2020
DOI: 10.1111/str.12334
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Inverse identification of constitutive parameters from heat source fields: A local approach applied to hyperelasticity

Abstract: In this paper, a new inverse identification method of constitutive parameters is developed from full kinematic and thermal field measurements. It consists in reconstructing the heat source field from two different approaches by using the heat diffusion equation. The first one requires the temperature field measurement and the value of the thermophysical parameters. The second one is based on the kinematic field measurement and the choice of a thermo‐hyperelastic model that contains the parameters to be identif… Show more

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Cited by 16 publications
(13 citation statements)
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“…Fused Deposition Modelling (FDM) printed rolls of 6 mm in diameter were glued (Loctite 406, Henkel, Düsseldorf, Germany) to the ends of the specimen. Such rolls prevent the specimens from slipping into the jaws, which shape has been designed accordingly [ 26 , 27 ].…”
Section: Methodsmentioning
confidence: 99%
See 3 more Smart Citations
“…Fused Deposition Modelling (FDM) printed rolls of 6 mm in diameter were glued (Loctite 406, Henkel, Düsseldorf, Germany) to the ends of the specimen. Such rolls prevent the specimens from slipping into the jaws, which shape has been designed accordingly [ 26 , 27 ].…”
Section: Methodsmentioning
confidence: 99%
“…As explained in [ 27 ], the components of the deformation gradient tensor are determined at the centre of the square elements, which are composed of four Zones Of Interest (ZOI). Each corner of the square element corresponds to a ZOI centre defined in the undeformed DIC grid.…”
Section: Methodsmentioning
confidence: 99%
See 2 more Smart Citations
“…Giovanni B. Broggiato [ 13 ] used the inverse method to accurately determine the parameters of the damage model. Sylvain Charles [ 14 ] proposed a new method for determining constitutive antithesis parameters based on total kinematics and thermal field measurements. It could be seen that there was a smaller parameter error and higher prediction accuracy in the constitutive model obtained by the inverse optimization algorithm.…”
Section: Introductionmentioning
confidence: 99%