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Secondary biaxial data application in a process of a hyperelastic material characterization

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dc.title Secondary biaxial data application in a process of a hyperelastic material characterization en
dc.contributor.author Keerthiwansa, Gustinna Wadu Rohitha
dc.contributor.author Javořík, Jakub
dc.contributor.author Kledrowetz, Jan
dc.relation.ispartof Materials Science Forum
dc.identifier.issn 0255-5476 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2019
utb.relation.volume 952
dc.citation.spage 275
dc.citation.epage 281
dc.type article
dc.language.iso en
dc.publisher Trans Tech Publications Ltd
dc.identifier.doi 10.4028/www.scientific.net/MSF.952.275
dc.relation.uri https://www.scientific.net/MSF.952.275
dc.subject Data fitting en
dc.subject Elastomers en
dc.subject Hyperelasticity en
dc.subject Material constants en
dc.description.abstract In order to find hyperelastic material model constants, data fitting technique is often used. For this task, the data is collected through different laboratory tests, namely, the uniaxial, the biaxial and the pure shear. However, due to the difficulty in getting biaxial data, often only uniaxial data was used for the fitting. Despite frequent use, it was established that this practice creates erroneous results. With a view to improve the data fitting results and at the same time to overcome the difficulty of collecting primary biaxial data, uniaxial data was used to generate a secondary biaxial data set. The data derived through this method was then tested with four common models as to examine the compatibility of the method. Subsequently, real biaxial data was used to compare with the data fitting results obtained through the proposed method. As results indicated combined data fitting for both instances were very much identical with respect to all tested models. Cases where somewhat higher deviation observed between experimental curves and data fitted curves for biaxial data, gave similar results for adjusted data driven data fitting too. However, such deviation could be attributed to mismatch between models with the particular material behaviour rather than the generated data. © 2019 Trans Tech Publications Ltd, Switzerland. en
utb.faculty Faculty of Technology
dc.identifier.uri http://hdl.handle.net/10563/1008762
utb.identifier.obdid 43880507
utb.identifier.scopus 2-s2.0-85066294926
utb.identifier.coden MSFOE
utb.source j-scopus
dc.date.accessioned 2019-08-13T10:17:18Z
dc.date.available 2019-08-13T10:17:18Z
utb.ou Department of Production Engineering
utb.contributor.internalauthor Keerthiwansa, Gustinna Wadu Rohitha
utb.contributor.internalauthor Javořík, Jakub
utb.contributor.internalauthor Kledrowetz, Jan
utb.fulltext.affiliation Rohitha Keerthiwansa 1,a*, Jakub Javorik 2,b, Jan Kledrowetz 3,c Department of Production Engineering, Faculty of Technology, Tomas Bata University in Zlin, nam. T.G. Masaryka 5555, 760 01 Zlin, Czech Republic. a [email protected], b [email protected], c [email protected]
utb.fulltext.dates Submitted: 2018-11-03 Revised: 2018-12-06 Accepted: 2018-12-07 Online: 2019-04-24
utb.fulltext.sponsorship This work and the project is realized with the financial support of the internal grant of TBU in Zlin No. IGA/FT/2018/004 funded from the resources of specific university research.
utb.scopus.affiliation Department of Production Engineering, Faculty of Technology, Tomas Bata University in Zlin, nam. T.G. Masaryka 5555, Zlin, 760 01, Czech Republic
utb.fulltext.projects IGA/FT/2018/004
utb.fulltext.faculty Faculty of Technology
utb.fulltext.faculty Faculty of Technology
utb.fulltext.faculty Faculty of Technology
utb.fulltext.ou Department of Production Engineering
utb.fulltext.ou Department of Production Engineering
utb.fulltext.ou Department of Production Engineering
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