scholarly journals Rough-surface shadowing of self-affine random rough surfaces

2007 ◽  
Vol 106 (1-3) ◽  
pp. 398-416 ◽  
Author(s):  
Hannu Parviainen ◽  
Karri Muinonen
1985 ◽  
Vol 54 ◽  
Author(s):  
J. R. Blanco ◽  
K. Vedam ◽  
P. J. McMarr ◽  
J. M. Bennett

ABSTRACTWell characterized rough surfaces of aluminum films have been studied by the nondestructive technique of Spectroscopie Ellipsometry (SE). The roughness of the aluminum specimens had been characterized earlier by Total Integrated Scattering and Stylus Profilometry techniques to obtain numerical estimates of ras roughness and autocovariance lengths. The present SE measurements on these specimens were carried out at a number of angles of incidence in the range 30–80° and at a number of discrete wavelengths in the spectral range 300–650nm. The SE results were then analyzed by the scalar theory of diffraction from random rough surfaces by treating the surface as a simple random rough surface. The results of such analyses of the SE measurements are compared with the results of the earlier characterization techniques.


Nanomaterials ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2018
Author(s):  
Niloufar Pirouzfam ◽  
Kursat Sendur

Spectrally selective absorbers have received considerable interest due to their applications in thermophotovoltaic devices and as solar absorbers. Due to extreme operating conditions in these applications, such as high temperatures, thermo-mechanically stable and broadband spectrally selective absorbers are of interest. This paper demonstrates anisotropic random rough surfaces that provide broadband spectrally selective absorption for the thermo-mechanically stable Tungsten surfaces. Anisotropic random rough surface has different correlation lengths in the x- and y-directions, which means their topography parameters have directional dependence. In particular, we demonstrate that spectral absorptance of Tungsten random rough surfaces at visible (VIS) and near-infrared (NIR) spectral regions are sensitive to correlation length and RMS height variations. Our results indicate that by optimizing random rough surface parameters, absorption values exceeding 95% can be obtained. Moreover, our results indicate that anisotropic random rough surfaces broaden the bandwidth of the high absorption region. It is shown that in VIS and NIR regions, the absorption enhancements of up to 47% and 52% are achieved for the isotropic and anisotropic rough surfaces, respectively.


Micromachines ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 368
Author(s):  
Shengguang Zhu ◽  
Liyong Ni

A novel static friction model for the unlubricated contact of random rough surfaces at micro/nano scale is presented. This model is based on the energy dissipation mechanism that states that changes in the potential of the surfaces in contact lead to friction. Furthermore, it employs the statistical theory of two nominally flat rough surfaces in contact, which assumes that the contact between the equivalent rough peaks and the rigid flat plane satisfies the condition of interfacial friction. Additionally, it proposes a statistical coefficient of positional correlation that represents the contact situation between the equivalent rough surface and the rigid plane. Finally, this model is compared with the static friction model established by Kogut and Etsion (KE model). The results of the proposed model agree well with those of the KE model in the fully elastic contact zone. For the calculation of dry static friction of rough surfaces in contact, previous models have mainly been based on classical contact mechanics; however, this model introduces the potential barrier theory and statistics to address this and provides a new way to calculate unlubricated friction for rough surfaces in contact.


2009 ◽  
Vol 131 (2) ◽  
Author(s):  
Stephen T. McClain ◽  
Jason M. Brown

The discrete-element model for flows over rough surfaces was recently modified to predict drag and heat transfer for flow over randomly rough surfaces. However, the current form of the discrete-element model requires a blockage fraction and a roughness-element diameter distribution as a function of height to predict the drag and heat transfer of flow over a randomly rough surface. The requirement for a roughness-element diameter distribution at each height from the reference elevation has hindered the usefulness of the discrete-element model and inhibited its incorporation into a computational fluid dynamics (CFD) solver. To incorporate the discrete-element model into a CFD solver and to enable the discrete-element model to become a more useful engineering tool, the randomly rough surface characterization must be simplified. Methods for determining characteristic diameters for drag and heat transfer using complete three-dimensional surface measurements are presented. Drag and heat transfer predictions made using the model simplifications are compared to predictions made using the complete surface characterization and to experimental measurements for two randomly rough surfaces. Methods to use statistical surface information, as opposed to the complete three-dimensional surface measurements, to evaluate the characteristic dimensions of the roughness are also explored.


1988 ◽  
Vol 110 (4) ◽  
pp. 380-384 ◽  
Author(s):  
R. P. Taylor ◽  
W. F. Scaggs ◽  
H. W. Coleman

The status of prediction methods for friction coefficients in turbulent flows over nonuniform or random rough surfaces is reviewed. Experimental data for friction factors in fully developed pipe flows with Reynolds numbers between 10,000 and 600,000 are presented for two nonuniform rough surfaces. One surface was roughened with a mixture of cones and hemispheres which had the same height and base diameter and were arranged in a uniform array. The other surface was roughened with a mixture of two sizes of cones and two sizes of hemispheres. These data are compared with predictions made using the previously published discrete element prediction approach of Taylor, Coleman, and Hodge. The agreement between the data and the predictions is excellent.


1992 ◽  
Vol 31 (22) ◽  
pp. 4534 ◽  
Author(s):  
Fatima Abdellani ◽  
Georges Rasigni ◽  
Monique Rasigni ◽  
Antoine Llebaria

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