DOI LINK: https://doi.org/10.59671/uu2Ap

Paper ID:uu2Ap

Volume:57

Issue:12

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

Abstract: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 �C target temperature, 3.5 m/s airflow rate, and 43� diffuser angle of the drying machine.

Keywords:Drying, solar energy, heat pump, cost value, modeling, optimization

Authors:Hakan Polatci, Adil Koray Yildiz,Muhammed Tasova

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