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This research work employs a machine learning approach with Python to analyze the complex relation of thermophoretic deposition and radiation effect on the mass and heat transfer of ternary hybrid nanofluid flow over the wedge. The colloidal comprising ${\mathrm{\text{CoFe}}}_2{\mathrm{\text{O}}}_4$, ${\mathrm{\text{Fe}}}_3{\mathrm{\text{O}}}_4$ and ZnO with Engine Oil and Water in equal proportion as a base fluid, is considered here, due to the potential enhancer of thermal performance in numerous applications. The governing PDEs for flow rate, heat and mass transfer are transformed into a system of ODEs and numerical dataset generated by Python for stochastic evaluation through Matlab Neural Network assisted by Levenberg Marquardt Machine Learning Algorithm to extract intricate patterns and comparison between numerical and stochastic simulations. The impact of influencing parameters such as volume fraction, wedge angles, Eckert ratio and Radiation coefficients are analyzed. The outcomes of this research shed light on the synergetic effects of thermophoretic deposition and radiation on the thermal mass exchange of tri-nanohybrid fluid across the sharp edge of the device. This machine learning artificial intelligence (AI) tool is cost-effective and far better than deterministic numerical outputs as compared with analytical evaluations. A detailed graphical representation is embedded in this paper for comparisons and error analysis. Influencing parameters are analyzed for temperature, velocity and concentration profiles. Moreover, engineering parameters are also evaluated and plotted against the infecting agents. Graphical analysis of Nusselt, Sherwood and Skin friction coefficients added for broad spectrum comparison and comprehensive analysis for the significant implementation of the present discussion at the industrial level, for the benefit of production units, heavy industry and energy management systems in numerous fields.

Molecular dynamics simulations (MDSs) are carried on to examine the effects of liquid–nanoparticle (NP) interaction strength, size and number of nanoparticles on the aggregation process in liquid-based nanofluid flowing inside nanochannel. The results show that the increase in liquid–NP interaction strength leads to the reduction of aggregation rate. In addition, the increase in the size and number of NPs leads to more aggregation rate. Predicted results for aggregation trend are in good agreement with experimental data. Likewise, variations of velocity profile and density distribution of liquid particles inside nanochannel are explored.

In the present work, forced convection heat transfer was investigated numerically for the fully developed fluid flow of incompressible viscous laminar flow under the constant wall heat flux in sudden expansion channels. Various fluids were used with different concentration of nanoparticle such as Al₂O₃, TiO₂, ZnO, CuO, SiO₂. These nanoparticles were dispersed with the range of 0.5–2% volume concentrations in pure water to form stable suspensions of nanofluids. The flow assumed to be uniform in the channel inlet and numerical computations were performed for the fully developed laminar flow conditions. Ansys Fluent 16.1 code, based on finite volume approach was used to calculate the governing continuity, momentum and energy equations. Effect of the Re numbers (100$\le$Re$\le$500), nanoparticle volume concentration (0.5%$\le \phi \le$2.0%) and nanofluid type on the flow and heat transfer characteristics such as convective heat transfer coefficient, Nu number, friction factor and pressure drop has been investigated. Al₂O₃/water nanofluid was found better when compared the other references working fluids by means of heat transfer enhancement.

Aerogel is studied numerically using a one-dimensional two-phase flow equations system. A hyperbolic and conservative two-phase flow model is applied to a mixture of porous media containing nanofluids. The application of non-equilibrium mixture behavior between phases is adopted and promoted in this current investigation. By establishing mixture conservation balance laws, finite volume techniques using Godunov methods of centered type are extended to aerogel simulations. Numerical results are compared with other methods providing a remarkable agreement. The computed results demonstrate the key capabilities of this existing mixture model in the resolution of discontinuities in aerogel problems and more reliable than applying a sophisticated single-phase flows with complex property models.