Stoichio-kinetic model discrimination and parameter identification in continuous microreactors - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Chemical Engineering Research and Design Année : 2016

Stoichio-kinetic model discrimination and parameter identification in continuous microreactors

Résumé

Kinetics is essential for chemical reactor modelling, in particular to reduce the inherent risks of extrapolation going along with scaling-up. Pharmaceutical industries are especially concerned. However, when chemical systems are very complex, development of good models may lead to prohibitively expensive and time consuming experiments. The aim of this paper is to describe an efficient experimental design strategy for discrimination of stoichio-kinetic models. The proposed methodology is based on model-based experimental design(optimal design), which uses information already acquired on models to determine the best conditions to implement a new experiment with the highest discrimination potential. The combination with microreactor technology is also proposed in this work. The whole procedure for model discrimination is firstly described in detail and then, applied to a numerical study case, consisting of a chemical synthesis carried out in a microreactor. The discrimination procedure efficiently leads to the determination of the single adequate model among the various potential models proposed before the implementation of the designed experiments.It is verified that the procedure does not depend on the set of preliminary experiments and is time-saving when compared to a classical factorial plan.
Fichier principal
Vignette du fichier
violet_17718.pdf (833.93 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03139553 , version 1 (12-02-2021)

Identifiants

Citer

Léo Violet, Karine Loubière, Alain Rabion, Robert Samuel, Stéphane Hattou, et al.. Stoichio-kinetic model discrimination and parameter identification in continuous microreactors. Chemical Engineering Research and Design, 2016, 114, pp.39-51. ⟨10.1016/j.cherd.2016.07.025⟩. ⟨hal-03139553⟩
29 Consultations
27 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More