Elasto-plastic material parameter identification by inverse methods: Calculation of the sensitivity matrix

By S. Cooreman, C. Bouffioux, David Lecompte, H. Sol, D. Debruyne, J. Vantomme. 2007

131 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computer Vision and Pattern Recognition, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/1cc0e5ca2fcc0d80841e07236e90289133c8e72c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. François Hild
2. Stéphane Roux
3. Hugo Leclerc
4. F. Mathieu
5. David Lecompte
6. J. Vantomme
7. H. Sol
8. J. Réthoré

In Computer Vision and Pattern Recognition

1. François Hild
2. Stéphane Roux
3. Hugo Leclerc
4. F. Mathieu
5. D. Debruyne
6. S. Cooreman
7. Bing Pan
8. David Lecompte

In Mechanical Engineering

1. Stéphane Roux
2. François Hild
3. Hugo Leclerc
4. Bing Pan
5. J. Réthoré
6. Michel Grédiac
7. Fabrice Pierron

Citations in the corpus

• Estimation of Elastoplastic Parameters via Weighted FEMU and Integrated-DIC (2015, methodology): “The computation of the sensitivity elds ∂uc/∂{p} can be performed analytically [19, 36] or numerically by computing the elds for small variations of each parameter of the considered set, as is the case herein by resorting to the commercial FE code Abaqus.”
• Identification of plastic constitutive parameters at large deformations from three dimensional displacement fields (2011, unknown): “The comparison can be made either on the force measured during the test [27,28] or including also the displacement measured at the surface of the specimen, for instance using full-field measurements [22,26].”
• Identification of Mechanical Material Behavior Through Inverse Modeling and DIC (2008, methodology): “More information on the above described analytical approach can be found in Cooreman et al. [ 24 ].”