Modeling and Optimization of Temperature Distribution on Heat Pump Convective Food Dryers By Artificial Neural Networks (ANN)

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Polatci H., Yıldız A. K., Tasova M.

INTERCIENCIA, cilt.57, sa.12, ss.14-27, 2023 (SCI-Expanded, Scopus)

• Yayın Türü: Makale / Tam Makale
• Cilt numarası: 57 Sayı: 12
• Basım Tarihi: 2023
• Doi Numarası: 10.59671/uu2ap
• Dergi Adı: INTERCIENCIA
• Derginin Tarandığı İndeksler: Scopus, Agricultural & Environmental Science Database, Science Citation Index Expanded (SCI-EXPANDED), Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, Veterinary Science Database, DIALNET
• Sayfa Sayıları: ss.14-27
• Yozgat Bozok Üniversitesi Adresli: Evet

Özet

It is generally subjected to a drying process to extend the shelf life of agricultural

products and to obtain products with high added value. Commonly used drying

methods are open-sun, hot air, infrared, microwave, and hybrid methods. The

open-sun drying method is advantageous in terms of energy consumption and

practicality. However, it is quite disadvantageous in terms of obtaining a

homogeneous temperature distribution and hygienic end product. For this reason,

renewable energy sources are used both to reduce the increasing energy

consumption and to provide a quality and fast drying process. Especially solar

dryers have become quite popular. However, one of the most important problems

in solar dryers in the literature review is the temperature difference between the

drying racks. This problem causes an increase in energy consumption and the

formation of end products that are not of homogeneous quality. In this study, the

temperature distribution between the shelves of a conventional dryer with a solar

assisted heat pump was modeled with artificial neural networks. Present

calculations revealed the lowest total cost value as 54.48 at 55 ºC target

temperature, 3.5 m/s airflow rate, and 43º diffuser angle of the drying machine.