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dc.contributor.authorKrál, Petrcs
dc.contributor.authorHokeš, Filipcs
dc.contributor.authorHušek, Martincs
dc.contributor.authorKala, Jiřícs
dc.contributor.authorHradil, Petrcs
dc.date.accessioned2018-12-07T11:55:28Z
dc.date.available2018-12-07T11:55:28Z
dc.date.issued2017-06-12cs
dc.identifier.citationIOP Conference Series: Materials Science and Engineering. 2017, vol. 245, issue 1, p. 1-10.en
dc.identifier.issn1757-899Xcs
dc.identifier.other146034cs
dc.identifier.urihttp://hdl.handle.net/11012/137175
dc.description.abstractIssues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations, gradient based and nature inspired optimization algorithms and experimental data, the latter of which take the form of a load-extension curve obtained from the evaluation of uniaxial tensile test results. The aim of this research was to obtain material model parameters corresponding to the quasi-static tensile loading which may be further used for the research involving dynamic and high-speed tensile loading. Based on the obtained results it can be concluded that the set goal has been reached.en
dc.formattextcs
dc.format.extent1-10cs
dc.format.mimetypeapplication/pdfcs
dc.language.isoencs
dc.publisherIOP Publishingcs
dc.relation.ispartofIOP Conference Series: Materials Science and Engineeringcs
dc.relation.urihttp://iopscience.iop.org/article/10.1088/1757-899X/245/3/032078cs
dc.rightsCreative Commons Attribution 3.0 Unportedcs
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/cs
dc.subjectUnconfined uniaxial tensile testen
dc.subjectoptimization-based parameter identificationen
dc.subjectconcrete modellingen
dc.subjectmaterial parameteren
dc.subjectcomputer simulationen
dc.titleOptimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Modelen
thesis.grantorVysoké učení technické v Brně. Fakulta stavební. Ústav stavební mechanikycs
sync.item.dbidVAV-146034en
sync.item.dbtypeVAVen
sync.item.insts2019.08.08 16:54:54en
sync.item.modts2019.08.08 16:17:20en
dc.coverage.issue1cs
dc.coverage.volume245cs
dc.identifier.doi10.1088/1757-899X/245/3/032078cs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1757-899X/cs
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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Creative Commons Attribution 3.0 Unported
Except where otherwise noted, this item's license is described as Creative Commons Attribution 3.0 Unported