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          Institute: MPI für Dynamik komplexer technischer Systeme     Collection: Physical and Chemical Foundations of Process Engineering     Display Documents



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ID: 611393.0, MPI für Dynamik komplexer technischer Systeme / Physical and Chemical Foundations of Process Engineering
Model-Based Optimal Design of Experiments for Determining Reaction Network Structures
Authors:Minh, D. H.; Wozny, G.; Brunsch, Y.; Behr, A.; Markert, J.; Hamel, C.; Seidel-Morgenstern, A.; Arellano-Garcia, H.
Language:English
Publisher:Elsevier
Place of Publication:Amsterdam, The Netherlands
Date of Publication (YYYY-MM-DD):2012
Title of Proceedings:11 International Symposium on Process Systems Engineering
Full Name(s) of Series Editor(s):Rafiqul Gani, E. Pistikopoulos
Start Page:705
End Page:709
Title of Series:Computer Aided Chemical Engineering
Volume (in Series):31
Full Name(s) of Series Editor(s):Rafiqul Gani, E. Pistikopoulos
Physical Description:1732 p.
Name of Conference/Meeting:11th International Symposium on Process Systems Engineering
Place of Conference/Meeting:Singapore, Singapore
(Start) Date of Conference/Meeting
 (YYYY-MM-DD):
2012-07-15
End Date of Conference/Meeting 
 (YYYY-MM-DD):
2012-07-19
Review Status:not specified
Audience:Experts Only
Abstract / Description:A new approach for optimal experimental design has been developed to support the work of chemists and process engineers in determining reaction kinetics of complex reaction networks. The methodology is applied on sub-networks of the hydroformylation process of 1-dodecene with a Biphephos-modified rhodium catalyst in a DMF-decane thermomorphic solvent system (TMS). The isomerization and hydrogenation sub-networks are systematically analyzed with respect to parameter estimability. They are determined in a sequential approach using model-based optimal experimental design via perturbations with respect to temperature and synthesis gas pressure, and subsequently used to build up the reaction network. The focus of this contribution is the parameter estimation procedure at the very early investigation stage where model uncertainties are high. Sensitivities of sensitive parameters are increased while others are suppressed, which are carried over from the estimated sub-networks or structurally more difficult to determine. This subsequently leads to more reliable parameter estimations.
Copyright © 2012 Elsevier B.V. All rights reserved. [accessed August 17th 2012]
Free Keywords:optimal experiment design; model discrimination; parameter estimation; hydroformylation; 1-dodecene
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Andreas Seidel-Morgenstern
Affiliations:MPI für Dynamik komplexer technischer Systeme/Physical and Chemical Foundations of Process Engineering
External Affiliations:Technische Universität Berlin
Institut für Prozess- und Verfahrenstechnik
Berlin, Germany

Technische Universität Dortmund
Lehrstuhl für Technische Chemie A
Dortmund, Germany

Otto-von-Guericke-Universität
Institut für Verfahrenstechnik,
Magdeburg
Identifiers:ISBN:978-0-444-59505-8
URL:http://dx.doi.org/10.1016/B978-0-444-59507-2.50133...
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