Araştırma Makalesi

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

Cilt: 9 Sayı: 1 31 Mart 2022
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An experimental and theoretical examination of pine woods dried in the vacuum dryer by artificial neural network

Öz

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.

Anahtar Kelimeler

Destekleyen Kurum

Süleyman Demirel University Scientific Research Projects Unit (SDUBAP)

Proje Numarası

1527-D-07

Teşekkür

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

Kaynakça

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  2. Pedreno-Molina, J.L., Monzo-Cabrera, J., Toledo-Moreo, A. and Sánchez-Hernández, D. 2005. A novel predictive architecture for microwave-assisted drying processes based on neural Networks. International Communications in Heat and Mass Transfer, 32, 1026–1033.
  3. Ceylan, I. 2008. Determination of drying characteristics of timber by using artificial neural networks and mathematical models. Drying Technology, 26, 1469–1476.
  4. Menlik, T., Ozdemir, M.B. and Kirmaci, V. 2010. Determination of freeze-drying behaviors of apples by artificial neural network. Expert Systems with Applications, 37, 7669–7677.
  5. Momenzadeh, L., Zomorodian, A. and Mowla, D. 2011. Experimental and theoretical investigation of shelled corn drying in a microwave-assisted fluidized bed dryer using artificial neural network. Food and Bioproducts Processing, 89, 15–21.
  6. Ceylan, I. and Aktas, M. 2008. Modeling of a hazelnut dryer assisted heat pump by using artificial neural networks. Applied Energy, 85, 841–854.
  7. Movagharnejad K. and Nikzad M. 2007. Modeling of tomato drying using artificial neural network. Computers and Electronics in Agriculture, 59, 78–85.
  8. Esteban L.G., Fernandez F.G. and Palacios P. 2009. MOE prediction in Abies pinsapo Boiss. timber: Application of an artificial neural network using non-destructive testing. Computers and Structures, 87, 1360–1365.

Ayrıntılar

Birincil Dil

İngilizce

Konular

-

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

31 Mart 2022

Gönderilme Tarihi

6 Şubat 2022

Kabul Tarihi

31 Mart 2022

Yayımlandığı Sayı

Yıl 2022 Cilt: 9 Sayı: 1

Kaynak Göster

APA
Dikmen, E., Şencan Şahin, A., & Yakut, K. (2022). An experimental and theoretical examination of pine woods dried in the vacuum dryer by artificial neural network. International Journal of Energy Applications and Technologies, 9(1), 31-37. https://doi.org/10.31593/ijeat.1069080
AMA
1.Dikmen E, Şencan Şahin A, Yakut K. An experimental and theoretical examination of pine woods dried in the vacuum dryer by artificial neural network. International Journal of Energy Applications and Technologies. 2022;9(1):31-37. doi:10.31593/ijeat.1069080
Chicago
Dikmen, Erkan, Arzu Şencan Şahin, ve Kemal Yakut. 2022. “An experimental and theoretical examination of pine woods dried in the vacuum dryer by artificial neural network”. International Journal of Energy Applications and Technologies 9 (1): 31-37. https://doi.org/10.31593/ijeat.1069080.
EndNote
Dikmen E, Şencan Şahin A, Yakut K (01 Mart 2022) An experimental and theoretical examination of pine woods dried in the vacuum dryer by artificial neural network. International Journal of Energy Applications and Technologies 9 1 31–37.
IEEE
[1]E. Dikmen, A. Şencan Şahin, ve K. Yakut, “An experimental and theoretical examination of pine woods dried in the vacuum dryer by artificial neural network”, International Journal of Energy Applications and Technologies, c. 9, sy 1, ss. 31–37, Mar. 2022, doi: 10.31593/ijeat.1069080.
ISNAD
Dikmen, Erkan - Şencan Şahin, Arzu - Yakut, Kemal. “An experimental and theoretical examination of pine woods dried in the vacuum dryer by artificial neural network”. International Journal of Energy Applications and Technologies 9/1 (01 Mart 2022): 31-37. https://doi.org/10.31593/ijeat.1069080.
JAMA
1.Dikmen E, Şencan Şahin A, Yakut K. An experimental and theoretical examination of pine woods dried in the vacuum dryer by artificial neural network. International Journal of Energy Applications and Technologies. 2022;9:31–37.
MLA
Dikmen, Erkan, vd. “An experimental and theoretical examination of pine woods dried in the vacuum dryer by artificial neural network”. International Journal of Energy Applications and Technologies, c. 9, sy 1, Mart 2022, ss. 31-37, doi:10.31593/ijeat.1069080.
Vancouver
1.Erkan Dikmen, Arzu Şencan Şahin, Kemal Yakut. An experimental and theoretical examination of pine woods dried in the vacuum dryer by artificial neural network. International Journal of Energy Applications and Technologies. 01 Mart 2022;9(1):31-7. doi:10.31593/ijeat.1069080

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