Abstract
For the application of the digital image correlation (DIC) method in the deformation measurement of geomaterials, the conventional approaches can hardly realize optimized results in terms of precision and speed, especially for geotechnical tests with variable scales and going through discontinuities. Considering the deformation characteristics of geomaterials, two algorithmic approaches were proposed to deal with the conundrums in the application of DIC for experimental measurement. Incorporated with DIC and the acoustic emission system, uniaxial compression tests were performed on rock-like materials to investigate the effectiveness of the proposed methods. Based on preliminary trials through the adjustment of conventional DIC parameters, it is hard to reach an accurate result for materials with obserable cracks. The proposed algorithm shows an optimized revision for subsets in regions subject to discontinuity influence whose efficiency is independent of the crack size. Meanwhile, the fast-speed algorithm designed for DIC enables the searching scope auto-adjusted, and the computation time can be reduced to approximately one-tenth of the conventional one. The proposed algorithm was implemented in the self-developed DIC software, implemented program, which is specially designed for geotechnical tests.
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References
Ab Ghani A, Ali M, DharMalingam S, Mahmud J (2016) Digital image correlation (DIC) technique in measuring strain using opensource platform Ncorr. J Adv Res Appl Mech 26(1):10–21
Anuta PE (1970) Spatial registration of multispectral and multitemporal digital imagery using fast Fourier transform techniques. IEEE Trans Geosci Electron 8(4):353–368
Avril S, Pierron F, Sutton MA, Yan J (2008) Identification of elasto-visco-plastic parameters and characterization of Lüders behavior using digital image correlation and the virtual fields method. Mech Mater 40(9):729–742
Benabou L, Nguyen-Van TA, Tao QB, Le VN, Ould Ouali M, Nguyen-Xuan H (2020) Methodology for DIC-based evaluation of the fracture behaviour of solder materials under monotonic and creep loadings. Eng Fract Mech 239:107285
Blaber J, Adair B, Antoniou A (2015) Ncorr: open-source 2D digital image correlation matlab software. Exp Mech 55(6):1105–1122
Chen Y, Yang J, Zhang C, Wang F, Ji C (2020) Effects of hole reaming on fatigue performance of thin sheets for fuselage: DIC and FEM analysis. Int J Fatigue 141:105893
Gates M, Lambros J, Heath MT (2011) Towards high performance digital volume correlation. Exp Mech 51(4):491–507
Grediac M, Pierron F, Avril S, Toussaint E (2006) The virtual fields method for extracting constitutive parameters from full-field measurements: a review. Strain 42(4):233–253
Harilal R (2014) Adaptation of open source 2D DIC software Ncorr for solid mechanics applications. In: 9th international symposium on advanced science and technology in experimental mechanics
Hassan GM (2021) Deformation measurement in the presence of discontinuities with digital image correlation: a review. Opt Lasers Eng 137:106394
He J, Lei D, Xu W (2020) In-situ measurement of nominal compressive elastic modulus of interfacial transition zone in concrete by SEM-DIC coupled method. Cement Concr Compos 114:103779
Hild F, Roux S (2006) Measuring stress intensity factors with a camera: Integrated digital image correlation (I-DIC). Comptes Rendus Mécanique 334(1):8–12
Hild F, Roux S (2006) Digital image correlation: from displacement measurement to identification of elastic properties–a review. Strain 42(2):69–80
Huang F, Wu C, Jang BA, Hong Y, Guo N, Guo W (2020) Instability mechanism of shallow tunnel in soft rock subjected to surcharge loads. Tunn Undergr Space Technol 99:103350
Huang F, Wu C, Ni P, Wan G, Zheng A, Jang BA, Karekal S (2020) Experimental analysis of progressive failure behavior of rock tunnel with a fault zone using non-contact DIC technique. Int J Rock Mech Min Sci 132:104355
Keating TJ, Wolf P, Scarpace F (1975) An improved method of digital image correlation. Photogramm Eng Remote Sens 41(8):993–1002
Koko A, Earp P, Wigger T, Tong J, Marrow TJ (2020) J-integral analysis: An EDXD and DIC comparative study for a fatigue crack. Int J Fatigue 134:105474
Leclerc H, Périé JN, Roux S, Hild F (2009) Integrated digital image correlation for the identification of mechanical properties. In: international conference on computer vision/computer graphics collaboration techniques and applications
Li BQ, Einstein HH (2017) Comparison of visual and acoustic emission observations in a four point bending experiment on barre granite. Rock Mech Rock Eng 50(9):2277–2296
Li Y, Jing H, Zeng Q (2006) Development and application of digital photogrammetry software package for geotechnical engineering. Chin J Rock Mech Eng 25(2):3859–3866
Li Y, Tang X, Yang S, Chen J (2019) Evolution of the broken rock zone in the mixed ground tunnel based on the DSCM. Tunn Undergr Space Technol 84:248–258
Li Y, Zhang Q, Lin Z, Wang X (2016) Spatiotemporal evolution rule of rocks fracture surrounding gob-side roadway with model experiments. Int J Min Sci Technol 26(5):895–902
McNeill S, Peters W, Sutton M (1987) Estimation of stress intensity factor by digital image correlation. Eng Fract Mech 28(1):101–112
Nguyen TL, Hall SA, Vacher P, Viggiani G (2011) Fracture mechanisms in soft rock: identification and quantification of evolving displacement discontinuities by extended digital image correlation. Tectonophysics 503(1–2):117–128
Réthoré J, Gravouil A, Morestin F, Combescure A (2005) Estimation of mixed-mode stress intensity factors using digital image correlation and an interaction integral. Int J Fract 132(1):65–79
Stirling RA, Simpson DJ, Davie CT (2013) The application of digital image correlation to Brazilian testing of sandstone. Int J Rock Mech Min Sci 60(6):1–11
Sun F, Blackman BRK (2020) A DIC method to determine the Mode I energy release rate G, the J-integral and the traction-separation law simultaneously for adhesive joints. Eng Fract Mech 234:107097
Sutton MA, Li N, Joy D, Reynolds AP, Li X (2007) Scanning electron microscopy for quantitative small and large deformation measurements part I: SEM imaging at magnifications from 200 to 10,000. Exp Mech 47(6):775–787
Triconnet K, Derrien K, Hild F, Baptiste D (2009) Parameter choice for optimized digital image correlation. Opt Lasers Eng 47(6):728–737
Wang P, Guo X, Sang Y, Shao L, Yin Z, Wang Y (2020) Measurement of local and volumetric deformation in geotechnical triaxial testing using 3D-digital image correlation and a subpixel edge detection algorithm. Acta Geotech 15(10):2891–2904
Wang X, Jin Z, Liu J, Chen F, Feng P, Tang J (2021) Research on internal monitoring of reinforced concrete under accelerated corrosion, using XCT and DIC technology. Constr Build Mater 266:121018
Xing HZ, Zhang QB, Braithwaite CH, Pan B, Zhao J (2017) High-speed photography and digital optical measurement techniques for geomaterials: fundamentals and applications. Rock Mech Rock Eng 50(6):1611–1659
Xing T, Zhu H, Wang L, Liu G, Ma Q, Wang X, Ma S (2020) High accuracy measurement of heterogeneous deformation field using spatial-temporal subset digital image correlation. Measurement 156:107605
Yang G, Cai Z, Zhang X, Fu D (2015) An experimental investigation on the damage of granite under uniaxial tension by using a digital image correlation method. Opt Lasers Eng 73:46–52
Yang SQ, Chen M, Fang G, Wang YC, Meng B, Li YH, Jing HW (2018) Physical experiment and numerical modelling of tunnel excavation in slanted upper-soft and lower-hard strata. Tunn Undergr Space Technol 82:248–264
Yang J, Hazlett L, Landauer AK, Franck C (2020) Augmented lagrangian digital volume correlation (ALDVC). Exp Mech 60(9):1205–1223
Yue ZQ, Chen S, Tham LG (2003) Finite element modeling of geomaterials using digital image processing. Comput Geotech 30(5):375–397
Zhang QB, He L, Zhu WS (2016) Displacement measurement techniques and numerical verification in 3D geomechanical model tests of an underground cavern group. Tunn Undergr Space Technol 56:54–64
Zhang H, Huang G, Song H, Kang Y (2012) Experimental investigation of deformation and failure mechanisms in rock under indentation by digital image correlation. Eng Fract Mech 96:667–675
Zhang ZX, Xu Y, Kulatilake PHSW, Huang X (2012) Physical model test and numerical analysis on the behavior of stratified rock masses during underground excavation. Int J Rock Mech Min Sci 49:134–147
Zhao B, Lei D, Fu J, Yang L, Xu W (2019) Experimental study on micro-damage identification in reinforced concrete beam with wavelet packet and DIC method. Constr Build Mater 210:338–346
Zhou K, Lei D, He J, Zhang P, Bai P, Zhu F (2021) Single micro-damage identification and evaluation in concrete using digital image correlation technology and wavelet analysis. Constr Build Mater 267:120951
Acknowledgements
The work was funded by the Science and Technology Plan Project of Xuzhou, China, with Grant Number KC21310, the National Basic Research Program of China (973 Program) with Grant Number 2014CB046905, and the National Natural Science Foundation of China with Grant Number 42077235.
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Appendices
Appendix 1
1.1 Comparison of DIC results computed from the implemented program and open-source programs in the MATLAB platform
In this section, we present a case comparing the displacement results computed from the implemented program and the open-source program in the MATLAB platform, Ncorr [1, 5]. DIC parameters input into two programs stays the same, with subset radius and subset interval set as 15 pixels and 5 pixels, respectively. Color maps corresponding to displacement data in horizontal and vertical directions are depicted in Fig.
16 (deformed material surface can be seen in Fig.
17b). Firstly, the displacement data are almost the same in the two programs in terms of the deformation pattern and magnitudes. Moreover, it can be observed that the displacement data near the crack region in both programs are subject to the discontinuity influence shown as several irregularly displaced points distributed near the crack surface. The reason corresponding to such computational error is given in the former sections. Here, we conclude that the implemented program in conventional modes can reach reliable results which are the same as the ones performed on other open-source DIC programs, and secondly, the computational error induced by cracks is widely encountered in DIC analysis.
Appendix 2
2.1 Supplemented cases illustrating the function of the OPFPM to revise the computation error in regions subject to cracking influence
In this appendix, two supplemented cases for crack revision are presented to show the effectiveness and reliability of the OPFPM. DIC parameters in these two tests stay the same as that in the former sections. As shown in Fig. 17, for these two randomly selected material surfaces, the computation of DIC in conventional mode meets discontinuity influence near the crack surface with the number of error points associated with the crack width. Since additional image information from the crack region, the DIC tracing is affected a lot in terms of the computation of the correlation coefficient which induces incorrect identification of target subsets. While the OPFPM is activated in the implemented program, the DIC result near the cracking region gets well revised, and the remaining area stays the same as the conventional cases, as shown from the displacement vectors in Fig. 17a2 and b2. Here, the Mode-I crack is denoted by volumetric strain invariants for its tensile opening characteristics. Figure 17a3 and b3 describe the color mapping corresponding to volumetric strain invariants with strain data in the OPFPM mode. The mapping results show that the localized region identified in DIC agrees well with the real location of cracks. During a deformed process with cracks generated on the material surface, the activation of the OPFPM has been proved to significantly optimize the DIC computation for revising the error induced by discontinuities.
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Li, Y., Tang, X. & Zhu, H. Optimization of the digital image correlation method for deformation measurement of geomaterials. Acta Geotech. 17, 5721–5737 (2022). https://doi.org/10.1007/s11440-022-01646-x
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DOI: https://doi.org/10.1007/s11440-022-01646-x