Shape Texture Research Articles

Effect of Y2O3 dispersoids on microstructure and creep properties of Hastelloy X processed by laser powder-bed fusion

• The effect of Y 2 O 3 dispersoids on microstructure and creep properties of Hastelloy X processed by LPBF is investigated. • Grains are found aligned along build direction, with a strong <001>Ni texture along both build and laser scanning directions. • LPBF Hastelloy X exhibits anisotropic creep response, with elongated grains showing higher creep resistance when aligned along loading direction than when aligned perpendicular to loading direction. • Y 2 O 3 dispersoids improve alloy creep resistance at dislocation-creep regime. • Alloy grain structure remains resistant to recrystallization during high-temperature solutionizing and creeping. Laser powder bed fusion (LPBF) was used to consolidate powders of a Ni-Cr-Fe-Mo alloy (Hastelloy X) blended with 1 wt% Y 2 O 3 nanometric powders. The nearly-dense, crack-free specimens, with and without oxide dispersion strengthening (ODS), exhibit high-aspect ratio grains, aligned in the build direction and with a strong texture: 〈001〉 is aligned along both build direction and laser scanning direction. Creep tests performed at 950 °C, with compressive stresses aligned with the elongated grains (and the build direction), reveal two creep regimes: (i) at stresses below ∼50 MPa, diffusional creep dominates, and the ODS alloy is less creep resistant than the non-ODS alloy, consistent with a somewhat smaller grain size resulting from grain-boundary pinning by the oxide dispersoids; (ii) at stresses above ∼50 MPa, dislocation creep dominates and the ODS alloy is more creep resistant, as expected from oxide dispersoids impeding dislocation motion. When tested perpendicular to the build direction, both alloys have the same creep resistance, which is however much lower than when the stress is aligned with the build direction, reflecting a strong effect of texture and grain shape. After ∼10% compressive creep deformation, grain structure and texture remain largely unchanged as compared to pre-creep structure.

Evolution of tire-pavement friction with the regular surface macro-texture characteristics and environmental factors using three-dimensional (3D) printing technology

Conventional gradation-based pavement design makes the constructed pavement surface too complex to quantify the contribution of texture on the tire-pavement friction accurately. This study aims to investigate the influence of regular macro-texture characteristics and environmental factors on friction using three-dimensional (3D) printing technology. The variation of friction with different texture shapes, heights, and gaps was investigated under dry and wet conditions. The evolutions of friction under different water film thicknesses and temperatures were also quantitatively analyzed. The results show that all specimens with different texture shapes, heights, and gaps can contribute to large friction under dry conditions, where the British pendulum number (BPN) is larger than 90. The friction sharply decreases under wet conditions, especially for the semi-circular texture specimens. The specimens with positive textures are much better than those with negative textures. The impact of texture shapes is more significant than texture height and gaps under wet conditions, where the texture gaps are relatively insignificant. The friction is slightly linearly increased with the water film thickness while slightly decreasing with the temperature. This study provides a friction-oriented pavement texture design method and manufacturing techonology.

Friction and Sealing Performance of the Textured End-Face Seal in the Internal Mixer

To improve the friction and sealing performance of the end-face seal device in the internal mixer, surface texture technology was introduced into the end-face seal device. Based on the hydrodynamic lubrication theory, the effects of different shape textures on the end-face sealing performance under steady and unsteady conditions were simulated, and friction-wear experiments were carried out by the Swiss Anton Paar Friction-Wear Tester TRB3. The theoretical study indicates that under the same conditions, the friction performance and seal effect of Ellipse⊥ and Triangle⊥ textured end-face seals are better, with lower leakage and better average dimensionless pressure. The experimental study indicates that under the same texture parameters, the Triangle⊥ and Ellipse⊥ textured pins have the lowest friction coefficient when the texture depth is 6 μm and 9 μm respectively, and the texture area ratio is 5.56%. In addition, the Triangle⊥ texture has the best friction performance under lower texture depths and the same area ratio. Therefore, it’s concluded that reasonable texture shapes and parameters can effectively improve the friction and seal performance of the end-face seal device in the internal mixer.

The morphological and molecular variability of Sporisorium scitamineum isolates from Eswatini

Sugarcane smut is a disease of economic importance in the sugarcane industry, occasioning losses of up to 50%. Current management practices have been ineffective in controlling the fungal disease, and hence the understanding of the pathogen and the development of appropriate control measures are required. This study investigates the morphology, virulence and molecular variability of Sporisorium scitamineum isolates from Eswatini to understand its pathogenicity for effective control. Fungal isolates were collected along the Sugarbelt in the Lowveld of Eswatini. The isolates were verified by polymerase chain reaction using the bE4 and bE8 specific primers with amplification of a 459bp fragment. The identity was further verified by DNA sequencing. The teliospores from the isolates were uniform in brown colour, spiny texture and circular shape. The teliospore sizes were significantly (P=0.05) different among the isolates. The isolate from Big-Bend had a mean spore diameter of 5.55µm, while Simunye, Nsoko and Mhlume had average diameters of 4.69µm, 4.98µm and 4.87µm, respectively. The documentation of the developmental stages revealed that the samples were of variable virulence with significantly (P=0.05) different rates of promycelium development. The variable virulence of the isolates was further confirmed by the in-vivo pathogen biomass quantification by RT-qPCR. Genetic distance matrix analysis and cluster analysis showed high homology (99-100%) among the local isolates which indicate that there is a low variability among the strains that are found in the selected sugarcane growing areas of Eswatini

Effect of textures fabricated by ultrasonic surface rolling on dry friction and wear properties of GCr15 steel

Linear textures and cross textures with different processing stepovers were fabricated on the surface of GCr15 steel by ultrasonic surface rolling processing (USRP). The effects of texture shape and processing stepover on the dry friction and wear performance of the samples were investigated using a ball-and-disk friction tribometer. The results showed that all the USRP texturing samples had lower friction coefficients and wear rates than those of the substrate sample under dry friction conditions. The best tribological performance was achieved at the stepover of 150 μm for linear textures and 250 μm for cross textures. For two shapes of textures with the same stepover, the linear texture had better wear resistance and the cross texture had better friction reduction. The texture shape and processing stepover influenced the texture height and the strengthening effect, which in turn affected the tribological properties of the samples. The improvement in friction and wear performance by ultrasonic rolling texturing was attributed to the synergistic effect of the strengthened substrate, reduced actual contact area, and entrapment of wear debris.

Printability evaluation of Chlorella vulgaris snacks

The aim of this work was to evaluate the influence of Chlorella vulgaris (C. vulgaris) additions on the printability of cereal-based doughs. Increasing C. vulgaris levels of incorporation (2–30 % w/w) were tested and a limit of incorporation (30 %) for printing was reached. Evaluation of printability was conducted based on the rheology and texture properties of the doughs and shape fidelity of the 3D printed doughs. The combination of rheology and texture properties and shape fidelity assessment led to the development of printability maps, where doughs were grouped into different levels of printability (1–3), providing industrial relevant information for successful printing of food materials. Doughs with lower texture (firmness and adhesiveness) and rheology (viscoelasticity and viscosity) properties corresponded to doughs with lower levels of C. vulgaris incorporation. Doughs with up to 12 % microalga incorporation presented the most accurate printed structures. Color measurements indicated that increasing additions of microalga produced darker doughs with perceptible color differences by human eye, when comparing the control dough to doughs with C. vulgaris. Sensory analysis revealed that low microalga incorporation (2 %) improved snack's global appreciation. Further results from CATA analysis revealed that subtle sensory attributes had a positive impact on global appreciation.

Performance of hybrid thrust bearing textured surface operating with electro-rheological lubricant

This article concerns with the numerical simulations of textured surface hybrid thrust bearings operating with Electro-rheological (ER) lubricant. An ER fluid comprises dielectric particles suspended in an insulating viscous medium. Electrorheological (ER) lubricants are considered smart lubricants. Reynold's equation is used to model the flow of an ER lubricant in textured surface thrust bearings. The texture is provided as hemispherical, cylindrical, elliptical, and square shape micro-depression oriented along the circumferential and radial direction. The Patir and Cheng model is used to describe micro-roughness on a thrust pad. The continuous Bingham model is used to define the viscosity of the ER lubricant in terms of yielding stress, electric field, and shear-strain rate. The Reynolds equation is solved by applying the finite element method to obtain film pressure, load-supporting capacity, frictional power loss, film stiffness, and damping parameters. The texture shapes are optimized for dimple size, depth, and length for getting maximum load-supporting capacity and stiffness coefficient, and minimum frictional power loss. The numerical results predicted an enhancement in the load-supporting capacity (+257.3%) and film stiffness parameters (+323.2%) owing to the synergistic use of ER lubricant and optimized geometric parameters of square/elliptical dimples. The frictional power loss was reported to reduce significantly (−48.8%) by the use of micro-dimples. The application of ER lubricant was also found to slightly enhance (+4.3%) the frictional power loss in textured bearings. The transverse surface roughness vis-à-vis smooth surface is observed to improve the load-supporting capacity, stiffness, and damping parameters of textured surface bearings.

LW-CovidNet: Automatic covid-19 lung infection detection from chest X-ray images.

Coronavirus Disease 2019 (Covid‐19) overtook the worldwide in early 2020, placing the world's health in threat. Automated lung infection detection using Chest X‐ray images has a ton of potential for enhancing the traditional covid‐19 treatment strategy. However, there are several challenges to detect infected regions from Chest X‐ray images, including significant variance in infected features similar spatial characteristics, multi‐scale variations in texture shapes and sizes of infected regions. Moreover, high parameters with transfer learning are also a constraints to deploy deep convolutional neural network(CNN) models in real time environment. A novel covid‐19 lightweight CNN(LW‐CovidNet) method is proposed to automatically detect covid‐19 infected regions from Chest X‐ray images to address these challenges. In our proposed hybrid method of integrating Standard and Depth‐wise Separable convolutions are used to aggregate the high level features and also compensate the information loss by increasing the Receptive Field of the model. The detection boundaries of disease regions representations are then enhanced via an Edge‐Attention method by applying heatmaps for accurate detection of disease regions. Extensive experiments indicate that the proposed LW‐CovidNet surpasses most cutting‐edge detection methods and also contributes to the advancement of state‐of‐the‐art performance. It is envisaged that with reliable accuracy, this method can be introduced for clinical practices in the future.

Spatio-Frequency Decoupled Weak-Supervision for Face Reconstruction.

3D face reconstruction has witnessed considerable progress in recovering 3D face shapes and textures from in-the-wild images. However, due to a lack of texture detail information, the reconstructed shape and texture based on deep learning could not be used to re-render a photorealistic facial image since it does not work in harmony with weak supervision only from the spatial domain. In the paper, we propose a method of spatio-frequency decoupled weak-supervision for face reconstruction, which applies the losses from not only the spatial domain but also the frequency domain to learn the reconstruction process that approaches photorealistic effect based on the output shape and texture. In detail, the spatial domain losses cover image-level and perceptual-level supervision. Moreover, the frequency domain information is separated from the input and rendered images, respectively, and is then used to build the frequency-based loss. In particular, we devise a spectrum-wise weighted Wing loss to implement balanced attention on different spectrums. Through the spatio-frequency decoupled weak-supervision, the reconstruction process can be learned in harmony and generate detailed texture and high-quality shape only with labels of landmarks. The experiments on several benchmarks show that our method can generate high-quality results and outperform state-of-the-art methods in qualitative and quantitative comparisons.

Effect of surface modification on friction characteristics of sliding bearings: A review

The purpose of the paper is to investigate the effect of surface modification on the friction characteristics of sliding bearings. This paper reviews the previous studies on the influences of surface texture, coating materials and lubricant additives on the performance of the sliding bearings. Through the theoretical models and simulation experiments between different friction couple, the researchers found that under the condition of fluid lubrication, the surface modification design can significantly improve the friction characteristics of the surface of the friction couple, which has attracted the wide attention of researchers. The development status and latest progress in improving the surface properties of friction couple are introduced mainly from the geometrical characteristics of surface texture, the matrix of surface coating materials and the types of lubricating additives. Among them, the geometric features of texture mainly include texture shape, scale, parameters, position and combination form. The types of coating material substrates mainly include iron-based alloys and aluminum-based alloys. Lubricating oil additives mainly include ionic liquids and nanoparticles. Finally, the existing problems and future development directions of surface modification are pointed out.

Design and Optimization of the Surface Texture at the Hydrostatic Bearing and the Spindle for High Precision Machining

Hydrostatic bearing spindles are widely applied in high precision grinding and turning machines due to their good dynamic stability and rotational accuracy. However, under the condition of high-speed rotations, the heat generated by the friction of the oil film will cause the shear thinning effect. It not only reduces the rotation accuracy of the spindle but also reduces the service life of the spindle. The surface texture structure and configuration between the planes play the role of homogenizing oil film temperature and preventing the bearing surface wear caused by excessive concentration of temperature, which can change the relative motion from the inside of the oil film and thus improve the performance of the hydrostatic spindle more effectively. In this paper, the influence of the surface texture shape and height on the thrust bearing performance of the hydrostatic spindle is systematically investigated by comparative analysis. The CFD simulations are developed to analyze the computational results based on the theory of viscosity-temperature characteristics. The results show that when the height of the surface structure is 1 ~ 2 times the oil film thickness, the spindle bearing performance is the best. The average temperature in the bearing region is the lowest and the accuracy of the simulations was verified by experimental results.

Shape-Texture Debiased Training for Robust Template Matching.

Finding a template in a search image is an important task underlying many computer vision applications. This is typically solved by calculating a similarity map using features extracted from the separate images. Recent approaches perform template matching in a deep feature space, produced by a convolutional neural network (CNN), which is found to provide more tolerance to changes in appearance. Inspired by these findings, in this article we investigate whether enhancing the CNN’s encoding of shape information can produce more distinguishable features that improve the performance of template matching. By comparing features from the same CNN trained using different shape–texture training methods, we determined a feature space which improves the performance of most template matching algorithms. When combining the proposed method with the Divisive Input Modulation (DIM) template matching algorithm, its performance is greatly improved, and the resulting method produces state-of-the-art results on a standard benchmark. To confirm these results, we create a new benchmark and show that the proposed method outperforms existing techniques on this new dataset.

Distribution of Lobaria pulmonaria (L.) Hoffm. in Mt Kilimanjaro and Mt Meru forests: altitudinal range and specificity to substratum tree species

AbstractIn this study, we sampled L. pulmonaria thalli from Mt Kilimanjaro and Mt Meru, Tanzania. Across all sampled tree species, a range of 1–35 thalli of L. pulmonaria were counted per trunk (up to 5 m above ground level), with sampling distributed across 13 (c. 1 ha) plots located in the sub-alpine to montane forest altitudinal gradients of Mt Kilimanjaro and Mt Meru. Descriptive analyses were performed to determine the association of L. pulmonaria with particular host trees among the study sites and regions, and linear mixed effects models (LMM) were used to explore relationships with tree-level variables. The analyses showed that most thalli of L. pulmonaria were unevenly distributed among the tree species in the montane and sub-alpine forests of Mt Kilimanjaro and Mt Meru. Host tree characteristics such as trunk circumference, height on trunk, bark texture and trunk shape appeared to have an effect on the local population size of L. pulmonaria and the frequency of occurrence. Also, the results indicated an effect of trunk circumference and tree bark on the development of L. pulmonaria thallus size among the study sites. Furthermore, host tree species, for example, Hypericum revolutum and Rapenea melanophloeos were important habitats for L. pulmonaria on both mountains, whereas Ilex mitis, Bersama abyssinica and Hagenia abyssinica were important only on one mountain. The wider literature on L. pulmonaria ecology is also reviewed and it is therefore recommended that for successful conservation of the threatened L. pulmonaria in tropical montane forests, strategies should consider the type of the forests, together with the host tree species and their size.

On the optimal texture shape with the consideration of surface roughness

The optimal texture shape considering surface roughness is determined by solving the average Reynolds equation, selecting Jakobsson–Floberg–Olsson boundary conditions, and using a genetic algorithm. The effects of surface roughness as indicated by the combined root-mean-square (RMS), surface pattern parameter, and operating parameters on the friction coefficient, area ratio, and depth of the optimal self-defined shape and optimal dimple were studied. Results show that the friction coefficient will be significantly reduced during the shape optimization considering the effect of surface roughness. The variation laws of the optimal dimple area ratio with the combined RMS, surface pattern parameter, minimum film thickness, sliding speed and the variation law of the optimal depth of the optimal self-defined shape with surface roughness and working parameters are obtained. Finally, this study concludes that the influence of roughness parameters on the optimal dimple shape is greater than that on the optimal self-defined shape under different sliding speeds.

Fabrication of random nanocones to improve wideband light trapping for thin film photovoltaic devices using nanosecond laser processing

Light-trapping is very crucial for thin film solar cells for the efficient collection of light to reach high light conversion efficiencies. Recently, the use of surface micro/nanostructure has emerged as a suitable technique to improve the absorption of light in thin solar absorbers. Amorphous silicon (a-Si) has strong absorption in the visible region. Expansion of this absorption band towards near infrared (IR) region by reducing the reflectance with light trapping has been presented in this in this work. This is achieved by fabricating random nanocones using laser texturing on the a-Si thin film surface. In this study, periodic structures with different shapes are theoretically investigated to identify the ideal texture shape for wideband light coupling and compared with the surface reflective properties of random nanocones. The light-trapping properties of random nanocones, fabricated using a ns pulsed Nd3+: YAG (neodymium-doped yttrium aluminium garnet) laser in water and air are investigated, and the influence of texture dimensions in improving the antireflection characteristics are studied. Numerical simulation shows the reduction in reflection in the near (IR) region with the random nanocones compared to regular periodic structures, overall exhibiting wideband antireflectance in ultraviolet (UV)–visible–near IR region due to the presence of multiscale structures. Experimentally measured reflectance across the whole spectra decreased by 14% to 19% in comparison with the untextured surfaces suggesting an enhancement in light coupling through multiple reflections on the laser fabricated nanocones. A small decrease of about ∼ 0.15 to 0.8% in efficiency was observed in the first one hour when continuously exposed to light in the thermal stability studies, and it remained stable for the rest of the test. This study will help in designing thin film solar absorber with a wide absorption range to aid in meeting the energy demand.

Roughness Effects of Textured Surfaces in Hydrodynamic Lubrication

Several studies have been conducted to improve and model the lubricated contact between surfaces. The main subjects were defining the hydrodynamic parameters to reduce energy losses and protect the environment. Some of the proposed models have studied the effect of textures in hydrodynamic lubrication and have proved that adapted shapes and geometries can improve the performance of lubricated contacts. A hydrodynamic model was developed by assuming the roughness of the textured surface and considering the cavitation in a steady-state regime. The proposed model was validated and compared with the analytical model of Fowell &lt;i&gt;et al.&lt;/i&gt; [1]. Three different textures shapes were considered. The results showed that the rough-textured thrust affects the hydrodynamic performance significantly. Thus, by increasing the arithmetic roughness of textured surfaces, the hydrodynamic pressure, and the lifting force increase depending on the texture shape. A rougher surface slightly increases the friction force for the three considered textures.

Influence of hydroxyapatite composite coating on the textured surface of patient specific dental implant: An in silico 3D finite element study

Titanium dental implants are one of the best replacements for the natural teeth. It can reduce early failures compared to other implant materials. During mastication, generally, implant loosening occurs between the bone and the implant surface. Therefore, to resolve this issue, surface modification of the implant surface was done which can provide better bonding between the implant and the bone. In this study, we designed five different types of surface texture on the implant and compared them with the solid non-textured implant. In addition to that, we used four different hybrid composite coating materials along with hydroxyapatite, for better osseointegration and bone formation. Thus, we modeled a bony structure like mandible using solid modeling technique. We considered average biting force of 250 N with different bone conditions. After the analysis, it has been observed that ‘U’ and ‘V’ shape textures exhibited the optimized textures for dental implant with coating combination of HA1.5TO1.5SR and HA3Sr for weak and very weak bone conditions. The coating for straight and dome shaped textures for strong and very strong bone conditions showed better results, whereas ‘U’ shaped and dome shaped textures showed better results for normal bone condition.

Temperature Distribution Measurement and Internal Flow Visualization in the Lubrication Film of Non-contacting Mechanical Seals

The surface textures of non-contacting mechanical seals form a few micrometers thick lubrication film that aids in achieving high performance of the seal. Improved texture design can control internal fluid flow, improving the sealing performance and lubrication characteristics. However, film thickness is sensitive to thermal deformation, making seals vulnerable to heat. Excessive temperature increases and deviations in temperature distribution can cause performance degradation or damage to seals. Previous studies have suggested that heat transfer impacting these thermal issues may be influenced by the internal flow, however, experimental studies examining flow fields have not been conducted yet. This study presents the design of experimental equipment, measurement of temperature distributions and observation of flow fields in lubrication films with three different textures—non-textured, Rayleigh step, and spiral groove. Furthermore, the results were compared with those of numerical analysis. Temperature was found to be higher at the downstream end of the flow. In particular, the Rayleigh step seal exhibited a nonuniform temperature distribution that alternated between low and high-temperature areas. This was caused by cooling related to radial grooves that had a pumping effect. In contrast, a uniform temperature distribution was confirmed in the case of the spiral groove seal, which was formed by mixing outer and inner side fluids. The results indicate that the temperature distribution in lubrication films can be controlled via flow field by the surface texture shape or depth to protect against thermal degradation and to achieve high reliability of non-contacting mechanical seals.Graphical

Color contour texture based peanut classification using deep spread spectral features classification model for assortment identification

Agriculture is one of great economic growth in India by producing variety of peanuts for various co products development. Peanut Crop and weed identification is an important step in developing a highly efficient automotive peanut production system. Most of the exiting classification fix the threshold margins to select the inappropriate features cause classification inaccuracy. Deep learning, as a powerful image processing technology, can extract conventional and characteristic features in layers. Spectral information is used as the input of the network, and the output spectral characteristics of the network are directly passed to the subsequent classifiers to achieve pixel-level classification. To resolve the classification categorization problem, we propose a Color contour texture based peanut classification using deep spread spectral features classification model for variety identification. Initial the Cascading subset Feature Filtering (CSFF) is applied to select the shape textures, color gradient rate form histogram equivalence and returns the feature scalar values. Based in CSFF the feature weight is attained to Social Spider Optimization to select the Impact Features Weight (SSO-IFW). The optimal object segmentation war applied based on cross fold object verification to select the shape projection features. Then Ada Boosting classifier generate the type of object structural for identifying type definition to generate pattern to produce peanut characteristic clusters. Based on Image Features recognition clusters, deep spread spectral neural classification is applied to train the features with soft-max logical activation function with Adaptive Convolution Neural Network (ACNN) to categorize the peanuts based on feature characteristics using image recognition, 20 varieties of peanut are collected through scanner type dataset to train the images into deep neural network. This produce high classification accuracy up to 89 %, high precision, recall rate under F-measure with low false rate. This achieves high classification than other existing methods.

Impact of packaging design method of cultural heritage with Biotechnology

Packaging is an important element in marketing, as it helps to communicate the message of the product and blends in with the market trends. Packaging design has been an effective tool for food manufacturers to express their own values, enhance customer’s perceptions and experience of using the product. However, recent packaging design, such as cartons with textured surfaces or geometric shapes that signal a new kind of energy-efficient insulation technology have become more common and wide spread across many sectors. Meanwhile, bio-technology has been developing rapidly in recent years and research on packaging design oriented at biotechnology is emerging gradually. Experimental results: the average printing time of the intangible cultural heritage product packaging personalized design method in this paper and the other two intangible cultural heritage product packaging personalized design methods is 23.987h, 28.577h and 28.149h, which proves that the intangible cultural heritage product packaging personalized design method integrating 3D printing has higher application value.