This study employs numerical and statistical approaches to investigate the entropy optimization of steady Casson nanofluidflow over three different geometries subject to boundary conditions induced by convectiveflow.M...This study employs numerical and statistical approaches to investigate the entropy optimization of steady Casson nanofluidflow over three different geometries subject to boundary conditions induced by convectiveflow.Multiple linear regression is employed to statistically examine.The present model incorporates several novel elements,such as Arrhenius activation energy,Brownian motion,the Cattaneo-Christov dualflux,thermophoresis,thermal radiation,and so on.Moreover,a comparison is presented between Newtonian and non-Newtonianfluids.By applying the proper similarity transformations,ordinary differential equations(ODEs)are ob-tained by converting foundational partial differential equations(PDEs).The Runge-Kutta fourth-order method is utilised to solve the obtained ODEs along with the shooting technique.The out-comes are visually depicted via tables and graphs.The velocity drops with increasing Grashof number,and the magneticfield becomes progressively more forceful as the suction parameter in-creases.The temperature gets reduced with the increase of the suction parameter,solute Grashof number increases with the magneticfield,thermophoresis,and radiation parameters.The entropy is observed to rise with the increase of the effective parameters(magneticfield,Brinkmann num-ber and radiation).The MAD(mean absolute deviation),MSE(mean squared error),and RMSE(root mean square error)values are approaching zero,indicating that the derived outcomes are highly accurate.A lower MAPE(mean absolute percentage error)suggests that the model has a higher level of precision.Therefore,the outcomes of the present model are more precise and reliable.This study has various potential applications such as power plant heat exchangers,material processing industries,and solar thermal energy systems.展开更多
文摘This study employs numerical and statistical approaches to investigate the entropy optimization of steady Casson nanofluidflow over three different geometries subject to boundary conditions induced by convectiveflow.Multiple linear regression is employed to statistically examine.The present model incorporates several novel elements,such as Arrhenius activation energy,Brownian motion,the Cattaneo-Christov dualflux,thermophoresis,thermal radiation,and so on.Moreover,a comparison is presented between Newtonian and non-Newtonianfluids.By applying the proper similarity transformations,ordinary differential equations(ODEs)are ob-tained by converting foundational partial differential equations(PDEs).The Runge-Kutta fourth-order method is utilised to solve the obtained ODEs along with the shooting technique.The out-comes are visually depicted via tables and graphs.The velocity drops with increasing Grashof number,and the magneticfield becomes progressively more forceful as the suction parameter in-creases.The temperature gets reduced with the increase of the suction parameter,solute Grashof number increases with the magneticfield,thermophoresis,and radiation parameters.The entropy is observed to rise with the increase of the effective parameters(magneticfield,Brinkmann num-ber and radiation).The MAD(mean absolute deviation),MSE(mean squared error),and RMSE(root mean square error)values are approaching zero,indicating that the derived outcomes are highly accurate.A lower MAPE(mean absolute percentage error)suggests that the model has a higher level of precision.Therefore,the outcomes of the present model are more precise and reliable.This study has various potential applications such as power plant heat exchangers,material processing industries,and solar thermal energy systems.
