Optimizing heat transfer in solar collector aircraft through oblique chemically reactive hybrid nanofluid flow: AI-based mathematical analysis

A key concept in the study of radiative heat transfer, which deals with the interaction of thermal radiation, is quadratic thermal radiation to investigate the performance of solar aircraft, powered by nanotechnology and photovoltaic energy. It includes a quadratic relationship between radiative characteristics and temperature. Despite the fact that thermal radiations is more common in Non-linear thermal radiation is significant in many real-world applications, especially where a more accurate depiction of the radiative transport of heat is needed. In certain situations where increased precision in simulating radiative heat transport is required, the phenomenon plays a critical role. Because of this, the current study looks how a hybrid nanofluid flows around a cylindrical wing of solar aircraft when heat radiation and activation energy are quadratic, nonlinear and linear. Through similarity transformations the governing system of nonlinear differential equations is converted into a system of ordinary differential equations. Those ODEs are solved numerically using Mathematica with ND-Solver technique. Temperature, velocity, and concentration profiles are computed for a range of values of pertinent parameters. Effect of different flow parameters are taken into consideration for checking behavior of flow system's velocity, temperature, and concentration. Through predictive modeling that takes into account nonlinear turbulent behavior and the unpredictability of affecting parameters, AI analysis improves and optimizes findings. The Neural-Network Back-propagated Levenberg-Marquardt Algorithm (NN-BLMA) is then used in MATLAB to analyze the acquired data and provide numerical function fits (FF), state functions (ST), error histograms (EH), regression analysis (RA), and performance graphs. The study also points out that flow parameters have a major impact on velocity, temperature and concentration as finding results as velocity profile decreases with increase in thermal slip parameter and curvature flow parameter while velocity profile increases with increase in thermal slip parameter and curvature flow parameter. Temperature decreases due to increase in (Pr) Prandtl number, thermal slip parameter and curvature flow parameter. Concentration decreases with increase in, curvature flow parameter, chemical reaction parameter and (Sc) Schmidt’s number. The numerical code is validated by comparing results with existing studies, showing good agreement.