Oscillatory performance of magnetite-water nanofluid and radiative heat transfer over heat-exchanger plate with Levenberg-Marquardt algorithm

Oscillatory magnetite-water nanofluid flow over heat-exchanger plate signifies the energy efficiency, cooling rate and fault prediction in power plants, chemical industries, civil engineering, and marine turbines. Fluctuating and steady flow sequence of heat transfer and nanoparticle concentration rate with exothermic catalytic reaction and Arrhenius activation energy effects exhibits important novelty of this analysis. The objective of this analysis presents performance of temperature amplitude at lower and higher volume concentrations using artificial neural network based Levenberg-Marquardt algorithm. The significance of this work illustrates the thermal performance, mass flow control, corrosion protection and temperature management of high-theta plate heat exchanger. The partial differential equations are reduced into balanced form using dimensionless variables. The governing steady, real and imaginary models are solved to analyze amplitude and oscillating flow physical properties using stokes and complex variables. The numerical and graphical outcomes are illustrated through implicit finite-difference and Gaussian elimination methods with primitive variable formulation. The lowest percentage error (0.00054%) between present and existing work indicates the stability and convergence of heat transfer results. The increasing amplitude in temperature and concentration rates is deduced at lower values of magnetic number M_f, Richardson number R_iT and Schmidt number Sc. The steady and oscillating frequency of heat rate enhances at higher concentration volume. The magnitude of streamlines elevates far from the surface due to free-stream velocity but isotherms enhance at the bottom of plate. The major applications of heat exchanger plate include steam condensers, boilers, air conditioning systems, chillers, food industry, computer processors, and ship engine cooling.