COMPUTATIONAL FLUID DYNAMICS OF A FLUID BED EMPLOYING TUNED GAS-SOLID DRAG MODELS

Detalhes bibliográficos
Autor(a) principal: Kestering, Daniel
Data de Publicação: 2017
Outros Autores: Bleyer, George C., Zinani, Flávia S. F., VanOsdol, John
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Interdisciplinar de Pesquisa em Engenharia
Texto Completo: https://periodicos.unb.br/index.php/ripe/article/view/21345
Resumo: Fluidized beds are devices in which a fluid flows from the bottom through a bed of particles, keeping them under suspension. Fluidized beds find many applications as reactors for combustion and gasification of solid fuels. For a given fluid-particulate combination, there is a minimum fluidization velocity (U mf) which exerts a drag force that equals the weight of the bed, fluidizing the system. Therefore, it is possible to calculate gas-solid drag forces parameters from a minimum fluidization velocity (Umf) obtained experimentally. In the present work, the objective was to tune gas-solid drag correlations to be used in the Computational Fluid Dynamics (CFD) of a fluidized bed employing the Umf and to analyze the improvement of CFD results. The particles employed were one of Geldart-B (sand-like) and two of Geldart-D (spoutable) types, fluidized in a cylindrical riser with 0.114 m internal diameter. The CFD multiphase model employed was the Two-Fluid-Model (TFM). In this model both gas and solid phases are assumed interpenetrating continua, mapped along the domain via its volume fraction, and the Kinetic Theory of Granular Flows (KTGF) is used to model solids phase viscosity term. The force interactions between phases are modeled using gas-solid drag correlations, which in this work were based on Syamlal-O'Brien and Di Felice models. A finite volume method CFD code was used to perform the simulations. The simulations for superficial velocity of 1.5 Umf was performed in order to confront experimental and numerical results of pressure drop and bed height. So far tuned models were better than the original ones in the prediction of fluidization curves (pressure drop versus superficial velocity), and in the prediction of bed expansion and bubble formation.
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spelling COMPUTATIONAL FLUID DYNAMICS OF A FLUID BED EMPLOYING TUNED GAS-SOLID DRAG MODELSTuned drag model. Adjusted drag model. Di Felice. Syamlal-O’Brien. Fluidized bed.Fluidized beds are devices in which a fluid flows from the bottom through a bed of particles, keeping them under suspension. Fluidized beds find many applications as reactors for combustion and gasification of solid fuels. For a given fluid-particulate combination, there is a minimum fluidization velocity (U mf) which exerts a drag force that equals the weight of the bed, fluidizing the system. Therefore, it is possible to calculate gas-solid drag forces parameters from a minimum fluidization velocity (Umf) obtained experimentally. In the present work, the objective was to tune gas-solid drag correlations to be used in the Computational Fluid Dynamics (CFD) of a fluidized bed employing the Umf and to analyze the improvement of CFD results. The particles employed were one of Geldart-B (sand-like) and two of Geldart-D (spoutable) types, fluidized in a cylindrical riser with 0.114 m internal diameter. The CFD multiphase model employed was the Two-Fluid-Model (TFM). In this model both gas and solid phases are assumed interpenetrating continua, mapped along the domain via its volume fraction, and the Kinetic Theory of Granular Flows (KTGF) is used to model solids phase viscosity term. The force interactions between phases are modeled using gas-solid drag correlations, which in this work were based on Syamlal-O'Brien and Di Felice models. A finite volume method CFD code was used to perform the simulations. The simulations for superficial velocity of 1.5 Umf was performed in order to confront experimental and numerical results of pressure drop and bed height. So far tuned models were better than the original ones in the prediction of fluidization curves (pressure drop versus superficial velocity), and in the prediction of bed expansion and bubble formation.Programa de Pós-Graduação em Integridade de Materiais da Engenharia2017-01-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.unb.br/index.php/ripe/article/view/2134510.26512/ripe.v2i12.21345Revista Interdisciplinar de Pesquisa em Engenharia; Vol. 2 No. 12 (2016): COMPUTATIONAL THERMAL SCIENCES; 71-85Revista Interdisciplinar de Pesquisa em Engenharia; v. 2 n. 12 (2016): COMPUTATIONAL THERMAL SCIENCES; 71-852447-6102reponame:Revista Interdisciplinar de Pesquisa em Engenhariainstname:Universidade de Brasília (UnB)instacron:UNBenghttps://periodicos.unb.br/index.php/ripe/article/view/21345/19687Copyright (c) 2018 Revista Interdisciplinar de Pesquisa em Engenharia - RIPEinfo:eu-repo/semantics/openAccessKestering, DanielBleyer, George C.Zinani, Flávia S. F.VanOsdol, John2019-06-16T01:46:52Zoai:ojs.pkp.sfu.ca:article/21345Revistahttps://periodicos.unb.br/index.php/ripePUBhttps://periodicos.unb.br/index.php/ripe/oaianflor@unb.br2447-61022447-6102opendoar:2019-06-16T01:46:52Revista Interdisciplinar de Pesquisa em Engenharia - Universidade de Brasília (UnB)false
dc.title.none.fl_str_mv COMPUTATIONAL FLUID DYNAMICS OF A FLUID BED EMPLOYING TUNED GAS-SOLID DRAG MODELS
title COMPUTATIONAL FLUID DYNAMICS OF A FLUID BED EMPLOYING TUNED GAS-SOLID DRAG MODELS
spellingShingle COMPUTATIONAL FLUID DYNAMICS OF A FLUID BED EMPLOYING TUNED GAS-SOLID DRAG MODELS
Kestering, Daniel
Tuned drag model. Adjusted drag model. Di Felice. Syamlal-O’Brien. Fluidized bed.
title_short COMPUTATIONAL FLUID DYNAMICS OF A FLUID BED EMPLOYING TUNED GAS-SOLID DRAG MODELS
title_full COMPUTATIONAL FLUID DYNAMICS OF A FLUID BED EMPLOYING TUNED GAS-SOLID DRAG MODELS
title_fullStr COMPUTATIONAL FLUID DYNAMICS OF A FLUID BED EMPLOYING TUNED GAS-SOLID DRAG MODELS
title_full_unstemmed COMPUTATIONAL FLUID DYNAMICS OF A FLUID BED EMPLOYING TUNED GAS-SOLID DRAG MODELS
title_sort COMPUTATIONAL FLUID DYNAMICS OF A FLUID BED EMPLOYING TUNED GAS-SOLID DRAG MODELS
author Kestering, Daniel
author_facet Kestering, Daniel
Bleyer, George C.
Zinani, Flávia S. F.
VanOsdol, John
author_role author
author2 Bleyer, George C.
Zinani, Flávia S. F.
VanOsdol, John
author2_role author
author
author
dc.contributor.author.fl_str_mv Kestering, Daniel
Bleyer, George C.
Zinani, Flávia S. F.
VanOsdol, John
dc.subject.por.fl_str_mv Tuned drag model. Adjusted drag model. Di Felice. Syamlal-O’Brien. Fluidized bed.
topic Tuned drag model. Adjusted drag model. Di Felice. Syamlal-O’Brien. Fluidized bed.
description Fluidized beds are devices in which a fluid flows from the bottom through a bed of particles, keeping them under suspension. Fluidized beds find many applications as reactors for combustion and gasification of solid fuels. For a given fluid-particulate combination, there is a minimum fluidization velocity (U mf) which exerts a drag force that equals the weight of the bed, fluidizing the system. Therefore, it is possible to calculate gas-solid drag forces parameters from a minimum fluidization velocity (Umf) obtained experimentally. In the present work, the objective was to tune gas-solid drag correlations to be used in the Computational Fluid Dynamics (CFD) of a fluidized bed employing the Umf and to analyze the improvement of CFD results. The particles employed were one of Geldart-B (sand-like) and two of Geldart-D (spoutable) types, fluidized in a cylindrical riser with 0.114 m internal diameter. The CFD multiphase model employed was the Two-Fluid-Model (TFM). In this model both gas and solid phases are assumed interpenetrating continua, mapped along the domain via its volume fraction, and the Kinetic Theory of Granular Flows (KTGF) is used to model solids phase viscosity term. The force interactions between phases are modeled using gas-solid drag correlations, which in this work were based on Syamlal-O'Brien and Di Felice models. A finite volume method CFD code was used to perform the simulations. The simulations for superficial velocity of 1.5 Umf was performed in order to confront experimental and numerical results of pressure drop and bed height. So far tuned models were better than the original ones in the prediction of fluidization curves (pressure drop versus superficial velocity), and in the prediction of bed expansion and bubble formation.
publishDate 2017
dc.date.none.fl_str_mv 2017-01-10
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.unb.br/index.php/ripe/article/view/21345
10.26512/ripe.v2i12.21345
url https://periodicos.unb.br/index.php/ripe/article/view/21345
identifier_str_mv 10.26512/ripe.v2i12.21345
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.unb.br/index.php/ripe/article/view/21345/19687
dc.rights.driver.fl_str_mv Copyright (c) 2018 Revista Interdisciplinar de Pesquisa em Engenharia - RIPE
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2018 Revista Interdisciplinar de Pesquisa em Engenharia - RIPE
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Programa de Pós-Graduação em Integridade de Materiais da Engenharia
publisher.none.fl_str_mv Programa de Pós-Graduação em Integridade de Materiais da Engenharia
dc.source.none.fl_str_mv Revista Interdisciplinar de Pesquisa em Engenharia; Vol. 2 No. 12 (2016): COMPUTATIONAL THERMAL SCIENCES; 71-85
Revista Interdisciplinar de Pesquisa em Engenharia; v. 2 n. 12 (2016): COMPUTATIONAL THERMAL SCIENCES; 71-85
2447-6102
reponame:Revista Interdisciplinar de Pesquisa em Engenharia
instname:Universidade de Brasília (UnB)
instacron:UNB
instname_str Universidade de Brasília (UnB)
instacron_str UNB
institution UNB
reponame_str Revista Interdisciplinar de Pesquisa em Engenharia
collection Revista Interdisciplinar de Pesquisa em Engenharia
repository.name.fl_str_mv Revista Interdisciplinar de Pesquisa em Engenharia - Universidade de Brasília (UnB)
repository.mail.fl_str_mv anflor@unb.br
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