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.

A Microscopic Wear Measurement Method for General Surfaces

2002 ◽  
Vol 124 (4) ◽  
pp. 829-833 ◽  
Author(s):  
Yeau-Ren Jeng ◽  
Zhi-Way Lin ◽  
Shiuh-Hwa Shyu
Keyword(s):  
Surface Roughness ◽  
Measurement Method ◽  
Current Method ◽  
Current Approach ◽  
Height Distribution ◽  
Initial Surface ◽  
Roughness Parameters ◽  
Wear Measurement ◽  
Non Gaussian ◽  
Worn Surfaces

A method was developed to measure the wear of general engineering surfaces based on the roughness parameters of the worn surfaces. This method does not require any information of the initial surface. The surface height distribution is described using Johnson translatory system where the loss of surface height is attributed to wear. Experiments of engine running in were conducted to validate the method. The results show that the current method can determine wear comparable to surface roughness. The current approach simplifies the profilometrical wear measurement and extends such a measurement to non-Gaussian surfaces.

Application of Boltzmann Statistical Mechanics in the Validation of the Gaussian Summit-Height Distribution in Rough Surfaces

1997 ◽  
Vol 119 (4) ◽  
pp. 846-850 ◽  
Author(s):  
M. Leung ◽  
C. K. Hsieh ◽  
D. Y. Goswami
Keyword(s):  
Surface Roughness ◽  
Statistical Mechanics ◽  
Theoretical Basis ◽  
Rough Surfaces ◽  
Electrical Contact ◽  
Height Distribution ◽  
Probable Distribution ◽  
Theoretical Predictions ◽  
Most Probable Distribution ◽  
Roughness Measurements

In theoretical modeling of contact mechanics, a homogeneously, isotropically rough surface is usually assumed to be a flat plane covered with asperities of a Gaussian summit-height distribution. This assumption yields satisfactory results between theoretical predictions and experimental measurements of the physical characteristics, such as thermal/electrical contact conductance and friction coefficient. However, lack of theoretical basis of this assumption motivates further study in surface modeling. This paper presents a theoretical investigation by statistical mechanics to determine surface roughness in terms of the most probable distribution of surface asperities. Based upon the surface roughness measurements as statistical constraints, the Boltzmann statistical model derives a distribution equivalent to Gaussian. The Boltzmann statistical mechanics derivation in this paper provides a rigorous validation of the Gaussian summit-height assumption presently in use for study of rough surfaces.

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.

Numerical Investigations of Various Surface Roughness Parameters on the Performance of Profiled Hydrostatic Thrust Bearing

2005 ◽  
Author(s):  
Kirat Shah ◽  
Robert E. Johnson ◽  
Harish P. Cherukuri
Keyword(s):  
Surface Roughness ◽  
Thrust Bearings ◽  
Lubrication Equation ◽  
Load Carrying ◽  
Minimum Film Thickness ◽  
Order Of Magnitude ◽  
Auto Correlation Function ◽  
Non Gaussian ◽  
Gaussian Surface ◽  
Lubrication Conditions

Measurements of surface roughness on hydrostatic bearing slipper indicate that the surfaces are not always Gaussian. Previous studies in this area were primarily concerned with Gaussian surfaces. In this research the effects of non-Gaussian surface roughness on the performance of profiled hydrostatic thrust bearings are analyzed. This study is applicable to the lubrication conditions where the surface roughness is of the same order of magnitude as the minimum film thickness. Surfaces with different skewness, kurtosis, mean, auto-correlation function and standard deviation are generated numerically using a combination of Fast Fourier Transform (FFT) and Johnson translatory system. The finite difference method is used to solve the Reynolds lubrication equation. The effect of roughness on the load carrying capacity is investigated and compared with the results for ideal smooth surfaces.

The Contact of Two Nominally Flat Rough Surfaces

1970 ◽  
Vol 185 (1) ◽  
pp. 625-633 ◽  
Author(s):  
J. A. Greenwood ◽  
J. H. Tripp
Keyword(s):  
Surface Roughness ◽  
General Theory ◽  
Rough Surface ◽  
Rough Surfaces ◽  
Deformation Mode ◽  
Surface Model ◽  
Geometrical Properties ◽  
Rough Plane ◽  
Surface Contact ◽  
Compliance Curve

Most models of surface contact consider the surface roughness to be on one of the contacting surfaces only. The authors give a general theory of contact between two rough plane surfaces. They show that the important results of the previous models are unaffected: in particular, the load and the area of contact remain almost proportional, independently of the detailed mechanical and geometrical properties of the asperities. Further, a single-rough-surface model can always be found which will predict the same laws as a given two-rough-surface model, although the required model may be unrealistic. It does not seem possible to deduce the asperity shape or deformation mode from the load-compliance curve.

Effect of Surface Roughness on Fouling of Calcium Carbonate: An Experimental Investigation

2010 ◽  
Author(s):  
M. Izadi ◽  
D. K. Aidun ◽  
P. Marzocca ◽  
H. Lee
Keyword(s):  
Surface Roughness ◽  
Calcium Carbonate ◽  
Rough Surface ◽  
Smooth Surface ◽  
Rough Surfaces ◽  
Operating Conditions ◽  
Tubular Heat Exchanger ◽  
Analytical Microscopy ◽  
Deposit Layer ◽  
Effect Of Surface

The effect of surface roughness on the fouling behavior of calcium carbonate is experimentally investigated. The real operating conditions of a tubular heat exchanger are simulated by performing prolonged experiments with duration of 3 to 7 days. The solution used is a mixture of sodium bicarbonate and calcium chloride in de-ionized water with the concentration of 0.4 g/l of each. An on-line fouling evaluation system was developed such that the fouling resistance for a selected solution could be measured in real time. The experiments are repeated with the same procedure for 90/10 Cu/Ni tubes with different internal surface roughness. After the experiment the surface is analyzed by analytical microscopy to investigate the morphology of the deposit layer. Comparison of the experimental results of smooth and rough surfaces shows that a combination of aragonite and calcite polymorphs are formed on rough surface while only dendritic porous aragonite crystals are formed on smooth surface. Accordingly, the deposit layer formed on rough surface is denser and has a higher thermal resistance comparing to that formed on smooth surface. The fouling factor-time curves of smooth and rough surfaces obtained by the current experimental study agree with the results found by the analytical microscopy of the surface and show higher fouling resistances for rough surface. Experimental data is significantly important for the design, and formulating operating, and cleaning schedules of the equipment.

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