ANFIS approach and thermal performance of solar air heaters integrated with phase change materials and porous foam gradient under mechanical vibrations

This study numerically examines the performance of a solar air heater (SAH) that combines PCM, porous foam gradients, and forced mechanical vibrations. The impact of using PCMs, porous foam gradients, forced vibrations, and Re on the thermal efficiency of SAH(η) has been analyzed. Simulations were conducted using ANSYS Fluent software based on the FVM approach. Various scenarios for the spatial variation of porosity coefficients in the porous foam gradient were considered. The results designate that the incorporation of PCMs leads to a significant increment in η, with enhancements of 78%, 77.07%, 77.8%, and 75.43% for different materials, including RT35HC, Paraffin wax, Eicosane, and Tetracosane, respectively. Additionally, an increment in the Re correlates with a decrement in the average melting fraction, with the highest thermal efficiency observed at Re=3000. Positioning the porous foam gradient in the PCM region, rather than in the air zone, results in an increment of η 13.35% to 13.74%. The effect of mechanical vibrations on system performance leads to a reduction in η by 14% to 30%. Finally, the artificial intelligence model, ANFIS neural network demonstrated a correlation coefficient of 0.99731, accurately predicting η. These findings can contribute to improving the design and η of SAHs.