Performance of triangular fin device coated with (SiC–Co3O4)/diathermic nanolubricant inspired by convective and radiation conduction using AI driven approach

Abstract

Enhanced heat transport in triangular fins have promising applications in heat exchangers, electronics cooling, automobile radiators and power plants etc. Use of nanolubricants is an innovative way to enhance the performance of triangular fin. Thus, this work aims to analyze the triangular fin’s performance coated with hybrid nanolubricant (SiC–Co3O4)/diathermic oil and investigate that how the active parameters radiation, convective-conduction, porosity and heating source affect the performance. The formulation is accomplished using the energy equations together with enhanced characteristics of SiC–Co3O4 and diathermic oil. As a result, the second order model obtained. The artificial intelligence (AI) based scheme levenberg marquardt back-propagation (LMBP) method implemented. Further, the results for the model furnished using feasible ranges of the parameters. Authenticity of the scheme is verified through histogram error, functions fitting, regression analysis and validation checks. It is examined that the device can be maintained at low temperature by augmenting the conduction parameter from 1.0 to 4.0. Optimum heat transfer is acquired when the heating source Q and Peclet number Pe increased. Presence of pores at the triangular fin’s surface would be advantageous to cool the device. In conclusion, the use of hybrid nanolubricant subject to radiations, heating source, and porosity effects together with AI scheme provided beneficial results regarding the transport of heat using triangular fin.