Application of response surface methodology and artificial neural network on pyrolysis of safflower seed press cake

作者：Angin Dilek^*; Tiryaki Aysun Egrisogut

来源：Energy Sources, Part A: Recovery, Utilization, and Environmental Effects , 2016, 38(8): 1055-1061.

DOI：10.1080/15567036.2013.862585

• Fixed-bed reactor
• neural network
• product yields
• pyrolysis
• response surface methodology

In this study, mathematical correlation between the process variables and product yields for pyrolysis of safflower seed press cake (SPC) in fixed-bed reactor was investigated by using the response surface methodology (RSM) and artificial neural networks (ANNs). The RSM results showed that the second-order response model can be used to describe the relationship between the various factors and the response. Several feed-forward fully connected neural networks were investigated and optimal configuration of the ANN model was obtained. The results revealed that the ANN model could be considered as an alternative to RSM and practical modeling technique for the pyrolysis product yields.

• 出版日期2016