A thermal management algorithm for flow analysis of water-based Cu–Al ₂ O ₃ hybrid nanofluid in multiple fields

Advanced thermal management is significant for flat-plate solar collectors, microelectronic cooling devices, thin-film drying units, and advanced heat exchangers. For a solar collector, its physical model can be described as a hybrid nanofluid heat transfer over a planar surface under magnetic field and solar thermal radiation, which has not been studied before. By combining Response Surface Methodology (RSM) and Artificial Neural Network (ANN), we present a model with a comprehensive analysis of a three-dimensional laminar thin-film water-based Cu–Al2O3 hybrid nanofluid over an inclined rotating planar surface under the impacts of gravitational field, magnetic field, and incident solar radiation using thermal convective boundary condition. The sensitivity of the key factors influencing the thermal performance of the nanosystem is recognized and ranked by RSM. Results reveal that the thermal Biot number is the supreme critical factor affecting the heat transfer rate, followed in order by irradiance and absorption factors. In addition, the reliability of the RSM model is validated by the error analysis, which demonstrates an excellent agreement between the results obtained by RSM and numerically computed (obtained via collocation method); moreover, both results well match the experimental runs. Based on the numerical data, an Artificial Neural Network (ANN) model is also developed to predict thermal performance. Results demonstrate an outstanding predictive accuracy of the ANN model with minimal mean squared (relative) error of 1.386 × 10−8 and near-perfect regression value of 99.99%. Overall, this analysis highlights the successful applications of numerical simulation, RSM-based sensitivity analysis and ANN-based predictive modelling for analysing hybrid nanofluid flow and heat transfer in thin film configurations. Significant technical insights provided by this research will benefit the design of thermal systems requiring advanced thermal management.