Search

The enhancement of heat transfer for electronic kits and automobiles has become highly dependent on the finned heat exchangers; this is because fin provides high heat transfer rate and superior performance with a significant temperature reduction. In this manuscript, a fractional modeling of non-Fourier heat conduction problem of a fin is proposed within the periodic temperature boundary condition. The mathematical modeling is performed via classical theory of heat conduction that is directly proportional to temperature gradient through which hyperbolic heat conduction equation for a fin is generated. The hyperbolic heat conduction equation for a fin is fractionalized via modern approaches of fractional differentiations, namely Atangana–Baleanu and Caputo–Fabrizio differential operators. In order to have analyticity of hyperbolic heat conduction equation for a fin, we invoked the mathematical techniques of Laplace transform. The exact solutions of temperature distribution have been obtained in terms of Fox-H and Mittag–Leffler functions with the product of convolution. The solutions of temperature distribution have been classified into integer verses non-integer theories by making fractional parameters α = β = 1 and α ≠ β ≠ 1 , respectively. Our results suggest that due to variability of different rheological parameters on temperature distribution, the cooling process is faster via fractional models in comparison to non-fractional model. Additionally, it is also observed that thermal wave propagates at a specific time results the reciprocal trend in temperature distribution. [ABSTRACT FROM AUTHOR]

The registration of a 3D model over an image can be seen as the alignment of visual correspondences extracted from these two data. This is a challenging task and it is even more complex when the two images have a different modality. This paper introduces an approach that allows matching features detected in two different modalities: photographs and 3D models, by using a common 2D representation. Our approach is based on a modification of the Marching Cubes algorithm aiming to remove ambiguous cases without adding further calculations in each cube. We share the idea about the crucial importance of splitting the equivalence cases into two classes. Considering all the possible states inside/outside in the four corners of a cube side, indeed, there are only four non-trivial cases after eliminating those equivalences through the rotation. The obtained results allow us to validate the feasibility of the proposed methodology. [ABSTRACT FROM AUTHOR]

Accurate and fast characterization of voltage variations helps to evaluate their severity on equipment and activate protections. In this paper, a methodology for tracking and characterization of voltage variations, sample to sample, is presented. It consists of a Hilbert transform to estimate the voltage of the signal’s envelope, a fuzzy logic system to track down the type of voltage variation, and a rule-based method for the final identification and decision making according to IEEE Std 1159-2009. Unlike some techniques presented in the literature for tracking voltage variations such as the Kalman filter and adaptive linear network techniques, the proposed methodology requires neither a harmonic model nor an algorithm to adjust the model parameters, which in many cases increases the computational burden and time tracking. It is worth mentioning that the proposed classification stage does not need a training stage; therefore, its development is easier and its efficiency does not depend on a data training set. The performance of the proposed methodology is validated and tested using synthetic signals as well as real measurements of voltage variations. In addition, an implementation of our methodology into an field-programmable gate array based system is performed in an effort to offer a low-cost and portable system-on-a-chip solution for online and real-time monitoring of voltage variations. [ABSTRACT FROM PUBLISHER]