Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
56336 | Catalysis Today | 2011 | 7 Pages |
Abstract
This investigation has employed artificial neural network (ANN) modeling to describe the complex relationship between the forced cycling parameters and the reactor performance during periodic operation between propane steam reforming and CO2—carbon gasifying agent. Experimental data from our laboratory were assessed against different ANNs and based on a 2-way ANOVA treatment of various error indices, a two-hidden layer network with 5 neurons emerged as the best model for both descriptive and predictive purposes. Cycle split has the most significant (85%) positive effect on the improvement in H2 and CO production and the appearance of resonant peaks while cycle period appeared to have detrimental effect on product yield.
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Catalysis
Authors
Viswanathan Arcotumapathy, Feraih Alenazey, Adesoji A. Adesina,