Applications of Nimonic 80A/HFE-7100-based nanofluid in industrial systems: an examination of Cattaneo-Christov flux and LTNE effects using artificial neural network

Abstract

The proposed research investigates the effects of local thermal non-equilibrium conditions on an axisymmetric nanofluid flow via an infinite disk with a surface tension gradient based on Nimonic 80A/HFE-7100. The Cattaneo-Christov flow model examines the properties of heat transfer. This novel heat flux model is more comprehensive than the original Fourier's law as it explains thermal relaxation time. It is especially useful in the design of next-generation gas turbine blades and aerospace engine components, where the Nimonic 80A super alloy can resist extreme temperatures and the model accurately forecasts non-Fourier heat transport and interphase thermal lag. Furthermore, it optimizes high-flux cooling systems for microelectronics and tiny heat exchangers, which rely heavily on the HFE-7100 dielectric fluid and nano-enhancements. The artificial neural network component enables rapid, intelligent design, and real-time performance prediction of these systems, resulting in increased efficiency, safety, and durability in the energy, propulsion, and industrial sectors. The PDE system is transformed into a nonlinear ODE system by using the proper variables. The homotopy analysis method is utilized to solve this problem. The concentration and thermal profiles decrease as the thermal and concentration relaxation parameters increase.