Optimizing heat transfer rate with sensitivity analysis on nonlinear radiative hydromagnetic hybrid nanofluid flow considering catalytic effects and slip condition: Hamilton–Crosser and Yamada–Ota modelling

In current investigation the optimization of heat transportation rate in a nonlinear radiative buoyancy‐driven hydromagnetic carbon nanotube (CNT) hybrid nanofluid flow is analysed. The proposed catalytic effects and slip condition is accounted for the real‐world complexities of the system. The Hamilton–Crosser (HC) and Yamada–Ota (YO) models are employed to characterize the behaviour of the nanofluid. The primary objective is to enhance the heat transmission rate, which is crucial for various engineering applications such as thermal management, energy systems and so forth. To achieve this, sensitivity analysis is performed to identify the most influential parameters affecting heat transfer in the system. By understanding the sensitivity of these parameters, the performance of the system can be improvised. The study focuses on the interplay between key factors including radiative heat transfer, buoyancy‐driven flow, magnetic field influence, catalytic effects, and slip condition. The presence of CNTs in the nanofluid adds another dimension to the complexity of the system that explores the effects of varying the concentration and size of CNTs on the heat transfer rate. By utilizing advanced mathematical modelling and numerical simulations, the performance of the system under different scenarios and identify the optimal conditions for maximizing heat transfer rate is evaluated. The findings of this research provide valuable insights into the design and optimization of heat transfer systems involving nanofluids with nonlinear radiative and hydromagnetic effects. The observation shows that, irrespective to single wall and multi wall CNT nanoparticles the fluid velocity attenuates significantly whereas it favours in enhancing the fluid temperature. Further, the comparative analysis reveals that the heat transfer augments in the case of HC model than that of YO model.