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Identification of material parameters of the Gurson–Tvergaard–Needleman model by combined experimental and numerical techniques

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Title: Identification of material parameters of the Gurson–Tvergaard–Needleman model by combined experimental and numerical techniques
Authors: Springmann, M. marcel.springmann@imfd.tu-freiberg.de, Kuna, M.1
Source: Computational Materials Science. Jun2005, Vol. 33 Issue 4, p501-509. 9p.
Subjects: Construction materials, Differential equations, Structural steel, Iron & steel building
Abstract: Abstract: To identify material parameters from suitable experiments it is prevalent to use global informations like force–displacement or force–necking curves. The quality of accordance between measured and calculated forces at given displacements can be expressed by a least-squares functional. In this contribution a non-linear optimization method will be presented, which minimizes the least-squares functional by use of a gradient based method. The gradient of this functional is calculated in a semi-analytical sensitivity analysis. To determine the derivatives of the force with respect to the material parameters, the local sensitivities on an intersection will be added together. On this intersection, the total nodal force and the external force have to be equal and the normal displacements have to be independent on the material parameters. The parameter identification is embedded in the finite element code SPC-PMHP for solving non-linear boundary and initial value problems on parallel computers. The Gurson–Tvergaard–Needleman model is used to describe the plastic deformation and damage behaviour of the ductile structural steel StE 690. The developed algorithm is applied to tensile tests with notched cylindrical bars. [Copyright &y& Elsevier]
Copyright of Computational Materials Science is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 17663265
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PubTypeId: academicJournal
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  Data: Identification of material parameters of the Gurson–Tvergaard–Needleman model by combined experimental and numerical techniques
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  Data: <searchLink fieldCode="AR" term="%22Springmann%2C+M%2E%22">Springmann, M.</searchLink><i> marcel.springmann@imfd.tu-freiberg.de</i><br /><searchLink fieldCode="AR" term="%22Kuna%2C+M%2E%22">Kuna, M.</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Computational+Materials+Science%22">Computational Materials Science</searchLink>. Jun2005, Vol. 33 Issue 4, p501-509. 9p.
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  Data: <searchLink fieldCode="DE" term="%22Construction+materials%22">Construction materials</searchLink><br /><searchLink fieldCode="DE" term="%22Differential+equations%22">Differential equations</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+steel%22">Structural steel</searchLink><br /><searchLink fieldCode="DE" term="%22Iron+%26+steel+building%22">Iron & steel building</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Abstract: To identify material parameters from suitable experiments it is prevalent to use global informations like force–displacement or force–necking curves. The quality of accordance between measured and calculated forces at given displacements can be expressed by a least-squares functional. In this contribution a non-linear optimization method will be presented, which minimizes the least-squares functional by use of a gradient based method. The gradient of this functional is calculated in a semi-analytical sensitivity analysis. To determine the derivatives of the force with respect to the material parameters, the local sensitivities on an intersection will be added together. On this intersection, the total nodal force and the external force have to be equal and the normal displacements have to be independent on the material parameters. The parameter identification is embedded in the finite element code SPC-PMHP for solving non-linear boundary and initial value problems on parallel computers. The Gurson–Tvergaard–Needleman model is used to describe the plastic deformation and damage behaviour of the ductile structural steel StE 690. The developed algorithm is applied to tensile tests with notched cylindrical bars. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Computational Materials Science is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.commatsci.2005.02.002
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      – Code: eng
        Text: English
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        PageCount: 9
        StartPage: 501
    Subjects:
      – SubjectFull: Construction materials
        Type: general
      – SubjectFull: Differential equations
        Type: general
      – SubjectFull: Structural steel
        Type: general
      – SubjectFull: Iron & steel building
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      – TitleFull: Identification of material parameters of the Gurson–Tvergaard–Needleman model by combined experimental and numerical techniques
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              Text: Jun2005
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              Y: 2005
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              Value: 33
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