Machine learning based technique for heat transfer enhancement of cylindrical battery modules utilizing hybrid nanofluids

Due to their exceptional heat transmission capabilities and variety of uses, Hybrid Nano-fluids have attracted to research community and scientists of modern era. The current work revealed the numerical approach to application of Hybrid Nano-fluids to competency modules of cylindrical battery and latest cooling systems. Principally Hybrid Nano-fluids are made of basic coolant fluid supplemented by using nano-particles of several materials for enhancing thermal conductivity of battery as well as cooling systems including properties of heat transmission. Through merging of two distinct sorts of nanoparticles, aluminum oxide and copper, which are disseminated throughout a water-based liquid, this study produces a Hybrid Nano-fluid of . The energy equations under consideration are outcomes of viscous dissipation, heat production and Joule heating, convection boundary conditions are used in momentum equation and magnetic field variables are also taken in account. By use of suitable similarity variables, a structure of Nonlinear PDEs transmuted into the resultant ODEs. By exploiting extraordinary Levenberg-Marquardt Backpropagation Algorithm (LMBP-Algorithm) along with Artificial Intelligence’s Neural Networks equations are numerically resolved. The competence of the foreseen NNs of AI with LMBP-Algorithm under several conditions is assessed through several performance metrics, including Mean square error, Histograms for error and Regression analysis. A detailed inspection is also applied to decide impacts of key constraints on velocity as well as temperature profiles. Increasing behavior of velocity profile for Local Grashof number, Heat source/sink factor and Brinkman number and a decreasing behavior for Magnetic field parameter, whereas an increasing behavior of temperature profile for all these four parameters is observed. They are considered most likely remarkable adoptions for effectively cooling battery packs in a variety of uses, comprising renewable energy storage, latest electronics along with modern electric vehicles.