Prediction of energy and exergy of mushroom slices drying in hot air impingement dryer by artificial neural network
作者： Zi-Liang Liu , Jun-Wen Bai , Shu-Xi Wang , Jian-Sheng Meng , Hui Wang
DOI: 10.1080/07373937.2019.1607873
关键词: Environmental science 、 Exergy 、 Range (statistics) 、 Exergy efficiency 、 Current (fluid) 、 Work (thermodynamics) 、 Artificial neural network 、 Energy (signal processing) 、 Process engineering 、 Second law of thermodynamics
摘要: In current work, the energy and exergy analysis of hot air impingement drying mushroom slices was conducted under different temperature (55, 60, 65, 70, 75 °C), velocity (3, 6, 9, 12 m/s), sample thickness (6, 12 mm) by first second law thermodynamics. The statistical results indicated that effect on more important than it. utilization ratio were in range 0.067–0.859 kJ/s 0.087–0.34, respectively. loss efficiency varied from 0.045–0.571 kJ/s 0.315–0.879, Besides, artificial neural network (ANN) employed to predict parameters. modeling revealed ANN models with arranged training algorithms transfer function could be utilized performance system satisfactory accuracy.
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