LES Study on High Reynolds Turbulent Drag-Reducing Flow of Viscoelastic Fluids Based on Multiple Relaxation Times Constitutive Model and Mixed Subgrid-Scale Model

Jingfa Li; Bo Yu; Xinyu Zhang; Shuyu Sun; Dongliang Sun; Tao Zhang

doi:10.1007/978-3-319-93713-7_14

LES Study on High Reynolds Turbulent Drag-Reducing Flow of Viscoelastic Fluids Based on Multiple Relaxation Times Constitutive Model and Mixed Subgrid-Scale Model

Jingfa Li, Bo Yu^*, Xinyu Zhang, Shuyu Sun, Dongliang Sun, Tao Zhang

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Due to complicated rheological behaviors and elastic effect of viscoelastic fluids, only a handful of literatures reporting the large-eddy simulation (LES) studies on turbulent drag-reduction (DR) mechanism of viscoelastic fluids. In addition, these few studies are limited within the low Reynolds number situations. In this paper, LES approach is applied to further study the flow characteristics and DR mechanism of high Reynolds viscoelastic turbulent drag-reducing flow. To improve the accuracy of LES, an N-parallel FENE-P constitutive model based on multiple relaxation times and an improved mixed subgrid-scale (SGS) model are both utilized. DR rate and velocity fluctuations under different calculation parameters are analyzed. Contributions of different shear stresses on frictional resistance coefficient, and turbulent coherent structures which are closely related to turbulent burst events are investigated in details to further reveal the DR mechanism of high Reynolds viscoelastic turbulent drag-reducing flow. Especially, the different phenomena and results between high Reynolds and low Reynolds turbulent flows are addressed. This study is expected to provide a beneficial guidance to the engineering application of turbulent DR technology.

Original language	English (US)
Title of host publication	Computational Science – ICCS 2018 - 18th International Conference, Proceedings
Editors	Jack Dongarra, Haohuan Fu, Valeria V. Krzhizhanovskaya, Michael Harold Lees, Peter M. Sloot, Yong Shi, Yingjie Tian
Publisher	Springer Verlag
Pages	174-188
Number of pages	15
ISBN (Print)	9783319937120
DOIs	https://doi.org/10.1007/978-3-319-93713-7_14
State	Published - 2018
Event	18th International Conference on Computational Science, ICCS 2018 - Wuxi, China Duration: Jun 11 2018 → Jun 13 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10862 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Conference on Computational Science, ICCS 2018
Country/Territory	China
City	Wuxi
Period	06/11/18 → 06/13/18

Bibliographical note

Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.

Keywords

Constitutive model
Large-eddy simulation
Subgrid-scale model
Turbulent drag-reducing flow
Viscoelastic fluid

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-93713-7_14

Cite this

Li, J., Yu, B., Zhang, X., Sun, S., Sun, D., & Zhang, T. (2018). LES Study on High Reynolds Turbulent Drag-Reducing Flow of Viscoelastic Fluids Based on Multiple Relaxation Times Constitutive Model and Mixed Subgrid-Scale Model. In J. Dongarra, H. Fu, V. V. Krzhizhanovskaya, M. H. Lees, P. M. Sloot, Y. Shi, & Y. Tian (Eds.), Computational Science – ICCS 2018 - 18th International Conference, Proceedings (pp. 174-188). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10862 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-93713-7_14

Li, Jingfa ; Yu, Bo ; Zhang, Xinyu et al. / LES Study on High Reynolds Turbulent Drag-Reducing Flow of Viscoelastic Fluids Based on Multiple Relaxation Times Constitutive Model and Mixed Subgrid-Scale Model. Computational Science – ICCS 2018 - 18th International Conference, Proceedings. editor / Jack Dongarra ; Haohuan Fu ; Valeria V. Krzhizhanovskaya ; Michael Harold Lees ; Peter M. Sloot ; Yong Shi ; Yingjie Tian. Springer Verlag, 2018. pp. 174-188 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "LES Study on High Reynolds Turbulent Drag-Reducing Flow of Viscoelastic Fluids Based on Multiple Relaxation Times Constitutive Model and Mixed Subgrid-Scale Model",

abstract = "Due to complicated rheological behaviors and elastic effect of viscoelastic fluids, only a handful of literatures reporting the large-eddy simulation (LES) studies on turbulent drag-reduction (DR) mechanism of viscoelastic fluids. In addition, these few studies are limited within the low Reynolds number situations. In this paper, LES approach is applied to further study the flow characteristics and DR mechanism of high Reynolds viscoelastic turbulent drag-reducing flow. To improve the accuracy of LES, an N-parallel FENE-P constitutive model based on multiple relaxation times and an improved mixed subgrid-scale (SGS) model are both utilized. DR rate and velocity fluctuations under different calculation parameters are analyzed. Contributions of different shear stresses on frictional resistance coefficient, and turbulent coherent structures which are closely related to turbulent burst events are investigated in details to further reveal the DR mechanism of high Reynolds viscoelastic turbulent drag-reducing flow. Especially, the different phenomena and results between high Reynolds and low Reynolds turbulent flows are addressed. This study is expected to provide a beneficial guidance to the engineering application of turbulent DR technology.",

keywords = "Constitutive model, Large-eddy simulation, Subgrid-scale model, Turbulent drag-reducing flow, Viscoelastic fluid",

author = "Jingfa Li and Bo Yu and Xinyu Zhang and Shuyu Sun and Dongliang Sun and Tao Zhang",

note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG, part of Springer Nature.; 18th International Conference on Computational Science, ICCS 2018 ; Conference date: 11-06-2018 Through 13-06-2018",

year = "2018",

doi = "10.1007/978-3-319-93713-7_14",

language = "English (US)",

isbn = "9783319937120",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "174--188",

editor = "Jack Dongarra and Haohuan Fu and Krzhizhanovskaya, {Valeria V.} and Lees, {Michael Harold} and Sloot, {Peter M.} and Yong Shi and Yingjie Tian",

booktitle = "Computational Science – ICCS 2018 - 18th International Conference, Proceedings",

address = "Germany",

}

Li, J, Yu, B, Zhang, X, Sun, S, Sun, D & Zhang, T 2018, LES Study on High Reynolds Turbulent Drag-Reducing Flow of Viscoelastic Fluids Based on Multiple Relaxation Times Constitutive Model and Mixed Subgrid-Scale Model. in J Dongarra, H Fu, VV Krzhizhanovskaya, MH Lees, PM Sloot, Y Shi & Y Tian (eds), Computational Science – ICCS 2018 - 18th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10862 LNCS, Springer Verlag, pp. 174-188, 18th International Conference on Computational Science, ICCS 2018, Wuxi, China, 06/11/18. https://doi.org/10.1007/978-3-319-93713-7_14

LES Study on High Reynolds Turbulent Drag-Reducing Flow of Viscoelastic Fluids Based on Multiple Relaxation Times Constitutive Model and Mixed Subgrid-Scale Model. / Li, Jingfa; Yu, Bo; Zhang, Xinyu et al.
Computational Science – ICCS 2018 - 18th International Conference, Proceedings. ed. / Jack Dongarra; Haohuan Fu; Valeria V. Krzhizhanovskaya; Michael Harold Lees; Peter M. Sloot; Yong Shi; Yingjie Tian. Springer Verlag, 2018. p. 174-188 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10862 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Li, Jingfa

AU - Yu, Bo

AU - Zhang, Xinyu

AU - Sun, Shuyu

AU - Sun, Dongliang

AU - Zhang, Tao

PY - 2018

Y1 - 2018

N2 - Due to complicated rheological behaviors and elastic effect of viscoelastic fluids, only a handful of literatures reporting the large-eddy simulation (LES) studies on turbulent drag-reduction (DR) mechanism of viscoelastic fluids. In addition, these few studies are limited within the low Reynolds number situations. In this paper, LES approach is applied to further study the flow characteristics and DR mechanism of high Reynolds viscoelastic turbulent drag-reducing flow. To improve the accuracy of LES, an N-parallel FENE-P constitutive model based on multiple relaxation times and an improved mixed subgrid-scale (SGS) model are both utilized. DR rate and velocity fluctuations under different calculation parameters are analyzed. Contributions of different shear stresses on frictional resistance coefficient, and turbulent coherent structures which are closely related to turbulent burst events are investigated in details to further reveal the DR mechanism of high Reynolds viscoelastic turbulent drag-reducing flow. Especially, the different phenomena and results between high Reynolds and low Reynolds turbulent flows are addressed. This study is expected to provide a beneficial guidance to the engineering application of turbulent DR technology.

AB - Due to complicated rheological behaviors and elastic effect of viscoelastic fluids, only a handful of literatures reporting the large-eddy simulation (LES) studies on turbulent drag-reduction (DR) mechanism of viscoelastic fluids. In addition, these few studies are limited within the low Reynolds number situations. In this paper, LES approach is applied to further study the flow characteristics and DR mechanism of high Reynolds viscoelastic turbulent drag-reducing flow. To improve the accuracy of LES, an N-parallel FENE-P constitutive model based on multiple relaxation times and an improved mixed subgrid-scale (SGS) model are both utilized. DR rate and velocity fluctuations under different calculation parameters are analyzed. Contributions of different shear stresses on frictional resistance coefficient, and turbulent coherent structures which are closely related to turbulent burst events are investigated in details to further reveal the DR mechanism of high Reynolds viscoelastic turbulent drag-reducing flow. Especially, the different phenomena and results between high Reynolds and low Reynolds turbulent flows are addressed. This study is expected to provide a beneficial guidance to the engineering application of turbulent DR technology.

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KW - Large-eddy simulation

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KW - Turbulent drag-reducing flow

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Li J, Yu B, Zhang X, Sun S, Sun D, Zhang T. LES Study on High Reynolds Turbulent Drag-Reducing Flow of Viscoelastic Fluids Based on Multiple Relaxation Times Constitutive Model and Mixed Subgrid-Scale Model. In Dongarra J, Fu H, Krzhizhanovskaya VV, Lees MH, Sloot PM, Shi Y, Tian Y, editors, Computational Science – ICCS 2018 - 18th International Conference, Proceedings. Springer Verlag. 2018. p. 174-188. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-93713-7_14

LES Study on High Reynolds Turbulent Drag-Reducing Flow of Viscoelastic Fluids Based on Multiple Relaxation Times Constitutive Model and Mixed Subgrid-Scale Model

Abstract

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Keywords

ASJC Scopus subject areas

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