Pankajakshan, Arun;
Bawa, Solomon Gajere;
Gavriilidis, Asterios;
Galvanin, Federico;
(2023)
Autonomous kinetic model identification using optimal experimental design and retrospective data analysis: methane complete oxidation as a case study.
Reaction Chemistry & Engineering
10.1039/d3re00156c.
(In press).
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Abstract
Automation and feedback optimization are combined in a smart laboratory platform for the purpose of identifying appropriate kinetic models online. In the platform, model-based design of experiments methods are employed in the feedback optimization loop to design optimal experiments that generate data needed for rapid validation of kinetic models. The online sequential decision-making in the platform, involving selection of the most appropriate kinetic model structure followed by the precise estimation of its parameters is done by autonomously switching the respective objective functions to discriminate between competing models and to minimise the parametric uncertainty of an appropriate model. The platform is also equipped with data analysis methods to study the behaviour of models within their uncertainty limits. This means that the platform not only facilitates rapid validation of kinetic models, but also returns uncertainty-aware predictive models that are valuable tools for model-based decision systems. The platform is tested on a case study of kinetic model identification of complete oxidation of methane on Pd/Al2O3 catalyst, employing a micro packed bed reactor. A suitable kinetic model with precise estimation of its parameters was determined by performing a total of 20 automated experiments, completed in two days.
| Type: | Article |
|---|---|
| Title: | Autonomous kinetic model identification using optimal experimental design and retrospective data analysis: methane complete oxidation as a case study |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1039/d3re00156c |
| Publisher version: | https://doi.org/10.1039/D3RE00156C |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10172788 |
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