2007
DOI: 10.1016/j.cma.2007.03.010
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Generalized parameter identification for finite viscoelasticity

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Cited by 33 publications
(24 citation statements)
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“…Moreover, note that the incorporation of a plane or uni-axial stress state-for example, by means of an additional iterative scheme-in combination with an anisotropic and isochoric response may over-constrain the identification procedure. Nevertheless, in general, material parameters should be identified based on inhomogeneous deformations and by means of different types of experiments (compare, Mahnken and Stein, 1996b;Kleuter et al, 2007). Apart from related experimental data not yet being available to the authors, such finite-element-based identification approaches are out of the scope of this contribution.…”
Section: Parameter Identificationmentioning
confidence: 99%
“…Moreover, note that the incorporation of a plane or uni-axial stress state-for example, by means of an additional iterative scheme-in combination with an anisotropic and isochoric response may over-constrain the identification procedure. Nevertheless, in general, material parameters should be identified based on inhomogeneous deformations and by means of different types of experiments (compare, Mahnken and Stein, 1996b;Kleuter et al, 2007). Apart from related experimental data not yet being available to the authors, such finite-element-based identification approaches are out of the scope of this contribution.…”
Section: Parameter Identificationmentioning
confidence: 99%
“…e.g. [5] for a detailed derivation. From this, the standard argumentation due to Coleman and Gurtin [6] yields the conditional equations for the equilibrium and non-equilibrium stress in Eq.…”
Section: Phenomenological Example: Viscoelastic Neo-hooke Curing Modelmentioning
confidence: 99%
“…In view of the above assumptions on eq and neq , equilibrium stress S eq and tangent operator E eq are updated according to Eqs. (5) and (6), respectively, whereas their non-equilibrium counterparts are determined from neq as in standard viscoelasticity. All further details required for an implementation in finite element codes will be derived in the subsequent Sects.…”
Section: Introduction and Outlinementioning
confidence: 99%
“…For these types of optimization problems, different methods like sensitivity analysis [15] or variation methods, genetic algorithm [16] neural networks [17] and the cascade model [18] have been applied. In this paper, the EVO, IVC and overlap degrees considered as input variables and the SFC is the output.…”
Section: Stage Onementioning
confidence: 99%