Artificial neural network model of non-Darcy MHD Sutterby hybrid nanofluid flow over a curved permeable surface: Solar energy applications

Shaik Jakeer ^a, Maduru Lakshmi Rupa ^b, Seethi Reddy Reddisekhar Reddy ^c,*, A.M. Rashad ^d         

a. Centre for Computational Modeling, Chennai Institute of Technology, Chennai 600069, India
         b. Department of Mathematics, S.A.S., Vellore Institute of Technology, Vellore 632014, India
         c. Department of Mathematics, Koneru Lakshmaiah Education Foundation, Bowrampet, Hyderabad 500043, Telangana, India
         d. Department of Mathematics, Aswan University, Faculty of Science, Aswan 81528, Egypt

Abstract: The conversion of solar radiation to thermal energy has recently much interest as the requirement for renewable heat and power grows. Due to their enhanced ability to promote heat transmission, nanofluids can significantly improve solar-thermal systems' efficiency. This section aims to study the heat transfer behavior of the Sutterby hybrid nanofluid flow of magnetohydrodynamics in the presence of a non-uniform heat source/sink and linear thermal radiation over a non-Darcy curved permeable surface. A novel implementation of an intelligent numerical computing solver based on multi-layer perceptron (MLP) feed-forward back-propagation artificial neural network (ANN) with the Levenberg-Marquard algorithm is provided in the current study. Data were gathered for the ANN model's testing, certification, and training. Established mathematical equations are nonlinear, which are resolved for velocity, the temperature in addition to the skin friction coefficient, and the rate of heat transfer by using the bvp4c with MATLAB solver. The ANN model selects data, constructs and trains a network, then evaluates its efficacy via mean square error. Graphs illustrate the impact of a wide range of physical factors on variables, including pressure, velocity, and temperature. In the entire study, the thermal energy improved by the SiO2 (silicon dioxide) - Au (gold) hybrid nanofluid than the SiO2-TiO2 (titanium dioxide) hybrid nanofluid. The higher internal heat generation/absorption parameter values increase the temperature.

Keywords: ANN model; Sutterby hybrid nanofluid; magnetic field; Non-Darcy-Forchheimer; Curved surface; Radiation

https://doi.org/10.1016/j.jppr.2023.07.002