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Stochastic separated flow models with applications in numerical computations of supersonic particle-laden turbulent flows
Advances in Mechanical Engineering, Volume: 7, Issue: 8, Start page: 168781401560133
Swansea University Author: Zhaoxin Ren
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DOI (Published version): 10.1177/1687814015601335
Abstract
In this article, three stochastic separated flow models were applied to predict the dispersion of inertial fuel particles in the supersonic turbulent flows. The flow field of continuous phase was simulated by means of Reynolds-averaged Navier–Stokes method with a two-equation turbulence model. Clift...
Published in: | Advances in Mechanical Engineering |
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ISSN: | 1687-8140 1687-8140 |
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SAGE Publications
2015
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URI: | https://cronfa.swan.ac.uk/Record/cronfa59361 |
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2022-02-23T15:34:12.9407118 v2 59361 2022-02-11 Stochastic separated flow models with applications in numerical computations of supersonic particle-laden turbulent flows 62a1a0da0fa78e05c3deafcdee5551ce 0000-0002-6305-9515 Zhaoxin Ren Zhaoxin Ren true false 2022-02-11 AERO In this article, three stochastic separated flow models were applied to predict the dispersion of inertial fuel particles in the supersonic turbulent flows. The flow field of continuous phase was simulated by means of Reynolds-averaged Navier–Stokes method with a two-equation turbulence model. Clift’s expression was used to modify the drag force on the particle considering the compressibility effects. The particle-phase statistics were obtained by a secondary-order time-weighed Eulerian method. The ability of those stochastic separated flow models was then compared for predicting the mean particle velocity and the particle dispersion. For obtaining a statistically stationary solution, the stochastic separated flow model required the largest number of computational particles, whereas the improved stochastic separated flow model was found to need the least. The time-series stochastic separation flow model lay in-between. Compared with the other two models, the particle dispersion was over-predicted by the stochastic separated flow model in the supersonic particle-laden boundary layer flow, while the improved stochastic separated flow model was less predictable for the particle spatial distribution in the particle-laden strut-injection flow. Three models could well predict the mean velocities of the particle phase. This study is valuable for selecting a validated model used for predicting the particle dispersion in supersonic turbulent flows. Journal Article Advances in Mechanical Engineering 7 8 168781401560133 SAGE Publications 1687-8140 1687-8140 Stochastic separated flow model, supersonic turbulent flows, particle-laden flow, numerical simulation 1 8 2015 2015-08-01 10.1177/1687814015601335 COLLEGE NANME Aerospace Engineering COLLEGE CODE AERO Swansea University 2022-02-23T15:34:12.9407118 2022-02-11T01:09:28.8090240 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering Bing Wang 1 Zhaoxin Ren 0000-0002-6305-9515 2 Huiqiang Zhang 3 59361__22443__d6073bfbf0f24b77905527aac26ae279.pdf 59361.pdf 2022-02-23T15:33:19.4682418 Output 4417560 application/pdf Version of Record true This article is distributed under the terms of the Creative Commons Attribution 3.0 License true eng http://www.creativecommons.org/licenses/by/3.0/) |
title |
Stochastic separated flow models with applications in numerical computations of supersonic particle-laden turbulent flows |
spellingShingle |
Stochastic separated flow models with applications in numerical computations of supersonic particle-laden turbulent flows Zhaoxin Ren |
title_short |
Stochastic separated flow models with applications in numerical computations of supersonic particle-laden turbulent flows |
title_full |
Stochastic separated flow models with applications in numerical computations of supersonic particle-laden turbulent flows |
title_fullStr |
Stochastic separated flow models with applications in numerical computations of supersonic particle-laden turbulent flows |
title_full_unstemmed |
Stochastic separated flow models with applications in numerical computations of supersonic particle-laden turbulent flows |
title_sort |
Stochastic separated flow models with applications in numerical computations of supersonic particle-laden turbulent flows |
author_id_str_mv |
62a1a0da0fa78e05c3deafcdee5551ce |
author_id_fullname_str_mv |
62a1a0da0fa78e05c3deafcdee5551ce_***_Zhaoxin Ren |
author |
Zhaoxin Ren |
author2 |
Bing Wang Zhaoxin Ren Huiqiang Zhang |
format |
Journal article |
container_title |
Advances in Mechanical Engineering |
container_volume |
7 |
container_issue |
8 |
container_start_page |
168781401560133 |
publishDate |
2015 |
institution |
Swansea University |
issn |
1687-8140 1687-8140 |
doi_str_mv |
10.1177/1687814015601335 |
publisher |
SAGE Publications |
college_str |
Faculty of Science and Engineering |
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering |
document_store_str |
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description |
In this article, three stochastic separated flow models were applied to predict the dispersion of inertial fuel particles in the supersonic turbulent flows. The flow field of continuous phase was simulated by means of Reynolds-averaged Navier–Stokes method with a two-equation turbulence model. Clift’s expression was used to modify the drag force on the particle considering the compressibility effects. The particle-phase statistics were obtained by a secondary-order time-weighed Eulerian method. The ability of those stochastic separated flow models was then compared for predicting the mean particle velocity and the particle dispersion. For obtaining a statistically stationary solution, the stochastic separated flow model required the largest number of computational particles, whereas the improved stochastic separated flow model was found to need the least. The time-series stochastic separation flow model lay in-between. Compared with the other two models, the particle dispersion was over-predicted by the stochastic separated flow model in the supersonic particle-laden boundary layer flow, while the improved stochastic separated flow model was less predictable for the particle spatial distribution in the particle-laden strut-injection flow. Three models could well predict the mean velocities of the particle phase. This study is valuable for selecting a validated model used for predicting the particle dispersion in supersonic turbulent flows. |
published_date |
2015-08-01T04:16:36Z |
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1763754111869648896 |
score |
11.013148 |