An experimental and theoretical examination of pine woods dried in the vacuum dryer by artificial neural network

Year 2022, , 31 - 37, 31.03.2022

Erkan Dikmen , Arzu Şencan Şahin , Kemal Yakut

https://doi.org/10.31593/ijeat.1069080

Cited By: 1

Abstract

The drying characteristics of the pine woods were examined in the vacuum drying system under different operating conditions. Three drying temperatures (40, 50 and 60 ◦C), three operating pressures (0.6, 0.7 and 0.8 bar) and three times of exposure to vacuum (5, 10 and 15 minutes) were investigated. Experiments were carried out to obtain data from the sample moisture content. In this study, the application of Artificial Neural Network (ANN) to estimate pine woods' moisture content (output parameters for ANN modeling) was examined. Drying time, drying temperature, relative humidity, pressure and air temperature were accepted as the input parameters of the model. Training and validation were performed with great accuracy. The moisture content of woods is formulated by the ANN method. The proposed method offers more flexibility; therefore, the determination of the moisture content in pine woods is quite simpler.

Keywords

Vacuum drying, Wood, Artificial Neural Network, Modeling

Supporting Institution

Süleyman Demirel University Scientific Research Projects Unit (SDUBAP)

Project Number

1527-D-07

Thanks

Authors would like to thank Süleyman Demirel University Scientific Research Projects Unit (SDUBAP) for the financial support for the Project No: 1527-D-07.

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