Experimental investigation and artificial neural networks (ANNs) based prediction of thermal performance of solar air heaters with different surface geometry
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Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Pergamon-Elsevier Science Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Solar air heaters (SAHs) are one of the most utilized tools to obtain heat energy from the sun. A variety of SAH models exist with different geometries used for improving the heat transfer between the absorber plate and the air in the SAHs. In today ' s world, many researchers are focusing on designs that occupy the same dimensions but can generate more useful energy. In this study, two SAH with the same external volume (same base area and height), but different absorber surface geometries: a V -corrugated type (V -Type) and an internal baffle -installed type (B -Type), were designed, manufactured and experimentally tested in the climatic conditions of Osmaniye, T & uuml;rkiye. B -Type SAH, unlike the literature, is constructed with 11 inner baffles to allow the air to circulate more within the collector, aiming to achieve higher temperatures. The performances of the SAHs were compared by means of energy, exergy and enviro-economic (3E) analyses in the experiments lasting four consecutive days without interruption. The results show that the average amount of useful heat, energy efficiency ( eta I ) and exergy efficiency ( eta II ) of the V -Type SAH was 35.71%, 38.00% and 80.11% higher, respectively, than those obtained with the B -Type SAH, and also that the V -Type SAH was more environmentally friendly than the B -Type SAH. Additionally, in this study, common ANN models predicting the performance parameters of both SAHs were developed, constituting the another novelty of the research. Among the common ANN models developed for the outlet temperature ( T o ) , besides the eta I and eta II parameters, the best results were obtained with ANN 15, ANN 13 and ANN 18, respectively. Therefore, it is possible to use these developed models safely.
Açıklama
Anahtar Kelimeler
Solar air heater, Energy, Exergy, Enviro-economic, Artificial neural networks
Kaynak
Solar Energy
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
273
