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Research Papers: Flows in Complex Systems

A Cubic Nonlinear Subgrid-Scale Model for Large Eddy Simulation

[+] Author and Article Information
Huang Xianbei

Beijing Engineering Research Center
of Safety and Energy Saving Technology for
Water Supply Network System,
College of Water Resources
and Civil Engineering,
China Agricultural University,
Beijing 100083, China
e-mail: znhuang@163.com

Liu Zhuqing

Beijing Engineering Research Center
of Safety and Energy Saving Technology
for Water Supply Network System,
College of Water Resources and
Civil Engineering,
China Agricultural University,
Beijing 100083, China
e-mail: lzq@cau.edu.cn

Yang Wei

Beijing Engineering Research Center
of Safety and Energy Saving Technology
for Water Supply Network System,
College of Water Resources and
Civil Engineering,
China Agricultural University,
Beijing 100083, China
e-mail: wyang@cau.edu.cn

Li Yaojun

Beijing Engineering Research Center
of Safety and Energy Saving Technology for
Water Supply Network System,
College of Water Resources and
Civil Engineering,
China Agricultural University,
Beijing 100083, China
e-mail: liyaojun@cau.edu.cn

Yang Zixuan

Department of Mechanical Engineering,
University of Minnesota,
Minneapolis, MN 55455
e-mail: yangz348@ad.umanitoba.ca

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received May 26, 2015; final manuscript received October 26, 2016; published online February 6, 2017. Assoc. Editor: Zhongquan Charlie Zheng.

J. Fluids Eng 139(4), 041101 (Feb 06, 2017) (12 pages) Paper No: FE-15-1355; doi: 10.1115/1.4035217 History: Received May 26, 2015; Revised October 26, 2016

In this paper, a new cubic subgrid-scale (SGS) model is proposed to capture the rotation effect. Different from the conventional nonlinear model with second-order term, the new model contains a cubic term which is originated in the Reynolds stress closure. All the three model coefficients are determined dynamically using the Germano’s identity. The model is examined in the rotating turbulent channel flow and the Taylor–Couette flow. Comparing with the linear model and the second-order model, the new model shows better performance.

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References

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Figures

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Fig. 1

Sketch of the rotating turbulent channel flow case

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Fig. 2

Comparison of mean streamwise velocity

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Fig. 3

Comparison of Reynolds stress components at Ro=0.3

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Fig. 4

Each model’s relative error of wrms at Ro=0.3

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Fig. 5

Comparison of Reynolds stress components at Ro=0.6

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Fig. 6

Each model’s relative error of wrms at Ro=0.6

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Fig. 7

Comparison of Taylor–Görtler vortices at Ro=0.3

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Fig. 8

Sketch of the Taylor–Couette case

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Fig. 9

Comparison of mean circumferential velocity

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Fig. 10

Comparison of circumferential Reynolds stress

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Fig. 11

Time-averaged velocity field in a radial–axial plane at Re=5000 (left to right: DSM, DCNM, and DNM)

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Fig. 12

Time-averaged velocity field in a radial–axial plane at Re=8000 (left to right: DSM, DCNM, DNM, and DNS (Dong [22]))

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Fig. 13

Contour plots of the temporal circumferential velocity along an axial line at Re=5000

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Fig. 14

Contour plots of the temporal circumferential velocity along an axial line at Re=8000

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Fig. 15

TKE productions in channel flow and Taylor–Couette flow

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