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Numerical Investigation of Heat and Mass Transfer in Nanofluid-Filled Porous Medium

Advances in Nanoparticles 2024年第3期13卷 29-44页

作者： Dalel Helel Noureddine Boukadida issats University of Sousse Souuse Tunisia Laboratory of Metrology and Energy Systems ENIM University of Monastir Monastir Tunisia ESSTHS University of Sousse Sousse Tunisia

In this work, we numerically study the laminar mixed convection of fluid flow in a vertical channel filled with porous media during the drying process. The porous medium, modeled as a vertical wall, consists of solid and nanofluid phase (Water-Al2O3 or Water-Cu), as well as a gas phase. The established model is developed based on Whitaker’s theory and resolved by our numerical code using Fortran. Results principally show the influence of various physical parameters, such as nanoparticle volume fraction, ambient temperature, and saturation on heat and mass transfer on the drying process. This study brings the effect of the presence of nanofluids in porous media. It contributes not only to our fundamental understanding of drying processes but also provides practical insights that can guide the development of more efficient and sustainable drying technologies. .

关键词： Mixed Convection Heat Transfer Nanofluid Drying Porous Media

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DYNAMICS OF NEW CLASS OF HOPFIELD NEURAL NETWORKS WITH TIME-VARYING AND DISTRIBUTED DELAYS

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Acta Mathematica Scientia 2016年第3期36卷 891-912页

作者： Adnene ARBI Farouk CHERIF Chaouki AOUITI Abderrahmen TOUATI Department of Mathematics Facultd des Sciences de BizerteUniversity of CarthageJarzouna 7021BizerteTunisia Department of Computer Science ISSATSLaboratory of Math PhysicsUniversity of SousseSpecials Functions and Applications LR11ES35ecole suprieure des sciences et de technologieSousse 4002Tunisia

In this paper, we investigate the dynamics and the global exponential stability of a new class of Hopfield neural network with time-varying and distributed delays. In fact, the properties of norms and the contraction principle are adjusted to ensure the existence as well as the uniqueness of the pseudo almost periodic solution, which is also its derivative pseudo almost periodic. This results are without resorting to the theory of exponential dichotomy. Furthermore, by employing the suitable Lyapunov function, some delayindependent sufficient conditions are derived for exponential convergence. The main originality lies in the fact that spaces considered in this paper generalize the notion of periodicity and almost periodicity. Lastly, two examples are given to demonstrate the validity of the proposed theoretical results.

关键词： delayed functional differential equations neural networks pseudo-almost peri- odic solution global exponential stability time-varying and distributed delays fixed point theorem

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