Simultaneous Full-Field Multi-Experiment Identification

Abstract : Identification of constitutive parameters relies mainly on their sensitivity to the measurands. In particular, the specific static and kinematic responses controlled by each parameter of interest has to be captured by full-field measurements. The development of modern constitutive models has led to many new and interesting sample geometries and loading histories, aiming at maximizing the sensitivity to their delicate material parameters, especially through their kinematics of interest. However, it is often impossible to design an experiment that activates all material parameters of interest, and thus multiple experiments are needed. This paper discusses a methodology for combining the data from such multi-experiments into a single identification process to calibrate a complete set of parameters at once. Many different ways of merging experimental data exist, leading to unbiased identifications of the parameters of interest. However, only one optimal procedure leads to minimal uncertainty, taking into account the noise of each acquisition source. The proposed identification method is a natural extension of inverse methods such as Finite Element Method Updating (FEMU) with appropriate weights or Integrated Digital Image Correlation (I-DIC). This procedure is illustrated by the identification of the planar parameters of the so-called Hill48 anisotropic yield surface together with an exponential isotropic hardening law of AA2219.
Complete list of metadatas

Cited literature [37 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02055605
Contributor : François Hild <>
Submitted on : Monday, March 4, 2019 - 10:22:31 AM
Last modification on : Tuesday, May 14, 2019 - 10:57:22 AM
Long-term archiving on : Wednesday, June 5, 2019 - 1:08:21 PM

File

MOM2019-ccsd.pdf
Files produced by the author(s)

Identifiers

Citation

J. Neggers, F. Mathieu, François Hild, Stéphane Roux. Simultaneous Full-Field Multi-Experiment Identification. Mechanics of Materials, Elsevier, 2019, 133, pp.71-84. ⟨10.1016/j.mechmat.2019.03.001⟩. ⟨hal-02055605⟩

Share

Metrics

Record views

26

Files downloads

56