Numerical Simulations of a Polydisperse Sedimentation Model by Using Spectral WENO Method with Adaptive Multiresolution
In this work, we apply adaptive multiresolution (Harten's approach) characteristic-wise fifth-order Weighted Essentially Non-Oscillatory (WENO) for computing the numerical solution of a polydisperse sedimentation model, namely, the Höfler and Schwarzer model. In comparison to other related work...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2016
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/8974
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/8974
- Palabra clave:
- Adaptive multiresolution
Höfler and Schwarzer model
Spectral-based WENO
SSPRK methods
Numerical methods
Numerical models
Polydispersity
Adaptive multi resolutions
Essentially non-oscillatory
Numerical solution
Sedimentation model
Spectral-based WENO
SSPRK methods
Strong stability preserving
Time discretization
Runge Kutta methods
- Rights
- restrictedAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
| id |
UTB2_72b9277acb3650988334640cf7d6bb6d |
|---|---|
| oai_identifier_str |
oai:repositorio.utb.edu.co:20.500.12585/8974 |
| network_acronym_str |
UTB2 |
| network_name_str |
Repositorio Institucional UTB |
| repository_id_str |
|
| dc.title.none.fl_str_mv |
Numerical Simulations of a Polydisperse Sedimentation Model by Using Spectral WENO Method with Adaptive Multiresolution |
| title |
Numerical Simulations of a Polydisperse Sedimentation Model by Using Spectral WENO Method with Adaptive Multiresolution |
| spellingShingle |
Numerical Simulations of a Polydisperse Sedimentation Model by Using Spectral WENO Method with Adaptive Multiresolution Adaptive multiresolution Höfler and Schwarzer model Spectral-based WENO SSPRK methods Numerical methods Numerical models Polydispersity Adaptive multi resolutions Essentially non-oscillatory Numerical solution Sedimentation model Spectral-based WENO SSPRK methods Strong stability preserving Time discretization Runge Kutta methods |
| title_short |
Numerical Simulations of a Polydisperse Sedimentation Model by Using Spectral WENO Method with Adaptive Multiresolution |
| title_full |
Numerical Simulations of a Polydisperse Sedimentation Model by Using Spectral WENO Method with Adaptive Multiresolution |
| title_fullStr |
Numerical Simulations of a Polydisperse Sedimentation Model by Using Spectral WENO Method with Adaptive Multiresolution |
| title_full_unstemmed |
Numerical Simulations of a Polydisperse Sedimentation Model by Using Spectral WENO Method with Adaptive Multiresolution |
| title_sort |
Numerical Simulations of a Polydisperse Sedimentation Model by Using Spectral WENO Method with Adaptive Multiresolution |
| dc.subject.keywords.none.fl_str_mv |
Adaptive multiresolution Höfler and Schwarzer model Spectral-based WENO SSPRK methods Numerical methods Numerical models Polydispersity Adaptive multi resolutions Essentially non-oscillatory Numerical solution Sedimentation model Spectral-based WENO SSPRK methods Strong stability preserving Time discretization Runge Kutta methods |
| topic |
Adaptive multiresolution Höfler and Schwarzer model Spectral-based WENO SSPRK methods Numerical methods Numerical models Polydispersity Adaptive multi resolutions Essentially non-oscillatory Numerical solution Sedimentation model Spectral-based WENO SSPRK methods Strong stability preserving Time discretization Runge Kutta methods |
| description |
In this work, we apply adaptive multiresolution (Harten's approach) characteristic-wise fifth-order Weighted Essentially Non-Oscillatory (WENO) for computing the numerical solution of a polydisperse sedimentation model, namely, the Höfler and Schwarzer model. In comparison to other related works, time discretization is carried out with the ten-stage fourth-order strong stability preserving Runge-Kutta method which is more efficient than the widely used optimal third-order TVD Runge-Kutta method. Numerical results with errors, convergence rates and CPU times are included for four and 11 species. © 2016 World Scientific Publishing Company. |
| publishDate |
2016 |
| dc.date.issued.none.fl_str_mv |
2016 |
| dc.date.accessioned.none.fl_str_mv |
2020-03-26T16:32:41Z |
| dc.date.available.none.fl_str_mv |
2020-03-26T16:32:41Z |
| dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.type.driver.none.fl_str_mv |
info:eu-repo/semantics/article |
| dc.type.hasversion.none.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.spa.none.fl_str_mv |
Artículo |
| status_str |
publishedVersion |
| dc.identifier.citation.none.fl_str_mv |
International Journal of Computational Methods; Vol. 13, Núm. 6 |
| dc.identifier.issn.none.fl_str_mv |
02198762 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/8974 |
| dc.identifier.doi.none.fl_str_mv |
10.1142/S0219876216500377 |
| dc.identifier.instname.none.fl_str_mv |
Universidad Tecnológica de Bolívar |
| dc.identifier.reponame.none.fl_str_mv |
Repositorio UTB |
| dc.identifier.orcid.none.fl_str_mv |
56423657700 57189266430 |
| identifier_str_mv |
International Journal of Computational Methods; Vol. 13, Núm. 6 02198762 10.1142/S0219876216500377 Universidad Tecnológica de Bolívar Repositorio UTB 56423657700 57189266430 |
| url |
https://hdl.handle.net/20.500.12585/8974 |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_16ec |
| dc.rights.uri.none.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| dc.rights.accessrights.none.fl_str_mv |
info:eu-repo/semantics/restrictedAccess |
| dc.rights.cc.none.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ Atribución-NoComercial 4.0 Internacional http://purl.org/coar/access_right/c_16ec |
| eu_rights_str_mv |
restrictedAccess |
| dc.format.medium.none.fl_str_mv |
Recurso electrónico |
| dc.format.mimetype.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
World Scientific Publishing Co. Pte Ltd |
| publisher.none.fl_str_mv |
World Scientific Publishing Co. Pte Ltd |
| dc.source.none.fl_str_mv |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84967102576&doi=10.1142%2fS0219876216500377&partnerID=40&md5=5e51497960f2d1bb8cf3e76f42051863 |
| institution |
Universidad Tecnológica de Bolívar |
| bitstream.url.fl_str_mv |
https://repositorio.utb.edu.co/bitstream/20.500.12585/8974/1/MiniProdInv.png |
| bitstream.checksum.fl_str_mv |
0cb0f101a8d16897fb46fc914d3d7043 |
| bitstream.checksumAlgorithm.fl_str_mv |
MD5 |
| repository.name.fl_str_mv |
Repositorio Institucional UTB |
| repository.mail.fl_str_mv |
repositorioutb@utb.edu.co |
| _version_ |
1808397591738580992 |
| spelling |
2020-03-26T16:32:41Z2020-03-26T16:32:41Z2016International Journal of Computational Methods; Vol. 13, Núm. 602198762https://hdl.handle.net/20.500.12585/897410.1142/S0219876216500377Universidad Tecnológica de BolívarRepositorio UTB5642365770057189266430In this work, we apply adaptive multiresolution (Harten's approach) characteristic-wise fifth-order Weighted Essentially Non-Oscillatory (WENO) for computing the numerical solution of a polydisperse sedimentation model, namely, the Höfler and Schwarzer model. In comparison to other related works, time discretization is carried out with the ten-stage fourth-order strong stability preserving Runge-Kutta method which is more efficient than the widely used optimal third-order TVD Runge-Kutta method. Numerical results with errors, convergence rates and CPU times are included for four and 11 species. © 2016 World Scientific Publishing Company.Recurso electrónicoapplication/pdfengWorld Scientific Publishing Co. Pte Ltdhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84967102576&doi=10.1142%2fS0219876216500377&partnerID=40&md5=5e51497960f2d1bb8cf3e76f42051863Numerical Simulations of a Polydisperse Sedimentation Model by Using Spectral WENO Method with Adaptive Multiresolutioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Adaptive multiresolutionHöfler and Schwarzer modelSpectral-based WENOSSPRK methodsNumerical methodsNumerical modelsPolydispersityAdaptive multi resolutionsEssentially non-oscillatoryNumerical solutionSedimentation modelSpectral-based WENOSSPRK methodsStrong stability preservingTime discretizationRunge Kutta methodsVega C.A.Arias Amaya, FabiánAnderson, J., A secular equation for the eigenvalues of a diagonal matrix perturbation (1996) Lin. Alg. Appl., 246, pp. 49-70Batchelor, G.K., Sedimentation in a dilute polydisperse system of interacting spheres. Part 1. General theory (1982) J. Fluid Mech., 119, pp. 379-408Batchelor, G.K., Wen, C.S., Sedimentation in a dilute polydisperse system of interacting spheres. Part 2. Numerical results (1982) J. Fluid Mech., 124, pp. 495-528Bürger, R., Kozakevicius, A., Adaptive multiresolution WENO schemes for multi-species kinematic flow models (2007) J. Comput. Phys., 224, pp. 1190-1222Bürger, R., Donat, R., Mulet, P., Vega, C.A., Hyperbolicity analysis of polydisperse sedimentation models via a secular equation for the flux Jacobian (2010) SIAM J. Appl. Math., 70, pp. 2186-2213Bürger, R., Donat, R., Mulet, P., Vega, C.A., On the implementation of WENO schemes for a class of polydisperse sedimentation models (2011) J. Comput. Phys., 230, pp. 2322-2344Bürger, R., Mulet, P., Villada, L., Spectral WENO schemes with adaptive mesh refinement for models of polydisperse sedimentation (2013) ZAMM Z. Angew. Math. Mech., 93, pp. 373-386Chiavassa, G., Donat, R., Müller, S., Multiresolution-based adaptive schemes for hyperbolic conservation laws (2003) Adaptive Mesh Refinement - Theory and Applications, 41, pp. 137-159. , eds. Plewa, T., Lindec, T. and Weiss, V. G., Lecture Notes in Computational Science and Engineering, (Springer-Verlag, Berlin)Davis, R.H., Gecol, H., Hindered settling function with no empirical parameters for polydisperse suspensions (1994) AIChE J., 40, pp. 570-575Donat, R., Mulet, P., A secular equation for the Jacobian matrix of certain multi-species kinematic flow models (2010) Numer. Methods Part. Differ. Equ., 26, pp. 159-175Gottlieb, S., Ketcheson, D.I., Shu, C.W., High order strong stability preserving time discretization (2009) J. Sci. Comput., 38, pp. 251-289Greenspan, H.P., Ungarish, M., On hindered settling of particles of different sizes (1982) Int. J. Multiphase Flow, 8, pp. 587-604Harten, A., Multiresolution algorithms for the numerical solution of hyperbolic conservation laws (1995) Commun. Pure Appl. Math., 48, pp. 1305-1342Henrick, A.K., Aslam, T.D., Powers, J.M., Mapped weighted essentially nonoscillatory schemes: Achieving optimal order near critical points (2005) J. Comput. Phys., 207, pp. 542-567Höfler, K., (2000) Simulation and Modeling of Mono-and Bidisperse Suspensions, , Doctoral Thesis, Institut für Computeranwendungen, Universität Stuttgart, GermanyHöfler, K., Schwarzer, S., The structure of bidisperse suspensionsal low Reynolds numbers (2000) Multifield Problems: State of the Art, pp. 42-49. , Sändig, A. M., Schiehlen, W. and Wendland, W. L., (Springer Verlag, Berlin)Jiang, G.S., Shu, C.W., Efficient implementation of weighted ENO schemes (1996) J. Comput. Phys., 126, pp. 202-228Ketcheson, D.I., Highly efficient stability preserving Runge-Kutta methods with low storage implementation (2008) J. Sci. Comput., 30, pp. 2113-2136Liu, X.D., Osher, S., Chan, T., Weighted essentially non-oscillatory schemes (1994) J. Comput. Phys., 115, pp. 200-212Müller, S., (2003) Adaptive Multiscale Schemes for Conservation Laws, , 1st edition (Springer)Shu, C.H., High order weighted essentially nonoscillatory schemes for convection dominated problems (2009) SIAM Rev., 51, pp. 82-126Tenaud, C., Duarte, M., Tutorials on adaptive multiresolution for mesh refinement applied to conservation law problems (2011) ESAIM Proc., 34, pp. 184-239http://purl.org/coar/resource_type/c_6501THUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/8974/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/8974oai:repositorio.utb.edu.co:20.500.12585/89742023-05-25 11:42:06.262Repositorio Institucional UTBrepositorioutb@utb.edu.co |