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Optimal reduction of the C1–C3 combustion mechanism for the simulation of flaring / Helen H. Lou in Industrial & engineering chemistry research, Vol. 51 N° 39 (Octobre 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 39 (Octobre 2012) . - pp. 12697–12705 Titre : Optimal reduction of the C1–C3 combustion mechanism for the simulation of flaring Type de document : texte imprimé Auteurs : Helen H. Lou, Auteur ; Daniel Chen, Auteur ; Christopher B. Martin, Auteur Année de publication : 2012 Article en page(s) : pp. 12697–12705 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Combustion Résumé : Flaring is a combustion process designed to relieve pressures and safely dispose of vent gases from chemical and petrochemical plants. An industrial flaring activity typically involves various combustible waste gases and a large number of reactions and species. Because most of the detailed kinetic mechanisms for the speciation study of flaring events are too complicated to use in the computational fluid dynamics simulation of industrial-scale flares, several techniques for reduction of the detailed combustion mechanisms have been developed. In this paper, a new rigorous skeleton mechanism (RSM) based reduction technique, namely, the LU 2.0 algorithm, is proposed. It falls under the category of identification of redundancy. Other techniques in this category try to remove redundant species and reactions based on criteria such as sensitivity and quasi-steady-state analyses. These are highly dependent on the preanalysis of the mechanism and require species concentration sets for the conditions of interest. This algorithm tries to find out the skeleton mechanism with the lowest possible error. It works by rigorously testing all of the possible combinations of species sets. This RSM-based optimized mechanism was validated successfully against experimental data for various key performance indicators (laminar flame speeds, burner-stabilized flame, adiabatic flame temperature, and ignition delay) for methane, ethylene, and propylene flames. The efficacy of this algorithm was demonstrated by its improved predictability. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie2027684 [article] Optimal reduction of the C1–C3 combustion mechanism for the simulation of flaring [texte imprimé] / Helen H. Lou, Auteur ; Daniel Chen, Auteur ; Christopher B. Martin, Auteur . - 2012 . - pp. 12697–12705. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 39 (Octobre 2012) . - pp. 12697–12705 Mots-clés : Combustion Résumé : Flaring is a combustion process designed to relieve pressures and safely dispose of vent gases from chemical and petrochemical plants. An industrial flaring activity typically involves various combustible waste gases and a large number of reactions and species. Because most of the detailed kinetic mechanisms for the speciation study of flaring events are too complicated to use in the computational fluid dynamics simulation of industrial-scale flares, several techniques for reduction of the detailed combustion mechanisms have been developed. In this paper, a new rigorous skeleton mechanism (RSM) based reduction technique, namely, the LU 2.0 algorithm, is proposed. It falls under the category of identification of redundancy. Other techniques in this category try to remove redundant species and reactions based on criteria such as sensitivity and quasi-steady-state analyses. These are highly dependent on the preanalysis of the mechanism and require species concentration sets for the conditions of interest. This algorithm tries to find out the skeleton mechanism with the lowest possible error. It works by rigorously testing all of the possible combinations of species sets. This RSM-based optimized mechanism was validated successfully against experimental data for various key performance indicators (laminar flame speeds, burner-stabilized flame, adiabatic flame temperature, and ignition delay) for methane, ethylene, and propylene flames. The efficacy of this algorithm was demonstrated by its improved predictability. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie2027684