Clustering instabilities in sedimenting fluid–solid systems: critical assessment of kinetic-theory-based predictions using direct numerical simulation data
Abstract
In this paper the quantitative and qualitative ability of a kinetic-theory-based two-fluid model (KT-TFM) is assessed in a state of fully periodic sedimentation (fluidization), with a focus on statistically steady, unstable (clustered) states. The accuracy of KT-TFM predictions is evaluated via direct comparison to direct numerical simulation (DNS) data. The KT-TFM and DNS results span a rather wide parameter space: mean-flow Reynolds numbers on the order of 1 and 10, mean solid volume fractions from 0.1 to 0.4, solid-to-fluid density ratios from 10 to 1000 and elastic and moderately inelastic (restitution coefficient of 0.9) conditions. Data from both KT-TFM and DNS display a rich variety of statistically steady yet unstable structures (clusters). Instantaneous snapshots of KT-TFM and DNS demonstrate remarkable qualitative agreement. This qualitative agreement is quantified by calculating the critical density ratio at which the structure transitions from a chaotic, dynamic state to a regular, plug-flow state, with good overall comparisons. Further quantitative assessments of mean and fluctuating velocities show good agreement at high density ratios but weaker agreement at intermediate to low density ratios depending on the mean-flow Reynolds numbers and solid fractions. Deviations of the KT-TFM results from the DNS data were traced to a breakdown inmore »
- Authors:
-
[1];
- Univ. of Colorado, Boulder, CO (United States)
- Harbin Inst. of Technology (China)
- Colorado School of Mines, Golden, CO (United States)
- Publication Date:
- Research Org.:
- Univ. of Colorado, Boulder, CO (United States)
- Sponsoring Org.:
- USDOE Office of Fossil Energy (FE)
- OSTI Identifier:
- 1832979
- Grant/Contract Number:
- FE0026298
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Fluid Mechanics
- Additional Journal Information:
- Journal Volume: 823; Journal ID: ISSN 0022-1120
- Publisher:
- Cambridge University Press
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 42 ENGINEERING; clustering instability; multiphase flow; kinetic-theory-based two-fluid model
Citation Formats
Fullmer, William D., Liu, Guodong, Yin, Xiaolong, and Hrenya, Christine M. Clustering instabilities in sedimenting fluid–solid systems: critical assessment of kinetic-theory-based predictions using direct numerical simulation data. United States: N. p., 2017.
Web. doi:10.1017/jfm.2017.295.
Fullmer, William D., Liu, Guodong, Yin, Xiaolong, & Hrenya, Christine M. Clustering instabilities in sedimenting fluid–solid systems: critical assessment of kinetic-theory-based predictions using direct numerical simulation data. United States. https://doi.org/10.1017/jfm.2017.295
Fullmer, William D., Liu, Guodong, Yin, Xiaolong, and Hrenya, Christine M. Tue .
"Clustering instabilities in sedimenting fluid–solid systems: critical assessment of kinetic-theory-based predictions using direct numerical simulation data". United States. https://doi.org/10.1017/jfm.2017.295. https://www.osti.gov/servlets/purl/1832979.
@article{osti_1832979,
title = {Clustering instabilities in sedimenting fluid–solid systems: critical assessment of kinetic-theory-based predictions using direct numerical simulation data},
author = {Fullmer, William D. and Liu, Guodong and Yin, Xiaolong and Hrenya, Christine M.},
abstractNote = {In this paper the quantitative and qualitative ability of a kinetic-theory-based two-fluid model (KT-TFM) is assessed in a state of fully periodic sedimentation (fluidization), with a focus on statistically steady, unstable (clustered) states. The accuracy of KT-TFM predictions is evaluated via direct comparison to direct numerical simulation (DNS) data. The KT-TFM and DNS results span a rather wide parameter space: mean-flow Reynolds numbers on the order of 1 and 10, mean solid volume fractions from 0.1 to 0.4, solid-to-fluid density ratios from 10 to 1000 and elastic and moderately inelastic (restitution coefficient of 0.9) conditions. Data from both KT-TFM and DNS display a rich variety of statistically steady yet unstable structures (clusters). Instantaneous snapshots of KT-TFM and DNS demonstrate remarkable qualitative agreement. This qualitative agreement is quantified by calculating the critical density ratio at which the structure transitions from a chaotic, dynamic state to a regular, plug-flow state, with good overall comparisons. Further quantitative assessments of mean and fluctuating velocities show good agreement at high density ratios but weaker agreement at intermediate to low density ratios depending on the mean-flow Reynolds numbers and solid fractions. Deviations of the KT-TFM results from the DNS data were traced to a breakdown in one of the underlying assumptions of the kinetic theory derivation: high thermal Stokes number. Surprisingly, however, even though the low Knudsen number assumption, also associated with the kinetic theory derivation, is violated throughout most of the parameter space, it does not seem to affect the good quantitative accuracy of KT-TFM simulations.},
doi = {10.1017/jfm.2017.295},
journal = {Journal of Fluid Mechanics},
number = ,
volume = 823,
place = {United States},
year = {Tue Jun 20 00:00:00 EDT 2017},
month = {Tue Jun 20 00:00:00 EDT 2017}
}
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