Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

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AbstractIn the study, we inspect the impact of cross diffusion and aligned magnetic field on Casson fluid flow along a stretched surface of variable thickness. The differential equations explaining the flow situation have been transitioned with the succor of suited transfigurations. The solution of the problem is achieved by using bvp5c Matlab package. From the solution, it is perceived that the flow, temperature and concentration fields are affected by the sundry physical quantities. Results explored for the flow over a uniform and a non-uniform thickness surfaces. The influence of emerging parameters on the flow, energy and mass transport are discussed with graphical and tabular results. Results show that the thermal, flow and species boundary layers are uneven for the flow over a uniform and non-uniform thickness stretched surfaces.

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Electronics

School of Electronics Engineering

Chennai Campus

VIT Unitversity

Fulltext

Nonlinear Engineering

Effect of aligned magnetic field on Casson fluid flow over a stretched surface of non-uniform thickness

Department of Mathematics

School of Advanced Sciences

Vellore Campus

IOP Conference Series: Materials Science and Engineering

Aligned magnetic field effect on unsteady liquid film flow of Casson fluid over a stretching surface

Zn1−xNixO with 0 ≤ x ≤ 0.2 nanoparticles (NPs) were prepared by co-precipitation with subsequent annealing at 500 °C for 2 h. For a better control of particle's growth, a non-ionic surfactant namely Tween-80 was used during the preparation process. XRD Rietveld analysis confirmed the formation of the hexagonal wurtzite-type structure along with a secondary phase namely NiO. SEM observations revealed remarkable change in morphology, including rods, sheets and spheres. The purity of the as-prepared NPs as checked by EDAX analysis indicated that the chemical composition of Zn, Ni and O was in good agreement with the starting stoichiometries. The defect states were revealed from the UV and visible emissions of the photoluminescence spectra. The DRS analysis showed blue shift as Ni2+increases from 5 to 20%. The existence of a peak at 432 cm−1in FTIR spectra confirmed the formation of ZnO phase. The Magnetization-Field (M-H) curves revealed the existence of ferromagnetism in Ni-doped ZnO NPs, which was attributed to bound magnetic polaron (BMP) mechanism. © 2016 Elsevier B.V.

Physics

Journal of Alloys and Compounds

Optical and magnetic properties of Ni-doped ZnO nanoparticles

Nanostructured Co1-xZnxFe2O4 (0≤x≤0.5) catalyst synthesized by the microwave combustion method was employed for the photocatalytic degradation of rhodamine B (RhB) under visible light. Doping of Zn2+ ions in the cobalt ferrite matrices were confirmed by the diffraction peak-shift towards lower angles. The Williamson-Hall method was used to calculate the crystallite size considering the strain components. The conduction band (CB) and valence band (VB) edges of all the samples were calculated using optical studies. Photoluminescence analysis performed at an excitation wavelength of 330 nm disclosed the rate of recombination of electron-hole pairs and the defects present. Photocatalytic degradation of RhB with pure cobalt ferrite system was performed at pH 2.0 by varying the time, initial concentration and addition of hydrogen peroxide to behave like a Fenton like process. However the effective photodegradation of all zinc doped cobalt ferrite were done at optimal RhB concentration of 6 mg/l at identical operational conditions. Among all the samples Co0.6Zn0.4Fe2O4 exhibited an enhanced degradation efficiency of 99.9% at visible light exposure time of 210 min. The degradation pathway followed first order rate rather than the second order rate kinetics. Based on the values of CB and VB edges in the Co0.6Zn0.4Fe2O4 system, possible routes for the degradation of RhB are suggested. © 2016 Elsevier Ltd and Techna Group S.r.l.

Ceramics International

Photocatalytic degradation of rhodamine B under visible light using nanostructured zinc doped cobalt ferrite: Kinetics and mechanism

A comparative study has been made on the solutions obtained using combined economic emission dispatch (CEED) problem considering line flow constraints using different intelligent techniques for the regulated power system to ensure a practical, economical and secure generation schedule. The objective of the paper is to minimize the total production cost of the power generation. Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuel cost of generating units. Combined economic emission dispatch (CEED) is obtained by considering both the economic and emission objectives. This bi-objective CEED problem is converted into single objective function using price penalty factor approach. In this paper, intelligent techniques such as genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), differential evolution (DE) are applied to obtain CEED solutions for the IEEE 30-bus system and 15-unit system. This proposed algorithm introduces an efficient CEED approach that obtains the minimum operating cost satisfying unit, emission and network constraints. The proposed algorithm has been tested on two sample systems viz the IEEE 30-bus system and a 15-unit system. The results obtained by the various artificial intelligent techniques are compared with respect to the solution time, total production cost and convergence criteria. The solutions obtained are quite encouraging and useful in the economic emission environment. The algorithm and simulation are carried out using Matlab software. © 2009 Elsevier Ltd. All rights reserved.

Department of Electrical Engineering

School of Electrical Engineering

International Journal of Electrical Power & Energy Systems

Comparison of AI techniques to solve combined economic emission dispatch problem with line flow constraints