An incremental approach for the identification of stoichiometries and kinetics of complex homogeneous reaction systems is presented in this paper. The identification problem is decomposed into a sequence of subproblems. First, the reaction fluxes for the various species are estimated on the basis of balance equations and concentration measurements stemming from isothermal experiments. This task represents an ill-posed inverse problem that requires appropriate regularization. Using target factor analysis, suitable reaction stoichiometries can then be identified. In a further step, the reaction rates are estimated without postulating a kinetic structure. Finally, the kinetic laws, i.e., the dependencies of the reaction rates on concentrations, are constructed by selecting the best model structure from a set of model candidates. This incremental approach is shown to be both efficient and flexible for utilizing the available process knowledge. The methodology is illustrated on the industrially relevant acetoacetylation of pyrrole with diketene. ᭧

No abstract

No abstract

in Wiley InterScience (www.interscience.wiley.com).Despite their importance, rigorous process models are rarely available for reaction and especially multi-phase reaction systems. The high complexity of these systems, which is due to the superposed effects of mass transfer and intrinsic reaction, is the major barrier for the development of process models. A methodology that allows the systematic decomposition of mass transfer and chemical reaction and thus enables the efficient identification of multi-phase reaction systems is proposed in this work. The method is based on the so-called Incremental Identification Method, recently presented by Brendel et al., Chem Eng Sci. 2006;61:5404-5420. The method allows to easily test the identifiability of a system based on the available measurement data. If identifiability is given, the intrinsic reaction kinetics can be identified in a sound and numerically robust manner. These benefits are illustrated using a simulated 2-phase enzyme reaction system.