Scattering from an elastic shell and a doubly infinite fluid–solid interface with random surface roughness

1993 ◽  
Vol 93 (4) ◽  
pp. 2420-2420
Author(s):  
Garner C. Bishop ◽  
Judy Smith
Keyword(s):  
Surface Roughness ◽  
Elastic Shell ◽  
Random Surface ◽  
Solid Interface

The effect of a footprint on perceived surface roughness

1986 ◽  
Vol 405 (1829) ◽  
pp. 303-327 ◽  
Keyword(s):  
Surface Roughness ◽  
Weighting Function ◽  
Sampling Interval ◽  
Asymptotic Convergence ◽  
Reference Surface ◽  
Two Dimensional ◽  
Random Surface ◽  
Spectral Density Functions ◽  
Continuous Theory ◽  
Discrete Theory

A two-dimensional homogeneous random surface { y ( X )} is generated from another such surface { z ( X )} by a process of smoothing represented by y ( X ) = ∫ ∞ d u w ( u – X ) z ( u ), where w ( X ) is a deterministic weighting function satisfying certain conditions. The two-dimensional autocorrelation and spectral density functions of the smoothed surface { y ( X )} are calculated in terms of the corresponding functions of the reference surface { z ( X )} and the properties of the ‘footprint’ of the contact w ( X ). When the surfaces are Gaussian, the statistical properties of their peaks and summits are given by the continuous theory of surface roughness. If only sampled values of the surface height are available, there is a corresponding discrete theory. Provided that the discrete sampling interval is small enough, profile statistics calculated by the discrete theory should approach asymptotically those calculated by the continuous theory, but it is known that such asymptotic convergence may not occur in practice. For a smoothed surface { y ( X )} which is generated from a reference surface { z ( X )} by a ‘good’ footprint of finite area, it is shown in this paper that the expected asymptotic convergence does occur always, even if the reference surface is ideally white. For a footprint to be a good footprint, w ( X ) must be continuous and smooth enough that it can be differentiated twice everywhere, including at its edges. Sample calculations for three footprints, two of which are good footprints, illustrate the theory.

Random surface roughness effect on slider microbearing lubrication

2010 ◽  
Vol 5 (5) ◽  
pp. 347 ◽  
Author(s):  
Wen-Ming Zhang ◽  
Guang Meng ◽  
Zhi-Ke Peng
Keyword(s):  
Surface Roughness ◽  
Roughness Effect ◽  
Random Surface

scholarly journals Modeling Nanoelectromechanical Switches With Random Surface Roughness

2017 ◽  
Vol 64 (5) ◽  
pp. 2409-2416 ◽  
Author(s):  
Daniel Connelly ◽  
Tsu-Jae King Liu
Keyword(s):  
Surface Roughness ◽  
Random Surface

A New Technique for Classifying Random Surface Roughness

1967 ◽  
Author(s):  
Bruce D. Van Deusen ◽  
Gerald E. Mccarron
Keyword(s):  
Surface Roughness ◽  
New Technique ◽  
Random Surface ◽  
A New Technique

scholarly journals Cylinder-Flat Contact Mechanics with Surface Roughness

2020 ◽  
Vol 69 (1) ◽  
Author(s):  
A. Tiwari ◽  
B. N. J. Persson
Keyword(s):  
Surface Roughness ◽  
Contact Pressure ◽  
Dimensionless Parameter ◽  
Elastic Half Space ◽  
Root Mean Square Roughness ◽  
Mean Square ◽  
Hertz Contact ◽  
Random Surface ◽  
Roughness Amplitude ◽  
Flat Contact

AbstractWe study the nominal (ensemble averaged) contact pressure p(x) acting on a cylinder squeezed in contact with an elastic half space with random surface roughness. The contact pressure is Hertzian-like for $$\alpha < 0.01$$ α < 0.01 and Gaussian-like for $$\alpha > 10$$ α > 10 , where the dimensionless parameter $$\alpha = h_{\rm rms}/\delta $$ α = h rms / δ is the ratio between the root-mean-square roughness amplitude and the penetration for the smooth surfaces case (Hertz contact).

scholarly journals Effect of the Dynamic Load on Stresses in a Deck Pavement with an Interlayer Contact Model

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Xuntao Wang ◽  
Jianhu Feng ◽  
Hu Wang ◽  
Shidi Hong ◽  
Xiaohan Cheng ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Dynamic Load ◽  
Asphalt Concrete ◽  
Element Model ◽  
Superposition Method ◽  
Vehicle Speed ◽  
Random Surface ◽  
Bonding Condition ◽  
Concrete Layer ◽  
Road Surface Roughness

Random surface roughness of bridge deck pavement just like random road surface roughness was simulated by the harmony superposition method in this paper. The dynamic load of vehicle was calculated by the random surface roughness of the deck pavement and the quarter-car model. A finite element model of a box girder bridge and its deck pavement was established, and the bonding condition between the adjacent layers was assumed to be contact bonding condition. The stress values of the asphalt concrete layer were calculated and analyzed when surface roughness condition, vehicle speed, and disengaging area changed. Results show that random surface roughness of deck pavement affected the stress trend of the asphalt concrete layer obviously. The appearance of disengaging area would increase the stress values of the asphalt concrete layer and the normal tensile stress value between the asphalt concrete layer and the waterproof layer. This would speed up the damage of the asphalt concrete layer and enlarge further the disengaging area.

scholarly journals Surface Roughness Effects on the Broadband Reflection for Refractory Metals and Polar Dielectrics

Materials ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3090 ◽  
Author(s):  
Lina Cao ◽  
Kursat Sendur
Keyword(s):  
Material Processing ◽  
Surface Roughness ◽  
Plasma Frequency ◽  
Refractory Metals ◽  
Roughness Effects ◽  
Random Surface ◽  
Spectral Reflectivity ◽  
Infrared Spectral ◽  
Gaussian Surface ◽  
Surface Distortions

Random surface roughness and surface distortions occur inevitably because of various material processing and fabrication techniques. Tailoring and smoothing the surface roughness can be especially challenging for thermomechanically stable materials, including refractory metals, such as tungsten (W), and polar dielectrics, such as silicon carbide (SiC). The spectral reflectivity and emissivity of surfaces are significantly impacted by surface roughness effects. In this paper, we numerically investigated the surface roughness effects on the spectral reflectivity and emissivity of thermomechanically stable materials. Based on our results, we determined that surface roughness effects are strongly impacted by the correlation length of the Gaussian surface. In addition, our results indicate that surface roughness effects are stronger for the materials at the epsilon-near-zero region. Surface roughness effects are stronger between the visible and infrared spectral region for W and around the wavelength of 12 μ m for SiC, where plasma frequency and polar resonance frequency are located.

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