Abstract

The current study is the authors’ next work from the thermo vision perspective of real time single sun solar field performance infrared thermography (IRT) on commercial grade Alumina solar absorber surface coatings (SASCs) to recognize surface roughness (Ra) as one of the important production process parameters. In a previous study, it was investigated with IRT, and found that Ra<1.8 is favorable and hard anodized Alumina (HAAO) coatings exhibits better surface temperature (Ts) gain as compared to organic dyed non-HAAO coatings on Aluminum substrate, and are more stable in solar field for many years in open air environment without degrading their performance. It may be useful in better optimization of SASCs specifically for personal protective equipments (PPEs) sanitization and artificial intelligence (AI) driven heating ventilation air conditioning (HVAC) systems (AIDHVACS) design to control Covid-19 in current situations.The influence of Ra of few microns ∼ <15 µm on Alumina SASCs’ Ts gain is examined. The presented study shows that more than 1.05 mm thickness of substrate flat is necessary to develop good quality of alumina coating; Ra<1.8 µm is favorably expected to the extent of Ra value approaching as close as to nanoscale ∼ 5-500 nm; local surface temperature gained is depending upon local Ra profile as well as upon surface morphology in addition to the anodizing process parameters and other environmental factors. It suggests that the optimal surface profile should be designed as an integral to the production line processes. The substrate surface chemical composition may also change while processing due to surface contact with the processing tools, which may also result in altered solar field performance due to substrate altered material composition prior to hard anodizing process, as examined with X-ray fluorescence spectrometry (XRF) and ultraviolet–visible spectrophotometry (UV-VIS). The novelty is that other studies of surface roughness parameter is focused upon convective heat transfer inside tunnel or duct solar heat absorbers e.g. air heaters, whereas the authors have focused upon surface roughness of solar radiation receiving outer surface as an important commercial production process variable having effect upon conductive heat transfer in solar thermal power systems. The AIDHVACS needs machine learning and big data analysis as the need of the hour.

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