Stacking regression model approach to mixed convection flow of ternary- nanofluid over slanted surface with magnetic field, waste discharge concentration, and joule heating effects

Abstract

The current work is carried out to investigate the mixed convection flow behavior of ternary-based nanofluid over an inclined surface in the presence of a magnetic field, waste discharge concentration, and joule heating effects. The governing equations with proper assumptions were converted into ordinary differential equations (ODEs) form by implementing suitable similarity constraints and solved with Runge Kutta Fehlberg 4th 5th order and shooting scheme. The stacking regression model approach is implemented along with the Runge Kutta Fehlberg 4th 5th order technique. The obtained outcomes are presented with graphs, and model correctness is assessed using the combination of Gaussian Process Regression (GPR), Extra Tree Regression (ETR), and Random Forest (RF). The consistency and stability of the model are demonstrated by the closely linked testing and training data. The study outcomes show that the rise in the magnetic constraint will improve the velocity profile while improved values of local pollutant external source and external pollutant source variation parameters will enhance the concentration profile. Enhancement in Eckart number and solid volume fraction values will improve the rate of thermal distribution. Ternary nanofluid shows significant improvement than nanofluid. The surface drag force is increased about 8 %-9 % in assisting flow case and 8 %-17 % for opposing flow case for different values of magnetic parameter, the rate of thermal distribution improved from 75.54 % to 11.55 % in assisting flow case and 16.87 % to 25.70 % in opposing flow case for different values of Eckert number. The study's results might contribute to the advancement of more effective heat exchangers and cooling systems for electronics and engines. Exploration and extraction of oil, as well as the creation of efficient water purification systems.

Keywords

• Ternary nanofluid
• Mixed convection
• Joule heating
• Magnetic field
• Pollutant concentration
• Staking regression model