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Dergiler / International Journal of Energy Applications and Technologies / 2026 / Cilt: 9 Sayı: 1

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

Erkan Dikmen(ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ, TEKNOLOJİ FAKÜLTESİ)0000-0002-6804-8612
Arzu Şencan Şahin(ISPARTA UNIVERSITY OF APPLIED SCIENCES, FACULTY OF TECHNOLOGY, DEPARTMENT OF MECHANICAL ENGINEERING, MECHANICAL ENGINEERING PR.)0000-0001-8519-4788
Kemal Yakut(ISPARTA UNIVERSITY OF APPLIED SCIENCES, FACULTY OF TECHNOLOGY, DEPARTMENT OF MECHANICAL ENGINEERING, MECHANICAL ENGINEERING PR.)0000-0002-5156-9892
Sayfa
31–37
Yayın Tarihi
2022-03-31
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The proposed method offers more flexibility; therefore, the determination of the moisture content in pine woods is quite simpler.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:The drying characteristics of the pine woods were examined in the vacuum drying system under different operating conditions.
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Temel Bulgular & Veri: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.
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Sonuç & Katkı:The proposed method offers more flexibility; therefore, the determination of the moisture content in pine woods is quite simpler.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Vacuum drying · Wood · Artificial Neural Network

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.

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Bu Makaleye Atıf Yap

Dikmen, E., Şahin, A. Ş., 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, Cilt: 9 Sayı: 1, 31–37. https://doi.org/10.31593/ijeat.1069080

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