Fluid dynamic research on rectangular and trapezoidal fins is aimed at increasing heat transfer by means of large surfaces. The trapezoidal cavity form is compared with its thermal and flow performance, and it is revealed that trapezoidal fins tend to be more efficient, particularly when material optimization is critical. Motivated by the increasing need for sustainable energy management, this work analyses the thermal performance of inclined trapezoidal and rectangular porous fins utilising a unique hybrid nanofluid. The effectiveness of nanoparticles in a working fluid is primarily determined by their thermophysical properties; hence, optimising these properties can significantly improve overall performance. This study considers the dispersion of Graphene Oxide $\left(GO\right)$ and Molybdenum Disulfide in the base fluid, engine oil. Temperature profiles are analysed by altering the radiative, porosity, wet porous, and angle of inclination parameters. Surface and contour plots are constructed by using the Lobatto IIIa Collocation Method with BVP5C solver in MATLAB and Gradient Descent Optimisation to predict the combined heat transfer rate. According to the study, fluid temperature consistently decreases when the angle of inclination, wet porous parameter, porosity parameter, and radiative parameter increase, suggesting significantly improved heat dissipation. The trapezoidal fin consistently exhibits a superior heat transfer mechanism than a rectangular fin. It is found that the trapezoidal fin transmits heat at a rate that is 0.05% higher than that of the rectangular fin. Validation of the present study is done through the comparison of previous studies. This research provides useful design insights for sophisticated engineering uses, including electrical cooling devices, heat exchangers, radiators, and solar heaters.

This study examines the flow of an incompressible flow over a linear stretching surface with the inclusion of momentum and thermal slip conditions. A scaling set of alterations is applied to the governing system for both with and without magnetic field situations. The physical system being leftover invariant caused by some associations surrounded by the transformations. Later we find the absolute invariants 3^rd -order ODEs for the linear momentum equation and two 2^nd order ODEs consistent with the energy and concentration are obtained. The equations that coincide with the boundary circumstances are elucidated mathematically. The physical pertinent parameters as shown in graphs and the friction factor, Nusselt number and Salts 1 and 2 Sherwood numbers are shown in surface plots. We observed that the momentum slip parameter decelerates the skin friction coefficient in the presence of a magnetic field and enhances in the absence of the magnetic field parameter. The thermal slip parameter enhances the Nusselt number in both the presence and absence of magnetic field parameter. Finally, the thermal and concentration buoyancy ratio parameters are shown to upsurge the friction factor, Nusselt and Salts 1 and 2 Sherwood numbers in both cases of $M=0$ and $M=1$.

In this work, the adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) were used to anticipate the behavior of heat transfer in ternary hybrid nanofluid flow through thin films. For intricate heat transfer processes in nanofluid applications, the combined ANFIS-PSO model improved forecast accuracy. The simulated PDEs were converted into ODEs by varying similarity factors. A ternary hybrid nanofluid across the surface, radiation, heat source/sink, and non-uniform magnetic field were used to theoretically examine the unique properties of unstable thin film flow; nanoparticles, namely $MWCNT,SWCNT$, and $Ti{O}_2$, were used in both the Casson and non-Casson scenarios, using the base fluid, blood. The ANFIS-PSO models were trained using the numerical results from MATLAB's built-in BVP4C function to control the complexity and predict the results. Plotting and analysis were done to see how various flow parameters affect temperature, velocity, and heat transfer. A ternary hybrid nanofluid without a Casson scenario had a higher Nusselt number, per the study's conclusions, than a Casson ternary nanofluid with blood as the base fluid with nanoparticles $SWCNT+Ti{O}_2+MWCNT.$ It was discovered that the truth values are accurately predicted by ANFIS-PSO models, and in most of the runs in Table 3, in Case-2, the rate of heat transmission is 1% higher than in Case-1.