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 us...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.展开更多
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 surfa...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.展开更多
基金Large research project(RGP2/159/45)supported by the Deanship of Research and Graduate Studies at King Khalid University,Saudi Arabia。
文摘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.
基金funding this work through Small Research Project under grant number RGP.1/141/45。
文摘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.
