Reduction of Single Event Kinetic Models by Rigorous Relumping: Application to Catalytic Reforming

摘要

Modeling of refining processes using metal-acid bifunctional catalysts involves an exponentially increasing number of species and reactions, which may rapidly exceed several thousands for complex industrial feedstocks. When building a model for such a process, a priori lumped kinetic models by chemical family do no longer meet the current requirements in terms of simulation details, predictive power and extrapolability. Due to the large number of elementary steps occurring in bifunctional catalysis, it would be quite unrealistic to manually build a detailed kinetic network of this scale. Hence, computer generation of the reaction network according to simple rules offer an elegant solution in such a case. Nevertheless, it remains difficult to determine and solve the kinetic equations, mainly due to the lack of analytical detail required by a detailed model. For several refining processes, however, reasonable assumptions on the equilibria between species allow to perform an a posteriori relumping of species, thus reducing the network size substantially while retaining a kinetic network between lumps that is strictly equivalent to the detailed network. This paper describes a network generation tool and the a posteriori relumping method associated with the single-event kinetic modeling methodology. This a posteriori relumping approach is illustrated for and successfully applied to the kinetic modeling of catalytic reforming reactions.