Sequential model identification of reaction systems—The missing path between the incremental and simultaneous approaches

Abstract

Modeling chemical reaction systems is an important but complex task. The identified kinetic model must be able to explain all the underlying rate processes such as chemical reactions and heat and mass transfers. Traditionally, the modeling task is carried out using a simultaneous approach, which, for model prediction, requires having model candidates for all rate processes. The simultaneous approach leads to statistically optimal parameter estimates in the maximum‐likelihood sense, but it can be computationally expensive due to its combinatorial nature. The incremental approach, via either rates or extents, was introduced as an alternative to the simultaneous approach. It is characterized by the fact that each rate process can be modeled individually, that is, independently of the other rate processes. Hence, the incremental approach is computationally more attractive, however, at the price of not guaranteeing statistically optimal parameter estimates. This article proposes a novel sequential approach that combines the advantages of the incremental and simultaneous approaches. © 2019 American Institute of Chemical Engineers AIChE J, 65: 1211–1221, 2019