Roughness Parameters Research Articles

A review on optimum substrate surface roughness to create better wetting

Surface roughness or texture is one of the key parameters for liquid fluids or liquid metals to achieve good or poor wetting. In certain applications surface roughness of a smooth surface [mirror finish] is treated as a slippery surface for poor wettability however in a few applications’ roughness surfaces are considered as better wetting, especially for liquid metals. In this regard, to understand the parameters for the optimum surface roughness of the substrates to achieve good wetting is essential. In the present review paper, an attempt has been made to find the ideal roughness value of the substrate for better wetting of liquid metals or alloys based on substrates and fluids.

A novel methodology to assess optical profilometer stability to discriminate surface roughness

A new method is proposed to investigate the measurement variation of instruments and their ability to discriminate two TA6V surfaces obtained by grinding with SiC grit papers (80 and 120). Three optical measurement technologies included into a single apparatus, namely Confocal Microscopy (CM), Focus Variation (FV) and Coherence Scanning Interferometry (CSI), were used to measure both ground surfaces according to a specific experimental protocol (MorphoMeca Monitoring) based on measurement iterations and repetitions. From the measurements, four indices were built from the Sa roughness parameter to assess the Quality (ratio of the topographical variability over the measurement noise), the Drift (related to surface fluctuations) and the Stability (estimation of the temporal drift using a second order autoregressive model) of the three measurement technologies (modes), as well as their Relevance (computed from an analysis of variance) to discriminate ground surfaces with close roughness. For these investigated surfaces, it was especially highlighted that the Quality Index is four times higher for the CSI mode than for the FV and CM modes. All the used measurement modes experienced small drifting (Drift Index) during the measurements. The CSI mode was slightly more sensitive to drift than the FV and CM modes. The Stability Index indicated that there was no memory effect between two acquisitions for each measurement mode, i.e., the temporal drift did not depend on the measurement mode. Moreover, the three measurement modes are able to discriminate the two ground surfaces with the same accuracy through the Sa parameter. However, the Sa values may vary depending on the measurement modes, and it was finally shown that the Sa parameter is minimized by 0.03 μm for the FV mode compared with the CSI mode, due to its smoothing effect.

Transformation of quinoa seeds to nanoscale flour by ball milling: Influence of ball diameter and milling time on the particle sizing, microstructure, and rheology

Among various size reduction techniques, high-energy ball milling is one of the most attractive means for plant-based foods. The objectives of the work were to investigate the influence of ball diameters (3, 6, and 13 mm) and milling time (2, 4, and 6 h) on particle size and microstructural properties of quinoa flours. Particle size analysis demonstrated that ball-milled particles were mostly in the range of nanoscales (122–295 nm). A longer milling time with larger balls significantly increased the particles to microscale (3.58 μm). The scanning electron microscopy displayed the conversion of quinoa starch granules into flakes after ball milling, however, the X-ray diffraction crystallinity peak observed at a 2θ value of 19–20° did not change. The AFM roughness parameters, arithmetic and squared mean heights of flours increased with increasing ball diameters. These results provided new insights for the application of ball milling, in particular in functional foods and pickering emulsion.

Discrimination of wear performance based on surface roughness parameters arithmetic mean height (Sa) and skewness (Ssk)

Enhancing interfacial contact bearing performance typically involves minimizing the roughness parameter Sa (arithmetic mean height). Yet, exceedingly low Sa incur steep increases in processing costs, indicating that Sa-centric optimization strategies may not be universally suitable for interface performance control. Roughness parameters skewness (Ssk) and kurtosis (Sku) exert a pronounced influence on component contact wear performance. Accordingly, investigating the correlation between Ssk, Sku, and wear performance holds significant promise for enhancing wear resistance. A finite element wear calculation model for rough-surface abrasive wear employing elastic-plastic contact mechanics and the Jump-in-Cycle method. Cylindrical roller dry sliding experiments validate the model's reliability. Integrating this model, a method is proposed for wear performance discrimination based on Sa and Ssk at different loads. It enables the identification of critical roughness parameter values for improved surface wear resistance. The calculated wear model aligns with experiment trends, with predicted surface textures mirroring observed wear surface characteristics. Critical Sa and Ssk diverge under distinct loads. The study underscores the importance of moving beyond the exclusive pursuit of exceptionally low Sa and Ssk. It provides a foundation for reducing workpiece processing costs while optimizing wear performance.

Effects of SiO2 Nanoparticles on Polyvinyl Alcohol/Carboxymethyl Cellulose Polymer Blend Films’ Structural, Wettability, Surface Roughness, and Optical Characteristics

The blend matrix composed of polyvinyl alcohol and carboxymethylcellulose (PVA/CMC) was prepared via the casting method. SiO2 nanoparticles were added as reinforcement in different amounts (SiO2 = 1, 2, 3, and 4 wt.%). The study utilized FTIR to examine the alterations in composition and the interplay between the blend matrix and the inclusion of SiO2. Also, for the first time, the surface roughness and surface wettability of the PVA/CMC blend matrix were investigated with the addition of SiO2 using measurements of contact angle and surface roughness parameters. The surface roughness and wettability of the blend matrix increased as the SiO2 content increased. In addition, the blend matrix optical features were determined by the UV–visible spectrophotometer. Based on the analysis using Tauc’s relation, it was found that the energy bandgap decreases from 5.52 to 5.17 eV (direct transition) and from 4.79 to 4.32 eV (indirect transition) for the PVA/CMC and PVA/CMC/4%SiO2 blend films, respectively. The refractive index increases from 2.009 to about 2.144 for the PVA/CMC and PVA/CMC/4%SiO2 blend films, respectively. Furthermore, optical conductivity and dielectric constants were improved for the PVA/CMC blend film after the addition of SiO2 nanoparticles.

Influence of Tool Inclination and Effective Cutting Speed on Roughness Parameters of Machined Shaped Surfaces

Free-form surfaces in the automotive or aviation industry where the future shape of the product will contain complex surfaces raises the question of how to achieve the necessary shape of the required quality in the milling process. One of the methods of their production is the use of 5-axis milling, in which it is necessary to consider not only the input data of the process itself, but also the methodology for evaluating the desired results. Correctly answered questions can thus facilitate the choice of the inclination of the tool when machining parts of the surfaces defined in the experiment. The primary goal of the paper was to monitor the influence of tool inclination on the quality of the machined surface and effective cutting speed by evaluating surface roughness and surface topography. The experiment was designed to show the effect of different tool positions while the feed per tooth fz for the finishing operation remained constant. The best result in terms of surface quality was achieved with a tool inclination of 15° in the cutting process. The most unfavorable result was obtained with a tool axis inclination of zero degrees due to unfavorable cutting conditions.

Assessment of Roughness Characterization Methods for Data-Driven Predictions

A comparative analysis is undertaken to explore the impact of various roughness characterization methods as input variables on the performance of data-driven predictive models for estimating the roughness equivalent sand-grain size ks\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$k_s$$\\end{document}. The first type of model, denoted as ENNPS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {ENN}_\ ext {PS}$$\\end{document}, incorporates the roughness height probability density function (p.d.f.) and power spectrum (PS), while the second type of model, ENNPA\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {ENN}_\ ext {PA}$$\\end{document}, utilizes a finite set of 17 roughness statistical parameters as input variables. Furthermore, a simplified parameter-based model, denoted as ENNPAM\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {ENN}_\ ext {PAM}$$\\end{document}, is considered, which features only 6 input roughness parameters. The models are trained based on identical databases and evaluated using roughness samples similar to the training databases as well as an external testing database based on literature. While the predictions based on p.d.f. and PS achieves a stable error level of around 10% among all considered testing samples, a notable deterioration in performance is observed for the parameter-based models for the external testing database, indicating a lower extrapolating capability to diverse roughness types. Finally, the sensitivity analysis on different types of roughness confirms an effective identification of distinct roughness effects by ENNPAM\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {ENN}_\ ext {PAM}$$\\end{document}, which is not observed for ENNPA\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {ENN}_\ ext {PA}$$\\end{document}. We hypothesize that the successful training of ENNPAM\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {ENN}_\ ext {PAM}$$\\end{document} is attributed to the enhanced training efficiency linked to the lower input dimensionality.

Polarization-multiplexed snapshot lateral shearing interferometric sensor for surface roughness measurements

A compact optical roughness measurement sensor based on lateral shearing interferometry is theoretically described and experimentally verified. By adopting the advanced surface roughness parameter extraction methods based on statistical machine learning technique and the partial integration approach, the sensor using a polarization grating and a polarization camera can instantaneously obtain a surface gradient map and provide reliable surface roughness parameters. To verify the operation and the performance of the sensor, a flat mirror and roughness standard specimens were measured, and the results were compared with those of a white light scanning interferometer as the reference values. As a result, the roughness parameters were very close to the reference values with <5 nm accuracy and <0.1 nm repeatability.

Application of the TOPSIS decision-making method for selecting a manufacturing technique for children’s furniture elements with therapeutic functions

Making furniture or furniture elements that account for the needs of children at various stages of development or with psychomotor dysfunctions is very difficult. From the point of view of exploitation and production technology, it is difficult to select a specific material and manufacturing technique. In this article, the results of using the APEKS method, which is a type of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, are presented to select the best solution for the production of children’s furniture elements with surface structures similar to those of natural materials. Wood bark was selected as a material that, due to the sensory tactile sensations of dysfunctional children, could contribute to therapy and education. Comparative analysis was performed on the basis of the subtractive and additive methods used for manufacturing furniture products. Precise multiaxis milling of ash wood and 3D printing with fused filament fabrication technology using wood PLA filaments were carried out. The method used to select the best option considered quantitative and qualitative criteria in the assessment. Various parameters characterizing the surfaces were analyzed, such as geometric dimensions, hill heights, valley depths, and 3D surface parameters. The quality and surface roughness (Sa, Sz, Ssk, Sku, Sp, and Sv) parameters obtained based on 3D microscope measurements were determined. A scale of 1 to 10 was used to assess qualitative factors (i.e., usability and aesthetics). Based on the critical values obtained from the coefficient Kcri = 79.36, it was assumed that multiaxis wood milling was the best method for producing furniture elements with the required surface characteristics for use as therapeutic and educational tools for children with dysfunctions. The applied method allowed an effective evaluation of the compared variants of the production of furniture elements for customized applications.

Surface roughness and cyclic fatigue resistance of a novel shaping system: An in-vitro study.

Recently developed Nickel-Titanium (NiTi) instruments with practical changes have resulted in safer instrumentation. In addition, topographical features on the file surface are a contributing factor to clinical durability. Therefore, this study aimed to investigate both the cyclic fatigue resistance and the roughness change of MTwo and Rotate instruments (VDW, Munich, Germany). Each instrument (n = 6/each group) was scanned with an atomic force microscopy prior to and after instrumentation. In addition, cyclic fatigue testing was conducted for each instrument (n = 11/each group) with stainless-steel blocks, including 45°-60°-90° degrees of curvature milled to the instruments' size. The roughness parameters increased for both systems after instrumentation (p<0.05). Both systems presented an increased roughness following instrumentation (p<0.05). The cyclic fatigue resistance was lowest at 90° for both systems (p<0.05), whereas the Rotate files presented a higher resistance than that of the Mtwo files (p<0.05). Compared to the Mtwo files, Rotate files presented better resistance, while the resistance decreased as the curvature increased.

The Effects of Ultrasonic Scaling and Air-Abrasive Powders on the Topography of Implant Surfaces: Scanning Electron Analysis and In Vitro Study.

This in vitro study aimed to investigate the impact of bicarbonate air-abrasive powders and ultrasonic scaling with stainless steel tips on the micro- and nanotopography and roughness of three different implant-abutment junction titanium surfaces. Three types of sterile and decontaminated titanium surfaces (RS, UTM, XA) were used for analysis. Nine disks per surface type were subjected to micro- and nanotopography analysis, scanning electron microscopy (SEM), roughness analysis, and fibroblast cultivation. Ultrasonic debridement and air polishing were performed on the surfaces. Human dermal fibroblasts were cultured on the surfaces for 5 days. Data analysis adhered to ISO 25178 standards for surface texture assessment. SEM micrographs were used to reconstruct areas for extracting roughness parameters. Excel and Mex 6.0 software were utilized for quantitative and stereoscopic analysis. The study found varying effects on surface roughness posttreatment. RS Disco samples exhibited higher surface roughness compared with UTM and XA samples, both in average and nanoscale roughness. Decontamination led to increased surface roughness for all samples, particularly RS Disco. Fibroblast growth tests revealed enhanced cell network formation on decontaminated discs, possibly due to increased nanoscale roughness or the presence of bicarbonate salts. The study underscores the complex interplay between surface topography, microbial biofilm, and treatment efficacy in peri-implant disease management. While smoother surfaces may resist biofilm accumulation, increased nanoscale roughness postdecontamination can enhance fibroblast attachment and soft tissue integration. This dichotomy highlights the need for tailored treatment protocols that consider material-specific factors, emphasizing that successful implant therapy should balance microbial control with conducive surface characteristics for long-term osseointegration and soft tissue stability.

Development of correlations of Nusselt number and friction factor of solar thermal collector equipped with hybrid rib roughness

In this advanced and comprehensive research, a pioneering hybrid rib configuration, amalgamating arc and V-shaped ribs, is precisely engineered to delve into the complex synergistic effects between this cutting-edge rib design and the heat transfer and fluid flow behavior within a solar thermal collector (STC) specifically utilized for direct air heating. The focal point of this investigation is the impact of the rib pattern on pivotal performance indicators, notably the Nusselt number (Nu) and the friction factor (f). This specific rib roughness design emanates from an exhaustive analysis of a spectrum of non-dimensional roughness parameters: the arc angle (α), the attack angle (β), the relative positioning of the V ribs (D/w), the relative spacing of the ribs (p/e), and the rib height (e/D). These parameters are studied within defined ranges: 30̊‐60̊, 30̊‐60̊, 0.2–1, 8–12, and 0.023–0.043, respectively. The results of highlight a significant improvement in heat transport, as indicated by a significant increase in the Nusselt number (Nu), which has risen impressively by a factor of 3.08. Furthermore, this paper presents development of correlations for Nu and f, taking into account the roughness parameters of the hybrid ribs and the flow Reynolds number, in order to precisely forecast these key performance measurements.

A Neoteric Feature Extraction Technique to Predict the Survival of Gastric Cancer Patients.

At the time of cancer diagnosis, it is crucial to accurately classify malignant gastric tumors and the possibility that patients will survive. This study aims to investigate the feasibility of identifying and applying a new feature extraction technique to predict the survival of gastric cancer patients. A retrospective dataset including the computed tomography (CT) images of 135 patients was assembled. Among them, 68 patients survived longer than three years. Several sets of radiomics features were extracted and were incorporated into a machine learning model, and their classification performance was characterized. To improve the classification performance, we further extracted another 27 texture and roughness parameters with 2484 superficial and spatial features to propose a new feature pool. This new feature set was added into the machine learning model and its performance was analyzed. To determine the best model for our experiment, Random Forest (RF) classifier, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Naïve Bayes (NB) (four of the most popular machine learning models) were utilized. The models were trained and tested using the five-fold cross-validation method. Using the area under ROC curve (AUC) as an evaluation index, the model that was generated using the new feature pool yields AUC = 0.98 ± 0.01, which was significantly higher than the models created using the traditional radiomics feature set (p < 0.04). RF classifier performed better than the other machine learning models. This study demonstrated that although radiomics features produced good classification performance, creating new feature sets significantly improved the model performance.

Method for design of finishing processing with free abrasive

The dependences of changes in the Ra parameter of surface roughness during finishing processing with free abrasive when using different abrasive materials are analyzed. A method for designing such a technological operation as flow barrel polishing is proposed. An example of determining of the optimal sequence of using of abrasive materials during finishing is shown. Keywords:finishing, free abrasive, technological operation, surface roughness parameter, design, optimization aka111996@mail.ru, al.goncharow@yandex.ru, maxim.albom@yandex.ru, ilya32zog@gmail.com

Effect of surface roughness parameters on frictional properties of AlSi10Mg alloy

Experimental study of the effects of surface roughness parameters and their relationship to the coefficient of friction (COF) on AlSi10Mg alloy. The information demonstrates that the average surface roughness (Ra) does not directly correlate with COF when sliding is presented. This work is focused on the relationship and interaction between the roughness parameters (Ra), maximum profile height (Rt), average profile slope, and COF. To alter the surface roughness effect, the samples of the alloy are chemically treated with an alkaline 0, 5, 10, 15, 25, and 50 minutes and tested under different circumstances. Using a T-05 block-on-ring tribometer, the COF is calculated, and surface roughness measurements are collected utilizing an optical system for measuring three-dimensional surfaces. The program MATLAB is used to analyze the obtained data. Contrarily, the results demonstrate that there is a substantial positive association with COF under sliding conditions, while Ra and Rt can change without affecting CO significantly.

Regeneration Effect of a New Bio-Based Warm-Mix Rejuvenator on Performance and Micro-Morphology of Aged Asphalt.

The use of warm-mix recycling technology can reduce the mixing temperature and the secondary aging of binders in reclaimed asphalt pavement (RAP), which is one of the effective ways to recycle high-content RAP. In this study, the penetration, softening point, ductility, and viscosity were used to characterize the conventional physical properties of aged asphalt after regenerating, while a dynamic shear rheometer (DSR), force ductility tester (FDT), and atomic force microscope (AFM) were used to evaluate the rheological performance and micro-morphology of aged asphalt incorporating a new bio-based warm-mix rejuvenator (BWR) and a commercial warm-mix rejuvenator (ZJ-WR). The regeneration mechanism of warm-mix rejuvenators on aged asphalt was analyzed by Fourier transform infrared spectroscopy (FTIR). The results show that the new bio-based warm-mix rejuvenator can restore the conventional physical properties, low-temperature performance, and micro-morphology of aged asphalt with an appropriate dosage, but it has a negative effect on high-temperature performance. In comparison with 2D area parameters, 3D roughness parameters were more accurate in evaluating the variation in micro-morphology of aged asphalt after regeneration. The FTIR analysis results indicate that both the new bio-based warm-mix rejuvenator and the commercial warm-mix rejuvenator regenerate aged asphalt by physical action, and AS=O and AC-H values are more reasonable than the AC=O value for the restoration evaluation of aged asphalt. And the new bio-based warm-mix rejuvenator has a better regeneration effect on the performance and micro-morphology of aged asphalt than the commercial warm-mix rejuvenator.

Concrete self-healing performance using surface roughness parameters: Metrological approach

Traditional test methods for evaluating concrete self-healing performance, such as scanning electron microscopy, ultrasonic waves including velocity pulse and emissions and x-ray imaging have limited accuracy resulting from the damages during the sample preparation and capability of the instruments. Very limited work has been performed to date to conduct non-destructive evaluations using non-contact test methods, hence obtaining three-dimensional images that can evaluate the self-healing performance in cementitious materials. This study meteorological instruments to obtain three-dimensional surface profiles without any external impacts that could potentially cause damage to the concrete surface has been used. The study aims evaluate the healing efficiency and performance of the crack at different time intervals for 28 days by using different healing agents such as microcapsules, cellulose fibre and applying sodium silicate directly on the developed crack. Healing efficiency and performance assessment is conducted through the maximum visualisation featuring, crack width, depth healed product from the contact angle. Metrological selective roughness parameters such as Sa, Sq, Vvv and Smr2 values are also used to evaluate the self-healing performance at various time intervals. A comparison of the numerically obtained data, both individually and from different surface roughness parameters, indicates that crack healing occurrences can be observed when utilizing different healing agents.

Multiparameter signal-to-noise ratio optimization for end milling cutting conditions of aluminium alloy 5083

Surface integrity problems during selective material removal processes are a very common limitation for process productivity and part quality, especially in difficult-to-machine materials like 5083 aluminium alloy (AA), which is known for its remarkable performance in extreme environments. In general, tuning the cutting-part material properties with cutter geometry and cutting parameters can optimize surface texture, increase parts accuracy and resistance in corrosion, and eliminate process noise and energy waste. This work is an experimental study of surface parameter optimization during finish end milling of an AA5083 under a specific range of three cutting parameters with an optimized two-flute carbide cutter by previous work. So, twenty-seven experiments were run having varied the radial depth of cut (RDOC), feed rate (f), and cutting speed (S). Surface roughness parameters (Ra and Rt) were measured in the direction of cutting speed at three different distances by the upper edge. The signal-to-noise (SN) ratios have been calculated, and the process was optimized following the analysis of means. Then, additive models with linear interactions were fitted on SN ratios, and the analysis of variances and residual normality plots were utilized to validate the models’ goodness. The SN approach and analysis of means conclude that 0.5 mm RDOC, 6000 rpm speed, and 0.082 mm/tooth feed optimize the process and can effectively predict the Ra and Rt responses. The newly produced machinability data can benefit further applications of AA5083 in industrial applications such as shipbuilding and vehicle bodies.

Simulation on metal-rubber contact behavior based on a reconstructed 3D topography of rough surfaces

A contact model with refined surface topography is important to the frictional wear study of rubber seal. But the traditional modeling method relies on the measurement of surface characteristics of rubber material, which increases the cost due to high-precision instruments and complex data processing. In the paper, a new modeling method on reconstructing the 3D surface topography is proposed. The coordinate cloud of the surface is generated based on the random distribution of asperity height, which is established according to the initiate parameters of the surface roughness. The metal-rubber assembly model with 3D topography of rough surfaces are built. The simulation on metal-rubber contact behavior is conducted in ANSYS. The result shows a power-exponent relation is between the real contact area and the external pressure, and three contact states of no contact, adhesion and slippage are defined to describe the dynamic distribution of real contact area. The authors proved the reliability of the topography reconstruction method by an indentation experiment on rubber material. The area ratio reflects not only the change rule of contact area under an increasing pressure, but also the difference of contact behavior of the contact pairs under different surface roughness.

Characterization of road surface topography changes during polishing process with characteristic roughness parameter

In this paper, three-dimensional structure feature points of the asphalt mixture were obtained based on the industrial CT. The surface morphology of the asphalt mixture was then extracted through image morphology processing and evolutionary matching algorithms. A series of accelerated polishing tests were utilized to simulate the long-term polishing effect of the tire load on the asphalt pavement. Combining with digital image analysis, the full-life morphology evolution trend of the asphalt pavement was analyzed, and the full-life surface morphology datasets of the asphalt pavement were constructed. By comparing the power spectrum density of the asphalt pavement morphology at different wear stages, a segmented evaluation method based on the spectral fractal method was proposed. Combining the spectral fractal parameters and statistical geometric parameters, a multi-scale asphalt pavement surface morphology feature evaluation index was proposed. This provides a more intricate and detailed analysis of the surface structure of asphalt mixtures.