Skip to Main content Skip to Navigation
Journal articles

Surrogate-based modeling techniques with application to catalytic reforming and isomerization processes

Abstract : In this paper, we first briefly survey the main surrogate model building approaches discussed in the literature considering also design of experiments strategies and dimensionality reduction procedures: we mainly focus on sub-set approaches and sampling strategies for constrained regression problems. We delineate a systematic methodology for surrogate modelling in presence of model constraints, such as non-negativity of the model responses. The main contribution of this paper is twofold: from one side we extend the principal component analysis framework to the case of constrained regression problem, from the other we propose a novel methodology which integrates the subset selection and the previous principal component regression procedure. Finally, we apply the two novel algorithms to two fundamental chemical processes in petroleum refinery, namely catalytic reforming and light naphtha isomerization. The numerical results show the comparisons between the two algorithms in terms of computational and accuracy trade-offs.
Document type :
Journal articles
Complete list of metadata

Cited literature [108 references]  Display  Hide  Download
Contributor : Catherine Belli Connect in order to contact the contributor
Submitted on : Friday, April 24, 2020 - 2:53:38 PM
Last modification on : Friday, January 15, 2021 - 11:18:07 AM


 Restricted access
To satisfy the distribution rights of the publisher, the document is embargoed until : 2022-02-06

Please log in to resquest access to the document





Luca Mencarelli, Alexandre Pagot, Pascal Duchêne. Surrogate-based modeling techniques with application to catalytic reforming and isomerization processes. Computers & Chemical Engineering, Elsevier, 2020, 135, pp.106772. ⟨10.1016/j.compchemeng.2020.106772⟩. ⟨hal-02553492⟩



Les métriques sont temporairement indisponibles