scholarly journals A Comparative Study on Asperity Peak Modeling Methods

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Wei Zhou ◽  
Daiyan Zhao ◽  
Jinyuan Tang ◽  
Jun Yi
Keyword(s):  
Rough Surface ◽  
Surface Profile ◽  
Statistical Characteristics ◽  
Height Distribution ◽  
Statistical Distributions ◽  
Spectral Moment ◽  
Correlation Pattern ◽  
Modeling Methods ◽  
Distribution Parameters ◽  
Moment Approach

AbstractThe peak identification scheme based method (three-point definition) and the spectral moments based method (spectral moment approach) are both widely used for asperity peak modeling in tribology. To discover the differences between the two methods, a great number of rough surface profile samples with various statistical distributions are first randomly generated using FFT. Then the distribution parameters of asperity peaks are calculated for the generated samples with both methods. The obtained results are compared and verified by experiment. The variation rules of the differences between the two methods with statistical characteristics of rough surfaces are investigated. To explain for the discovered differences, the assumptions by spectral moment approach that the joint distribution of surface height, slope and curvature is normal and that the height distribution of asperities is Gaussian, are examined. The results show that it is unreasonable to assume a joint normal distribution without inspecting the correlation pattern of [z], [z′] and [z′′], and that the height distribution of asperities is not exactly Gaussian before correlation length of rough surface increases to a certain extent, 20 for instance.

scholarly journals A Comparative Study on Asperity Peak Modeling Methods

2020 ◽  
Author(s):  
Wei Zhou ◽  
Jin-Yuan Tang ◽  
Jun Yi
Keyword(s):  
Rough Surface ◽  
Surface Profile ◽  
Statistical Characteristics ◽  
Height Distribution ◽  
Statistical Distributions ◽  
Spectral Moment ◽  
Correlation Pattern ◽  
Modeling Methods ◽  
Distribution Parameters ◽  
Moment Approach

Abstract The peak identification scheme based method (three-point definition) and the spectral moments based method (spectral moment approach) are both widely used for asperity peak modeling in tribology. To discover the differences between the two methods, a great number of rough surface profile samples with various statistical distributions are first randomly generated using FFT. Then the distribution parameters of asperity peaks are calculated for the generated samples with both methods. The obtained results are compared and verified by experiment. The variation rules of the differences between the two methods with statistical characteristics of rough surfaces are investigated. To explain for the discovered differences, the assumptions by spectral moment approach that the joint distribution of surface height, slope and curvature is normal and that the height distribution of asperities is Gaussian, are examined. The results show that it is unreasonable to assume a joint normal distribution without inspecting the correlation pattern of [z], [z′] and [z′′], and that the height distribution of asperities is not exactly Gaussian before correlation length of rough surface increases to a certain extent, 20 for instance.

scholarly journals Radar Imaging Statistics of Non-Gaussian Rough Surface: A Physics-Based Simulation Study

2022 ◽  
Vol 14 (2) ◽  
pp. 311
Author(s):  
Cheng-Yen Chiang ◽  
Kun-Shan Chen ◽  
Ying Yang ◽  
Yang Zhang ◽  
Lingbing Wu
Keyword(s):  
Surface Roughness ◽  
Rough Surface ◽  
Rough Surfaces ◽  
Parameters Estimation ◽  
Statistical Characteristics ◽  
Height Distribution ◽  
Sar Imaging ◽  
Non Gaussian ◽  
Physics Based Simulation ◽  
Gaussian Surface

This paper investigates the radar image statistics of rough surfaces by simulating the scattered signal’s dependence on the surface roughness. Statistically, the roughness characteristics include the height probability density (HPD) and, to the second-order, the power spectral density (PSD). We simulated the radar backscattered signal by computing the far-field scattered field from the rough surface within the antenna beam volume in the context of synthetic aperture radar (SAR) imaging. To account for the non-Gaussian height distribution, we consider microscopic details of the roughness on comparable radar wavelength scales to include specularly, singly, and multiply scatterers. We introduce surface roughness index (RSI) to distinguish the statistical characteristics of rough surfaces with different height distributions. Results suggest that increasing the RMS height does not impact the Gaussian HPD surface but significantly affects the Weibull surface. The results confirm that as the radar frequency increases, or reaches a relatively larger roughness, the surface’s HPD causes significant changes in incoherent scattering due to more frequent multiple scattering contributions. As a result, the speckle move further away from the Rayleigh model. By examining individual RSI, we see that the Gaussian HPD surface is much less sensitive to RMS height than the Weibull HPD surface. We demonstrate that to retrieve the surface parameters (both dielectric and roughness) from the estimated RCS, less accuracy is expected for the non-Gaussian surface than the Gaussian surface under the same conditions. Therefore, results drawn from this study are helpful for system performance evaluations, parameters estimation, and target detection for SAR imaging of a rough surface.

scholarly journals Correlation Analysis of Roughness Surface Height Distribution Parameters and Maximum Mises Stress

2021 ◽  
Author(s):  
Duo Yang ◽  
Qibo Wang ◽  
Jinyuan Tang ◽  
Fujia Xia ◽  
Wei Zhou ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Rough Surface ◽  
Contact Stress ◽  
Extreme Values ◽  
Combination Method ◽  
Particle Swarm Algorithm ◽  
Height Distribution ◽  
Roughness Surface ◽  
Distribution Parameters ◽  
The Relationship

Abstract Roughness surfaces contact analysis is an advanced research topic in interface design. The 3D rough surface amplitude distribution characterized by height distribution parameters(Sq (root mean square), Ssk (skewness), Sku (kurtosis)) has a great influence on the extreme value and distribution of the interface contact stress. However, the relationship between height distribution parameters and surface maximum mises stress (σmax) is still unclear and lacks of in-depth study. With the assistance of roughness surface reconstruction and contact stress algorithm proposed by the research group, σmax under a large sample was calculated and used as the data support for correlation analysis. Through BP neural network, global sensitivity qualitative (Morris) and quantitative (Sobol) analysis methods, the relationship between Sq, Ssk, Sku and σmax under different loads is studied. Based on complete polynomial and permutation combination method, the optimal correlation model between height distribution parameters and σmax was established, and particle swarm algorithm was introduced to analyze σmax extreme values under different Sq. The results show that: (1) Under different loads, the order about height distribution parameters influence on surface contact stress is: Sq> Ssk > Sku, and as the load increases, the influence of Ssk and Sku gradually decreases. (2) In different roughness surfaces, the influence of Ssk and Sku on the contact performance is significantly full of discrepancy. The research results provide reference and technical support for active design of rough surface microstructure to improved contact performance.

Rubber–Road Contact: Comparison of Physics-Based Theory and Indoor Experiments

2016 ◽  
Vol 44 (3) ◽  
pp. 150-173 ◽  
Author(s):  
Mehran Motamedi ◽  
Saied Taheri ◽  
Corina Sandu
Keyword(s):  
Rough Surface ◽  
Practical Importance ◽  
Surface Profile ◽  
Surface Characteristics ◽  
Mechanical Analysis ◽  
Friction Model ◽  
Rubber Friction ◽  
Optical Profilometer ◽  
Viscoelastic Modulus ◽  
Longitudinal Slip

ABSTRACT For tire designers, rubber friction is a topic of pronounced practical importance. Thus, development of a rubber–road contact model is of great interest. In this research, to predict the effectiveness of the tread compound in a tire as it interacts with the pavement, the physics-based multiscale rubber-friction theories developed by B. Persson and M. Klüppel were studied. The strengths of each method were identified and incorporated into a consolidated model that is more comprehensive and proficient than any single, existing, physics-based approach. In the present work, the friction coefficient was estimated for a summer tire tread compound sliding on sandpaper. The inputs to the model were the fractal properties of the rough surface and the dynamic viscoelastic modulus of rubber. The sandpaper-surface profile was measured accurately using an optical profilometer. Two-dimensional parameterization was performed using one-dimensional profile measurements. The tire tread compound was characterized via dynamic mechanical analysis. To validate the friction model, a laboratory-based, rubber-friction test that could measure the friction between a rubber sample and any arbitrary rough surface was designed and built. The apparatus consisted of a turntable, which can have the surface characteristics of choice, and a rubber wheel in contact with the turntable. The wheel speed, as well as the turntable speed, could be controlled precisely to generate the arbitrary values of longitudinal slip at which the dynamic coefficient of friction was measured. The correlation between the simulation and the experimental results was investigated.

scholarly journals Finite Element Study of the Effect of Internal Cracks on Surface Profile Change due to Low Loading of Turbine Blade

2020 ◽  
Vol 10 (14) ◽  
pp. 4883
Author(s):  
Junji Sakamoto ◽  
Naoya Tada ◽  
Takeshi Uemori ◽  
Hayato Kuniyasu
Keyword(s):  
Finite Element ◽  
Surface Properties ◽  
Strain Distribution ◽  
Power Plants ◽  
Thermal Power ◽  
Turbine Blades ◽  
Surface Profile ◽  
Height Distribution ◽  
Small Load ◽  
The Difference

Turbine blades for thermal power plants are exposed to severe environments, making it necessary to ensure safety against damage, such as crack formation. A previous method detected internal cracks by applying a small load to a target member. Changes in the surface properties of the material were detected before and after the load using a digital holographic microscope and a digital height correlation method. In this study, this technique was applied in combination with finite element analysis using a 2D and 3D model simulating the turbine blades. Analysis clarified that the change in the surface properties under a small load varied according to the presence or absence of a crack, and elucidated the strain distribution that caused the difference in the change. In addition, analyses of the 2D model considering the material anisotropy and thermal barrier coating were conducted. The difference in the change in the surface properties and strain distribution according to the presence or absence of cracks was elucidated. The difference in the change in the top surface height distribution of the materials with and without a crack was directly proportional to the crack length. As the value was large with respect to the vertical resolution of 0.2 nm of the digital holographic microscope, the change could be detected by the microscope.

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