Investigation of fin model using RNN intelligent computing associated to physical parameters and hybrid nanomaterials

The efficient thermal transport through trapezoidal fin surface remains a significant multi engineering problem because traditional fins configuration offers unsatisfactory heat transport subject to high thermal loads which limits the colling system's thermal performance. Although, the nanoparticles have potential role in the heat mechanism across trapezoidal fin but the combined contribution of hybrid nanofluid properties, magnetic field, wetting surface and temperature dependent thermal conductivity has not been adequately presented using AI based computational paradigm. Therefore, the present research aims to formulate a nonlinear energy model for heat transport through trapezoidal fin and to examine the model parameters influence on its thermal behaviour. The formulated problem handled by implementing the RNN (Recurrent neural network) coupled with bvp4c and the numerical experiment executed against different parameters to explore their role in the heat transfer. The achieved results determine that higher thermal conductivity parameter ([Formula: see text]) significantly improves the heat transfer while emissivity ([Formula: see text]) suppresses the heat mechanism under the conditions [Formula: see text] and [Formula: see text]. The conductive/convective effects ([Formula: see text]) and wetted surface help to regulate the temperature and highlighted lower heat transfer. The temperature index parameter [Formula: see text] increases thermal response of the fin. The convergence and accuracy of the RNN predictions are measured through error histogram, regression and MSE (mean squared error) which demonstrate better agreement between the predicted and numerical data. Further, the benchmark solution over the domain from [Formula: see text] to [Formula: see text] is provided for future replication of the results. These theoretical findings provided computational basis for better understanding and heat controlling parametric ranges with potential applications in solar energy systems, heat and cooling process of mining environment. Thermal transport across the trapezoidal shaped fin is relevant to the fins based heat exchangers using for thermal control and heat dissipation purposes in mining technology. The heat transfer through trapezoidal fin using nanofluids can enhance thermal dissipation from including motors, mining equipment, compressors, and drilling machinery operating under high thermal loads.Clinical trial number not applicable.