Analyses of strain localisation in hdpe butterfly specimen during biaxial tests using digital image correlation

This work presents a study of high density polyethylene (hdpe) strain under biaxial loading. An Arcan apparatus is achieved in order to load a newly-designed flat specimen called “butterfly specimen” to various combinations of tensile and shear loading.These specimens have a central region with a minimal thickness (1mm); witch constitutes a small area where the strain and the stress should be uniform before necking. All tests are conducted on an Instrone tensile machine at constant speed of the upper cross-head (v = 0,5 mm/min) at the ambient temperature. Displacement fields are measured in the central area of the specimens, during the tests, by coupling digital image correlation (DIC) with imaging using high-speed CCD cameras placed in front of the specimen. The experimental results show a strain localisation in the specimen gauge section

One-step deposition of nano-to-micron-scalable, high-quality digital image correlation patterns for high-strain in-situ multi-microscopy testing

Digital Image Correlation (DIC) is of vital importance in the field of experimental mechanics, yet, producing suitable DIC patterns for demanding in-situ mechanical tests remains challenging, especially for ultra-fine patterns, despite the large number of patterning techniques in the literature. Therefore, we propose a simple, flexible, one-step technique (only requiring a conventional deposition machine) to obtain scalable, high-quality, robust DIC patterns, suitable for a range of microscopic techniques, by deposition of a low melting temperature solder alloy in so-called 'island growth' mode, without elevating the substrate temperature. Proof of principle is shown by (near-)room-temperature deposition of InSn patterns, yielding highly dense, homogeneous DIC patterns over large areas with a feature size that can be tuned from as small as 10nm to 2um and with control over the feature shape and density by changing the deposition parameters. Pattern optimization, in terms of feature size, density, and contrast, is demonstrated for imaging with atomic force microscopy, scanning electron microscopy (SEM), optical microscopy and profilometry. Moreover, the performance of the InSn DIC patterns and their robustness to large deformations is validated in two challenging case studies of in-situ micro-mechanical testing: (i) self-adaptive isogeometric digital height correlation of optical surface height profiles of a coarse, bimodal InSn pattern providing microscopic 3D deformation fields (illustrated for delamination of aluminum interconnects on a polyimide substrate) and (ii) DIC on SEM images of a much finer InSn pattern allowing quantification of high strains near fracture locations (illustrated for rupture of a Fe foil). As such, the high controllability, performance and scalability of the DIC patterns offers a promising step towards more routine DIC-based in-situ micro-mechanical testing.Comment: Accepted for publication in Strai

Some experimental observations of crack-tip mechanics with displacement data

Estudio de la mecánica en el vértice de la grieta mediante datos de desplazamiento.In the past two decades, crack-tip mechanics has been increasingly studied with full-field techniques. Within these techniques, Digital Image Correlation (DIC) has been most widely used due to its many advantages, to extract important crack-tip information, including Stress Intensity Factor (SIF), Crack Opening Displacement, J-integral, T-stress, closure level, plastic zone size, etc. However, little information is given in the literature about the experimental setup that provides best estimations for the different parameters. The current work aims at understanding how the experimental conditions used in DIC influence the crack-tip information extracted experimentally. The influence of parameters such as magnification factor, size of the images, position of the images with respect the crack-tip and size of the subset used in the correlation is studied. The influence is studied in terms of SIF and T-stress by using Williams’ model. The concept of determination of the K-dominance zone from experimental data has also explored. In this regard, cyclic loading on a fatigue crack in a compact tension (CT) specimen, made of aluminium 2024-T351 alloy, has been applied and the surface deformation ahead of the crack tip has been examined. The comparison between theoretical and experimental values of KI showed that the effect of subset size on the measured KI is negligible compared to the effect of size of the image.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Clusters and the Cosmic Web

We discuss the intimate relationship between the filamentary features and the rare dense compact cluster nodes in this network, via the large scale tidal field going along with them, following the cosmic web theory developed Bond et al. The Megaparsec scale tidal shear pattern is responsible for the contraction of matter into filaments, and its link with the cluster locations can be understood through the implied quadrupolar mass distribution in which the clusters are to be found at the sites of the overdense patches. We present a new technique for tracing the cosmic web, identifying planar walls, elongated filaments and cluster nodes in the galaxy distribution. This will allow the practical exploitation of the concept of the cosmic web towards identifying and tracing the locations of the gaseous WHIM. These methods, the Delaunay Tessellation Field Estimator (DTFE) and the Morphology Multiscale Filter (MMF) find their basis in computational geometry and visualization.Comment: 13 pages, 6 figures, appeared in proceedings workshop "Measuring the Diffuse Intergalactic Medium", eds. J-W. den Herder and N. Yamasaki, Hayama, Japan, October 2005. For version with high-res figures see http://www.astro.rug.nl/~weygaert/weywhim05.pd

On the use of simulated experiments in designing tests for material characterization from full-field measurements

The present paper deals with the use of simulated experiments to improve the design of an actual mechanical test. The analysis focused on the identification of the orthotropic properties of composites using the unnotched Iosipescu test and a full-field optical technique, the grid method. The experimental test was reproduced numerically by finite element analysis and the recording of deformed grey level images by a CCD camera was simulated trying to take into account the most significant parameters that can play a role during an actual test, e.g. the noise, the failure of the specimen, the size of the grid printed on the surface, etc. The grid method then was applied to the generated synthetic images in order to extract the displacement and strain fields and the Virtual Fields Method was finally used to identify the material properties and a cost function was devised to evaluate the error in the identification. The developed procedure was used to study different features of the test such as the aspect ratio and the fibre orientation of the specimen, the use of smoothing functions in the strain reconstruction from noisy data, the influence of missing data on the identification. Four different composite materials were considered and, for each of them, a set of optimized design variables was found by minimization of the cost function

Development of a Computer Vision-Based Three-Dimensional Reconstruction Method for Volume-Change Measurement of Unsaturated Soils during Triaxial Testing

Problems associated with unsaturated soils are ubiquitous in the U.S., where expansive and collapsible soils are some of the most widely distributed and costly geologic hazards. Solving these widespread geohazards requires a fundamental understanding of the constitutive behavior of unsaturated soils. In the past six decades, the suction-controlled triaxial test has been established as a standard approach to characterizing constitutive behavior for unsaturated soils. However, this type of test requires costly test equipment and time-consuming testing processes. To overcome these limitations, a photogrammetry-based method has been developed recently to measure the global and localized volume-changes of unsaturated soils during triaxial test. However, this method relies on software to detect coded targets, which often requires tedious manual correction of incorrectly coded target detection information. To address the limitation of the photogrammetry-based method, this study developed a photogrammetric computer vision-based approach for automatic target recognition and 3D reconstruction for volume-changes measurement of unsaturated soils in triaxial tests. Deep learning method was used to improve the accuracy and efficiency of coded target recognition. A photogrammetric computer vision method and ray tracing technique were then developed and validated to reconstruct the three-dimensional models of soil specimen