Guidelines for DIC in geotechnical engineering research

Digital image correlation (DIC), also known as particle image velocimetry (PIV), has become a well-established approach for the calculation of field displacements in geotechnical engineering. However, commercial and open-source DIC/PIV software is often used without full realisation of the implications of various parameters on accuracy and efficiency. In this paper, a critical evaluation of the various methods and components of DIC relevant to geotechnical applications is presented. In addition, new algorithms are presented to address some specific problems encountered when using DIC techniques in geotechnical research. Examples and comparisons are presented to support the proposed guidelines, and thus demonstrate the effectiveness of the newly developed techniques.

[1]  R. Adrian.  Particle-Imaging Techniques for Experimental Fluid Mechanics , 1991 .

[2]  Magued Iskander,et al.  Adaptive Cross Correlation for Imaging Displacements in Soils , 2004 .

[3]  David White,et al.  Improved image-based deformation measurement for geotechnical applications , 2016 .

[4]  David White,et al.  Improved Image-Based Deformation Measurement in the Centrifuge Environment , 2013 .

[5]  Richard D. Keane,et al.  Theory of cross-correlation analysis of PIV images , 1992 .

[6]  Young Serk Shim,et al.  A fast hierarchical motion vector estimation algorithm using mean pyramid , 1995, IEEE Trans. Circuits Syst. Video Technol..

[7]  John M. Cowley,et al.  Auto-correlation analysis of high resolution electron micrographs of near-amorphous thin films , 1985 .

[8]  Malcolm D. Bolton,et al.  Displacement and strain paths during plane-strain model pile installation in sand , 2001 .

[9]  Zhibo Chen,et al.  Image-Based Lagrangian Analysis of Granular Kinematics , 2015, J. Comput. Civ. Eng..

[10]  Tanja Karp,et al.  Comparative study of retrospective methods to reduce non-uniform illumination effects to bridge coating , 2012 .

[11]  J. Nogueira,et al.  Identification of a new source of peak locking, analysis and its removal in conventional and super-resolution PIV techniques , 2001 .

[12]  Zhibo Chen,et al.  Visualizing kinematics of dynamic penetration in granular media using transparent soils , 2015 .

[13]  Tao Wang,et al.  Evaluation of mesh-based motion estimation in H.263-like coders , 1998, IEEE Trans. Circuits Syst. Video Technol..

[14]  Amy L. Rechenmacher,et al.  Finite strain analysis of nonuniform deformation inside shear bands in sands , 2012 .

[15]  L. Tsuei,et al.  Treatment of interfaces in particle image velocimetry , 2000 .

[16]  J. Westerweel,et al.  Efficient detection of spurious vectors in particle image velocimetry data , 1994 .

[17]  Tommaso Astarita,et al.  Analysis of interpolation schemes for image deformation methods in PIV , 2005 .

[18]  C. Willert,et al.  Digital particle image velocimetry , 1991 .

[19]  F. Scarano.  Iterative image deformation methods in PIV , 2002 .

[20]  Magued Iskander,et al.  Modelling of projectile penetration using transparent soils , 2014 .

[21]  J. J. Wang,et al.  Limitation and improvement of PIV: Part I: Limitation of conventional techniques due to deformation of particle image patterns , 1993 .

[22]  W. Andy Take,et al.  Thirty-Sixth Canadian Geotechnical Colloquium: Advances in visualization of geotechnical processes through digital image correlation1 , 2015 .

[23]  Amy L. Rechenmacher,et al.  Evolution of force chains in shear bands in sands , 2010 .

[24]  D. Wood,et al.  Vermiculate artefacts in image analysis of granular materials , 2016 .

[25]  Renée Heilbronner,et al.  The autocorrelation function: an image processing tool for fabric analysis , 1992 .

[26]  J. Westerweel,et al.  The effect of a discrete window offset on the accuracy of cross-correlation analysis of digital PIV recordings , 1997 .

[27]  Magued Iskander,et al.  Accuracy of Digital Image Correlation for Measuring Deformations in Transparent Media , 2003 .

[28]  C. H. Chen,et al.  Handbook of Pattern Recognition and Computer Vision , 1993 .

[29]  Hyung Jin Sung,et al.  A further assessment of interpolation schemes for window deformation in PIV , 2006 .

[30]  Buddhima Indraratna,et al.  Laboratory evaluation of coefficient of radial consolidation based on pore-water-pressure dissipation and settlement , 2013 .

[31]  Huimin Xie,et al.  Mean intensity gradient: An effective global parameter for quality assessment of the speckle patterns used in digital image correlation , 2010 .

[32]  Fulvio Scarano,et al.  Iterative multigrid approach in PIV image processing with discrete window offset , 1999 .