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Learning a hyperelastic constitutive model from 3D experimental data.

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Title: Learning a hyperelastic constitutive model from 3D experimental data.
Authors: Bourdyot, M.1, mathys.bourdyot@ens-paris-saclay.fr, Compans, M.1, marius.compans@ens-paris-saclay.fr, Langlois, R.2, raphael.langlois@ens-paris-saclay.fr, Smaniotto, B.1,2, benjamin.smaniotto@ens-paris-saclay.fr, Baranger, E.2, emmanuel.baranger@ens-paris-saclay.fr, Jailin, C.1,2, clement.jailin@ens-paris-saclay.fr
Source: Computer Methods in Applied Mechanics & Engineering; Mar2026, Vol. 450, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 190798669
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Learning a hyperelastic constitutive model from 3D experimental data.
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  Data: <searchLink fieldCode="JN" term="%22Computer+Methods+in+Applied+Mechanics+%26+Engineering%22">Computer Methods in Applied Mechanics & Engineering</searchLink>; Mar2026, Vol. 450, pN.PAG-N.PAG, 1p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=190798669
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.cma.2025.118592
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      – Code: eng
        Text: English
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      – TitleFull: Learning a hyperelastic constitutive model from 3D experimental data.
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              M: 03
              Text: Mar2026
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              Y: 2026
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