Elaboration of fracture prediction map using 2D digital image correlation - 2D CID

This work aims to present a methodology for the elaboration of a deformation map in a Portland cement concrete specimen to predict fractures caused by axial compression stresses, using the technique of Digital Image Correlation - DIC 2D. For this purpose, 5 concrete specimens with compressive strength expected at 28 days fck of 40 MPa were analyzed, which were tested in the ABNT NBR 5739/2018 standard - compression test of cylindrical concrete specimens. During the test, the necessary digital images were acquired in the DIC-2D array. These images were subsequently processed, and the results interpreted statistically. According to the result of the correlation of images obtained, it was found that 67% of the specimens had regions of accumulation of stresses that indicated in advance the location of the rupture, which enabled the development of a fracture prediction map. The results obtained in the research showed that the methodology used by means of the DIC-2D arrangement was able to predict the place where the rupture in the specimens occurred.

Tensile Creep of Cement and Concrete Composites: Monitoring by Means of 2D-Digital Image Correlation

Creep and shrinkage of Cement and Concrete Composites (CCC) are significant properties that need to be considered to use these materials in practice. Many previous scientific studies revealed CCC creep characteristics under sustained compression and shrinkage, using traditional test methods from design standards. Because of the complexity of experimental procedures, CCC creep in tension has not been studied as close. Furthermore, there is no unified standard that proposes applicable testing methods or specific testing apparatus. This study examines the suitability of 2D—Digital Image Correlation (DIC) to observe the creep deformations of specimens under tension. Ordinary Portland cement (OPC) mortar with 1% polyvinyl alcohol (PVA) fibres has been investigated in the research. Compact tension (CT) specimens 150 × 150 × 12 mm (with a notch) were used. Creep deformations under sustained uniaxial tension (applied loading corresponding to 60% of the ultimate strength) were measured. DIC images were captured using an entry/mid-level DSLR camera. Results show that DIC is suitable for studying uniaxial tensile creep of cement and concrete composites. Deformation of specimens in tension was similar to that measured using the conventional method (using surface-attached gauges).

Exploring the Role of Manufacturing Parameters on Microstructure and Mechanical Properties in Fused Deposition Modeling (FDM) Using PETG

Additive manufacturing develops rapidly, especially, fused deposition modeling (FDM) is one of the economical methods with moderate tolerances and high design flexibility. Ample studies are being undertaken for modeling the mechanical characteristics of FDM by using the Finite Element Method (FEM). Even in use of amorphous materials, FDM creates anisotropic structures effected by the chosen manufacturing parameters. In order to investigate these process-related characteristics and tailored properties of FDM structures, we prepare FDM-printed poly(ethylene terephthalate) glycol (PETG) samples with different process parameters. Mechanical and optical characterizations are carried out. We develop 2D-digital-image-correlation code with machine learning algorithm, namely K-means cluster, to analyze microstructures (contact surfaces, the changes in fiber shapes) and calculate porosity. By incorporating these characteristics, we draw CAD images. A digital twin of mechanical laboratory tests are realized by the FEM. We use computational homogenization approach for obtaining the effective properties of the FDM-related anisotropic structure. These simulations are validated by experimental characterizations. In this regard, a systematic methodology is presented for acquiring the anisotropy from the process related inner substructure (microscale) to the material response at the homogenized length scale (macroscale). We found out that the layer thickness and overlap ratio parameters significantly alter the microstructures and thereby, stiffness of the macroscale properties. Graphical Abstract

Correction: Atkinson, D.; Becker, T. A 117 Line 2D Digital Image Correlation Code Written in MATLAB. Remote Sens. 2020, 12, 2906

The authors wish to make the following corrections to the paper [...]

Target Based 2D Digital Image Correlation Deflection Monitoring to Analyze the Environmental Effect on Variations of Deflection on Structures

The truss upgrade for the Calgary Municipal Building posed a unique challenge for live tracking of the structure’s reaction to the pre-loadings, welding operations, and the removal of the preloads. The authors, therefore, devised a method for a special case of deflection monitoring, with the pre-condition of having a displacement-free location available where cameras could be installed. The dust and other construction material would appear above the specimen, and the light over the specimen was variable. The proposed approach of this research was to use a correlation-based object recognition for retro-reflective targets. The technique maintained an accuracy of 0.08 mm in deflection monitoring with a camera at 15-m away from the targets over a period of eight months data acquisition. The conclusion was that this digital image correlation (DIC) technique can provide deflections in the perpendicular plane to the line of sight of the cameras and can be used under harsh conditions for the targets (e.g., dust and physical damage), with a limited light source. The effect of external environmental parameters, such as daily temperature, solar radiation, and air pressure on the observed deflections, were analyzed and the close relationship between temperature and variations in deflection were observed.