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On numerical approximations to diffuse-interface tumor growth models

dc.contributor.authorAcosta Soba, Daniel
dc.contributor.authorGuillén González, Francisco
dc.contributor.authorRodríguez Galván, J. Rafael
dc.date.accessioned2021-06-15T07:06:44Z
dc.date.available2021-06-15T07:06:44Z
dc.date.issued2021
dc.identifier.citationAcosta Soba, D., Guillén González, F. y Rodríguez Galván, J. R. (2021) On numerical approximations to diffuse-interface tumor growth models. En Gallego, R. y Mateos, M.(editores) Proceedings of the XXVI Congreso de Ecuaciones Diferenciales y Aplicaciones. XVI Congreso de Matemática Aplicada (pp. 8-14). Oviedo : Universidad de Oviedo, Servicio de Publicaciones
dc.identifier.isbn978-84-18482-21-2
dc.identifier.urihttp://hdl.handle.net/10651/59049
dc.description.abstractThis work is devoted to developing new numerical schemes for a tumor-nutrient PDE model. It is based on phase field equations for the tumor variable and a diffusive equation for the nutrient one, coupled by reaction terms and cross-diffusion terms. The model conserves the sum of tumor+nutrient and has a dissipative energy law. We introduce two different time-discrete schemes: one is based on an Eyre-type decomposition of the energy and the other is an energy quadratization scheme. Both (continuous) Finite Elements and Discontinuous Galerkin are used for space discretization. The schemes are compared analytically and computationally.spa
dc.format.extentp. 8-14
dc.language.isoengspa
dc.publisherServicio de Publicaciones de la Universidad de Oviedospa
dc.relation.ispartofProceedings of the XXVI Congreso de Ecuaciones Diferenciales y Aplicaciones. XVI Congreso de Matemática Aplicadaspa
dc.rights© Los autores
dc.rights© 2021 Universidad de Oviedo
dc.rightsCC Reconocimiento - No comercial - Sin obras derivadas 3.0 España
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.titleOn numerical approximations to diffuse-interface tumor growth modelsspa
dc.typebook partspa
dc.rights.accessRightsopen access
dc.type.hasVersionVoR


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