Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/42001
Campo DC Valoridioma
dc.contributor.authorPaz Hernández, Rubénen_US
dc.contributor.authorMonzón Verona, Mario Domingoen_US
dc.contributor.authorDíaz Padilla, Noelia Del Carmenen_US
dc.date.accessioned2018-09-26T12:01:27Z-
dc.date.available2018-09-26T12:01:27Z-
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/10553/42001-
dc.description.abstractThis paper presents an optimization methodology based on genetic algorithms, metamodels and design of experiments combined with Finite Elements Analysis (FEA) to optimize the material assignation of bioprinted scaffolds. The method optimizes the material assignation of the different bars of the strut structure to achieve the desired stiffness of the scaffold in different points of time. Therefore, the optimized design is the best combination of materials that minimizes the difference between the desired and achieved stiffness over time, so that the degradation process (4D) will be considered in the optimization process. The optimization algorithm is based on genetic algorithms and FEA simulations to evaluate the different designs proposed during the algorithm evolution. Moreover, the methodology integrates design of experiments and metamodels to estimate the simulation results, thus decreasing the number of FEA simulations and consequently reducing the optimization processing time. The mechanical properties of the materials (such as the elastic modulus) is defined in the different points of time according to experimental results of several bioinks and biomaterials. Simple configurations of struts is proposed to apply the methodology.en_US
dc.languageengen_US
dc.relationH2020-MSCA-RISE-2016-734156en_US
dc.relationMejora de la Biofuncionalidad de Scaffolds Polimericos Obtenidos Por Fabricacion Aditivaen_US
dc.subject331399 Otras (especificar)en_US
dc.subject.otherOptimizationen_US
dc.subject.otherScaffolden_US
dc.subject.otherBioprintingen_US
dc.subject.otherGenetic algorithmsen_US
dc.subject.otherMetamodelsen_US
dc.titleOptimization methodology for the material assignation of bioprinted scaffolds based on genetic algorithms and finite element analysisen_US
dc.typeinfo:eu-repo/semantics/lectureen_US
dc.typeLectureen_US
dc.relation.conference5th TERMIS World Congress (4-7 september), 2018 International Conference Center, Kyoto, Japón. "Integration of Industry, Government, and Academia for Regenerative Medicine"en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Ponenciaen_US
dc.utils.revisionen_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-INGen_US
dc.contributor.buulpgcBU-INGen_US
dc.contributor.buulpgcBU-INGen_US
dc.contributor.buulpgcBU-INGen_US
item.fulltextCon texto completo-
item.grantfulltextopen-
crisitem.author.deptGIR Fabricación integrada y avanzada-
crisitem.author.deptDepartamento de Ingeniería Mecánica-
crisitem.author.deptGIR Fabricación integrada y avanzada-
crisitem.author.deptDepartamento de Ingeniería Mecánica-
crisitem.author.deptGIR Fabricación integrada y avanzada-
crisitem.author.orcid0000-0003-1223-7067-
crisitem.author.orcid0000-0003-2736-7905-
crisitem.author.orcid0000-0002-1461-7752-
crisitem.author.parentorgDepartamento de Ingeniería Mecánica-
crisitem.author.parentorgDepartamento de Ingeniería Mecánica-
crisitem.author.parentorgDepartamento de Ingeniería Mecánica-
crisitem.author.fullNamePaz Hernández, Rubén-
crisitem.author.fullNameMonzón Verona, Mario Domingo-
crisitem.author.fullNameDíaz Padilla,Noelia Del Carmen-
crisitem.project.principalinvestigatorMonzón Verona, Mario Domingo-
Colección:Ponencias
miniatura
Abstract
Adobe PDF (181,29 kB)
Vista resumida

Visitas

86
actualizado el 06-ene-2024

Descargas

28
actualizado el 06-ene-2024

Google ScholarTM

Verifica


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.