Integrated Digital Image Correlation for the Identification of Mechanical Properties
Pages 161 - 171
Abstract
Digital Image Correlation (DIC) is a powerful technique to provide full-field displacement measurements for mechanical tests of materials and structures. The displacement fields may be further processed as an entry for identification procedures giving access to parameters of constitutive laws. A new implementation of a Finite Element based Integrated Digital Image Correlation (I-DIC) method is presented, where the two stages (image correlation and mechanical identification) are coupled. This coupling allows one to minimize information losses, even in case of low signal-to-noise ratios. A case study for elastic properties of a composite material illustrates the approach, and highlights the accuracy of the results. Implementations on GPUs (using CUDA) leads to high speed performance while preserving the versatility of the methodology.
References
[1]
Rastogi, P.K. (ed.): Photomechanics, p. 77. Springer, Berlin (2000)
[2]
Sutton, M.A., Wolters, W.J., Peters, W.H., Ranson, W.F., McNeill, S.R.: Determination of Displacements Using an Improved Digital Correlation Method. Im. Vis. Comp. 1(3), 133-139 (1983)
[3]
Sutton, M.A., Cheng, M., Peters, W.H., Chao, Y.J., McNeill, S.R.: Application of an optimized digital correlation method to planar deformation analysis. Im. Vis. Comp. 4(3), 143-150 (1986)
[4]
Sutton, M.A., McNeill, S.R., Helm, J.D., Chao, Y.J.: Advances in Two-Dimensional and Three-Dimensional Computer Vision. In: Rastogi, P.K. (ed.) Photomechanics, pp. 323-372. Springer, Berlin (2000)
[5]
Elnasri, I., Pattofatto, S., Zhao, H., Tsitsiris, H., Hild, F., Girard, Y.: Shock enhancement of cellular structures under impact loading: Part I Experiments. J. Mech. Phys. Solids 55, 2652-2671 (2007)
[6]
Verhulp, E., van Rietbergen, B., Huiskes, R.: A three-dimensional digital image correlation technique for strain measurements in microstructures. J. Biomech. 37(9), 1313-1320 (2004)
[7]
Liu, L., Morgan, E.: Accuracy and precision of digital volume correlation in quantifying displacements and strains in trabecular bone. J. Biomech. 40, 3516-3520 (2007)
[8]
Lenoir, N., Bornert, M., Desrues, J., Bésuelle, P., Viggiani, G.: Volumetric digital image correlation applied to X-ray microtomography images from triaxial compression tests on argillaceous rock. Strain 43, 193-205 (2007)
[9]
Roux, S., Hild, F., Viot, P., Bernard, D.: Three dimensional image correlation from X-Ray computed tomography of solid foam. Comp. Part A 39(8), 1253-1265 (2008)
[10]
Moës, N., Dolbow, J., Belytschko, T.: A finite element method for crack growth without remeshing. Int. J. Num. Meth. Eng. 46(1), 133-150 (1999)
[11]
Réthoré, J., Hild, F., Roux, S.: Extended digital image correlation with crack shape optimization. Int. J. Num. Meth. Eng. 73(2), 248-272 (2008)
[12]
Réthoré, J., Tinnes, J.-P., Roux, S., Buffière, J.-Y., Hild, F.: Extended threedimensional digital image correlation (X3D-DIC). C. R. Mécanique 336, 643-649 (2008)
[13]
Fayolle, X., Calloch, S., Hild, F.: Controlling testing machines with digital image correlation. Exp. Tech. 31(3), 57-63 (2007)
[14]
Fennema, C., Thompson, W.: Velocity determination in scenes containing several moving objects. Comput. Graph. Im. Proc. 9, 301-315 (1979)
[15]
Horn, B.K.P., Schunck, B.G.: Determining optical flow. Artificial Intelligence 17, 185-203 (1981)
[16]
Simoncelli, E.P.: Bayesian Multi-Scale Differential Optical Flow. In: Jähne, B., Haussecker, H., Geissler, P. (eds.) Handbook of Computer Vision and Applications, pp. 297-422. Academic Press, London (1999)
[17]
Mitiche, A., Bouthemy, P.: Computation and analysis of image motion: A synopsis of current problems and methods. Int. J. Comp. Vision 19, 29-55 (1996)
[18]
Black, M.: Robust Incremental Optical Flow, Ph.D dissertation, Yale University (1992)
[19]
Odobez, J.-M., Bouthemy, P.: Robust multiresolution estimation of parametric motion models. J. Visual Comm. Image Repres. 6, 348-365 (1995)
[20]
Bogen, D., Rahdert, D.: A strain energy approach to regularization in displacement field fits of elastically deforming bodies. IEEE Trans. Pattern Analysis and Machine Intelligence 18, 629-635 (1996)
[21]
DeCarlo, D., Metaxas, D.: Optical flow constraints on deformable models with application to face tracking. Int. J. Comp. Vision 38, 99-127 (2000)
[22]
Roux, S., Hild, F.: Digital Image Mechanical Identification (DIMI). Exp. Mech. 48(4), 495-508 (2008)
[23]
Avril, S., Bonnet, M., Bretelle, A.-S., Grédiac, M., Hild, F., Ienny, P., Latourte, F., Lemosse, D., Pagano, S., Pagnacco, E., Pierron, F.: Overview of identification methods of mechanical parameters based on full-field measurements. Exp. Mech. 48(4), 381-402 (2008)
[24]
Kavanagh, K.T., Clough, R.W.: Finite Element Applications in the Characterization of Elastic Solids. Int. J. Solids Struct. 7, 11-23 (1971)
[25]
Besnard, G., Hild, F., Roux, S.: "Finite-element" displacement fields analysis from digital images: Application to Portevin-Le Chatelier bands. Exp. Mech. 46, 789-803 (2006)
[26]
Belleman, R.G., Bédorf, J., Portegies Zwart, S.F.: High performance direct gravitational N-body simulations on graphics processing units II: An implementation in CUDA. New Astron. 13(2), 103-112 (2008)
[27]
Göddeke, D., Strzodka, R., Mohd-Yusof, J., McCormick, P., Buijssen, S.H.M., Grajewski, M., Turek, S.: Exploring weak scalability for FEM calculations on a GPUenhanced cluster. Parallel Comput. 33, 685-699 (2007)
[28]
Gölddeke, D., Strzodka, R., Turek, S.: Performance and accuracy of hardwareoriented native-, emulated- and mixed-precision solvers in FEM simulations result. Int. J. Parallel, Emerg. Distrib. Syst. 22(4), 221-256 (2007)
[29]
Leclerc, H.: Plateforme metil : optimisations et facilités liées à la génération de code. In: Proc. 8e Colloque National en Calcul des Structures, Giens (2007)
[30]
Cooreman, S., Lecompte, D., Sol, H., Vantomme, J., Debruyne, D.: Elasto-plastic material parameter identification by inverse methods: Calculation of the sensitivity matrix. Int. J. Solids Struct. 44(13), 4329-4341 (2007)
[31]
NVIDIA Corporation, NVIDIA CUDA compute unified device architecture programming guide (2007), http://developer.nvidia.com/cuda
- Integrated Digital Image Correlation for the Identification of Mechanical Properties
Recommendations
Peridynamics enabled digital image correlation for tracking crack paths
AbstractThis study combines peridynamic differential operator (PDDO), digital image correlation (DIC) and the Strain Compatibility Functional (SCF) method to track crack paths. DIC provides the full-field displacements at pixel accuracy by matching ...
An integrated approach to model strain localization bands in magnesium alloys
Strain localization bands (SLBs) that appear at early stages of deformation of magnesium alloys have been recently associated with heterogeneous activation of deformation twinning. Experimental evidence has demonstrated that such "Lüders-type" band ...
Digital-Image-Correlation Technique versus Infinitely Small Element Technique for Crack Analysis of Pipe with Crevice
FSKD '09: Proceedings of the 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 05Conduits of water pipelines are subjected to huge internal pressure for conveying water. Cracks induced by water pollution, material defects and seismic excitation may be forming on a conduit to cause damage. This phenomenon generating stress ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 04 May 2009
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 27 Jan 2025