Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloHydrogen production as a green fuel in silica membrane reactor: Experimental analysis and artificial neural network modeling
Anno di pubblicazione2018
Autore/iGhasemzadeh K.; Aghaeinejad-Meybodi A.; Basile A.
Affiliazioni autoriChemical Engineering Faculty, Urmia University of Technology, Urmia, , Iran; Chemical Engineering Department, Faculty of Engineering, Urmia University, Urmia, , Iran; ITM-CNR, c/o University of Calabria, Via Pietro Bucci, Cubo 17/C, Rende, CS, 87036, , Italy
Autori CNR e affiliazioni
  • inglese
AbstractIn this work, artificial neural networks (ANNs) model has been developed for investigation of the silica membrane reactor (MR) performance during methanol steam reforming (MSR) reaction. Particularly, such parameters as the transmembrane pressure (from 0.5 to 1.5 bar), reaction temperature (from 513 to 573 K), gas hourly space velocity (GHSV) between 3300 and 10000 h-1 and Steam/MeOH molar ratio (from 1 to 3) have been taken to account from both experimental and modeling viewpoints in order to analyze their influences on the silica MR performance with respect to traditional reactor (TR) in terms of methanol conversion, CO selectivity, total hydrogen yield, hydrogen recovery, hydrogen and carbon monoxide compositions. The ANN model results have been validated by using portion of the experimental data. Moreover, regarding to optimization results of ANNs model, reaction temperature was selected as the most effective operating parameter in the silica membrane reactor and traditional reactor during MSR reaction.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da114
Pagine a124
Pagine totali-
RivistaFuel (Guildf.)
Attiva dal 1948
Editore: Butterworth Scientific, - Guildford
Paese di pubblicazione: Regno Unito
Lingua: inglese
ISSN: 0016-2361
Titolo chiave: Fuel (Guildf.)
Titolo proprio: Fuel. (Guildf.)
Titolo abbreviato: Fuel (Guildf.)
Numero volume della rivista222
Fascicolo della rivista-
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • Scopus (Codice:2-s2.0-85042468106)
Parole chiaveHydrogen production, Silica membrane reactor, Modeling Artificial neural network, Methanol steam reforming
Link (URL, URI)
Titolo parallelo-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • ITM — Istituto per la tecnologia delle membrane
Moduli/Attività/Sottoprogetti CNR-
Progetti Europei-
Hydrogen production as a green fuel in silica membrane reactor: Experimental analysis and artificial neural network modeling (documento privato )
Tipo documento: application/pdf