Impact of radiation,melting,and chemical reaction on magnetohydrodynamics nanoparticle aggregation flow across parallel plates

The heat transfer between two corresponding plates,disks,and concentric pipes has many applications,including water cleansing and lubrication.Furthermore,TiO_(2)-water-based nanofluids are used widely because it is useful for operating and controlling the temperature,especially in photovoltaic technology and solar panels.Motivated by these applications,the current study is based on the nanoparticle aggregation effect on magnetohydrodynamics(MHD)flow via rotating parallel plates with the chemical reaction.To achieve maximum heat transportation,the Bruggeman model is used to adapt the Maxwell model.Also,melting and thermal radiation effects are considered in the modeling to discuss heat transport.The Runge-Kutta-Fehlberg 4th−5th order method is used to attain numerical solutions.The main focus of this study is to see the thermodynamic behavior considering several aspects of nanoparticle aggregation.The heat transfer rate between the parallel plates is enhanced by improving the thermophoresis,radiation,and Brownian motion parameters.The rise in Schmidt number and chemical reaction rate parameter decreases the concentration distribution.This study will be helpful in enhancing the thermal efficiency of photovoltaic technology in solar plates,water purifying,thermal management of electronic devices,designing effective cooling systems,and other sustainable technologies.

Radiative heat transfer analysis of a concave porous fin under the local thermal non-equilibrium condition:application of the clique polynomial method and physics-informed neural networks

The heat transfer through a concave permeable fin is analyzed by the local thermal non-equilibrium(LTNE)model.The governing dimensional temperature equations for the solid and fluid phases of the porous extended surface are modeled,and then are nondimensionalized by suitable dimensionless terms.Further,the obtained nondimensional equations are solved by the clique polynomial method(CPM).The effects of several dimensionless parameters on the fin's thermal profiles are shown by graphical illustrations.Additionally,the current study implements deep neural structures to solve physics-governed coupled equations,and the best-suited hyperparameters are attained by comparison with various network combinations.The results of the CPM and physicsinformed neural network(PINN)exhibit good agreement,signifying that both methods effectively solve the thermal modeling problem.

Bio-Marangoni convection flow of Casson nanoliquid through a porous medium in the presence of chemically reactive activation energy

Bioconvection research is primarily focused on the augmentation of energy and mass species,which has implications in the processes intensification,mechanical,civil,electronics,and chemical engineering branches.Advanced bioconvection technology sectors include cooling systems for electronic devices,building insulation,and geothermal nuclear waste disposal.Hence,the present investigation is mainly discoursing the impact of Marangoni convention Casson nanoliquid flow under gyrotactic microorganisms over the porous sheet.The partial differential equations(PDEs)are re-structured into ordinary differential equations(ODEs)via suitable similar variables.These ODEs are numerically solved with the help of the spectral relaxation method(SRM).The numerical outcomes are illustrated graphically for various parameters over velocity,temperature,concentration,and bioconvection profiles.Three-dimensional(3 D)views of important engineering parameters are illustrated for various parameters.The velocity of the Casson nanoliquid increases with increasing the Marangoni parameter but decreases against higher porosity parameter.The surface drag force enhances for enhancement in the Marangoni number.The rate of mass transmission is higher for reaction rate constraint but diminishes for activation energy parameter.The higher radiative values augment the rate of heat transmission.

Bioconvective nanofluid flow over an exponential stretched sheet with thermophoretic particle deposition

The current work is being done to investigate the flow of nanofluids across a porous exponential stretching surface in the presence of a heat source/sink,thermophoretic particle deposition,and bioconvection.The collection of PDEs(partial differential equations)that represent the fluid moment is converted to a system of ODEs(ordinary differential equations)with the use of suitable similarity variables,and these equations are then numerically solved using Runge Kutta Fehlberg and the shooting approach.For different physical limitations,the numerical results are visually represented.The results show that increasing the porosity characteristics reduces velocity.The mass transfer decreases as the thermophoretic limitation increases.Increases in the porosity parameter reduce skin friction,increases in the solid volume fraction improve the rate of thermal distribution,and increases in the thermophoretic parameter increase the rate of mass transfer.