[+] Author and Article Information
Hirofumi Hattori

Mem. ASME
Information and Analysis Technologies Division,
Nagoya Institute of Technology,
Gokiso-cho, Showa-ku,
Nagoya 466-8555, Japan
e-mail: hattori@nitech.ac.jp

Tomoya Houra

Associate Professor
Department of Electrical and Mechanical
Engineering,
Nagoya Institute of Technology,
Nagoya 466-8555, Japan

Amane Kono, Shota Yoshikawa

Graduate School of Mechanical Engineering,
Nagoya Institute of Technology,
Nagoya 466-8555, Japan

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received October 3, 2016; final manuscript received February 25, 2017; published online March 23, 2017. Assoc. Editor: Ryo Amano.

J. Energy Resour. Technol 139(5), 051209 (Mar 23, 2017) (8 pages) Paper No: JERT-16-1394; doi: 10.1115/1.4036177 History: Received October 03, 2016; Revised February 25, 2017

The objectives of this study are to reconstruct a turbulence model of both the large Eddy simulation (LES) and the Reynolds-averaged Navier–Stokes simulation (RANS) which can predict wind synopsis in various thermally stratified turbulent boundary layers over any obstacles. Hence, the direct numerical simulation (DNS) of various thermally stratified turbulent boundary layers with/without forward-step, two-dimensional block, or two-dimensional hill is carried out in order to obtain detailed turbulent statistics for the construction of a database for the evaluation of a turbulence model. Also, DNS clearly reveals the characteristics of various thermally stratified turbulent boundary layers with/without forward-step, two-dimensional block, or two-dimensional hill. The turbulence models employed in LES and RANS are evaluated using the DNS database we obtained. In the LES, an evaluated turbulence model gives proper predictions, but the quantitative agreement of Reynolds shear stress with DNS results is difficult to predict. On the other hand, the nonlinear eddy diffusivity turbulence models for Reynolds stress and turbulent heat flux are also evaluated using DNS results of various thermally stratified turbulent boundary layers over a forward-step in which the turbulence models are evaluated using an a priori method. Although the evaluated models do not make it easy to properly predict the Reynolds shear stresses in all cases, the turbulent heat fluxes can be qualitatively predicted by the nonlinear eddy diffusivity for a heat turbulence model. Therefore, the turbulence models of LES and RANS should be improved in order to adequately predict various thermally stratified turbulent boundary layers over an obstacle.

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Figures

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Fig. 1

Computational domains and coordinate systems: (a) flat plate, (b) forward-facing step, (c) 2D-block, and (d) 2D-hill

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Fig. 2

DNS results of turbulent boundary layer with various thermal stratifications over forward-facing step: (a) streamwise mean velocity, (b) Reynolds shear stress, and (c) turbulence energy

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Fig. 3

Streamlines, separation, and reattachment lengths of turbulent boundary layer with various thermal stratifications over forward-facing step: (a) Ri = −0.06 (UBL), (b) Ri = −0.01 (UBL), (c) Ri = 0 (NBL), and (d) Ri = −0.06 (SBL)

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Fig. 4

DNS results of turbulent boundary layer with various thermal stratifications over 2D-block: (a) streamwise mean velocity, (b) Reynolds shear stress, and (c) turbulence energy

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Fig. 5

Streamlines, separation, and reattachment lengths of turbulent boundary layer with various thermal stratifications over 2D-block: (a) Ri = −0.005 (UBL), (b) Ri = 0 (NBL), and (c) Ri = 0.005 (SBL)

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Fig. 6

DNS results of turbulent boundary layer with various thermal stratifications over 2D-hill: (a) streamwise mean velocity, (b) Reynolds shear stress, and (c) turbulence energy

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Fig. 7

Streamlines, separation distance and reattachment length of turbulent boundary layer with various thermal stratifications over 2D-hill: (a) Ri=−0.005 (UBL), (b) Ri = 0 (NBL), (c) Ri = 0.005 (SBL), and (d) Ri = 0.04 (SBL)

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Fig. 8

LES predictions of various thermally stratified turbulent boundary layers: left: streamwise mean velocity and right: Reynolds shear stress: (a) Ri = −0.01 (UBL), (b) Ri = 0 (NBL), (c) Ri = 0.01 (SBL), and (d) Ri = 0.06 (SBL)

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Fig. 9

Results of a priori test for the modeled Reynolds shear stress of RANS in turbulent boundary layer with various thermal stratifications over forward-facing step: (a) Ri = −0.06 (UBL), (b) Ri = −0.01 (UBL), (c) Ri = 0 (NBL), and (d) Ri = 0.01 (SBL)

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Fig. 10

Results of a priori test for the modeled wall-normal turbulent heat flux of RANS in turbulent boundary layer with various thermal stratifications over forward-facing step: (a) Ri = −0.06 (UBL), (b) Ri = −0.01 (UBL), (c) Ri = 0 (NBL), and (d) Ri = 0.01 (SBL)

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Fig. 11

Results of a priori test for the modeled streamwise turbulent heat flux of RANS in turbulent boundary layer with various thermal stratifications over forward-facing step: (a) Ri = −0.06 (UBL), (b) Ri = −0.01 (UBL), (c) Ri = 0 (NBL), and (d) Ri = 0.01 (SBL)

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