Thermal management for conjugate heat transfer of curved solid conductive panel coupled with different cooling systems using non-Newtonian power law nanofluid applicable to photovoltaic panel systems

Thermal performance features for a coupled conjugate thermo-fluid system with different cooling configurations (flat channel (F-C), grooved channel (G-C) and impinging jets (I-J)) are explored numerically by using non-Newtonian nanofluid. The numerical work is performed for different Reynolds numbers (100 <= Re <= 300), index of power law (0.8 <= n <= 1.2), height (0.1H <= b <= 0.6..) and number (2 <= N <= 9) of corrugation in the G-C system, number (2 <= N-j <= 9) and distance (5 omega <= sx <= 25 omega) between jets in the I-J flow system. Different volume fractions (0 <= phi <= 0.04) and particle sizes (20 nm <= dp <= 80 nm) of nanoparticles are used. When systems operating at the highest and lowest Re are compared, 9 K, 11 K and 8 K temperature reduction are achieved for F-C, G-C and I-J cooling systems. However, I-J flow system at higher Re is very effective on the thermal performance improvement when shear thickening fluid is used. For the G-C flow system, increasing the height and number of the corrugation waves resulted in improvement in the thermal performance. Up to 46% increment in the Nu number (average) and reduction of 6.5 K in the average surface temperature are achieved with varying the height of the corrugation while these values are 17% and 1.6 K when wave number is increased. The average Nu number rises by about 32% and temperature drops by about 6.5 K when jet number is varied from 3 to 11, while these values are obtained as 8% and 4 K for when distance between jets are varied from sx = 5 omega to sx = 25 omega. For F-C, G-C and I-J flow systems, average Nu rises by about 15.5% and 14.5% and 16.3% for shear thinning fluid while they become 16.6%, 9.94% and 12.8% for shear thickening fluid at the highest solid volume fraction. As the nanoparticle size is increasing, there is 6% and 7% reduction in the average Nu number. Thermal performance estimations are made with four inputs and four outputs system by using artificial neural networks.

Automated summary

The thermal performance features of a coupled conjugate thermo-fluid system with different cooling configurations were explored using non-Newtonian nanofluid. Different system parameters, such as Reynolds numbers, power-law index, height, corrugation number, and jet distance, were studied to understand their effects on the thermal performance. The use of different nanoparticles and fluid parameters in various configurations resulted in different impacts on the thermal performance.