Augmented Lagrangian Digital Image Correlation and Tracking
Updated 02 Feb 2022
AL-DIC(Augmented Lagrangian DIC) is a fast, parallel-computing hybrid DIC algorithm, which combines advantages of local subset DIC method (fast computation speed, and parallel computing) and finite-element-based global DIC method (guarantee global kinematic compatibility and decrease noise).
-  It’s a fast algorithm using distributed parallel computing.
-  Global kinematic compatibility is added as a global constraint in the form of augmented Lagrangian, and solved using Alternating Direction Method of Multipliers scheme.
-  Both displacement fields and affine deformation gradients are correlated at the same time.
-  No need of much manual experience about choosing displacement smoothing filters.
-  It works well with compressed DIC images and adaptive mesh. See our paper: Yang, J. & Bhattacharya, K. Exp Mech (2019). https://doi.org/10.1007/s11340-018-00459-y;
-  Both accumulative and incremental DIC modes are implemented to deal with image sequences, which is especially quite useful for very large deformations.
-  ALDIC application example -- uniaxial compression experiment: https://github.com/jyang526843/2D_ALDIC_v3/blob/master/Example_aldic_foam_compression_strain_eyy.gif
-  ALDIC is extended with adaptive quadtree mesh to solve complex geometry. Some examples: https://uwmadison.box.com/s/4n5hmf04rzp4la96bt2rcjk4f6o5d5nf
AL-DIC MATLAB code was tested on MATLAB versions later than R2018a. Both single thread and parallel computing features are included in AL-DIC code. Please download and unzip the code to the MATLAB working path. Then, execute the mail file: main_ALDIC.m.
Full size code manual is available at: https://www.researchgate.net/publication/344796296_Augmented_Lagrangian_Digital_Image_Correlation_AL-DIC_Code_Manual
I also attach my EASF webinar to introduce AL-DIC/DVC algorithm and review other DIC/DVC methods: (Youtube) https://www.youtube.com/watch?v=-t61WrVagZ4 (Bilibili) https://www.bilibili.com/video/BV1ff4y1B71L/
-  For full details, and to use this code, please cite our paper: Yang, J. and Bhattacharya, K. Augmented Lagrangian Digital Image Correlation. Exp.Mech. 59: 187, 2018. https://doi.org/10.1007/s11340-018-00457-0. Full text can be requested at: www.researchgate.net/publication/329456141_Augmented_Lagrangian_Digital_Image_Correlation
-  Yang, J. (2019, March 6). 2D_ALDIC (Version 3.3). CaltechDATA. https://data.caltech.edu/records/1443
-  Yang, J. and Bhattacharya, K. Combining Image Compression with Digital Image Correlation. Exp.Mech. 59: 629-642, 2019. https://doi.org/10.1007/s11340-018-00459-y. Full text can be requested at: https://www.researchgate.net/publication/330489954_Combining_Image_Compression_with_Digital_Image_Correlation
-  Finite-element-based Global DIC code is also available at: https://www.mathworks.com/matlabcentral/fileexchange/82873-2d-finite-element-global-digital-image-correlation-fe-dic
-  Besides 2D-DIC, our new code "ALDVC" (augmented Lagrangian Digital Volume Correlation) to track deformations in volumetric images is also available: https://www.mathworks.com/matlabcentral/fileexchange/77019-augmented-lagrangian-digital-volume-correlation-aldvc
Jin Yang (Caltech solid mechanics, PhD '19): firstname.lastname@example.org -or- email@example.com I appreciate your comments and ratings to help me further improve this code. If you have other questions, feel free to email me.
Yang, J. and Bhattacharya, K. Augmented Lagrangian Digital Image Correlation. Exp.Mech. 59: 187, 2018. https://doi.org/10.1007/s11340-018-00457-0.
Yang, Jin. Augmented Lagrangian Digital Image Correlation (2D_ALDIC). CaltechDATA, 2020, doi:10.22002/D1.1443.
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