Accelerating Kinetic Parameter Identification by Extracting Information from Transient Data: A Hydroprocessing Study Case Article Swipe
Ngoc Yen Phuong Cao
,
Benoît Celse
,
Denis Guillaume
,
Isabelle Guibard
,
Joris Thybaut
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3390/catal10040361
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3390/catal10040361
Hydroprocessing reactions require several days to reach steady-state, leading to long experimentation times for collecting sufficient data for kinetic modeling purposes. The information contained in the transient data during the evolution toward the steady-state is, at present, not used for kinetic modeling since the stabilization behavior is not well understood. The present work aims at accelerating kinetic model construction by employing these transient data, provided that the stabilization can be adequately accounted for. A comparison between the model obtained against the steady-state data and the one after accounting for the transient information was carried out. It was demonstrated that by accounting for the stabilization, combined with an experimental design algorithm, a more robust and faster manner was obtained to identify kinetic parameters, which saves time and cost. An application was presented in hydrodenitrogenation, but the proposed methodology can be extended to any hydroprocessing reaction.
Related Topics
Concepts
Transient (computer programming)
Kinetic energy
Hydrodenitrogenation
Steady state (chemistry)
Work (physics)
Computer science
Experimental data
Identification (biology)
Biological system
Thermodynamics
Chemistry
Mathematics
Physics
Statistics
Catalysis
Physical chemistry
Hydrodesulfurization
Organic chemistry
Biology
Botany
Operating system
Quantum mechanics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/catal10040361
- https://www.mdpi.com/2073-4344/10/4/361/pdf?version=1585637910
- OA Status
- gold
- Cited By
- 5
- References
- 37
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3013952294
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3013952294Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/catal10040361Digital Object Identifier
- Title
-
Accelerating Kinetic Parameter Identification by Extracting Information from Transient Data: A Hydroprocessing Study CaseWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-03-26Full publication date if available
- Authors
-
Ngoc Yen Phuong Cao, Benoît Celse, Denis Guillaume, Isabelle Guibard, Joris ThybautList of authors in order
- Landing page
-
https://doi.org/10.3390/catal10040361Publisher landing page
- PDF URL
-
https://www.mdpi.com/2073-4344/10/4/361/pdf?version=1585637910Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://www.mdpi.com/2073-4344/10/4/361/pdf?version=1585637910Direct OA link when available
- Concepts
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Transient (computer programming), Kinetic energy, Hydrodenitrogenation, Steady state (chemistry), Work (physics), Computer science, Experimental data, Identification (biology), Biological system, Thermodynamics, Chemistry, Mathematics, Physics, Statistics, Catalysis, Physical chemistry, Hydrodesulfurization, Organic chemistry, Biology, Botany, Operating system, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2023: 1, 2021: 2Per-year citation counts (last 5 years)
- References (count)
-
37Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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