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Augmented Lagrangian Digital Image Correlation and Tracking

버전 4.2.2 (84.8 MB) 작성자: Jin Yang
2D-AL-DIC(Augmented Lagrangian DIC) is a fast, parallel-computing DIC algorithm which also considers global kinematic compatibility.

다운로드 수: 2.8K

업데이트 날짜: 2022/2/2

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Augmented Lagrangian Digital Image Correlation (2D_ALDIC)

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).

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Advantages of AL-DIC algorithm

  • [1] It’s a fast algorithm using distributed parallel computing.
  • [2] Global kinematic compatibility is added as a global constraint in the form of augmented Lagrangian, and solved using Alternating Direction Method of Multipliers scheme.
  • [3] Both displacement fields and affine deformation gradients are correlated at the same time.
  • [4] No need of much manual experience about choosing displacement smoothing filters.
  • [5] It works well with compressed DIC images and adaptive mesh. See our paper: Yang, J. & Bhattacharya, K. Exp Mech (2019).;
  • [6] Both accumulative and incremental DIC modes are implemented to deal with image sequences, which is especially quite useful for very large deformations.
  • [7] ALDIC application example -- uniaxial compression experiment:
  • [8] ALDIC is extended with adaptive quadtree mesh to solve complex geometry. Some examples:

Prerequisites & Installation

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.

Code manual

Full size code manual is available at:

Code demo videos

ALDIC Matlab code demo: (Youtube) (Bilibili)

I also attach my EASF webinar to introduce AL-DIC/DVC algorithm and review other DIC/DVC methods: (Youtube) (Bilibili)


Contact and support

Jin Yang (Caltech solid mechanics, PhD '19): -or- I appreciate your comments and ratings to help me further improve this code. If you have other questions, feel free to email me.

인용 양식

Yang, J. and Bhattacharya, K. Augmented Lagrangian Digital Image Correlation. Exp.Mech. 59: 187, 2018.

Yang, Jin. Augmented Lagrangian Digital Image Correlation (2D_ALDIC). CaltechDATA, 2020, doi:10.22002/D1.1443.

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개발 환경: R2018b
R2017b에서 R2020a까지의 릴리스와 호환
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