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Published in: Experimental Mechanics 9/2020

14-08-2020 | Research paper

Augmented Lagrangian Digital Volume Correlation (ALDVC)

Authors: J. Yang, L. Hazlett, A.K. Landauer, C. Franck

Published in: Experimental Mechanics | Issue 9/2020

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Abstract

Digital volume correlation (DVC), the volumetric extension of the popular digital image correlation (DIC) technique, is a powerful experimental tool for measuring 3D volumetric full-field displacements and strains. Most current DVC algorithms can be categorized into either local or finite-element-based global methods. As with most experimental approaches, there are drawbacks with each of these methods. In the local method the subvolume deformations are estimated independently and the computed displacement field may not necessarily be kinematically compatible. Thus, the deformation gradients can be noisy, especially when using small volumetric subsets. Although the global method often enforces kinematic compatibility, it generally incurs substantially greater computational costs than its local counterpart, which is especially significant for large volumetric data sets. To address these shortcomings, we present a new hybrid DVC algorithm, called augmented Lagrangian digital volume correlation (ALDVC), which combines the advantages of both the local (fast computation time) and global (compatible displacement field) methods. This new algorithm builds on our recent work on the augmented Lagrangian digital image correlation (2D-ALDIC) technique and solves the general motion optimization problem by using the alternating direction method of multipliers (ADMM). We demonstrate that our ALDVC algorithm has high accuracy and precision while maintaining low computational cost, and is a significant improvement compared to current local and global DVC methods. ALDVC is a computationally efficient algorithm to measure 3D volumetric displacements and strains. An open-source Matlab implementation is freely available.

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Appendix
Available only for authorised users
Footnotes
1
Both tri-cubic and tri-cubic spline interpolations are commonly used and interpolation bias errors are O(10− 3) voxels, cf. [27].
 
2
Practically, ALDVC ADMM can be stopped after \(3 \sim 5\) iterations.
 
3
To probe baseline local FFT performance, rather than that of a specific algorithm, we reduce the algorithm of [8] to a relatively generic “local FFT” method by removing the in-built IDM subset refinement and filtering steps.
 
4
This includes the iterative deformation method (IDM), but at a strictly enforced subset size, which will produce suboptimal results when compared to the self-refining FIDVC algorithm
 
5
Besides using a constant regularization coefficient, there are also methods to optimize a spatially variable, dependent regularization coefficient α, to achieve better performance [17]. However, these methods usually are extremely expensive.
 
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Metadata
Title
Augmented Lagrangian Digital Volume Correlation (ALDVC)
Authors
J. Yang
L. Hazlett
A.K. Landauer
C. Franck
Publication date
14-08-2020
Publisher
Springer US
Published in
Experimental Mechanics / Issue 9/2020
Print ISSN: 0014-4851
Electronic ISSN: 1741-2765
DOI
https://doi.org/10.1007/s11340-020-00607-3

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