Biological processes such as nutrient transport in tissues,and blood transport in mammalian systems are among the phenomena where a temperature gradient induces mass transfer of a multicomponent fluids.This occurs bec...Biological processes such as nutrient transport in tissues,and blood transport in mammalian systems are among the phenomena where a temperature gradient induces mass transfer of a multicomponent fluids.This occurs because different species in the fluid respond differently to temperature variations,leading to a separation effect.Given these notable dynamics,efficient management of solute-thermal flux phenomenon is essential across various systems and biomedical designs to achieve the necessary improvements for optimizing engineering system performance.As such,investigation herein present the dynamics of cross temperature and concentration gradient and predict mathematically the flux interactions in Ammonia-Prandtl Eyring nanofluid flow through an inclined vertical surface.A mathematical model of a non-Newtonian Prandtl Eyring fluid(PEF)is developed to represent physical systems exhibiting different diffusivities,subject to convective boundary conditions and solute-thermal flux interactions.The Ammonia-PE(NH 3-PE)nanofluid is proposed as a multi-component composition in water with nanoparticle aiming to significantly enhance the thermal properties in water through the Buongiorno’s nanofluid model.Additionally,radiative heat transfer and the Dufour effect are considered to enhance mixed convection dynamics.Group symmetry analysis is performed to reduce the governing partial differential equations into a system of ordinary differential equations(ODEs).A robust and efficient numerical scheme,spectral quasi-linearization method(SQLM)is utilized to investigate the dynamics of the ODE systems while the computational framework was implemented.Furthermore,statistical analysis via response surface methodology(RSM)is deployed to predict flow formation and optimise system behaviour.Results predict the dominance of convection process and enhanced momentum drag force,leading to a decrease in fluid flow and energy transfer.A higher PEF parameter enhances fluid internal molecular friction,identifying energy due to viscous heating dominant.The mixed convection and gravitational interplay assists flow rate more strongly as inclination increases.The prediction model identified that,minimum heat transfer rate can only be achieved with dominant convective heating,minimal PEF contribution and higher thermal effect.展开更多
文摘Biological processes such as nutrient transport in tissues,and blood transport in mammalian systems are among the phenomena where a temperature gradient induces mass transfer of a multicomponent fluids.This occurs because different species in the fluid respond differently to temperature variations,leading to a separation effect.Given these notable dynamics,efficient management of solute-thermal flux phenomenon is essential across various systems and biomedical designs to achieve the necessary improvements for optimizing engineering system performance.As such,investigation herein present the dynamics of cross temperature and concentration gradient and predict mathematically the flux interactions in Ammonia-Prandtl Eyring nanofluid flow through an inclined vertical surface.A mathematical model of a non-Newtonian Prandtl Eyring fluid(PEF)is developed to represent physical systems exhibiting different diffusivities,subject to convective boundary conditions and solute-thermal flux interactions.The Ammonia-PE(NH 3-PE)nanofluid is proposed as a multi-component composition in water with nanoparticle aiming to significantly enhance the thermal properties in water through the Buongiorno’s nanofluid model.Additionally,radiative heat transfer and the Dufour effect are considered to enhance mixed convection dynamics.Group symmetry analysis is performed to reduce the governing partial differential equations into a system of ordinary differential equations(ODEs).A robust and efficient numerical scheme,spectral quasi-linearization method(SQLM)is utilized to investigate the dynamics of the ODE systems while the computational framework was implemented.Furthermore,statistical analysis via response surface methodology(RSM)is deployed to predict flow formation and optimise system behaviour.Results predict the dominance of convection process and enhanced momentum drag force,leading to a decrease in fluid flow and energy transfer.A higher PEF parameter enhances fluid internal molecular friction,identifying energy due to viscous heating dominant.The mixed convection and gravitational interplay assists flow rate more strongly as inclination increases.The prediction model identified that,minimum heat transfer rate can only be achieved with dominant convective heating,minimal PEF contribution and higher thermal effect.
