Complete Mechanical Regularization Applied to Digital Image and Volume Correlation

Arturo Mendoza 1 Jan Neggers 1 François Hild 1 Stéphane Roux 1
1 LMT - Laboratoire de Mécanique et Technologie
Abstract : This paper presents a new regularization scheme for Digital Image Correlation (DIC) and Digital Volume Correlation (DVC) techniques based on the equilibrium gap method with reference to a linear elastic behavior. This scheme constitutes a unique framework for performing the so-called mechanical regu-larization for any problem dimension. "Complete regularization" refers to the fact that a specific treatment of boundaries (surfaces) is introduced here on the same footing as the bulk, independently of the complexity of their shape. The proposed treatment distinguishes the roles that different boundaries (Neumann or Dirichlet) play in mechanical tests. Numerical cases on synthetic data and a real experimental test validate the robustness and accuracy of the method. The analyzed experiment shows that only the use of (complete) regularization ensures convergence. Even in the cases where such regularization is not employed but convergence is achieved, it is at much higher cost. These results reveal the benefit of regularization on the convergence rate of DVC.
Keywords : equilibrium gap mechanical regularization digital image correlation digital volume correlation
Document type :
Journal articles
Complete list of metadatas

Cited literature [44 references]  Display  Hide  Download
https://hal.archives-ouvertes.fr/hal-02148780
Contributor : François Hild <>
Submitted on : Wednesday, June 5, 2019 - 6:18:07 PM
Last modification on : Tuesday, July 23, 2019 - 2:08:01 PM

File

CMAME2019-ccsd.pdf
Files produced by the author(s)

Identifiers

Collections

ENS-CACHAN | LMT | SU-SCIENCES | UNIV-PARIS-SACLAY | SORBONNE-UNIVERSITE

Citation

Arturo Mendoza, Jan Neggers, François Hild, Stéphane Roux. Complete Mechanical Regularization Applied to Digital Image and Volume Correlation. Computer Methods in Applied Mechanics and Engineering, Elsevier, 2019, 355, pp.27-43. ⟨10.1016/j.cma.2019.06.005 0045-7825⟩. ⟨hal-02148780⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

32

Files downloads

96

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD