Classic and inverse compositional Gauss‐Newton in global DIC

Summary Today, effective implementations of digital image correlation (DIC) are based on iterative algorithms with constant linear operators. A relevant idea of the classic finite element (or, more generally, global) DIC solver consists in replacing the gradient of the deformed state image with that...

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Veröffentlicht in:International journal for numerical methods in engineering Jg. 119; H. 6; S. 453 - 468
Hauptverfasser: Passieux, Jean‐Charles, Bouclier, Robin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Bognor Regis Wiley Subscription Services, Inc 10.08.2019
Wiley
Schlagworte:
Approximation
Deformation mechanisms
Digital imaging
Engineering Sciences
Finite element method
forward compositional Gauss‐Newton
global DIC
inverse compositional Gauss‐Newton
Iterative algorithms
Iterative methods
Linear operators
Mathematical analysis
Mechanics
Optimization
Structural mechanics
inverse compositional Gauss-Newton
forward compositional Gauss-Newton
global DIC
ISSN:0029-5981, 1097-0207
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Zusammenfassung:Summary Today, effective implementations of digital image correlation (DIC) are based on iterative algorithms with constant linear operators. A relevant idea of the classic finite element (or, more generally, global) DIC solver consists in replacing the gradient of the deformed state image with that of the reference image, so as to obtain a constant operator. Different arguments (small strains, small deformations, equality of the two gradients close to the solution, etc) have been given in the literature to justify this approximation, but none of them are fully accurate. Indeed, the convergence of the optimization algorithm has to be investigated from its ability to produce descent directions. Through such a study, this paper attempts to explain why this approximation works and what is its domain of validity. Then, an inverse compositional Gauss‐Newton implementation of finite element DIC is proposed as a cost‐effective and mathematically sound alternative to this approximation.
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ISSN:0029-5981
1097-0207
DOI:10.1002/nme.6057