Ghulam Mubashar Hassan

Rotations and pattern formation in granular materials under loading

Shear band formation and evolution is a predominant mechanism of deformation patterning in granular materials. Independent rotations of separate particles can affect the pattern formation by adding the effect of rotational degrees of freedom to the mechanism of instability. We conducted 2D physical modelling where the particles are represented by smooth steel discs. We use the digital image correlation in order to recover both displacement and independent rotation fields in the model. We performed model calibration and determine the values of mechanical parameters needed for a DEM numerical modelling. Both mono- and polydisperse particle assemblies are used. During the loading, the deformation pattern undergoes stages of shear band formation followed by its dissolution due to recompaction and particle rearrangement with the subsequent formation of multiple shear bands merging into a single one and the final dissolution. We show that while the average (over the assembly) values of the angles of disc rotations are insignificantly different from zero, the particle rotations exhibit clustering at the mesoscale (sizes larger than the particles but smaller than the whole assembly): monodisperse assemblies produce vertical columns of particles rotating the same direction; polydisperse assemblies 2D form clusters of particles with alternating rotations. Thus, particle rotations produce a structure on their own, a structure different form the ones formed by particle displacements and force chains. This can give a rise to moment chains. These emerging mesoscopic structures – not observable at the macroscale – indicate hidden aspects of ‘Cosserat behaviour’ of the particles.

A comparative study of techniques of distant reconstruction of displacement and strain fields using the DISTRESS simulator

Abstract Reconstruction and monitoring of displacement and strain fields is an important problem in engineering. We analyze the remote and non-obtrusive method of Digital Image Correlation (DIC) in 2D based on photogrammetry. The method involves covering the photographed surface with a pattern of speckles and comparing the images taken before and after the deformation. The analysis is based on a specially developed Digital Image Synthesizer To Reconstruct Strain in Solids (DISTRESS) Simulator to generate synthetic images of displacement and stress fields in two dimensions in order to investigate the intrinsic accuracy of the existing variants of DIC. We investigated the Basic DIC and a commercial software VIC 2d, both based on displacement field reconstruction with post processing strain determination based on numerical differentiation. We also investigated what we call the Extended DIC where the strain field is determined independently of the displacement field. While the Basic DIC is faster, the Extended DIC delivers the best accuracy. The speckle pattern is found to be playing a critical role in achieving high accuracy for DIC. Increase in the subset size for DIC does not significantly improves the accuracy, while the smallest subset size depends on the speckle pattern and speckle size. Increase in the overall image size provides more details but does not play significant role in improving the accuracy, while significantly increasing the computation cost. We observed that it is not reliable to measure very small strains using grayscale images in DIC. Thus, we propose Color DIC using color images and found that it improves the accuracy in measuring small strains.

Digital image correlation for small strain measurement in deformable solids and geomechanical structures

Digital image correlation (DIC) is a well-known contact-less technique offering highly accurate full-field deformation measurement using grayscale images. The practical implementation of DIC is still facing many challenges, especially limitations of accuracy in measuring small displacement gradients for solids in geosciences and biomedi-cal engineering. In this paper, we introduce a novel approach in which color images are employed to enhance the performance of DIC. A complete framework for Color DIC has been proposed and tested. The results show that Color DIC performs significantly better than grayscale DIC for measurement of small strains by a factor of 2.

Extending Digital Image Correlation to Reconstruct Displacement and Strain Fields around Discontinuities in Geomechanical Structures under Deformation

Reconstruction of displacement and strain fields in geomechanical structures from surface images is a challenging task. Digital Image Correlation (DIC) is a well known technique to achieve these tasks if deformation is continuous but it fails in the presence of discontinuities. This paper investigates the application of the DIC technique to displacement and strain field reconstruction in the presence of discontinuities, and presents a post-processing algorithm that leverages the convergence results in DIC to reconstruct displacement and strain fields around discontinuities with high accuracy. The proposed algorithm uses the results obtained from DIC and concentrates on the area where DIC fails. Pattern matching is conducted on the area around the discontinuities and associated displacement is found for each pixel. The proposed algorithm is tested using two different discontinuity scenarios: dislocation and fracture in structures. The results show that the proposed algorithm successfully reconstructs the displacement and strain fields to sub pixel accuracy of 1/10th of a pixel.

Towards affordable and robust remote photogrammetric sensing for early warning of fracturing and structural failure

Early warning systems are critical for saving human lives in the presence of structural failure. This is particularly relevant in mining operations in parts of the world with variable safety standards. To achieve this, affordable and robust structural health monitoring (SHM) is required. Photogrammetry is an image processing technique that can be used to measure deformation in geomechanical structures, enabling the reconstruction of displacement and strain fields with high accuracy (up to one-hundredth of a pixel). The use of standard cameras makes photogrammetry an inexpensive approach to automated SHM. However, while photogrammetric techniques have proven successful in laboratories and controlled environments, further development is needed to deal with a broader range of environments. This paper outlines recent research to overcome limitations of the Digital Image Correlation (DIC) photogrammetry technique, with the goal of achieving robust, low cost, automated SHM systems.