non-Gaussian Surfaces Research Articles

Investigation on Contact Behaviors Exhibited by Non-Gaussian Rough Surfaces

Investigation on Contact Behaviors Exhibited by Non-Gaussian Rough Surfaces

Evolution of tooth surface morphology and tribological properties of helical gears during mixed lubrication sliding wear

In mixed lubrication, the interplay of lubricant flows, solid asperity contact, and material wear between tooth surfaces creates complex and unpredictable contact states on tooth surface. To comprehensively understand the interaction between the lubrication and wear characteristics of the rough tooth surfaces of helical gears, this study established a mixed lubrication sliding wear calculation model for helical gears based on the mixed elastohydrodynamic lubrication model and Archard’s model. Specifically, the study aimed to examine the effects of surface topography features on average film thickness, contact area ratio, and accumulated wear at the meshing point. The findings demonstrated that the texture and power spectral density distributions of a non-Gaussian reconstructed surface closely resembled those of the actual ground surface. Furthermore, for non-Gaussian rough surfaces, a larger wavelength ratio enhanced microwedge motion, which increased film thickness and reduced wear. Additionally, a negatively skewed surface demonstrated better lubrication performance compared to both positively skewed and Gaussian surfaces. This improved performance is evident in the smaller contact area ratio and lower accumulated wear value of the negatively skewed surface.

Numerical study of leakage rate in reciprocating seal with non-Gaussian topography characteristics using percolation mechanism

The topography significantly affects the leakage prevention of the sealing surface. However, the topography effect on sealing performance is not yet fully understood. The leakage mechanism cannot be revealed by average flow model using a statistical distribution to characterize the surface. This paper proposes a new leakage analysis method for reciprocating seals based on the percolation theory. The contact and lubrication analysis of non-Gaussian surfaces with different characteristics is conducted to establish three-dimensional percolation channels. The leakage rate can be calculated from the flow velocity across the cross-section at the critical constriction in the channel. The results show that compared with experimental data, the simulation results of the percolation model are more accurate than those of the average flow model.

Coupling Study on Quasi-Static and Mixed Thermal Elastohydrodynamic Lubrication Behavior of Precision High-Speed Machine Spindle Bearing with Spinning

In this work, a modified numerical algorithm that couples the quasi-static theory with the mixed thermal elastohydrodynamic lubrication (mixed-TEHL) model is proposed to examine the mechanical properties and lubrication performance of the spindle bearing that is used in a high-speed machine tool with spinning. The non-Newtonian fluid characteristics of the lubricant and the non-Gaussian surface roughness are also considered. Moreover, the mechanical properties and lubrication state of the bearing are examined in various service environments. The results indicate that the temperature reduces the lubrication efficiency, which in turn exerts a significant impact on the mechanical properties. The lubrication that either behaves in the manner of Newtonian or non-Newtonian fluid has a relatively negligible influence on the bearing working state, while the non-Gaussian surface roughness significantly alters the oil film thickness and temperature. Calculations with different operating conditions demonstrate that the operating parameters (i.e., axial load, rotation speed) will directly affect the performance of the bearings via the changes in the oil film thickness and the temperature.

Molecular dynamics simulation of dry sliding between non-Gaussian copper rough surfaces

Friction plays a significant role in the wear and tear of sliding metallic surfaces, particularly in gears and bearings employed in nano and micro electro-mechanical systems (NEMS/MEMS). To comprehend the nature of dry sliding friction in mechanical devices, it is crucial to investigate surface interactions at the nano-scale. Molecular dynamics (MD) simulation has been utilized in this study to explore how asperities come into contact at this minute scale. Specifically, the interaction between two non-Gaussian rough surfaces is examined at varying dimensionless spacing (δ/Seq), ranging from 3.6 to 2.7. The von Mises strain, atomic wear, and changes in the atomic arrangement after sliding action are obtained for Cu-Cu (soft-to-soft) tribo-pair at a given sliding speed of 10 m/s. The average friction force on the lower surface increased when the space between surfaces was decreased. More percentage changes in surface topography are found for the lesser dimensionless spacing (δ/Seq) of 2.7. The changes in surface topography parameters during sliding action may have an immense effect on the performance of tribo-pair in NEMS/MEMS. A greater increase in autocorrelation length signifies a more pronounced flattening of the lower surface at the lower dimensionless spacing (δ/Seq).

Effects of Non-Gaussian Surface Roughness on Conductor Loss in High-Frequency Transmission Lines

Effects of Non-Gaussian Surface Roughness on Conductor Loss in High-Frequency Transmission Lines

Study on normal contact stiffness characteristics in non-Gaussian rough surfaces under mixed lubrication

Study on normal contact stiffness characteristics in non-Gaussian rough surfaces under mixed lubrication

Thermal mixed elastohydrodynamic lubrication modeling and analysis of the lubricated non-conformal contacts with non-Gaussian surface roughness and coating

The lubricated non-conformal contact generally works under the mixed-EHL regime. Optimizing the surface topography or selecting the right coating is an effective way to improve its performance. This paper presented an improved mixed-TEHL model for the lubricated non-conformal contacts with the effects of roughness and coating in consideration. The effect of coating was solved analytically by employing the Papkovich–Neuber potentials. It was found that the properties of coatings, especially their elastic modulus, significantly affect the pressure and stress distribution. In comparison to other roughness parameters, standard deviation and kurtosis have a significant impact. As expected, the present model can provide an efficient analysis of the tribological behavior and the stress distribution of the lubricated non-conformal contacts.

A deterministic mixed lubrication model for parallel rough surfaces considering wear evolution

A deterministic mixed lubrication model for parallel surfaces is proposed. The oil film force is solved by the Reynolds equation with a mass-conserving cavitation model. The contact force is predicted by using a neural network trained on a database, which was built by conducting finite element analysis on a single asperity. In addition, an extended Archard equation is introduced to predict the transient running-in wear. The contact model is proved to be suitable for Gaussian and non-Gaussian surfaces. The Stribeck curves calculated under the different wear coefficients and wear steps are compared with the experimental results. The influence of initial surface topography on the running-in behavior has also been studied. The contact database for GCr15 is provided.

On the effect of the height distribution function in adhesion of non Gaussian random rough surfaces, and a simple analytical model (BAM)

Two apparently very different theories of adhesion of rough surfaces called BAM (bearing-area-model), and that of Persson–Tosatti lead to similar predictions concerning the stickiness of Gaussian surfaces: the role of roughness is mainly governed by the low wavevector content of the PSD. Here, we study the adhesion of non-Gaussian surfaces by means of a DMT-based simplified BEM (Boundary-Element-Method), and report a clear difference in the adhesion and stickiness of surfaces with different height distribution function. We then obtain analytical equations for a generalized BAM model. Results of the extended BAM theory compare reasonably well with numerical BEM-DMT predictions. We also notice that any theory based on the surface energy, would show instead insensitivity to height distribution.

Application of maximum statistical entropy in formulating a non-gaussian probability density function in flow uncertainty analysis with prior measurement knowledge

In mechanical, civil and chemical engineering systems the accuracies of flow measurement instruments is conventionally specified by certified measurement capabilities (CMCs) that are symmetric, however it is physically possible for some flow instruments and equipment to exhibit asymmetric non-Gaussian behaviour. In this paper the influence of non-Gaussian uncertainties is investigated using direct Monte Carlo simulations to construct a probability density function (PDF) using representative non-Gaussian surface roughness data for a commercial steel pipe friction factor. Actual PDF results are compared and contrasted with a symmetric Gaussian PDF, and reveal inconsistencies in the statistical distributions that cannot be neglected in high accuracy flow measurements. The non-Gaussian PDF is visualized with a kernel density estimate (KDE) scheme to infer an initial qualitative shape of the actual PDF using the approximate locations of the normalized peaks as a initial metrologist estimate of the measurement density. This is then utilized as inputs in a maximum statistical entropy functional to optimize the actual non-Gaussian PDF using a nonlinear optimization of Lagrange multipliers for a mathematically unique PDE. Novelties in the present study is that a new methodology has been developed for statistical sampling from non-monotonic non-Gaussian distributions with accompanying Python and Matlab/GNU Octave computer codes, and a new methodology for utilizing metrologist's expert prior knowledge of PDF peaks and locations for constructing an a priori estimate of the shape of unknown density have been incorporated into the maximum statistical entropy nonlinear optimization problem for a faster and more efficient approach for generating statistical information and insights in constructing high accuracy non-Gaussian PDFs of real world messy engineering measurements.

Study on the influence of non-Gaussian honing surface on contact and flow characteristics

PurposeThe contact and lubrication performances, which were previously estimated assuming a Gaussian surface, are insufficient due to the non-Gaussian surface characteristics of the honing liner. The purpose of this study is to analyze the liner honing surface and examine its effects on the contact and flow performance.Design/methodology/approachThe fast Fourier transform (FFT) method was used to generate the liner honing texture. Subsequently, an elastoplastic contact model based on boundary element theory was constructed and simulated for the honing surface. The results were compared with those obtained using a Gaussian surface. In addition, flow factors of the honing surfaces were also compared.FindingsThe contact pressure and flow factors demonstrate significant disparities when dealing with non-Gaussian surfaces. In the deterministic model, the pressure exhibits considerably diminished magnitudes and a more evenly distribution. Moreover, when the gap between surfaces is narrow, the discrepancy in flow factor across different directions on the real honing surface becomes more prominent compared with the Gaussian surface.Originality/valueThe model incorporates the influence of the non-Gaussian honing surface, thereby enabling more accurate prediction.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2023-0198/

Investigation of Normal Dynamic Contact Stiffness and Damping Characteristics in Mixed Lubrication for Non-Gaussian Rough Surfaces

Investigation of Normal Dynamic Contact Stiffness and Damping Characteristics in Mixed Lubrication for Non-Gaussian Rough Surfaces

The influence of surface topography on thermal contact resistance of 7075-T6/beryllium bronze

The calculation of thermal contact resistance is crucial for studying heat transfer between solids. Surface topography has a significant impact on thermal contact resistance, however, the influence of surface topography parameters on thermal resistance is still limited to the parameters such as roughness. The effect of other topography parameters still lacks. Therefore, in this paper, randomly non-Gaussian rough surfaces with specified root mean square roughness value, kurtosis, skewness, and wave lengths are generated by two-dimensional digital filtering method combined with Johnson transformation system. The contact mechanical deformation, heat transfer performance and thermal contact resistance between 7075-T6 and beryllium bronze QBe2 are studied using ABAQUS. The results show that thermal contact resistance is correlated with real contact area. The thermal contact resistance decreases with the increase of pressure, and gradually gets a rise with the increase of root mean square roughness value. Normal distribution of asperities, the isotropic surface, and zero or a low negative value of skewness all can enhance heat transfer efficiency. Our results provide guidance for designing surface topography when heat transfer need be considered in application.

Scattering Properties of Non-Gaussian Ocean Surface with the SSA Model Applied to GNSS-R

Global Navigation Satellite System Reflectometry (GNSS-R) is an emerging earth observation method for remote sensing of feature parameters using reflected signals from navigation satellites, and is a purely specular bistatic forward scattering observation means with special right-handed circular polarization incident wave. In this paper, the small-slope approximation model of non-Gaussian sea surface is used as the basis to construct the scattering model for the observation geometry of GNSS-R as well as the L-band characteristics, and the fully-polarization normalized bistatic radar scattering cross section (NBRCS) are simulated by the method of polarization synthesis to analyze the scattering characteristics under different wind speeds and directions on the ocean surface, which highlights the variation of NBRCS with wind direction, and the scattering modeling accuracy is improved by comparing with the data of CYGNSS. In addition, we adopt the observation geometry deviating from purely specular geometry, discuss the scattering azimuth angle, scattering influence, and the relative relationship between different polarizations of the scattering angle under the non-specular geometry.

A Reciprocal Heuristic Model for Diffuse Scattering From Walls and Surfaces

Diffuse scattering of electromagnetic waves from natural and artificial surfaces has been extensively studied in various disciplines, including radio wave propagation, and several diffuse scattering models based on different approaches have been proposed over the years, two of the most popular ones being Kirchhoff Theory and the so-called Effective Roughness heuristic model. The latter, although less rigorous than the former, is more flexible and applicable to a wider range of real-world cases, including non-Gaussian surfaces, surfaces with electrically small correlation lengths and scattering from material inhomogeneities that are often present under the surface. Unfortunately, the Effective Roughness model, with the exception of its Lambertian version, does not satisfy reciprocity, which is an important physical-soundness requirement for any propagation model. In the present work, without compromising its effectiveness and its simple and yet sound power-balance approach, we propose a reciprocal version of the Effective Roughness model, which can be easily implemented and replaced to the old version in ray-based propagation models. The new model is analyzed and compared to the old one and to other popular models. Once properly calibrated, it is shown to yield similar - if not better - performance with respect to the old one when checked vs. measurements.

Investigation of the Static Performance of Hydrostatic Thrust Bearings Considering Non-Gaussian Surface Topography

The dynamic and static characteristics of hydrostatic thrust bearings are significantly affected by the bearing surface topography. Previous studies on hydrostatic thrust bearings have focused on Gaussian distribution models of bearing surface topography. However, based on actual measurements, the non-Gaussianity of the distribution characteristics of bearing surface topography is clear. To accurately characterize the non-Gaussian distribution of bearing surface topography, the traditional probability density function of Gaussian distribution was modified by introducing Edgeworth expansion. The non-Gaussian surface was then reflected by two parameters: kurtosis and skewness. This had an effect on the static characteristics of hydrostatic thrust bearings with both circumferential and radial surface topographies. The comparison between the Gaussian distribution results and those of the non-Gaussian model showed that errors between the two models could reach more than 10%. Therefore, it is important to take into account the non-Gaussianity of bearing surface when discussing static characteristics of hydrostatic thrust bearings considering the surface topography.

Investigations on electromagnetic wave scattering simulation from rough surface: Some instructions for surface roughness measurement based on machine vison

There are many experimental variables in the research of surface roughness measurement based on machine vision technology, such as light incident angle, light wavelength, workpiece material, surface features. It is, however, time-consuming and also labour-intensive to conduct experiments considering all these variables. In this work, we proposed to conduct Electromagnetic Wave Scattering Simulation considering these variables using finite element method (FEM) in order to give instructions for actual imaging design. The simulation process is more theoretically robust, more efficient and cost-effective rather than actual experiments with empirical models. In the simulation process, a simulation model is designed first. In this model, the light incident angles θ include 15°, 30°, 45°, 60° and 75°; the light wavelengths λ include 400 nm, 550 nm and 700 nm corresponding to blue, green and red; the workpiece materials include stainless steel (SUS), copper (Cu), aluminium (Al), and silicon carbide (SiC). Then, a series of rough surface with different surface roughness values are obtained by defining cosine functions and non-Gaussian surfaces. The simulation results show that given material, when 0≤Ra ≤ 0.1 μm, the performance of small θ is obviously better than that of large θ. When 0.1≤Ra ≤ 1 μm, large θ is better (θ ≥ 60°). This derives to obtain better measurement accuracy.

Simplified Calculation Model for Contact Resistance Based on Fractal Rough Surfaces Method

Electrical contact resistance (ECR) is critical to evaluate the stability and reliability of electrical connections. In this paper, a simplified contact model is established for rough surfaces based on the fractal theory and Monte Carlo method, which can overcome the difficulty of constructing the resistance networks for traditional contact models. The model reveals the influence of fractal parameters D and G on the surface morphology and contact characteristics. The established surface method can simulate Gaussian and non-Gaussian isotropic surfaces. Then the contact resistance considering a contaminated film is calculated, which provides a quantitative analysis of the change and the influencing factors. The accuracy of the calculation method in this paper is ensured by comparing the existing experimental data and finite element results. The results show that the contact surface with D of 1.5 has the largest real contact area and the smallest contact resistance. The model has accurate calculation results when dimensionless contact load F* is less than 4 × 10−3.

Evolution of the real contact area of self-affine non-Gaussian surfaces

The impact of non-Gaussian height distribution on the real contact area evolution of elastic, frictionless and non-adhesive contact is studied. The Weibull probability function is used to model the height distribution, as it can capture surfaces of practical relevance. The set of variables needed to parametrise the problem is discussed, including the shape parameter of the height distribution, the topography’s wavelength ratio and the Hurst exponent. As the topographies become more non-Gaussian, a significant deviation from the Gaussian case is observed. Moreover, the spectral properties show a distinct effect on different non-Gaussian surfaces and the dependency on Nayak’s parameter is not inherited. A power-law evolution of the real contact area is found to fit the numerical results obtained with the boundary element method precisely. Finally, two semi-analytical asperity-based models are compared with numerical results, using the statistics of artificially generated topographies. The qualitative behaviour predicted with the numerical simulations is captured.