Influence of grid resolution, parcel size and drag models on bubbling fluidized bed simulation
Abstract
Here in this paper, a bubbling fluidized bed is simulated with different numerical parameters, such as grid resolution and parcel size. We examined also the effect of using two homogeneous drag correlations and a heterogeneous drag based on the energy minimization method. A fast and reliable bubble detection algorithm was developed based on the connected component labeling. The radial and axial solids volume fraction profiles are compared with experiment data and previous simulation results. These results show a significant influence of drag models on bubble size and voidage distributions and a much less dependence on numerical parameters. With a heterogeneous drag model that accounts for sub-scale structures, the void fraction in the bubbling fluidized bed can be well captured with coarse grid and large computation parcels. Refining the CFD grid and reducing the parcel size can improve the simulation results but with a large increase in computation cost.
- Authors:
-
- National Energy Technology Lab. (NETL), Morgantown, WV (United States)
- National Energy Technology Lab. (NETL), Morgantown, WV (United States); West Virginia Univ., Morgantown, WV (United States). Research Corporation
- Publication Date:
- Research Org.:
- National Energy Technology Lab. (NETL), Pittsburgh, PA, and Morgantown, WV (United States). In-house Research
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1404697
- Alternate Identifier(s):
- OSTI ID: 1550291
- Report Number(s):
- NETL-PUB-21045
Journal ID: ISSN 1385-8947; PII: S1385894717309531
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Chemical Engineering Journal
- Additional Journal Information:
- Journal Volume: 326; Journal Issue: C; Journal ID: ISSN 1385-8947
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; 99 GENERAL AND MISCELLANEOUS; Computational fluid dynamics; discrete element method; coarse-grained particle method; bubbling fluidized bed
Citation Formats
Lu, Liqiang, Konan, Arthur, and Benyahia, Sofiane. Influence of grid resolution, parcel size and drag models on bubbling fluidized bed simulation. United States: N. p., 2017.
Web. doi:10.1016/j.cej.2017.06.002.
Lu, Liqiang, Konan, Arthur, & Benyahia, Sofiane. Influence of grid resolution, parcel size and drag models on bubbling fluidized bed simulation. United States. https://doi.org/10.1016/j.cej.2017.06.002
Lu, Liqiang, Konan, Arthur, and Benyahia, Sofiane. Fri .
"Influence of grid resolution, parcel size and drag models on bubbling fluidized bed simulation". United States. https://doi.org/10.1016/j.cej.2017.06.002. https://www.osti.gov/servlets/purl/1404697.
@article{osti_1404697,
title = {Influence of grid resolution, parcel size and drag models on bubbling fluidized bed simulation},
author = {Lu, Liqiang and Konan, Arthur and Benyahia, Sofiane},
abstractNote = {Here in this paper, a bubbling fluidized bed is simulated with different numerical parameters, such as grid resolution and parcel size. We examined also the effect of using two homogeneous drag correlations and a heterogeneous drag based on the energy minimization method. A fast and reliable bubble detection algorithm was developed based on the connected component labeling. The radial and axial solids volume fraction profiles are compared with experiment data and previous simulation results. These results show a significant influence of drag models on bubble size and voidage distributions and a much less dependence on numerical parameters. With a heterogeneous drag model that accounts for sub-scale structures, the void fraction in the bubbling fluidized bed can be well captured with coarse grid and large computation parcels. Refining the CFD grid and reducing the parcel size can improve the simulation results but with a large increase in computation cost.},
doi = {10.1016/j.cej.2017.06.002},
journal = {Chemical Engineering Journal},
number = C,
volume = 326,
place = {United States},
year = {Fri Jun 02 00:00:00 EDT 2017},
month = {Fri Jun 02 00:00:00 EDT 2017}
}
Web of Science
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