Modeling of bio-oil production by pyrolysis of woody biomass: artificial neural network approach
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Tarih
2020
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Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
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%).
Açıklama
Anahtar Kelimeler
Kaynak
Politeknik Dergisi
WoS Q Değeri
Scopus Q Değeri
Cilt
23
Sayı
4