Heat transfer analysis for 3d ternary hybrid nanofluid flow with MHD and non-fourier flux impact over a linearly stretching surface: Response surface optimization

Combining different-shaped nanoparticles enhances the mechanism of heat transfer. Nanoparticles can be spherical, cubic, rod, tube, helical, triangular, hexagonal, oval, or prismatic, and they are frequently combined with the base liquid. Biology and industry are two academic fields that are significantly impacted by nanotechnology. The use of hybrid nanoparticles to enhance heat transport in a working fluid has piqued the curiosity of numerous experts. Ternary hybrid nanofluids are frequently used in heat transfer applications because of have higher thermal conductivity than ordinary fluid, especially as heat exchangers. In contemporary times, the amalgamation of liquids has assumed paramount significance in diverse domains including healthcare, production, naval academies, aerosol particle processing, instrument design, and so on. The non-Fourier flux and magnetic impact in three-dimensional flow characteristics using the linear Roseland approximation. Furthermore, ternary solid nanoparticles in a variety of densities and forms were included. The primary goal of the research is in a three-dimensional rectangular closed domain stretching surface with Magnetic effect, linear thermal radiation and non-Fourier flux to analyze the heat and velocity transfer rate with different cases like Case-1: AA7072+SWCNT+MWCNT with PEG−water a base fluid, Case-2 Fe3O4+Diamond+TiO2 considered along as PEG−water a base fluid ternary hybrid nanofluid. ology: By transforming the three-dimensional model's governing PDEs into nonlinear ODEs. The ODE45 solver in MATLAB was utilized to construct the graphical representations of the numerical solution findings. It is investigated how well different flow and temperature parameters function when changed. The analysis is also done on simulation findings for friction and heat transmission for different values. And transfer rate are higher in case-2 Fe3O4+Diamond+TiO2 than in case-1 AA7072+SWCNT+MWCNT with base fluid PEG−water. A collection of statistical and mathematical techniques for problem modelling and analysis is known as response surface methodology, or RSM. To guarantee that the response gets close to the desired maximum or minimum value, factorial variable settings are optimised using processes included in RSM. Residual R2 in Case-1 92.65%, Case-2 91.90% will represent the accuracy of the model.