A multidisciplinary Journal in the field of Agricultural Engineering

Document Type : Original Article

Authors

1 Mechanical Engineering of Biosystems Tarbiat Modares University, Tehran

2 Department of Biosystems Engineering, Isfahan University of Technology, Isfahan, Iran

Abstract

In this Research, the effects of three parameters, including temperature, speed, and sample size, were evaluated on Energy utilization, the Energy utilization ratio, exergy loss, and exergy efficiency. The lowest Energy utilization and exergy loss were respectively at a size of 1.3 cm, the speed of 3 m/s and 40 °C and the high Energy utilization and exergy loss were observed at a size of 0.5 cm, the speed of 7 m/s and a temperature of 60 °C, as well as the maximum and minimum exergy efficiency were in the same temperature, but The least exergy efficiency was size of 1.3 cm, the speed of 5 m/s and the highest exergy efficiency was size of 0.5 cm, the speed of 3 m/s. The least the Energy utilization ratio was at a size of 1.3 cm, speed of 3 m/s, and a temperature of 60°C. The Energy utilization ratio was highest at a size of 0.5 cm, speed of 7 m/s, and 40°C; the lowest Energy utilization ratio was at a size of 1.3 cm, speed of 3 m/s, and a temperature of 60°C. Also in this study, an artificial neural network was used to predict the parameters of energy and exergy, and a simulation of the thermodynamic drying process was carried out using the created ANN. A network was designed from learning algorithms and transfer functions that could predict with reasonable accuracy the exergy and energy parameters related to the drying process. The statistical analysis results showed that neural networks can be used in the intelligent drying process, which has a large share of energy consumption in the food industry.

Keywords

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