Scale Texture Research Articles

Research on the Effects of Spatial Forms in Residential Blocks on Road Traffic Noise Distribution in Typical City of China

Integrating the block system into construction is the current trend in the development of residential areas in China. Road traffic noise is the major noise source in residential blocks, and its relationship with spatial forms of blocks remains unclear. In this study, 852 block models (258 block road network models and 594 models with buildings inside) were established and simulated with SoundPLAN 8.2 software, in order to reveal the impact of spatial forms (road network morphology, neighborhood scale, and architectural texture) on the road traffic noise distribution in residential blocks. Meantime, a prediction model based on spatial morphology parameters is proposed. It was found that (1) Without considering the impact of buildings, both the road network morphology and neighborhood scale parameters have significant effects on the distribution of road traffic noise, but road network morphology has a larger effect than neighborhood scale. (2) In the presence of buildings within the block, architectural texture parameters have effects on the distribution of road traffic noise, but to a lesser extent than road network morphology and neighborhood scale parameters. (3) This research employs principal component analysis to reduce the dimensionality of urban spatial form parameters. Subsequently, a model was developed to predict overall noise exposure levels in residential areas, which was validated by example. This model can be used as a tool for rapid prediction and diagnosis of the block acoustic environment. These findings offer insights for the planning and design of residential blocks from the perspective of optimizing the acoustic environment.

Laser-induced protruded bioinspired texturing of Ti-6Al-4V for controlled wettability in biomedical application

Bioinspired protruded textures with variable surface morphology and characteristics are getting worldwide popularity due to their wider applications. Among them controlled wettability for different materials through bioinspired textures is very essential to reduce the adhesion, bacterial contamination and growth, and drug delivery application. Even, identification and efficient fabrication of favorable bioinspired protrusions with optimum parameters are comparatively complex from normal textures through any material processing methods due to their complex shapes, form accuracy and dimensions. Therefore, this work targets the fabrication of four different types of protruded bioinspired textures namely, fish scale, protruded square, protruded circular, Python scale (snake) textured surface on biomedical grade Ti-6Al-4V titanium alloy for controlling the wettability using femtosecond laser surface texturing (LST). The optimum process parameters for the machining of Ti-6Al-4V were set as a temporal width of 350 fs, output power of 5.5 W, wavelength of 1030 nm, scanning speed of 100 mm/s and pulse rate of 500 KHz and three repetitions for all the texture types. To examine the effect of texture type, perimeter of all the fabricated textures was kept constant. Further, effect of varying perimeters was also analyzed for perimeter ranges from 300 to 500 µm. Surface morphology and characteristics were also analyzed for the measurement of texture consistency, dimensions and composition which was also related to the wettability results examined by static contact angle of the sessile drop method. Wetting of fish scale texture is decreased with increasing perimeter whereas of all other textures, wettability is going to be improved significantly.

Study on the influence of tire polishing on surface texture durability and skid resistance deterioration of asphalt pavement

As an inherent attribute of asphalt pavement, texture durability is the essential reason for the change in skid resistance. However, different scale texture deterioration behavior remains unclear by tire wearing at present. To explore the influence of the durability of multi-scaled textures on skid resistance, nine pavement specimens were tested using the Harbin polishing and dynamic friction integrated experimental machine (HPFM). The pavement anti-skid texture tester (PATT-II) was used for high-precision texture scanning and reconstruction. The results show that the texture richness and skid resistance of the three types of pavements in 300 min polishing are ranked as Open-graded Friction Coarse (OGFC) > Stone Mastic Asphalt (SMA) > Asphalt Concrete (AC), while SMA presents the best durability, determined by the material skeleton structure of asphalt mixture. The macro-texture deterioration occurs slightly at first and then tends to stabilize in 300 min polishing. The micro-texture deterioration behavior is the same as the μHPFM, increasing rapidly at the beginning, then slowly decreasing, and finally remaining constant. This deterioration is caused by the asphalt damage and continuously wearing aggregate surface. The 2D-PSD deterioration behavior is more significant with a smaller texture scale in 300min polishing, and the most considerable contribution wavelength in the microscopic scale range is 0.15 mm–0.3 mm, which is determined by the adhesion characteristics and molecular mechanism between a mineral mixture and asphalt material. The influence of pavement texture on the dynamic friction coefficient is significantly different under different water film thicknesses, the micro-texture and macro-texture play the main roles in boundary and mixed lubrication, respectively.

Effect of Salt (Nacl) and Vacuum Packaging on Some of the Quality Attributes of Snakehead Fish

Snakehead fish (Chana striata) is one of the important protein sources among Indonesian people. However, the shelf life is short leading to limited use of fresh snakehead fish. This study aimed to analyse the effect of vacuum packaging and addition of salt on the sensory properties, total plate count, water activity and pH of fresh snakehead fish. The fish was salted (NaCl) at various concentrations, including 0, 5, 10 and 15%, and kept for 14 days at refrigeration temperature (± 3°C). Sensory evaluation, total plate count (TPC) and water activity (aw) measurements, and pH analysis were performed at day 0, 7 and 14. All groups with salt addition exhibited a significantly slower decrease in the mean scores (9-point hedonic scale) of color, aroma, appearance and texture (p < 0.05), with the decrease for all sensory properties detected at day 7 of storage. In microbial tests, a significant increase in TPC was observed in the groups with 0% and 5% salt addition (p < 0.05). The group with 15% salt addition showed the lowest water activity. Also, the group without salt addition had the highest pH value. This study demonstrated that addition of salt to snakehead fish might gives beneficial effects on the shelf life of a vacuum packaged product. However, the optimum shelf life using vacuum packaging and salt addition needs further study.

Investigating Microbial Biosignatures in Aeolian Environments Using Micro-X-Ray: Simulation of PIXL Instrument Analyses at Jezero Crater Onboard the Perseverance Mars 2020 Rover.

Assessing the past habitability of Mars and searching for evidence of ancient life at Jezero crater via the Perseverance rover are the key objectives of NASA's Mars 2020 mission. Onboard the rover, PIXL (Planetary Instrument for X-ray Lithochemistry) is one of the best suited instruments to search for microbial biosignatures due to its ability to characterize chemical composition of fine scale textures in geological targets using a nondestructive technique. PIXL is also the first micro-X-ray fluorescence (XRF) spectrometer onboard a Mars rover. Here, we present guidelines for identifying and investigating a microbial biosignature in an aeolian environment using PIXL-analogous micro-XRF (μXRF) analyses. We collected samples from a modern wet aeolian environment at Padre Island, Texas, that contain buried microbial mats, and we analyzed them using μXRF techniques analogous to how PIXL is being operated on Mars. We show via μXRF technique and microscope images the geochemical and textural variations from the surface to ∼40 cm depth. Microbial mats are associated with heavy-mineral lags and show specific textural and geochemical characteristics that make them a distinct biosignature for this environment. Upon burial, they acquire a diffuse texture due to the expansion and contraction of gas-filled voids, and they present a geochemical signature rich in iron and titanium, which is due to the trapping of heavy minerals. We show that these intrinsic characteristics can be detected via μXRF analyses, and that they are distinct from buried abiotic facies such as cross-stratification and adhesion ripple laminations. We also designed and conducted an interactive survey using the Padre Island μXRF data to explore how different users chose to investigate a biosignature-bearing dataset via PIXL-like sampling strategies. We show that investigating biosignatures via PIXL-like analyses is heavily influenced by technical constraints (e.g., the XRF measurement characteristics) and by the variety of approaches chosen by different scientists. Lessons learned for accurately identifying and characterizing this biosignature in the context of rover-mission constraints include defining relative priorities among measurements, favoring a multidisciplinary approach to the decision-making process of XRF measurements selection, and considering abiotic results to support or discard a biosignature interpretation. Our results provide guidelines for PIXL analyses of potential biosignature on Mars.

Research on the Optimal Design Approach of the Surface Texture for Journal Bearings

Aiming to improve the comprehensive performance of the journal bearing system, this paper presents a multi-objective adaptive scale texture optimization design approach. A mixed lubrication model for the textured journal bearing system is established by considering the effects of cavitation and roughness. The geometrical parameters of the textures were co-optimized using a multi-objective grey wolf optimizer to obtain the optimal texture schemes that are suitable for different operating conditions. Through this approach, the influences of different texture schemes under transient operating conditions can be investigated. According to the results, it was found that different texture schemes result in different friction reduction effects. Proper surface texture is beneficial in increasing the minimum oil film thickness and reducing the possibility of asperity contact. The adaptive scale texture exhibits strong adaptability and achieves significant hydrodynamic effects. Therefore, the developed approach provides valuable insights for the optimization design of journal bearing systems.

The friction of surface textured cylinder liner segments modified by Direct Laser Writing and Direct Laser Interference Patterning processes

Direct Laser Writing (DLW) using ultrashort pulsed lasers and galvanometer scanning, has become an established process for surface texturing, allowing an extensive variety of feature geometries and texture designs to be produced. The minimum feature sizes that can be generated are however limited by factors such as the laser output power, beam diameter, beam wavelength and associated optics. To address the need to produce even smaller texture features, Direct Laser Interference Patterning (DLIP) has been developed, which utilises bespoke beam splitting and converging optics to produce periodic interference fringing and enabling surface textures in the micrometric size range to be produced.In this study, the texturing of cast iron cylinder liner segments using DLW and DLIP processes is explored, to assess their tribological performance in high efficiency internal combustion engines, such as for hybrid applications. To facilitate the designs of textures and to capture high resolution data on surface interactions at specific points in the combustion cycle, the segmentation of cylinder lines and piston rings is undertaken. The results of tribology tests covering combinations of high and low speeds and contact pressures, have shown that the mechanical honing of cylinder liners could potentially be replaced with the cleaner DLIP texturing as an alternative.Optimised texture designs using the DLW process achieved up to a 54 % reduction in kinematic friction between the piston ring and textured cylinder liner surfaces, compared with mechanically honed cylinder liner segments. These results have indicated that DLW texturing offers the best improvement in friction performance in the boundary and mixed lubrication regimes at higher contact pressures, at both lower and higher sliding speeds. The results also provide useful comparative data on the performance of meso and micrometric scale textures and how they can be best applied to cylinder liners.

Multi-scale conditional diffusion model for deposited droplet volume measurement in inkjet printing manufacturing

The volume consistency of deposited droplets is regarded as a core quality evaluation to achieve zero-defect manufacturing (ZDM) in inkjet printed organic light-emitting diode (OLED). In order to improve the product quality, the causal links between printing defects and its causes should be determined. However, the collection of the defects quantified data remains a challenge due to the micrometer scale and few texture features of droplets. In this paper, an accurate measurement method for deposited droplets based on coherence scanning interferometry (CSI) is proposed. Firstly, time series signals for topography reconstruction are recorded when CSI scans droplets vertically at a constant speed. Then, a deep learning method, multi-scale conditional diffusion model (MS-CDM), is proposed to restore the time series signals’ distortions led by the chromatic dispersion. Furthermore, a self-supervised learning method is proposed to efficiently train the MS-CDM, since the labeled data is hard to be acquired in industrial environment. Finally, the printing experiment indicates the collaboration of different modules in intelligent close-loop to reduce Mura defects. The volume measurement experiments demonstrate the ability to accurately measure the volume of deposited droplets, and the measurement error reaches 1.3%. The performance experiment on several public datasets demonstrates the method’s promising feature representation ability for time series mainstream task, and the MS-CDM achieves the best performance compared to those baselines methods.

Illusory optical defocus generated by shaded surface texture

The human visual system is tasked with the problem of extracting information about the world from images that contain a conflated mixture of environmental sources and optical artifacts generated by the focal properties of our eyes. In most contexts, our brains manage to distinguish these sources, but this is not always the case. Recent work showed that shading gradients generated by smooth three-dimensional (3D) surfaces can elicit strong illusory percepts of optical defocus1,2 - the perception of illusory blur is only eliminated when the surface appears attached to self-occluding contours3, surface discontinuities1, or sharp specular reflections1,2, which all generate sharp ('high spatial frequency') image structure. This suggests that it should also be possible to eliminate the illusory blur elicited by shaded surfaces by altering the surface geometry to include small-scale surface relief, which would also generate high-frequency image structure. We report the surprising result here that this manipulation fails to eliminate the perception of blur; the fine texture fails to perceptually 'bind' to the low-frequency image structure when there is a sufficient gap between the spatial scales of the fine and coarse surface structure. These findings suggest that discontinuous 'gaps' in the spatial scale of textures are a segmentation cue the visual system uses to extract multiple causes of image structure.

Combined effect of cavitation and multi-scale texture on the bearing properties of seawater-lubricated friction pair

To explore the tribological properties of a seawater-lubricated friction pair, the influence of cavitation and multi-scale texture on the load-carrying capacity is investigated under seawater lubrication conditions. In this paper, a numerical simulation method is proposed to reveal the influence mechanism of cavitation on the load-carrying capacity, and the simulation results are verified by experiments. The results show that cavitation, wedge action, and the vortex flow effect are the main mechanisms responsible for affecting the load-carrying capacity. Cavitation is not always advantageous for the load-carrying capacity. The results indicate that cavitation enhances the load-carrying capacity when the velocity is between 5 and 10 m/s. However, the cavitation effect shows a negative effect with a velocity exceeding 10 m/s. In three different scales of surface textures, the load-carrying capacity of the millimeter-scale texture is the highest, followed by the cross-scale texture and the micrometer-scale texture. The load-carrying capacity of the millimeter-scale texture is almost 10 times that of the micrometer-scale texture. Furthermore, regardless of the texture scale, a texture with a high depth-to-diameter ratio (H = 1) always exhibits a higher load-carrying capacity at low speeds (V < 10 m/s).

A truncated generalized Huber prior for image smoothing

Image smoothing is a fundamental task in computer vision and graphics. This paper presents a new image smoothing method based on a truncated generalized Huber prior. The proposed model is neither convex nor concave and is hard to optimize. We first transform the prior into a concave one, then utilize the technique of half-quadratic minimization to get an equivalent convex surrogate function. Thus the numerical algorithm is obtained by solving a weighted least square problem and iteratively updating the weights. The convergence of the algorithm is theoretically guaranteed. The proposed method is flexible and powerful in preserving edge/structure and eliminating undesired information. The effectiveness of the proposed method is demonstrated by several applications, including scale space filtering, texture removal, and clip-art JPEG artifacts removal.

MR image restoration and segmentation via denoising deep adversarial network for blood vessels accurate diagnosis

Segmenting the hepatic and portal veins is a difficult task, since it has multiple distortions. For effective restoration and to minimize distortions, a multi-stage deep adversarial learning network was proposed. The proposed network provides high reliability in segmenting hepatic and portal veins from distorted Magnetic Resonance (MR) images. The Proposed network directly considers the variation in vascular flow for vessel segmentation. By a two-stage deep adversarial network, which consist of geometric distortion by regularization in the first stage and in the second stage image blurriness is adjusted by a sub-pixel mechanism. To detect the hepatic venous flow, shared clustering was used to correlate the hepatic flow and venous flow. To have better image segmentation by restoration, end-to-end training by image adaptive by denoising was employed. The proposed Denoising Deep Adversarial Network (DDAN) generalizability is shown by curating a distorted TCGA dataset. We perform experiments by segmenting the distorted MR image with estimating depth, semantic interclass decision, and classification. The proposed DDAN is evaluated on a multi-phase open MRI public dataset from a local clinic and Kaggle Br35H. The obtained quantitative and qualitative evaluation data shows the practical applicability of the proposed deep learning model. We observed that the image edges, portal, and hepatic vein scale texture are clearly segmented to assist real-time applications like tumour surgery.

Pretreatment CT Texture Parameters as Predictive Biomarkers of Progression-Free Survival in Follicular Lymphoma Treated with Immunochemotherapy and Rituximab Maintenance.

The purpose of this study was to determine whether texture analysis features present on pretreatment unenhanced computed tomography (CT) images, derived from 18F-fluorodeoxyglucose positron emission/computed tomography (18-FDG PET/CT), can predict progression-free survival (PFS), progression-free survival at 24 months (PFS 24), time to next treatment (TTNT), and overall survival in patients with high-tumor-burden follicular lymphoma treated with immunochemotherapy and rituximab maintenance. Seventy-two patients with follicular lymphoma were retrospectively included. Texture analysis was performed on unenhanced CT images extracted from 18-FDG PET/CT examinations that were obtained within one month before treatment. Skewness at a fine texture scale (SSF = 2) was an independent predictor of PFS (hazard ratio = 3.72 (95% CI: 1.15, 12.11), p = 0.028), PFS 24 (hazard ratio = 13.38; 95% CI: 1.29, 138.13; p = 0.029), and TTNT (hazard ratio = 5.11; 95% CI: 1.18, 22.13; p = 0.029). Skewness values above -0.015 at SSF = 2 were significantly associated with lower PFS, PFS 24, and TTNT. Kurtosis without filtration was an independent predictor of PFS (SSF = 0; HR = 1.22 (95% CI: 1.04, 1.44), p = 0.013), and TTNT (SSF = 0; hazard ratio = 1.23; 95% CI: 1.04, 1.46; p = 0.013). This study shows that pretreatment unenhanced CT texture analysis-derived tumor skewness and kurtosis may be used as predictive biomarkers of PFS and TTNT in patients with high-tumor-burden follicular lymphoma treated with immunochemotherapy and rituximab maintenance.

Tribology of Pore-Textured Hard Surfaces under Physiological Conditions: Effects of Texture Scales.

Micro- and nanotexturing on hard biomaterials have shown advantages for tissue engineering and antifouling applications. However, a growing number of studies have also shown that texturing may cause an increase in friction, demanding further research on the tribological effects of texturing under physiological conditions. This study investigates the tribological effects of micro- and nanopore patterns on hard hydrophilic silicon sliding against soft hydrophobic polydimethylsiloxane (PDMS) immersed in aqueous liquids with various viscosities, simulating the sliding of a textured implant surface against soft tissues. The experimental results show that silicon surfaces with pore textures at both micro- and nanoscale feature sizes confer a higher coefficient of friction (COF) than an untextured one. It is attributed to the texture's edge effect caused by the periodic pore patterns between the two sliding objects with a large difference in material stiffness. For the same solid area fraction, nanopored surfaces show a higher COF than micropored surfaces because of the significantly higher texture edge length per unit area. For micropored surfaces with a similar length of texture edge length per unit area, the COF increases more significantly with the increase in pore size because of the greater stress at the rims of the larger pores. The COFs of both micro- and nanoscale pores generally decrease from ∼10 to 0.1 with an increase in the surrounding aqueous viscosity, indicating the transition from a boundary lubrication to a mixed lubrication regime while mostly remaining in boundary lubrication. In contrast, the COF of an untextured surface decreases from ∼1 to 0.01, indicating that it mostly remains in the mixed lubrication regime while showing the tendency toward hydrodynamic lubrication. Compared to a hydrophilic hard probe sliding against a textured hydrophobic soft substrate, the hydrophobic soft probe sliding against a textured hydrophilic hard substrate produces a significantly higher COF under similar physiological conditions due to the larger edge effect.

Feasibility of using bio-mimicking fish scale textures in LPBF for water drag-reducing surfaces

In this work, bio-mimicking fish scale textures are produced by LPBF and AlSi7Mg0.6 powder to reduce drag forces on nautical components. For this purpose, a surface texture inspired by the European bass skin was modelled and parametrized. Textures were applied over the external surface of purpose-designed specimens. Additive manufacturing quality of textures was assessed using focus variation microscopy to examine surface roughness as well as geometrical errors. Once the feasibility of producing the desired bio-mimicking surfaces was confirmed, the designed surface patterns were analysed in the computation fluid dynamics modelling environment. The behaviour of the surfaces was characterized in terms of drag force generated over a fixed dimension plate model. The most promising configuration was further investigated in a sensitivity analysis where variations in main stream velocity and in surface roughness are applied. Drag reduction was related to the lowering of the viscous component and was found to be in the order of 1–2%, with respect to a smooth surface, for free stream velocity of 2.5–5 m s−1 and average roughness smaller than the as-built condition. The results confirm that the modelled surfaces can be reproduced with sufficient geometrical fidelity, showing great promise for drag-reducing metallic components produced by additive manufacturing.

Hybrid reflected-ultrasound computed tomography versus B-mode-ultrasound for muscle scoring in spinal muscular atrophy.

Novel light- and sound-based technologies like multispectral optoacoustic tomography (MSOT) with co-registered reflected-ultrasound computed tomography (RUCT) could add additional value to conventional ultrasound (US) for disease phenotyping in pediatric spinal muscular atrophy (SMA). The aim of this study was to investigate the quality of RUCT compared to US for qualitative and quantitative assessment of imaging neuromuscular disorders. Subanalyzing the MSOT SMA study, 288 RUCT and 276 US images from 10 SMA patients (mean age 9.0±3.7) and 10 gender- and age-matched healthy volunteers (HV; mean age 8.7±4.3) were analyzed for quantitative (grayscale levels [GSLs]) and qualitative (echogenicity, distribution pattern, Heckmatt scale, and muscle texture) muscle changes. RUCT and US measures were further correlated with clinical standard motor outcomes. Quantitative agreement using GSLs revealed significantly higher GSLs in muscles of SMA patients compared to healthy muscles in both techniques (US mean GSL [SD] SMA vs. HV: 110.70 [27.8] vs. 68.85 [19.2], p<.0001; RUCT mean GSL [SD] SMA vs. HV: 91.81 [21.8] vs. 59.86 [8.2], p<.0001) with good correlation with motor outcome tests, respectively. Qualitative agreement between methods for muscle composition was excellent for differentiation of pathological versus healthy muscles, echogenicity, and distribution pattern, moderate for Heckmatt scale, and poor for muscle texture. The data suggest that RUCT may allow the assessment of basic qualitative and quantitative measures for muscular diseases with comparable results to conventional US.

Hybrid Color Texture Features Classification Through ANN for Melanoma

Melanoma is of the lethal and rare types of skin cancer. It is curable at an initial stage and the patient can survive easily. It is very difficult to screen all skin lesion patients due to costly treatment. Clinicians are requiring a correct method for the right treatment for dermoscopic clinical features such as lesion borders, pigment networks, and the color of melanoma. These challenges are required an automated system to classify the clinical features of melanoma and non-melanoma disease. The trained clinicians can overcome the issues such as low contrast, lesions varying in size, color, and the existence of several objects like hair, reflections, air bubbles, and oils on almost all images. Active contour is one of the suitable methods with some drawbacks for the segmentation of irregular shapes. An entropy and morphology-based automated mask selection is proposed for the active contour method. The proposed method can improve the overall segmentation along with the boundary of melanoma images. In this study, features have been extracted to perform the classification on different texture scales like Gray level co-occurrence matrix (GLCM) and Local binary pattern (LBP). When four different moments pull out in six different color spaces like HSV, Lin RGB, YIQ, YCbCr, XYZ, and CIE L*a*b then global information from different colors channels have been combined. Therefore, hybrid fused texture features; such as local, color feature as global, shape features, and Artificial neural network (ANN) as classifiers have been proposed for the categorization of the malignant and non-malignant. Experimentations had been carried out on datasets Dermis, DermQuest, and PH2. The results of our advanced method showed superiority and contrast with the existing state-of-the-art techniques.

Superresolution Reconstruction Algorithm of Ultrasonic Logging Images Based on High-Frequency Enhancement

High-resolution logging images with glaring detail information are useful for analysing geological features in the field of ultrasonic logging. The resolution of logging images is, however, severely constrained by the complexity of the borehole and the frequency restriction of the ultrasonic transducer. In order to improve the image superresolution reconstruction algorithm, this paper proposes a type of ultrasonic logging based on high-frequency characteristics, with multiscale dilated convolution to feature as the basis of network-learning blocks, training in the fusion of different scale texture feature. The outcomes of other superresolution reconstruction algorithms are then compared to the outcomes of the two-, four-, and eightfold reconstruction. The proposed algorithm enhances subjective vision while also enhancing PSNR and SSIM evaluation indexes, according to a large number of experiments.

Effective pavement skid resistance measurement using multi‐scale textures and deep fusion network

AbstractPavement skid resistance measurement is a fundamental component of roadway management and maintenance. Most traditional approaches rely on manual operations or heavy devices, which lead to a labor‐intensive, inefficient, and vulnerable testing environment. Precise laser scanning technology lays a solid foundation for effective and continuous pavement friction measurement. This paper proposed an automated pavement friction estimation model using 3D point cloud data and a deep neural network. The fine‐grained texture data of over 800 pavement sections with various anti‐skidding abilities were collected. The impact of the multi‐scale textures on pavement friction was separated and analyzed via two‐dimensional wavelet decomposition. A multi‐input fusion network with deep aggregation modules was designed to fuse the features of sub‐images generated by wavelet decomposition. The results show that the average prediction error is 0.0935, outperforming most state‐of‐the‐art models. The impact of different texture scales on friction estimation is then revealed. The proposed method provides a new tool for effective and large‐scale pavement friction evaluation.

Evaluating characteristics of particles’ surface micro-texture of granular materials based on the spectral analysis method

ABSTRACT Accurately evaluating particle surface micro-texture levels and distribution at different wavelength scales of granular material is critical to optimise service stability of granular material under long-term dynamic loads. Firstly, generalised regression neural network (GRNN) and empirical mode decomposition (EMD) were adopted to impute missing data points and remove the arc-shaped tendency of granular materials’ particle wear raw surface profile. Then, granular materials’ particle surface micro-texture levels and their distribution within constant bandwidth narrow band spectrum and octave/fractional octave band spectrum were obtained with spectral analysis method, which could characterise granular materials’ particle surface properties at different wavelength scales. Fourteen types of parent rocks of granular materials were tested with a modified micro tribological experiment simulating tribological behaviour among particle contact interfaces under dynamic loads. A contrastive analysis with traditionally used surface mean roughness was performed. The results indicate that the micro-texture levels and their distribution obtained in this study can detect the level of the exact texture scales (i.e. 32 and 2 μm wavelengths) significantly influencing the kinetic friction coefficient of granular materials, while surface mean roughness can only represent the global surface property. A high correlation was found between normalised micro-texture level (i.e. 32 μm) and Moh's hardness and coefficient of friction.