Odunsu Biyokütlenin Pirolizi ile Biyoyağ Üretiminin Modellenmesi: Yapay Sinir Ağları Yaklaşımı

Bu çalışma, piroliz sıvı ürününü (biyoyağ) modellemek için güvenilir bir yapay sinir ağı (YSA) modeli oluşturmak amacıyla yapılmıştır. Bu maksatla piroliz sıcaklığı, piroliz süresi, katalizör türü, katalizör oranı, biyokütle parçacık boyutu ve biyokütle kısmi ve kesin analizi gibi biyoyağ verimliliği ile ilgili parametreler test edilmiştir. Modellemede, farklı biyokütle tiplerinin ve piroliz yöntemlerinin neden olduğu farklı karakteristiklerden dolayı, yalnızca odunsu biyokütleden yavaş ve orta piroliz yöntemleri ile elde edilen sıvı ürün verimlilikleri dikkate alınmıştır. Sonuç olarak, korelasyon derecesini gösteren R değerleri eğitim, doğrulama ve test adımları için sırasıyla 0.992, 0.933 ve 0.951 bulunmuştur. YSA modelinin güvenilirliğini değerlendirmek amacıyla tahminlenen değerler, daha önce modele tanıtılmamış yeni deneysel veriler ile kıyaslanmıştır. Buna göre, simülasyon sonuçlarının deneysel sonuçlar ile uyum içerisinde bulunduğu ve oluşturulan modelin güvenilir olduğu tespit edilmiştir. Ayrıca, girdi parametrelerinin çıktı üzerine etkileri incelendiğinde, biyoyağ verimliliğini etkileyen en önemli parametrenin katalizör türü (%11.4) olduğu belirlenmiştir.

Modeling of bio-oil production by pyrolysis of woody biomass: artificial neural network approach

This study is dedicated to developing a reliable artificial neural network (ANN) model to model the pyrolysis liquid product (biooil). Some related parameters with the bio-oil yield such as the pyrolysis temperature, duration, catalyst type, catalyst ratio, particlesize, proximate, and ultimate analysis of the biomass were tested. Due to the different characteristics of different biomass typesand pyrolysis methods, only slow and intermediate pyrolysis data from woody biomass were used in modeling. The correlationcoefficients (R) were 0.992, 0.933, and 0.951 for training, validation, and testing, respectively. In order to evaluate the predictabilityof the ANN model, the predicted results were compared with the experimental results that were not introduced before. Thesimulated data were in good agreement with the experimental results indicating the reliability of the developed model. The relativeimpact results revealed that the most important parameter that affects the bio-oil yield was catalyst type (11.4%).

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Politeknik Dergisi-Cover
  • ISSN: 1302-0900
  • Yayın Aralığı: Yılda 4 Sayı
  • Başlangıç: 1998
  • Yayıncı: GAZİ ÜNİVERSİTESİ