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Mesh adaptivity driven by goal-oriented locally equilibrated superconvergent patch recovery

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Mesh adaptivity driven by goal-oriented locally equilibrated superconvergent patch recovery

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dc.contributor.author González Estrada, Octavio Andrés es_ES
dc.contributor.author Nadal Soriano, Enrique es_ES
dc.contributor.author Ródenas, J.J. es_ES
dc.contributor.author Kerfriden, P. es_ES
dc.contributor.author Bordas, S.P.A. es_ES
dc.contributor.author Fuenmayor Fernández, Francisco Javier es_ES
dc.date.accessioned 2015-06-26T11:33:42Z
dc.date.available 2015-06-26T11:33:42Z
dc.date.issued 2014-05
dc.identifier.issn 0178-7675
dc.identifier.uri http://hdl.handle.net/10251/52350
dc.description.abstract [EN] Goal-oriented error estimates (GOEE) have become popular tools to quantify and control the local error in quantities of interest (QoI), which are often more pertinent than local errors in energy for design purposes (e.g. the mean stress or mean displacement in a particular area, the stress intensity factor for fracture problems). These GOEE are one of the key unsolved problems of advanced engineering applications in, for example, the aerospace industry. This work presents a simple recovery-based error estimation technique for QoIs whose main characteristic is the use of an enhanced version of the Superconvergent Patch Recovery (SPR) technique previously used for error estimation in the energy norm. This enhanced SPR technique is used to recover both the primal and dual solutions. It provides a nearly statically admissible stress field that results in accurate estimations of the local contributions to the discretisation error in the QoI and, therefore, in an accurate estimation of this magnitude. This approach leads to a technique with a reasonable computational cost that could easily be implemented into already available finite element codes, or as an independent postprocessing tool. es_ES
dc.description.sponsorship This work was supported by the EPSRC Grant EP/G042705/1 "Increased Reliability for Industrially Relevant Automatic Crack Growth Simulation with the eXtended Finite Element Method". Stephane Bordas also thanks partial funding for his time provided by the European Research Council Starting Independent Research Grant (ERC Stg Grant Agreement No. 279578) "RealTCut Towards real time multiscale simulation of cutting in non-linear materials with applications to surgical simulation and computer guided surgery". This work has received partial support from the research project DPI2010-20542 of the Ministerio de Economia y Competitividad (Spain). The financial support of the FPU program (AP2008-01086), the funding from Universitat Politecnica de Valencia and Generalitat Valenciana (PROMETEO/2012/023) are also acknowledged. All authors also thank the partial support of the Framework Programme 7 Initial Training Network Funding under Grant No. 289361 "Integrating Numerical Simulation and Geometric Design Technology." en_EN
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Computational Mechanics es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Goal-oriented es_ES
dc.subject Error estimation es_ES
dc.subject Recovery es_ES
dc.subject Quantities of interest es_ES
dc.subject Error control es_ES
dc.subject Mesh adaptivity es_ES
dc.subject.classification INGENIERIA MECANICA es_ES
dc.title Mesh adaptivity driven by goal-oriented locally equilibrated superconvergent patch recovery es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s00466-013-0942-8
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/289361/EU/Integrating Numerical Simulation and Geometric Design Technology/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//DPI2010-20542/ES/DESARROLLO DE HERRAMIENTA 3D COMPUTACIONALMENTE EFICAZ Y DE ALTA PRECISION PARA ANALISIS Y DISEÑO ESTRUCTURAL BASADA EN MALLADOS CARTESIANOS DE EF INDEPENDIENTES DE GEOMETRIA/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/279578/EU/Towards real time multiscale simulation of cutting in non-linear materials with applications to surgical simulation and computer guided surgery/
dc.relation.projectID info:eu-repo/grantAgreement/UKRI//EP%2FG042705%2F1/GB/Increased Reliability for Industrially Relevant Automatic Crack Growth Simulation with the eXtended Finite Element Method/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//AP2008-01086/ES/AP2008-01086/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/RCUK/EPSRC/EP/G042705/1/GB/
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEO%2F2012%2F023/ES/MODELADO NUMERICO AVANZADO EN INGENIERIA MECANICA/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Centro de Investigación en Tecnología de Vehículos - Centre d'Investigació en Tecnologia de Vehicles es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Mecánica y de Materiales - Departament d'Enginyeria Mecànica i de Materials es_ES
dc.description.bibliographicCitation González Estrada, OA.; Nadal Soriano, E.; Ródenas, J.; Kerfriden, P.; Bordas, S.; Fuenmayor Fernández, FJ. (2014). Mesh adaptivity driven by goal-oriented locally equilibrated superconvergent patch recovery. Computational Mechanics. 53(5):957-976. https://doi.org/10.1007/s00466-013-0942-8 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1007/s00466-013-0942-8 es_ES
dc.description.upvformatpinicio 957 es_ES
dc.description.upvformatpfin 976 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 53 es_ES
dc.description.issue 5 es_ES
dc.relation.senia 256062
dc.identifier.eissn 1432-0924
dc.contributor.funder European Commission
dc.contributor.funder UK Research and Innovation es_ES
dc.contributor.funder Engineering and Physical Sciences Research Council, Reino Unido
dc.contributor.funder European Research Council
dc.contributor.funder Universitat Politècnica de València
dc.contributor.funder Generalitat Valenciana
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
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