A Systematic Technique for Kinetic Parameter Estimation in Heterogeneous Solid Catalytic Reaction Networks with Applications
Abstract Estimating kinetic parameters in heterogeneous solid catalytic reaction networks is known to being a difficult task. This work aims at proposing a down-to-earth methodology to obtain kinetic parameters from numerical experiments. We present three techniques: a multivariable linear regression model, a stochastic metamodeling, and an optimized Kriging metamodel connected to a least-squares method. We consolidate the methodology in two different applications. The first one is a process with few components in two reactions from where it was possible to acquire the reaction rate equations that fitted literature data. The second one is a complex industrial reaction network. The results showed that even if the candidate proposed reaction rate equations do not fit the experiments, it is possible to construct a mathematical metamodel that conforms to the behavior of the components. Statistical tests showed that in both cases the proposed models successfully fit the experimental data..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:41 |
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| Enthalten in: |
The Korean journal of chemical engineering - 41(2024), 3 vom: 14. Feb., Seite 647-664 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Fernandes, Thalita [VerfasserIn] |
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| Links: |
Volltext [lizenzpflichtig] |
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| Themen: |
Heterogeneous reactions |
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| Anmerkungen: |
© The Author(s), under exclusive licence to Korean Institute of Chemical Engineers, Seoul, Korea 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| doi: |
10.1007/s11814-024-00104-6 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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SPR055103723 |
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| 520 | |a Abstract Estimating kinetic parameters in heterogeneous solid catalytic reaction networks is known to being a difficult task. This work aims at proposing a down-to-earth methodology to obtain kinetic parameters from numerical experiments. We present three techniques: a multivariable linear regression model, a stochastic metamodeling, and an optimized Kriging metamodel connected to a least-squares method. We consolidate the methodology in two different applications. The first one is a process with few components in two reactions from where it was possible to acquire the reaction rate equations that fitted literature data. The second one is a complex industrial reaction network. The results showed that even if the candidate proposed reaction rate equations do not fit the experiments, it is possible to construct a mathematical metamodel that conforms to the behavior of the components. Statistical tests showed that in both cases the proposed models successfully fit the experimental data. | ||
| 650 | 4 | |a Heterogeneous reactions |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Kinetic parameters |7 (dpeaa)DE-He213 | |
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| 650 | 4 | |a Kriging |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Machine learning |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Silva, Sidinei |4 aut | |
| 700 | 1 | |a Araújo, Antonio |0 (orcid)0000-0001-6373-5571 |4 aut | |
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