A two-phase genetic algorithm to model the menisca horn repaired with suture

dc.centroEscuela de Ingenierías Industrialeses_ES
dc.contributor.authorEstébanez-Campos, María Belén
dc.contributor.authorPeña Trabalón, Alejandro
dc.contributor.authorMoreno-Vegas, Salvador
dc.contributor.authorEspejo-Reina, Alejandro
dc.contributor.authorNadal-Martínez, Fernando
dc.contributor.authorGarcía-Vacas, Francisco
dc.contributor.authorPérez-Blanca, Ana
dc.contributor.authorPrado-Novoa, María
dc.date.accessioned2022-07-07T09:19:58Z
dc.date.available2022-07-07T09:19:58Z
dc.date.created2022-07
dc.date.issued2022-07
dc.departamentoIngeniería Mecánica, Térmica y de Fluidos
dc.description.abstractMenisci suturing is a common surgical technique nowadays. Menisci have been modeled with different degrees of complexity in finite element models (FEM) of the human knee, but there are few works focused on simulating the meniscus subjected to traction loads in its longitudinal direction, such as those produced by sutures after repair. Moreover, there are no models that include the effect of the orifice for the suture. This study develops a material model of the meniscal horn when it is pulled by the thread used to reattach its root.es_ES
dc.description.sponsorshipUniversidad de Málaga.Campus de Excelencia Internacional Andalucía Tech. Subvencionado por el Proyecto del Plan Nacional RTI2018-094339-B-I00 y por el Proyecto de la Junta de Andalucía P20-00294.es_ES
dc.identifier.urihttps://hdl.handle.net/10630/24579
dc.language.isoenges_ES
dc.relation.eventdateJunio 2022es_ES
dc.relation.eventplacePorto, Portugales_ES
dc.relation.eventtitle27th Congress of the European Society of Biomechanics, ESB 2022es_ES
dc.rights.accessRightsopen accesses_ES
dc.subjectAlgoritmos genéticoses_ES
dc.subjectMeniscoses_ES
dc.subject.otherMeniscies_ES
dc.subject.otherGenetic Algorithmes_ES
dc.subject.otherOptimizationes_ES
dc.titleA two-phase genetic algorithm to model the menisca horn repaired with suturees_ES
dc.typeconference outputes_ES
dspace.entity.typePublication
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relation.isAuthorOfPublication107d1693-14af-44b8-950f-5bfe32bd45e6
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relation.isAuthorOfPublication12f47541-23eb-439f-98fb-3f7179345485
relation.isAuthorOfPublication.latestForDiscovery1000321b-951e-4b30-b9e1-081e747f3b0f

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