A dual domain decomposition method for finite element digital image correlation

Abstract : The computational burden associated to finite element based digital image correlation methods is mostly due to the inversion of finite element systems and to image interpolations. A non-overlapping dual domain decomposition method is here proposed to rationalize the computational cost of high resolution finite element digital image correlation measurements when dealing with large images. It consists in splitting the global mesh into submeshes and the reference and deformed states images into subset images. Classic finite element digital image correlation formulations are first written in each subdomain independently. The displacement continuity at the interfaces is enforced by introducing a set of Lagrange multipliers. The problem is then condensed on the interface and solved by a conjuguate gradient algorithm. Three different preconditionners are proposed to accelerate its convergence. The proposed domain decomposition method is here exemplified with real high resolution images. It is shown to combine the metrological performances of finite element based digital image correlation and the parallelisation ability of subset based methods.
Complete list of metadatas

Cited literature [45 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01094665
Contributor : Jean-Charles Passieux <>
Submitted on : Thursday, March 19, 2015 - 2:59:34 PM
Last modification on : Friday, October 11, 2019 - 8:22:58 PM
Long-term archiving on : Saturday, April 15, 2017 - 8:10:14 AM

File

passieux_ijnme15.pdf
Files produced by the author(s)

Identifiers

Citation

Jean-Charles Passieux, Jean-Noël Périé, Michel Salaün. A dual domain decomposition method for finite element digital image correlation. International Journal for Numerical Methods in Engineering, Wiley, 2015, 102 (10), pp.1670-1682. ⟨10.1002/nme.4868⟩. ⟨hal-01094665⟩

Share

Metrics

Record views

230

Files downloads

283