High-resolution Digital Images Research Articles

Characterization of Surface Runoff Pathways and Erosion Using Hydrological Attributes Under Simulated Rainfall

Conceptualisation of geo-hydrological characteristic of erosive runoff are of particular importance and has been required in recent soil erosion control. This study aimed to explore the feasibility of applying hydrological attributes to characterize surface runoff pathways in the process of hillslope soil erosion due to rainfall. Combined with sub-millimeter high-resolution laser scanning and computer digital image processing method, three hydrological indicators (i.e., sinuosity, gradient and orientation) were used to investigate the changes of the surface runoff pathways on the slope of three typical southern red soils (i.e., shale (HS), and Quaternary red clay soils (HQ1 and HQ2) under simulated rainfall conditions). The results indicated no significant changes of sinuosity with a mean value of 1.19. After the rainfall with the intensity of 1 mm/min and 2 mm/min, the orientation and gradient changed dramatically. The greatest changes appeared at the first rainfall, which showed that the biggest increase of gradient was 26.78% and it tended to be close to the original slope of the test plot, while the orientation dropped by 5.60–31.44%. Compared with HS and HQ1, the runoff pathway characteristics of HQ2 changed more consistent. The rainfall intensities had a significant impact on the correlation between indicators. The determination coefficients sorting with surface roughness were orientation > graient > sinuosity. And they were significantly linearly related to runoff under 1 mm/min rainfall intensity, while had positive correlation with sediment under 2 mm/min rainfall intensity (p < 0.05). In conclusion, there were more remarkable relationships between orientation, gradient and slope erosion under 1 mm/min rainfall intensity. This provided an innovative idea, that is applying the orientation and gradient to the simulation and prediction model of the rainfall erosion process in the sloping farmland in the southern red soil area.

Colour variation of the Maltese wall lizards (Podarcis filfolensis) at population and individual levels in the Linosa island

The research on animal colouration has always been of great interest for biologists but since the last decades it has grown exponentially thanks to multidisciplinary approaches. Animals have found several ways to deal with the camouflage/communication trade-off in colouration, leading to the evolution of alternative patterns of variation of colourations at different levels including signal partitioning and spatial resolution of colouration. In this paper we analyse the variability of dorsal and ventral colouration in males and females of Maltese wall lizards in three populations on Linosa. We collected high-resolution digital images of dorsal, ventral and throat colouration from 61 lizards (32 males and 29 females). We showed that the colouration differs among sexes and body regions within the same individual. Colourations are also variable among individuals within population, as well as among different populations across the Island. Finally, we detected a lizard’s colouration shifts with increasing body size. Those result supports the hypothesis that colouration in this species evolved under the competing pressures of natural and sexual selection to promote signals that are visible to conspecifics while being less perceptible to avian predators.Graphic abstract

Understanding the role of local texture variation on slip activity in a two-phase titanium alloy

During plastic deformation of engineering alloys with a hcp crystal structure, slip systems with different critical resolved shear stresses can be activated. In the case of two-phase titanium alloys such as Ti-6Al-4V, it is well established that various a→ and c→+a→ type slip systems can be activated in the α-phase, which dominates this alloy. However, their relative likelihood is less well established particularly when comparing prismatic a→ and basal a→ slip which are known to have similar critical resolved shear stress values. By combining EBSD-based grain orientation mapping and high-resolution digital image correlation, grain specific shear strain mapping and Burgers vector direction analysis was carried out after small levels of plasticity in two differently microtextured Ti-6Al-4V samples. This enabled the different types of strain heterogeneity and strain patterns to be linked to the underlying microstructure and microtexture. The detailed analysis shows that the dominance of a particular a→ type slip mode greatly varies with the local texture and that shear strain patterns extend across many grains when soft macrozones (clusters of similarly orientated grains) are present. The work highlights that the relative displacement ratio analysis significantly improves slip trace analysis in hcp crystals by reducing the cases of ambiguous solutions and that grain neighbourhood can have a greater impact on slip system activation than Schmid factor.

Slip localization in Inconel 718: A three-dimensional and statistical perspective

The slip localization behavior of the polycrystalline nickel base superalloy Inconel 718 during monotonic tensile loading at room temperature, is investigated for the first time in relation to the 3D microstructure. Multi-modal data merging tools are used to recombine high resolution digital image correlation (HR-DIC) data with 3D electron back-scatter diffraction tomography (3D EBSD), over a wide region of interest. This procedure enables reconstruction of the slip band planes in the 3D microstructure. Statistical analyses conducted over 500 individual slip bands reveal strong correlations between their location and specific microstructure configurations. In particular, over half of the slip bands emanate from triple junction lines (3D lines defined by the junction of three crystals). Moreover, the most intense and longest slip bands, which would become critical fatigue crack nucleation sites during cyclic loading, are located close and parallel to particular annealing twin boundaries and are simultaneously connected to triple junction lines. Crystal plasticity finite elements calculations are performed on the experimental microstructure to identify the slip activity that results in the formation of high intensity slip bands (localized plasticity) or zones of high lattice rotation (non-localized plasticity) in these particular microstructure regions.

Detecting Coronary Artery Calcium on Chest Radiographs: Can We Teach an Old Dog New Tricks?

Detecting Coronary Artery Calcium on Chest Radiographs: Can We Teach an Old Dog New Tricks?

Representative volume elements for plasticity and creep measured from high-resolution microscale strain fields

Homogenization techniques have been widely used in upscaling microscale numerical results to predict the macroscopic response of materials. Often homogenization is based on the concept of a representative volume element (RVE) and thus, measuring the RVE size and understanding what factors influence it are key elements in successful material modeling. Here, the size of the RVE for an austenitic stainless steel alloy is experimentally determined under, both separately and combined, plasticity and creep loading conditions with varying parameters (namely stress, temperature, and creep hold time). We use a high-resolution optical digital image correlation (DIC) methodology capable of discerning residual strain inhomogeneities at the microstructural level. Furthermore, by combining the strain results from DIC with surface microstructural information from electron backscatter diffraction (EBSD), the localized strains near grain boundaries can be isolated allowing for quantitative observations related to the deformation mechanisms responsible for strain accumulation. Finally, by comparing the results for RVE size and localized normal to shear strain ratios for different combinations of loading parameters, the relationship between grain-boundary sliding and the resulting heterogeneity of the strain field is explored. Cases where grain-boundary sliding was the dominant deformation mechanism (i.e., at elevated temperature) had considerably smaller RVE sizes (from 4 to 6 times the average grain size) when compared to samples where sliding was not as prevalent (around 10 times the average grain size).

Direct monitoring of twinning/detwinning in a TWIP steel under reversed cyclic loading

In situ tensile and reversed cyclic tests were run on a TWIP steel in a SEM, with High-Resolution Digital Image Correlation (HR-DIC) measurements of the plastic strain field in a few selected grains prone to twinning, with a spatial resolution between 150 and 250 nm, or under an AFM, with measurements of surface steps height at emerging deformation twins. Evidences of detwinning upon load reversal, as well as quantitative data on twinning/detwinning/retwinning were obtained. Detwinning and retwinning, which often were only partial, in spite of a fully reversed loading, did not seem to start at the onset of stress reversal. It required a sufficient variation of the stress, close to the twinning stress (estimated as 400–475 MPa) in absolute value, so that a mechanical hysteresis of the local twinned fraction occurred. Primary and secondary twinning along the same plane, inducing axial plastic strains in opposite directions, also allowed some grains to accommodate reversed plastic strain. Under fixed stress amplitude (±500 MPa), the twin fraction in all monitored grains saturated at values between 0.5 and 3.5%, from the 2nd cycle, while under fixed plastic strain amplitude (±0.5%), it increased in a ratchetting way during the whole cyclic hardening stage, reaching 0.5–5%. In both cases, however, the plastic strain amplitude accommodated by twinning/detwinning, which reached 0.35–0.42% in some grains during the 1st cycle, decreased down to less than 0.05% after 100 to 1000 cycles.

Development of Banknote Detection Circuit System

Due to the continuous improvement of digital imaging technology, making counterfeit banknotes has become easier and cheaper. In order to solve the problem of counterfeit banknotes, the main purpose of this article is to develop a banknote detection system (BDS). This system will detect whether banknotes are included in the digital image during scanning or printing, reducing the use of high-resolution digital imaging products for counterfeit banknote manufacturing opportunity. The system is divided into three main steps: magnetic detection, fluorescent detection and watermark detection. In the future, this system can be implanted in image-related computer peripherals (such as scanners, printers or multi-function printers) to scan banknotes at the beginning or prevent blockages when copying banknotes.

Contact angle measurements for automotive exterior water management

The simulation of fluid flow over solid surfaces is important in many applications, for example, in automotive applications where good visibility and the performance of external sensors are essential. Multiphase CFD simulation methods such as level set or coupled level set–volume of fluid typically require a validated dynamic contact angle model as a function of capillary number to accurately resolve the near wall behaviour. This paper explores an experimental approach to identify a suitable contact angle model for pure and contaminated water on glass and painted surfaces. Applying image processing methods to high-resolution digital images of droplets descending flat plate samples of the required surfaces, the dynamic advancing and receding contact angles and capillary number are determined. Cox–Voinov, de Gennes and Yokoi models are parameterised from the experimental data, and the Yokoi model is shown to be the most suited to these surface/fluid combinations where hysteresis is significant. A multiphase simulation implementing the Yokoi model demonstrates good correlation for the Bond number between simulation and experiment.Graphic abstract

Cool, Dry, Nano-scale DIC Patterning of Delicate, Heterogeneous, Non-planar Specimens by Micro-mist Nebulization

Background: Application of patterns to enable high-resolution Digital Image Correlation (DIC) at the small scale (μm/nm) is known to be very challenging as techniques developed for the macro- and mesoscale, such as spray painting, cannot be scaled down directly. Moreover, existing nano-patterning techniques all rely on harsh processing steps, based on high temperature, chemicals, physical contact, liquids, and/or high vacuum, that can easily damage fragile, small-scale, free-standing and/or hygro-sensitive specimens, such as MEMS or biological samples. Objective: To present a straightforward, inexpensive technique specially designed for nano-patterning highly delicate specimens for high-resolution DIC. Methods: The technique consists in a well-controlled nebulized micro-mist, containing predominantly no more than one nanoparticle per mist droplet. The micro-mist is subsequently dried, resulting in a flow of individual nanoparticles that are deposited on the specimen surface at near-room temperature. By having single nanoparticles falling on the specimen surface, the notoriously challenging task of controlling nanoparticle-nanoparticle and nanoparticle-surface interactions as a result of the complex droplet drying dynamics, e.g., in drop-casting, is circumvented. Results: High-quality patterns are demonstrated for a number of challenging cases of physically and chemically sensitive specimens with nanoparticles from 1 μm down to 50 nm in diameter. It is shown that the pattern can easily be scaled within (and probably beyond) this range, which is of special interest for micromechanical testing using in-situ microscopic imaging techniques, such as high-magnification optical microscopy, optical profilometry, atomic force microscopy, and scanning electron microscopy, etc. Conclusions: Delicate specimens can conveniently be patterned at near-room temperature (sim 37 ∘C), without exposure to chemicals, physical contact or vacuum, while the pattern density and speckle size can be easily tuned.

Application of Imaging Techniques to Determine the Post-Yield Behaviour of the Heterogeneous Microstructure of Friction Stir Welds

BackgroundFriction Stir Welding (FSW) causes intense plastic deformation and consequent thermomechanical interactions resulting in a localised heterogeneous microstructure. To understand the weld mechanical behaviour, it is necessary to identify each microstructural sub-region in the weld.ObjectiveDetermine the relationship between the local microstructure and mechanical behaviour of the different microstructural regions in a FSW.MethodsScanning electron microscopy (SEM) identified the microstructural sub-regions of an FSW joint. A novel High-Resolution Digital Image Correlation (HR-DIC) methodology enabled the determination of full-field strain response to provide the mechanical behaviour of the FSW sub-regions. X-ray computed tomography (CT) identified the geometry of the FSW and material composition.ResultsThe grain morphology in the FSW varied in the stir zone with a fine grain structure in the weld nugget and larger grains in the thermomechanical affected zone (TMAZ); the grains were larger in the retreating side (RS) compared to the advancing side (AS). Tungsten deposits were found in the weld nugget and attributed to tool wear. The mechanical properties of the weld subregions showed that the material in the stir zone had a greater yield strength than the base material and the RS of the FSW was much more ductile than the weld nugget and the AS side. The tungsten distributions in the stir zone correlated with the local mechanical behaviour.ConclusionsA novel methodology is developed that combines microstructural observations with HR-DIC enabling, for the first time, the FSW sub-region mechanical behaviour, to be related to the local grain morphology and inclusions caused by tool wear.

High-Precise True Digital Orthoimage Generation and Accuracy Assessment based on UAV Images

Unmanned aerial vehicles (UAVs) are modern tool for various scientific research areas such as agriculture, disaster management, mining and surveying. Among them, remote sensing is utilizing UAVs to acquire high-resolution digital images of ground surface. In remote sensing and photogrammetric operations, the geometric quality of the imagery basically depends on the relation between pixel size and the map scale, contrast information, atmosphere and the sun elevation, the printing technology, screen resolution and the visual acuity (ISPRS Int J Geo-Inf, Liu et al. Liu et al., ISPRS International Journal of Geo-Information 7:333, 2018; Eur Assoc Geosci Eng 1–5, Zatserkovnyi et al. Zatserkovnyi et al., European Association of Geoscientists and Engineers 25:1–5, 2020). In this study, accuracy has been assessed and compared of true digital orthoimages generated by two different software with same configuration. Three datasets of different places called dense urban, urban slum and forest mountains have been collected from field with area covering 0.061, 0.130 and 2.040 km2 and ground sampling distance 1.79, 2.19 and 11.86 cm, respectively. The orthoimages were generated using Pix4D and AgiSoft Photoscan software and then randomly distributed checkpoints, and visual angular distortion on the orthoimage was used to verify its precision. It was observed that in dense urban and urban slum Pix4D accuracy is more than AgiSoft Photoscan, but in forest mountain, it is vice versa. However, the process and mapping accuracy to generate TDOI require further improvement.

Edge Detection in 3D Point Clouds Using Digital Images

This paper presents an effective and semi-automated method for detecting 3D edges in 3D point clouds with the help of high-resolution digital images. The effort aims to contribute towards addressing the unsolved problem of automated production of vector drawings from 3D point clouds of cultural heritage objects. Edges are the simplest primitives to detect in an unorganized point cloud and an algorithm was developed to perform this task. The provided edges are defined and measured on 2D digital images of known orientation, and the algorithm determines the plane defined by the edge on the image and its perspective center. This is accomplished by applying suitable transformations to the image coordinates of the edge points based on the Analytical Geometry relationships and properties of planes in 3D space. This plane inevitably contains the 3D points of the edge in the point cloud. The algorithm then detects and isolates those points which define the edge in the world system. Finally, the goal is to reliably locate the points that describe the desired edge in their true position in the geodetic space, using several constraints. The algorithm is firstly investigated theoretically for its efficiency using simulation data and then assessed under real conditions and under different image orientations and lengths of the edge on the image. The results are presented and evaluated.

Slip band interactions and GND latent hardening in a galling resistant stainless steel

Slip activation, slip band interactions, and GND densities in iron-base, galling resistant alloy Nitronic 60 have been characterised at the grain length scale using small-scale mechanical testing with high resolution digital image correlation and high-angular resolution electron backscatter diffraction. By correlating the two measurement techniques, new insight into slip band interactions, the generation of lattice curvature and the corresponding accumulation of geometrically necessary dislocations (GNDs) is provided. Multiple discrete slip bands are typically active within single grains, resulting in significant slip band interactions. Crossing slip bands were found to generate accumulations of GNDs. Regions where slip bands block other slip bands were associated with the highest GND densities, in excess of three time the densities of crossing slip bands. Representative crystal plasticity modelling investigations have demonstrated that discrete slip blocking events are responsible for locally elevated GND density. This behaviour is rationalised in terms of lattice curvature associated with the differing levels of constraint provided by the crossing or blocking-type behaviours. Ferrite grains are also found to contribute to the generation of GNDs. Together, these two effects provide significant work hardening mechanisms, likely to be key to the development of future iron-base hard facing alloys.

Anisotropic strengthening of nanotwin bundles in heterogeneous nanostructured Cu: Effect of deformation compatibility

Anisotropic tensile behaviors of a heterogeneous nanostructured Cu composed of isotropic nanograin matrix and anisotropic nanotwin bundles were investigated under loading directions parallel, normal, and 45° inclined to the twin boundaries (TBs). Distinct from the anisotropic strengthening effect in the homogeneous nanotwinned (NT) counterpart, the heterostructure exhibits the highest strength under parallel tension, and moderate strength under normal tension. High-resolution digital image correlation analysis indicated an orientation-dependent deformation compatibility between the nanotwin bundles and nanograin matrix, i.e., compatible deformation in the parallel orientation; but significant incompatibility in orientations both normal and 45° inclined to TBs. The results reveal that the strengthening effect of nanotwins in heterogeneous nanostructure is not only dependent on the strength of themselves, but also influenced by the deformation compatibility with surrounding components. The orientation-dependent deformation compatibility was attributed to the interactions between isotropic shear bands in nanograin matrix and anisotropic deformation in nanotwin bundles.

A New Method for Extracting Individual Plant Bio-Characteristics from High-Resolution Digital Images

The extraction of automated plant phenomics from digital images has advanced in recent years. However, the accuracy of extracted phenomics, especially for individual plants in a field environment, requires improvement. In this paper, a new and efficient method of extracting individual plant areas and their mean normalized difference vegetation index from high-resolution digital images is proposed. The algorithm was applied on perennial ryegrass row field data multispectral images taken from the top view. First, the center points of individual plants from digital images were located to exclude plant positions without plants. Second, the accurate area of each plant was extracted using its center point and radius. Third, the accurate mean normalized difference vegetation index of each plant was extracted and adjusted for overlapping plants. The correlation between the extracted individual plant phenomics and fresh weight ranged between 0.63 and 0.75 across four time points. The methods proposed are applicable to other crops where individual plant phenotypes are of interest.

A pore-network-based upscaling framework for the nanoconfined phase behavior in shale rocks

The presence of extensive nanopores in organic-rich shale introduces unique thermodynamic fluid phase behaviors owing to large pressure differentials across fluid-fluid interfaces and strong fluid-wall interactions. While the nanoconfined phase behavior has been extensively studied in a single nanopore, its manifestation in complex nanopore networks remains poorly understood and rigorously derived macroscopic phase behavior formulations are not yet available. We develop a novel upscaling framework for deriving macroscopic phase behavior formulations in realistic nanopore networks (e.g., obtained from high-resolution digital images of shale samples). The framework employs a generalized phase equilibrium model that explicitly accounts for the impact of capillary pressure and multicomponent adsorption in each pore. Assuming thermodynamic equilibrium across the pore network, macroscopic phase behavior variables for the entire pore network are then derived by integrating the variables from the individual pores. This leads to a macroscopic network-scale phase equilibrium model that naturally accounts for the size- and geometry-dependent nanoconfinement effects of a complex pore structure. Simulated phase behaviors using three multiscale pore networks demonstrate that (1) the phase behavior in a pore network—controlled by the multiscale pore structure—significantly deviates from that in a single nanopore and (2) due to capillary trapping of the liquid phase and competitive adsorption on the pore wall, heavier components tend to reside in smaller pores and suppress the bubble point pressure therein. The upscaled phase behavior model shares the same mathematical structure as that of a standard phase behavior model and can thus be readily incorporated in commercial reservoir simulators. • We develop a novel upscaling framework for the phase behavior in nanopore networks. • Our formulation accounts for capillary pressure and competitive adsorption. • The nanopore networks can represent realistic pore structures of shale rocks. • The network-scale phase behavior is controlled by the multiscale pore structure. • The upscaled model can be readily incorporated in commercial reservoir simulators.

ALMI-A Generic Active Learning System for Computational Object Classification in Marine Observation Images.

In recent years, an increasing number of cabled Fixed Underwater Observatories (FUOs) have been deployed, many of them equipped with digital cameras recording high-resolution digital image time series for a given period. The manual extraction of quantitative information from these data regarding resident species is necessary to link the image time series information to data from other sensors but requires computational support to overcome the bottleneck problem in manual analysis. As a priori knowledge about the objects of interest in the images is almost never available, computational methods are required that are not dependent on the posterior availability of a large training data set of annotated images. In this paper, we propose a new strategy for collecting and using training data for machine learning-based observatory image interpretation much more efficiently. The method combines the training efficiency of a special active learning procedure with the advantages of deep learning feature representations. The method is tested on two highly disparate data sets. In our experiments, we can show that the proposed method ALMI achieves on one data set a classification accuracy A > 90% with less than N = 258 data samples and A > 80% after N = 150 iterations, i.e., training samples, on the other data set outperforming the reference method regarding accuracy and training data required.

Hydrogen assisted crack initiation in metals under monotonic loading: A new experimental approach

Hydrogen is foreseen as a promising energy carrier that can control global warming by reducing CO2 emissions. However, hydrogen is associated with an embrittlement phenomenon that imparts substantial damage to the infrastructure by reducing the ductility, fracture strength, strength bearing capacity, etc., of metallic components. Therefore, understanding hydrogen-induced crack initiation mechanisms in metals are of prime importance. Greater insights into this critical phenomenon are expected if the hydrogen-induced crack initiation can be correlated with the local microstructure and corresponding stress-strain state towards their propensity for hydrogen accumulation. With this motivation, in this work, crack initiation is studied for the uncharged and hydrogen charged nickel specimens during in-situ tensile loading under the scanning electron microscope. By assuming the material to be elastic at low strains, a novel approach is implemented for generating the microstructural stress maps through strain and stiffness tensor extracted at each point in the region of interest on the specimen surface using high-resolution digital image correlation (HR-DIC) and Euler angles (given by electron backscattered diffraction data), respectively. Based on this analysis at low strain, the crack initiation sites for uncharged and hydrogen charged nickel specimens are correlated with microstructural maps of maximum Schmid factor, elastic modulus in the loading direction, hydrostatic stress, von Mises stress, and triaxiality factor. The analysis highlighted two independent factors responsible for hydrogen enhanced decohesion (HEDE) based intergranular failure observed only at the random grain boundaries, (i) strain localization due to hydrogen enhanced localized plasticity (HELP) mechanism of hydrogen embrittlement, and (ii) hydrostatic stress-based hydrogen diffusion to the crack initiation sites. These critical insights thus can help to design hydrogen embrittlement resistant metals. In addition, the novel experimental approach can be used to calibrate advance micromechanical models while providing quantitative estimate of the hydrogen distribution in realistic metallic microstructure responsible for hydrogen-assisted crack initiation with deformation.

Orthotropic Behaviour of Magnesium AZ31 Sheet during Strain Localization

It is known that metallic materials are characterized by anisotropy of their mechanical properties, with this being attributed to the conditions during the manufacturing process. For sheet metals, this anisotropy occurs symmetrically to the three orthogonal axes of the rolling, transverse and normal direction. This characteristic is referred to as orthotropic behaviour and manifests itself, for example, in earing during cupping tests. Therefore, orthotropic yield criteria are highly relevant for the numerical simulation of sheet metal forming processes. The Lankford coefficient, also known as the r-value, is a good experimental measure for characterizing orthotropic ductile behaviour of sheets, and can easily aid in parameter identification for yield criteria such as the Hill approaches. In the present investigations, Lankford coefficients were determined as a function of local strain in uniaxial tensile tests through high-resolution digital image correlation. The sample direction was varied between 0°, 45° and 90° to the rolling direction and the test temperature varied from RT to 350 °C at three different strain rates (0.01-1 s-1). By means of a novel backward analysis, the measuring range for the Lankford coefficients was positioned exactly in the necking area. An increase in temperatures showed a decrease in the initial Lankford coefficient. The results showed non-constant Lankford coefficients and commence the course of a natural exponential function depending on the local strain. Regardless of strain rate, the results revealed that the Lankford coefficients (r-values) at 150 °C, 250 °C and 350 °C approaches a steady-state of r = 1.14 with strains greater than 50 %.