Modeling of Bio-Oil Production by Pyrolysis of Woody Biomass: Artificial Neural Network Approach

Yıl 2020, Cilt: 23 Sayı: 4, 1255 - 1264, 01.12.2020

Günay Özbay Erkan Sami Kökten

https://doi.org/10.2339/politeknik.659136

Cited By: 7

Öz

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

Anahtar Kelimeler

Artificial neural network, bio-oil, catalyst, modeling, pyrolysis

Destekleyen Kurum

TÜBİTAK

Proje Numarası

115O453

Teşekkür

The support from TUBITAK (The Scientific and Technological Research Council of Turkey) [Project grant number: 115O453 for this research are gratefully acknowledged.

Kaynakça

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