Surface Texture Analysis Research Articles

Analysis of High-Friction Surface Texture with Respect to Friction and Wear

High Friction Surfaces (HFS) are applied to increase friction capacity on critical roadway sections, such as horizontal curves. HFS friction deterioration on these sections is a safety concern. This study deals with characterization of the aggregate loss, one of the main failure mechanisms of HFS, using texture parameters to study its relationship with friction. Tests are conducted on selected HFS spots with different aggregate loss severity levels at the National Center for Asphalt Technology (NCAT) Test Track. Friction tests are performed using a Dynamic Friction Tester (DFT). The surface texture is measured by means of a high-resolution 3D pavement scanning system (0.025 mm vertical resolution). Texture data are processed and analyzed by means of the MountainsMap software. The correlations between the DFT friction coefficient and the texture parameters confirm the impact of change in aggregates’ characteristics (including height, shape, and material volume) on friction. A novel approach to detect the HFS friction coefficient transition based on aggregate loss, inspired by previous works on the tribology of coatings, is proposed. Using the proposed approach, preliminary outcomes show it is possible to observe the rapid friction coefficient transition, similar to observations at NCAT. Perspectives for future research are presented and discussed.

The Cutting Edge: Surface Texture Analysis following Resection of Nerve Stumps Using Various Instruments.

Background:Preparation of nerve ends is an essential part of nerve repair surgery. Multiple instruments have been described for this purpose; however, no consensus exists regarding which is the least traumatic for tissue handling. We believe that various instruments used for nerve-end excision will lead to different surface roughness.Methods:Median and ulnar nerves from fresh frozen cadavers were dissected, and 1–2 cm lengths were excised using a No. 11 blade, a razor blade, or a pair of scissors. Using electron microscopy, 3-dimensional surface analysis of roughness (Sa) for each specimen was performed using ZeeScan optical hardware and GetPhase software (PhaseView, Buisson, France). An ANOVA or Kruskal-Wallis test compared roughness measures among cutting techniques.Results:Forty nerves were included. Of these, 13 (32.5%) were cut using scissors, 15 (37.5%) using a razor blade, and 12 (30%) using a No. 11 blade. An ANOVA test showed statistical differences in Sa among the cutting techniques (P = 0.002), with the lowest mean Sa noted in the scissors group (7.2 µM, 95% CI: 5.34–9.06), followed by No. 11 blade (7.29 µM, 95% CI: 5.22–9.35), and razor blade (11.03 µM, 95% CI: 9.43–12.62). Median Ra (surface profile roughness) was 4.58 (IQR: 2.62–5.46). A Kruskal-Wallis test demonstrated statistical difference in Ra among techniques (P = 0.003), with the lowest by No. 11 blade (3 µM, IQR: 1.87–4.38), followed by scissors (3.29 µM, IQR: 1.56–4.96), and razor (5.41 µM, IQR: 4.95–6.21).Conclusion:This novel technique of 3-dimensional surface analysis found razor blade use demonstrated poor roughness, whereas a No. 11 blade or nerve-specific scissors led to equivocally smooth nerve ends.

Aurignacian grinding stone from Surein I (Crimea): “trace-ing” the roots of starch-based diet

This study is applied to the unique grinding stone from Surein I retrieved in the Aurignacian layers of the rockshelter located in the south of the Crimea Peninsula. Our research enables us (i) to make reliable inference on the agency establishing the functional modification on the surface of the Surein I grinding stone, (ii) to demonstrate this grinding stone served as steady surface (Face A) to mechanically process plant materials including roots and tubers (under surface storage organs, USOs) and (iii) to set a chrono-cultural framework for starchy plants tenderization, also responding to key issues relating to the dietary breadth of early waves of Homo sapiens at the northern latitudes. We present a pilot research design which integrates data derived from macro and micro-scales techniques, by coupling use-wear traces analysis and use-related starch granules observation. The multi-scale approach allows distinctive resolutions for surface texture analysis thanks to the combined use of stereo, metallographic and digital microscopes; whereas transmitted and polarized light microscopes were used to observe use-related biogenic residues (U-RBR), namely starch granules, and SEM provided resolution down to the nano-scale. Our data suggest that Homo sapiens was exploiting the rich environment of the Pontic steppe-grassland since its earliest presence in south-eastern Europe by processing starchy plants to obtain calorific food. Moreover, this study brings fresh lines of evidence to the broadening of dietary strategies during late MIS 3 (40–25 ka calBP) by analysing ground stones from the poorly investigated non-flaked industry, and opens new scenarios for the reasoning on Homo sapiens successful colonization of Eurasia.

Optimization and wear characteristics of TiAlN coated carbide when machining hardened high thermal conductivity (HTCS-150) die steel.

High Thermal Conductivity Steel-150 (HTC-150) is a specific steel designed for use in the hot stamping process as a stamping die. HTCS-150 die steel was difficult to machine due to its high strength, hardened state, and high thermal conductivity characteristics, which necessitated parameter control for a fine surface finish and maximum tool life. The characteristics of tool wear when machining HTCS-150 hardened steel (52 HRC) with a ball nose end mill TiAlN coated carbide insert is presented in this study. Cutting speed, feed rate, and axial depth of cut have all been varied in machining trials. Response surface methodology experimental design was used to create a parametric optimisation model. The results indicate that the model develops an accurate prediction, with comparisons between measured and expected results suggesting that the model operates within the 90% prediction interval with an error of less than 10%. The lowest tool wear was achieved at 130 m min−1 cutting speed, 0.4 mm/tooth feed rate, and 0.1 mm axial depth of cut, according to the optimisation results. The most influenced cutting parameters were found to be feed rate and depth of cut, followed by cutting speed. The wear surface texture analysis revealed coating delamination, adhesion, built-up edge formation, and tool edge chipping. The findings of this experimental study can be used to machine the HTCS-150 for the longest possible tool life while maintaining a fine surface finish.

Fractional spline wavelets within the surface texture analysis

The article describes the possibilities of applying fractional spline wavelets for diagnosing the surface texture of machine parts. The research was conducted on the surface profiles of samples prepared using additive technology and face milling. The surface profiles were analysed using fractional spline wavelets for various scaling function order values. The obtained results were compared with filtration results acquired using a one-dimensional wavelet transform, for various groups of mother wavelets. In order to better illustrate the spline wavelet application-wise possibilities, the analysis was conducted at several decomposition levels. The executed tests indicated the advantages and disadvantages of an approach towards surface texture using fractional spline wavelets, which can be directly translated to better surface diagnostics of manufactured machine parts.

Surface texture analysis of the X5CrNi18-10 steel after cutting with abrasive water jet and photon beam (laser)

The article presents an analysis of the geometric structure of the surface of X5CrNi18‑10 steel sheet after cutting with a abrasive water-jet (AWJ) and a photon beam (laser). Both methods and the workpiece material were also described. Using the laser triangulation method, the cut surface texture was measured by opto-digital microscopy. Additionally, microscopic images of the cut surface were made using the Dino-Lite Edge AM7915MZT microscope by ANMO Electronics Co. The analysis of changes in the value of the Sa parameter for the surface after laser cutting and abrasive water-jet showed that the thickness of the cut material has the most significant influence on the obtained measurement results.

Plain water jet cleaning of titanium alloy after abrasive water jet milling: Surface contamination and quality analysis in the context of maintenance

Abrasive water jet (AWJ) milling process, though being an effective alternative to conventional machining for difficult-to-machine materials, induces abrasive embedment which is an issue for repair application by structural bonding. In this context, the effectiveness of cleaning Ti6Al4V specimens by Plain Water Jet (PWJ) post AWJ milling is studied. For this, Ti6Al4V specimens are milled by AWJ process with varying parameters to create several levels of surface quality and contamination. Different characterization techniques have been used to perform a multi-scale analysis of the machined surfaces and surface quality has been quantified by an innovative criterion called “crater volume” (Cv). Then the specimens are subjected to PWJ cleaning operation (using a single set of parameters chosen after preliminary study). Finally, surface texture analysis and contamination quantification is performed and compared with the AWJ milled surfaces. The results revealed that PWJ cleaning reduced the surface contamination by 65% without any significant change in Cv, surface texture and topology. However, it was found that it was impossible to dislodge deeply embedded particles. The comparison of pre and post-cleaning contamination levels also revealed that PWJ cleaning process efficiency depends on the AWJ milling parameters (mainly pressure).

Problems of Selecting the Wavelet Transform Parameters in the Aspect of Surface Texture Analysis

Problems of Selecting the Wavelet Transform Parameters in the Aspect of Surface Texture Analysis

Reduction of the end-effect in surface texture analysis

The edge-effect in the filtering of the results of surface topography measurements is presently one of the most significant and radical challenges in surface texture assessments. Errors in data analysis are next to measurement problems the most affecting factor of the accuracy for the results obtained. This paper investigates reduction of the edge-filtering-effect of cylinder liner surface textures. Different edge-robust data analysis methods were applied and compared with commonly-used procedures, e.g. those available in commercial software of measurement equipment like various regression Gaussian filters. It was assumed that some of surface topography features are more vulnerable for their false estimation when they are edge-locates and their size (depth, width, section) might be a potentially decisive factor in selecting a correct procedure. The influence of the proposed methods on the selected surface topography parameters (from ISO 25178 standard) calculation and their comparison with the typically used procedures (e.g. Gaussian regression filter) was also comprehensively studied. It was found that some of the digital filters, commonly recommended for commercial software of measuring equipment, did not always provide consistent or direct results when textures with relatively large valleys were carefully examined.

Оценка параметров текстуры прецизионных поверхностей с применением квазиоптимальных корреляционных алгоритмов

The authors considered a new method of texture analysis of machined precision surfaces based on using computer optics and the autocorrelation method of processing the images of micro-relief textures under the study. This method is based on a probabilistic comparative evaluation of the unknown texture of the micro-relief under the investigation with the available textures of reference micro-patterns, in which microrelief parameters are determined. The paper proposes an approach to identify the profile surface roughness of a gas turbine engine (GTE) blade after vibro-contact polishing according to the parameters of correlation surface texture. The authors studied the surface micro-geometry of the blade back and pressure side using the optoelectronic complex based on the calculation of the average amplitude of the variable component of an autocorrelation function resulting from computer processing of a surface video image. The application of the electrooptic method for evaluating the surface texture of compressor and turbine blades allows building the surface roughness fields and more deeply analyzing the technology of final processing of the GTE blade feather profile. The relevance and novelty of the study lie in the promising technique to evaluate the surface quality parameters using the electrooptic method. A special feature of this method is the measurement of surface area roughness, while the stylus methods measure the roughness of the surface profile. An important advantage of the proposed method is its application to measure the roughness parameters of a curved surface by a non-contact method, which is advanced since there are surfaces of parts that do not imply being scratched with a diamond needle.

Effects of different irrigation protocols on dentin surfaces as revealed through quantitative 3D surface texture analysis

The combination of ethylenediaminetetraacetic acid (EDTA) and sodium hypochlorite (NaOCl) has been advocated as an effective irrigation methodology to remove organic and inorganic matter in root canal therapy. Yet, it was suggested that both solutions might lead to structural changes of the dentinal wall surface, depending on the order of application which might affect sealer mechanical retention. This study aims to evaluate the effect of different irrigating protocols on dentin surface roughness using quantitative 3D surface texture analysis. Data stems from 150 human root dentin sections, divided into five groups, each prepared according to one of the following protocols: Negative control; 17% EDTA; 17% EDTA followed by 5.25% NaOCl; 5.25% NaOCl; and 5.25% NaOCl followed by 17% EDTA. Each dentin sample was examined for its three-dimensional surface texture using a high-resolution confocal disc-scanning measuring system. EDTA 17% and the combined EDTA 17% with NaOCl 5.25% showed considerably higher roughness properties compared to the control and to NaOCl 5.25% alone. However, the irrigation sequence did not affect the dentin roughness properties. Therefore, mechanical retention is probably not dependent upon the selection of irrigation protocol sequence.

Mathematical approach to the validation of form removal surface texture software

A new approach to the validation of surface texture form removal methods is introduced. A linear algebra technique is presented that obtains total least squares (TLS) model fits for a continuous mathematical surface definition. This model is applicable to both profile and areal form removal, and can be used for a range of form removal models including polynomial and spherical fits. The continuous TLS method enables the creation of mathematically traceable reference pairs suitable for the assessment of form removal algorithms in surface texture analysis software. Multiple example reference pairs are presented and used to assess the performance of four tested surface texture analysis software packages. The results of each software are compared against the mathematical reference, highlighting their strengths and weaknesses.

Diets of Pleistocene insular dwarf deer revealed by dental microwear texture analysis

Microwear is defined as the microscopic scars left during mastication on the surfaces of teeth. Because microwear reflects the physical properties of the food eaten by animal, it has been used for reconstruction of the diets of extinct animals. We investigated the dental microwear of the extinct insular dwarf deer Cervus astylodon using materials excavated from Late Pleistocene archaeological sites on Okinawa Island (the Hananda-Gama Cave site and the Yamashita-cho Cave I site). We applied three-dimensional surface texture analysis to quantitatively evaluate microwear features. We analyzed 293 individual sika deer (Cervus nippon) from 15 populations in Japan with quantitative dietary data clarified by rumen contents or feces analyses, constructing one of the most comprehensive microwear databases of extant ruminants. We found that deer with a higher consumption of graminoids showed rougher tooth surfaces than those browsing on trees owing to the high content of abrasive silica in graminoid leaves. Using a regression equation relating surface roughness parameters and the percentage of graminoids in the diet, we estimated that C. astylodon from the Hananda-Gama Cave might have consumed a diet consisting of approximately 44% graminoids, whereas we estimate a predominantly graminoid-based diet (ca. 78%) for deer from the Yamashita-cho Cave. Therefore, contrary to the findings of mesowear and stable carbon isotope analysis, which indicated a browsing diet, we propose that C. astylodon were mixed feeders or possibly grazers. These findings provided an important implication of their peculiar evolution on islands.

Mathematical approach to the validation of surface texture filtration software

A novel method for the validation of surface texture filtration software is introduced. Mathematically traceable reference pairs for linear Gaussian filtration are developed, utilising Fourier series surface definitions in conjunction with the frequency dependent transmission characteristic of the linear Gaussian filter. The novel method is demonstrated using a library of reference pairs to validate the performance of five surface texture analysis software packages. Investigations into the effects of different surface properties are made in relation to the deviation of the software-obtained results from the traceable reference values. Analysis of variance tests are used to verify the statistical significance of the results.

A method for the taphonomic assessment of bone tools using 3D surface texture analysis of bone microtopography

Increasingly researchers have employed confocal microscopy and 3D surface texture analysis to assess bone surface modifications in an effort to understand ancient behavior. However, quantitative comparisons between the surfaces of purported archaeological bone tools and experimentally manufactured and used bones are complicated by taphonomic processes affecting ancient bone. Nonetheless, it may be reasonable to assume that bones within the same deposits are altered similarly and thus these alterations are quantifiable. Here we show how unworked bones can be used to quantify the taphonomic effect on bone surfaces and how this effect can then be controlled for and incorporated into an analysis for evaluating the modified surfaces of purported bone tools. To assess the baseline taphonomy of Middle Paleolithic archaeological deposits associated with typologically identified bone artifacts, specifically lissoirs, we directly compare the surface textures of ancient and modern unworked ribs. We then compare the ancient unworked ribs and lissoirs to assess their differences and predict the ancient artifacts’ original surface state using a multilevel multivariate Bayesian model. Our findings demonstrate that three of five tested surface texture parameters (Sa, Spc, and IsT) are useful for distinguishing surface type. Our model predictions show that lissoirs tend to be less rough, have more rounded surface peaks, and exhibit more directionally oriented surfaces. These characteristics are likely due to anthropogenic modifications and would have been more pronounced at deposition. Quantifying taphonomic alterations moves us one step closer to accurately assessing how bone artifacts were made and used in the ancient past.

Effects of surface texture and its mineral composition on interfacial behavior between asphalt binder and coarse aggregate

The interfacial behavior between asphalt binder and mineral aggregate could directly affect water infiltration and durability of asphalt mixtures. The properties of aggregate, especially the mineral composition and surface texture (ST) characteristics, have a significant impact on the interfacial performance between asphalt and aggregate. In this study, the texture characteristics of aggregates with different lithology (granite, limestone and tuff) were obtained by aggregate image measurement system (AIMS), and the mineral composition of aggregates was determined using X-ray diffraction (XRD). Based on the pull-off test combined with the water immersion method, the effects of aggregate mineral properties, water immersion and its interaction time on interfacial behavior between asphalt and aggregate, were quantitatively analyzed. Furthermore, molecular dynamics models with different mineral compositions and water film thickness were utilized to analyze interfacial behaviors. Results showed that the acid-base analysis method might not serve as an accurate assessment of the aggregate and asphalt interface properties. In addition, the sensitivity analysis of tensile strength (TS) and ST was an effective tool for the control test, and the range obtained was the variation of 0.1 MPa TS within the range of eight ST value with 95% confidence level, which can be adopted for the parallel test of real aggregates with large texture differences. Results also showed that the interface strength of granite was highly affected by the increase in immersion time. In addition, the molecular dynamics model calculation results showed that the electrostatic adsorption capacity of albite with {100} surface was much stronger than {001} section. The Wmwa (adhesion work considering water film) index can effectively characterize the attenuation of adhesion ability, and the electrostatic adsorption of albite model was greatly affected by water immersion.

Image surface texture analysis and classification using deep learning

Recently, the classification of surface textures is carried out using various modelling approaches. To analyse the surface texture, most of the techniques uses large amount of training data which adds up to considerable computational cost. However, the implementation of various neural network models also requires significant amount of training images to classify surface textures. In the proposed paper, a deep learning-based model is presented using convolution neural network (CNN). Further, this model is divided into two sub models knowing model-1 and model-2. The approach is designed with customized parameters configuration to classify surface texture using a smaller number of training samples. The image feature vectors are generated using statistical operations to compute the physical appearance of the surface and a CNN model is used to classify the generated surfaces with appropriate labels into classes. The Kylberg Texture dataset is used to evaluate the proposed models using 16 texture classes. The advantage of proposed models over pre-trained networks is that the entire models is customized according to specific training requirements. Further, to demonstrate the state-of-the-art results, the proposed approach is compared with other existing techniques. Our experimental results are better than the conventional techniques and achieves an accuracy of 92.42% for model-1 and 96.36% for model-2. In addition, the proposed models maintain balance between accuracy and computational cost.

The multi-scale analysis of ceramic surface topography created in abrasive machining process

The paper looks at the issues related to the shaping technology of the parts made of ceramic materials and at the influence that machined surface topography has on surface functional properties. The mono- and polycrystalline ceramic parts were shaped in the four treatments of finishing process. The studies of surface topography were performed using three measurement instruments: interference microscope, scanning electron microscope, and atomic force microscope. It was noticed that multi-scale analysis of surface topography allows for obtaining a complementary and detailed overview of changes that ceramic parts undergo during abrasive machining process. The characteristics of the machined surface created in finishing operations were prepared based on the quantitative and qualitative descriptions. Parametric analysis of surface texture allowed for assessing the quality and changes of the machined surface in the technological process. During the non-parametric analysis, surface views after each abrasive machining treatment showed different kinds of surface defects (cracks, crumbles, dents or scratches) which could play an important role in the operation process, i.e. generating various wear mechanisms.

Influence of surface properties on electro‐chemical supercapacitors utilizing Callerya atropurpurea pod derived porous nanocarbons: Structure property relationship between porous structures to energy storage devices

AbstractSurface properties always play a dominant role in the energy storage devices. Understanding the surface phenomena is the key to tune the energy storage device using biowaste based porous nano carbons. Here, Callerya atropurpurea pod derived peculiar porous nanocarbons are synthesized by pyrolysis at different temperatures without any synthetic templates approach. Elaborate analysis of surface textures on the effect of pore size, volume and specific surface area on specific capacitance and frequency response behavior of nanocarbons were studied in detail. Electrochemical characterizations establish the mutuality of porosity and microtextural properties of nanocarbons with specific capacitance. The electrochemical characterization of the novel materials as supercapacitor electrode shows a high specific capacitance of 326.54 F g−1 at 0.25 A g−1 in 1.0 M KOH. A practical symmetric supercapacitor device is fabricated with a specific capacitance of 86.38 F g−1 at 0.1 A g−1, and high energy density of 27.0 Wh kg−1. This symmetric supercapacitor also possesses outstanding capacitance retention of 92.16% for 5000 charge discharge cycles and also stability of 97.17%, after voltage holding at the maximum voltage for 100 hours. Present manuscript gives the strong evidence for structure‐property relationships so that one can tune the energy storage devices effectively.

Experimental investigations of threads surface integrity manufactured by cutting insert and with internal thread rolling head

The objective of this study was to provide insights for a deeply understanding of the threads surface integrity manufactured by cutting tap, rolling tap, cutting insert and with internal thread rolling head, using the multiscale surface texture and fractal analysis in order to show the performance of the internal rolling head by mechanical tests and also to highlight the advantages of rolling internal threads. A series of eight internal thread samples M80×1.5 manufactured by cutting insert and internal thread rolling head were analyzed on their surface texture characteristics and material properties. Surface characteristics of low carbon steel Ç1020 (equivalent to AISI 1020) were quantified by measuring four locations on regions of each sample. The threads made by cutting inserts and internal thread rolling head were subjected to tensile test and it was found that the average tensile load of threads made by internal rolling head is higher with 20% than the threads made by cutting insert. Furthermore, the internal thread sections of samples were analyzed using an optical projector by comparing the appearance of failed threads at low magnification to known failure modes, as well as scanning electron microscopy (SEM) for surface material characterization. It was found that it can be discriminate between the thread surface regions of samples manufactured by cutting insert and with internal thread rolling head, using area-scale analysis and surface texture characteristics. The surface micro-morphology results can be applied in studies about improving the lifetime of similar rolled threads and for mathematical modelling of lubrication processes between tool and workpiece.