BITS Faculty Publications
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Item Electroosmotic microchannel flow of blood conveying copper and cupric nanoparticles: Ciliary motion experiencing entropy generation using backpropagated networks(Wiley, 2024-03) Sharma, Bhupendra KumarA novel mathematical model for a hybrid (Cu–CuO/blood) Jeffrey nanofluid passing a vertical symmetric microchannel along with an electroosmosis pump is presented. The focuses on the advancement of mathematical modeling techniques, its comprehensive analysis of microfluidic system dynamics, and its potential to inform the optimal design of devices using nanofluids with broad applications in various fields. Arrhenius's law is used to analyze endothermic–exothermic reactions and activation energy. The governing partial differential equations of the fixed frame are transformed into ordinary differential equations of the wave frame using self-similarity transformations. Low Reynolds number and long-wavelength approximations helped to find solutions of the equations by applying a suitable BVP solver in MATLAB. The fluid's velocity, temperature, concentration, and electroosmosis properties are studied graphically. Two-dimensional contour plots of fluid velocity and three-dimensional surface plots of fluid properties are discussed. Physically significant quantities of mass transfer rate, skin friction coefficient, entropy generation, and heat transfer rate are studied using contour plots. Artificial neural network simulation using Bayesian regularization backpropagation algorithms is analyzed for training state, error histogram, fit, performance, and regression plots. Conclusively, the comprehensive analysis of the fluid dynamics, entropy generation, mass and heat transfer, and in the microchannel, coupled with the successful implementation of artificial neural network simulation, contributes to an improved understanding of the system's behavior. Entropy generation was raised for enhanced Brownian motion number and reduced values of thermophoresis, activation energy, and endothermic–exothermic reaction parameters. This study's results can be used to improve the efficiency and effectiveness of microfluidic devices used in fields as diverse as electrical cooling and medicine delivery.Item Computational analysis of entropy generation optimization for Cu–Al2O3 water-based chemically reactive magnetized radiative hybrid nanofluid flow(AIP, 2024-07) Sharma, Bhupendra KumarThis study aims to analyze the mass transfer and entropy generation in the flow system of chemically reactive, thermal radiative hybrid nanofluids (Al2O3/Cu with H2O as base fluid) flow across flat stretching porous surfaces in the presence of viscous dissipation and transverse magnetic field. The governing partial differential equations are converted into a set of ordinary differential equations by applying a group of self-similarity transformations. The resulting differential equations are solved using the Bvp4c technique in MATLAB. The impact of several physical parameters has been examined the velocity, heat, and mass transfer components of the fluid. To optimize the complete heat transfer process, the consequences of all physical parameters are discussed on entropy generation and Bejan number and presented graphically. It is observed that velocity increases with the increase in magnetic parameter M because pressure force dominates over Lorentz force, temperature increases with the rise of Ec, concertation reduces with the enhancement of chemical reaction parameter delta, and the Bejan number decreases with the increase in Br; however, reverse phenomena are observed with increasing the value of the magnetic number and entropy increases with the rise of magnetic parameter M. Due to the increase in magnetic parameter M, drag force is accelerated, which leads to increase in entropy, With an increment in Pr and Ec, the heat exchange rate declines although the skin friction coefficient and mass transfer remain constant. There are several significant applications of the study of thermal analysis of hybrid nanofluid flows in numerous mechanical processes, such as extrusion or metal manufacturing processes, heat transportation in biological tissues, cooling of electric devices, high-size refrigeration, hydroelectric dams, and fuel systems.Item Entropy Analysis for MHD Flow Subject to Temperature-Dependent Viscosity and Thermal Conductivity(Springer, 2022-10) Sharma, Bhupendra KumarThis research aimed to figure out how to optimise the entropy of MHD flow past a continuously stretching surface. The effect of temperature-dependent variables viscosity and electric conductivity has been taken into account. The fluid region is subjected to a uniform magnetic field. By using similarity analysis, the governing coupled partial differential equations (PDEs) that describe the model are turned into non-linear ordinary differential equations and then computed by employing “BVP4C” in MATLAB software. The effect of various pertinent parameters like Magnetic field parameter M, radiation parameter R, Grashof number Gr, Brinkman number Br, Reynold number Re, and a variation of variables viscosity ϵ1 and electric conductivity ϵ2 is analysed and presented graphically on velocity, temperature, entropy, and concentration profile. The comparison is based on previously published studies, and there is a considerable deal of agreement.