UVAM, Bilişim Teknolojileri Uygulama ve Araştırma Merkezi Koleksiyonu
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Öğe Neural network and thermodynamic optimization of magnetized hybrid nanofluid dissipative radiative convective flow with energy activation(Taylor & Francis Inc, 2024) Ferdows, M.; Ahmed, Muktadir; Bhuiyan, Miraj Ahmed; Beg, O. Anwar; Çolak, Andaç Batur; Leonard, H. J.This article, motivated by hybrid magnetic coating manufacturing developments, utilizes a neural network-based computational program to study the dynamics of hybrid magnetic nanofluids with entropy generation. A new physico-chemo-mathematical model has been presented to simulate the hybrid magnetic nano-coating flow along a stretching surface to a porous medium with viscous heating. A Rosseland flux model is used for radiation heat transfer and Darcy's model for the isotropic porous medium. The stretching sheet is porous, and wall suction or injection are possible. A robust neural network has been deployed to optimize the physical parameters controlling the transport characteristics of hybrid nanofluids. Specifically, two hybrid nanoparticle combinations are addressed, namely graphite oxide (GO)-molybdenum disulfide (MoS2) and copper (Cu)-silicon dioxide (SiO2), both with engine oil as the base fluid. The dimensional boundary layer model is transformed via suitable scaling variables from a partial differential system into a dimensionless non-linear coupled ordinary differential system. The transformed boundary value problem is solved numerically with the BVP4C subroutine in the symbolic software MATLAB, which achieves exceptional accuracy. Validation with previous simpler studies is conducted and a good correlation is obtained. The neural network optimization analysis incorporates Bayesian regularization as the training algorithm. The Bejan entropy generation minimization (EGM) analysis shows that with increasing radiation parameter R-d, both entropy generation rate and Bejan number are increased. Furthermore, an elevation in Brinkman number Br leads to an upsurge in entropy generation rate and a downtrend in the Bejan number. The numerical solution of the boundary value problem reveals that with an increment in nanoparticle solid volume fraction phi(2), magnetic parameter M, inverse permeability parameter epsilon, surface injection parameter (s<0), Eckert number Ec and radiation parameter R-d and with a decrement in suction parameter (s>0) and Prandtl number Pr, there is a strong enhancement in temperature magnitude and thermal boundary layer thickness. With greater nanoparticle solid volume fraction phi(2), magnetic parameter M, inverse permeability parameter epsilon, suction parameter s and a reduction in thermal buoyancy parameter lambda, strong flow deceleration is induced, and momentum boundary layer thickness is increased. The skin friction coefficient is substantially boosted with lower values of magnetic parameter M, inverse permeability parameter epsilon, suction parameter s and higher values of thermal buoyancy parameter lambda. There is a significant decrement also computed in Nusselt number with a greater radiation parameter R-d. The simulations provide a good benchmark for future extensions that may consider non-Newtonian behavior.Öğe Analyses of structural and electrical properties of aluminium doped ZnO-NPs by experimental and mathematical approaches(Elsevier, 2022) Mahmood, Arslan; Munir, Tariq; Fakhar-E-Alam, M.; Atif, Muhammad; Shahzad, Kaleem; Alimgeer, K. S.; Gia, Tuan Nguyen; Ahmad, Hijaz; Ahmad, ShafiqPure and aluminium doped ZnO-NPs were played the central role in every field of life due to extraordi-nary physical, chemical and electrical properties. The main objective of the present research was used to enhance the electrical conductivity and reduce the electrical resistivity of aluminium doped zinc oxide-NPs. Synthesis of pure and aluminium doped zinc oxide-NPs (Zn1-xAlxO) at x = 0, 2.5, 5, 7.5 and 10 wt% was carried out by co-precipitation method. The XRD results depicted that hexagonal wurtzite crystal structure and crystallite size in the range of 13-25 nm were calculated by using Debye-Scherrer's equa-tion. Likewise, the non-uniform, irregular and pore like surface morphology of the prepared NPs was evi-dent from SEM micrographs. Various functional groups (CH, CO, OH and ZnO) attached to the surface of aluminium doped zinc oxide-NPs were identified by FTIR analysis. The UV-VIS spectra also depicted a shift towards the blue region of the visible spectrum. In terms of electrical properties with the help of experimental and mathematical analyses of aluminum doped zinc oxide-NPs exhibited higher conductiv-ity (1.34 x 10(-6) to 1.43 x 10(-3) S/cm) and lower resistivity (5.46 x 10(5) to 6.99 x 10(2) Omega-cm). The present results suggest that the aluminum doped zinc oxide-NPs have been improved the structural and electrical properties which make it a good candidate for optoelectronic devices. (c) 2021 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
