TECHICAL Series MATHEMATICS • INFORMATICS • PHYSICS Series PHILOLOGY Series ECONOMIC SCIENCES Sereies EDUCATIONAL SCIENCES Series LAW AND SOCIAL SCIENCES Series
The Reforming of Ethanol over Co/CeO2 Catalysts: A Neural Network Approach
(Reformarea etanolului pe catalizator de Co/CeO2: Abordare utilizând reţeaua neuronală artificială)
Vol LXIX • No. 3/2017
Matei Dănuţa, Bogdan Doicin, Dorin Stănică-Ezeanu
Petroleum-Gas University of Ploiesti, Bd. Bucuresti, 39, Ploiești
e-mail: bogdan.doicin@upg-ploiesti.ro

 Keywords   ethanol, steam reforming, artificial neural network, catalyst

 Abstract
An artificial neural network has been developed for the design and simulation of the catalytic properties of a metal-support system based on Co/CeO2 for the steam reforming of ethanol. Ethanol (8% and 10% vol) was considered as raw material for hydrogen production by steam reforming. This investigation has employed this artificial neural network modeling to describe the complex relationship between ethanol steam reforming and the Co/CeO2 catalyst used in the process. The estimation of accuracy of the newly created neural network will be tested on a set of input data, which are already known, determined values for output. Specifically, the neural network was used to determine the optimum conditions for obtaining maximum hydrogen production.


 Rezumat
O reţea neuronală artificială a fost dezvoltată pentru proiectarea şi simularea proprietăţilor catalitice ale unui sistem de tip metal-suport în speţă Co/CeO2 pentru reformare cu abur a etanolului. Etanol (8% şi 10% volum) a fost considerat drept materie primă pentru producerea hidrogenului prin reformarea cu abur. Studiul a urmărit această modelare prin intermediulunei reţelei neuronale artificiale pentru a descrie relaţia complexă dintre performanţele procesului de reformare cu abur a etanolului şi catalizatorul de Co/CeO2utilizat în proces. Pentru a testa precizia de estimare a reţelei neuronale nou create, acesta va fi testată pe un set de date de intrare obţinute, care sunt deja cunoscute, valorile determinate pentru ieşire. În mod specific reţeaua neuronală a fost utilizată pentru a determina condiţiile optime de obţinere a unui randament maxim de hidrogen.



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