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Título

Application of response surface methodology to assess the combined effect of operating variables on high-pressure coal gasification for H2-rich gas production

AutorFermoso Domínguez, Javier CSIC ORCID; Gil Matellanes, María Victoria CSIC ORCID ; Arias Rozada, Borja CSIC ORCID ; González Plaza, Marta CSIC ORCID ; Pevida García, Covadonga CSIC ORCID ; Pis Martínez, José Juan CSIC; Rubiera González, Fernando CSIC ORCID
Palabras claveHydrogen production
High-pressure gasification
Coal
Response surface methodology
Fecha de publicaciónfeb-2010
EditorElsevier
CitaciónInternational Journal of Hydrogen Energy 35(3): 1191-1204 (2010)
ResumenCoal gasification was performed by means of a high-pressure fixed bed gasifier fitted with a solids feeding system in continuous mode, using oxygen and steam as gasifying agents. The main aim of the paper was to assess the combined effects of the operating variables (temperature, oxygen and steam concentrations) on high-pressure coal gasification. To this end a face centered central composite design (FCCCD) based on response surface methodology (RSM) was used. The response variables studied were: H2, CO and syngas production, H2/CO ratio, cold gas efficiency (η), and carbon conversion (X). The study was carried out at temperatures of 900, 950 and 1000 °C, using oxygen concentrations of 5, 10 and 15 vol.%, and steam concentrations of 25, 40 and 55 vol.%. The gasification temperature was found to be the most influential variable, with high temperatures leading to an increase in all the response variables studied. An increase in the oxygen content of the gasifying agent led to a decrease in H2 and CO production, and cold gas efficiency, whilst carbon conversion was favoured. An increase in steam concentration, on the other hand, favoured the production of H2 and syngas production, whereas CO production underwent a reduction; cold gas efficiency and carbon conversion were observed to increase. Response surface methodology (RSM) revealed the effects of interaction between the operating variables, which would not have been identified by the traditional “one-factor-at-a-time” method. The models developed successfully fitted the experimental results for all the response variables studied.
Versión del editorhttp://dx.doi.org/10.1016/j.ijhydene.2009.11.046
URIhttp://hdl.handle.net/10261/103913
DOI10.1016/j.ijhydene.2009.11.046
ISSN0360-3199
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