An Analysis of the Effects of Nanofluid-Based Serpentine Tube Cooling Enhancement in Solar Photovoltaic Cells for Green Cities

Abstract

In this work, the impact of the serpentine copper tube heat exchanger with nanofluids on 100 W solar photovoltaic thermal collectors (PV/T) was analyzed experimentally and numerically. The cooling fluids assessed in this system were distilled water, Al2O3 0.1%, and Al2O3 0.2% based nanofluids. Tests were accomplished at diverse coolant mass flow rate in India’s summer days of 2018. A computational fluid dynamics (CFD) investigation was carried out to perform a parametric study, identify surface and exit T profiles, and examine the cooling effectiveness. The impact of mass flow rate of nanofluid on the outside T and Reynolds number were studied. The Reynolds number obtained in the flow experiments and CFD analysis was in the range of 900–1,300. The maximum irreversibility occurred while using water, whereas minimum irreversibility obtained Al2O3 0.2% nanofluid. Exergy efficiency was found to be increased from 20% to 36% during the day. It was identified that the increase in PV/T scheme led to higher exergy losses. The thermal efficiency of a water-based cooling system resulted in 53.61%. Meanwhile, Al2O3 0.1% and Al2O3 0.2% based coolants provided 69.45% and 71.02%, respectively. A good agreement was obtained between the experimental results and the computer model.

Recurrent Neural Networks for Image Captioning: A Case Study with LSTM

“…Previous studies have investigated various designs, counting LSTM, GRU, consideration instruments, and transformers. Our work adjusts with the drift of leveraging RNNs, especially LSTMs, for picture captioning assignments [28]. The key commitments and differentiators of our study include:…”