Application of ANN and prediction of drying behavior of mushroom drying in side hybrid greenhouse solar dryer: An experimental validation

Yıl 2022, Cilt: 8 Sayı: 2, 221 - 234, 11.03.2022

Anand Kushwah M.k. Gaur Anil Kumar Pushpendra Sıngh

https://doi.org/10.18186/thermal.1086189

Cited By: 6

Öz

The newly developed Heat Exchanger Evacuated Tube Assisted Drying System (HE-ETADS) is fabricated in roof of campus of MITS, Gwalior, India. Heat transfer analysis of developed drying system is carried out by drying mushroom inside it. The heat transfer coefficient plays a significant role in drying method. The study emphasizes on determining the convective as well as evaporative heat transfer coefficients (CHTC & EHTC) and the determination of best drying rate model fit for mushroom drying inside novel drying system. The artificial neural network is developed for predicting the CHTC & EHTC. Value of CHTC & EHTC varies from 2.10 to 3.43 and 25.68 to 49.85 W/m2°C respectively. The developed ANN model helps in predicting the heat transfer coefficient once trained using input factors like solar radiation, relative humidity, environmental temperature and time. The value of R2 for the developed ANN model is 0.99, which shows that model predicts the value very close to the calculated value of heat transfer coefficients. Drying kinetics of mushroom is tried to fit in nine drying rate models. The Midili-Kucuk model shows the better fit among the other models.

Anahtar Kelimeler

Mushroom Drying, HGSD, Drying Kinetics, Heat transfer;, ANN.

Kaynakça

• The article references can be accessed from the .pdf file.