Theoretical Modeling and Analysis of Directional Spectrum Emissivity and Its Pattern for Random Rough Surfaces with a Matrix Method

The emissivity is an important surface property parameter in many fields, including infrared temperature measurement. In this research, a symmetry theoretical model of directional spectral emissivity prediction is proposed based on Gaussian random rough surface theory. A numerical solution based on a matrix method is determined based on its symmetrical characteristics. Influences of the index of refraction n and the root mean square (RMS) roughness σrms on the directional spectrum emissivity ε are analyzed and discussed. The results indicate that surfaces with higher n and lower σrms tend to have a peak in high viewing angles. On the contrary, surfaces with lower n and higher σrms tend to have a peak in low viewing angles. Experimental verifications based on infrared (IR) temperature measurement of Inconel 718 sandblasted surfaces were carried out. This model would contribute to understand random rough surfaces and their emitting properties in fields including machining, process controlling, remote sensing, etc.

Tungsten Based Spectrally Selective Absorbers with Anisotropic Rough Surface Texture

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.

Full Wave Modeling of Electromagnetic Scattering by an Object buried between two Rough Surfaces: Application to GPR

<pre>In this paper, we present an efficient numerical method to calculate the frequency and time responses of the field scattered by an object buried between two random rough surfaces. This method is called Generalized PILE (GPILE) method because it extends the PILE method which considers only two surfaces or an object buried under a surface. The GPILE method solves rigourously the Maxwell equations by using a simple matrix formulation. The obtained results have a straightforward physical interpretation and allow us to investigate the influence of the object buried between the two rough surfaces. We distinguish the primary echo of the upper surface, the multiple echoes coming from the lower surface and those arising from the object. The GPILE method is applied to simulate the Ground Penetrating Radar (GPR) signal at nadir. The resulting time response helps the user to detect the presence of the object buried between the two random rough surfaces.</pre>

Full Wave Modeling of Electromagnetic Scattering by an Object buried between two Rough Surfaces: Application to GPR

<pre>In this paper, we present an efficient numerical method to calculate the frequency and time responses of the field scattered by an object buried between two random rough surfaces. This method is called Generalized PILE (GPILE) method because it extends the PILE method which considers only two surfaces or an object buried under a surface. The GPILE method solves rigourously the Maxwell equations by using a simple matrix formulation. The obtained results have a straightforward physical interpretation and allow us to investigate the influence of the object buried between the two rough surfaces. We distinguish the primary echo of the upper surface, the multiple echoes coming from the lower surface and those arising from the object. The GPILE method is applied to simulate the Ground Penetrating Radar (GPR) signal at nadir. The resulting time response helps the user to detect the presence of the object buried between the two random rough surfaces.</pre>

A Static Friction Model for Unlubricated Contact of Random Rough Surfaces at Micro/Nano Scale

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.