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Auteur David Milne
Documents disponibles écrits par cet auteur
Affiner la rechercheCandidate attainable regions for the oxidative dehydrogenation of n-butane using the recursive constant control (RCC) policy algorithm / David Milne in Industrial & engineering chemistry research, Vol. 48 N° 11 (Juin 2009)
[article]
in Industrial & engineering chemistry research > Vol. 48 N° 11 (Juin 2009) . - pp. 5211–5222
Titre : Candidate attainable regions for the oxidative dehydrogenation of n-butane using the recursive constant control (RCC) policy algorithm Type de document : texte imprimé Auteurs : David Milne, Auteur ; Tumisang Seodigeng, Auteur ; David Glasser, Auteur Année de publication : 2009 Article en page(s) : pp. 5211–5222 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Attainable region Oxidative dehydrogenation N-butane Résumé : Attainable region (AR) ideas have previously been used to identify candidate attainable regions (ARCs) for the oxidative dehydrogenation (ODH) of n-butane to butenes and butadiene and in so doing to identify the maximum possible yields of different hydrocarbon product. Because of the large dimensionality of the problem, it was not possible then to do a complete AR analysis. Among the configurations considered, it was found that the reactor configuration for the respective ARCs in all instances was an inert membrane reactor (IMR) functioning as a differential side-stream reactor in which one of the reactants, oxygen, was introduced along the length of the reactor so as to maintain a very low and constant value of its partial pressure. Nevertheless, despite producing high yields of product, extremely large and impractical residence times ensued. In this paper, a new tool, the recursive convex control (RCC) policy, is used to identify the ARCs in the full dimensional space. These ARCs showed excellent agreement with those previously published, and the optimal reactor structures presented in those publications have been confirmed albeit with different oxygen control parameters. The maximum yields are now achieved with very much lower residence times. These results also confirm the benefit from using the AR approach on problems where a full AR analysis is not possible. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801600w [article] Candidate attainable regions for the oxidative dehydrogenation of n-butane using the recursive constant control (RCC) policy algorithm [texte imprimé] / David Milne, Auteur ; Tumisang Seodigeng, Auteur ; David Glasser, Auteur . - 2009 . - pp. 5211–5222.
Chemical engineering
Langues : Anglais (eng)
in Industrial & engineering chemistry research > Vol. 48 N° 11 (Juin 2009) . - pp. 5211–5222
Mots-clés : Attainable region Oxidative dehydrogenation N-butane Résumé : Attainable region (AR) ideas have previously been used to identify candidate attainable regions (ARCs) for the oxidative dehydrogenation (ODH) of n-butane to butenes and butadiene and in so doing to identify the maximum possible yields of different hydrocarbon product. Because of the large dimensionality of the problem, it was not possible then to do a complete AR analysis. Among the configurations considered, it was found that the reactor configuration for the respective ARCs in all instances was an inert membrane reactor (IMR) functioning as a differential side-stream reactor in which one of the reactants, oxygen, was introduced along the length of the reactor so as to maintain a very low and constant value of its partial pressure. Nevertheless, despite producing high yields of product, extremely large and impractical residence times ensued. In this paper, a new tool, the recursive convex control (RCC) policy, is used to identify the ARCs in the full dimensional space. These ARCs showed excellent agreement with those previously published, and the optimal reactor structures presented in those publications have been confirmed albeit with different oxygen control parameters. The maximum yields are now achieved with very much lower residence times. These results also confirm the benefit from using the AR approach on problems where a full AR analysis is not possible. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie801600w