Aku, Michael;
Bawa, Solomon Gajere;
Pankajakshan, Arun;
Lee, Lauren Ye Seol;
Galvanin, Federico;
(2025)
Optimizing Methane Conversion in a Flow Reactor System Using Bayesian Optimization and Model-Based Design of Experiments Approaches: A Comparative Study.
In:
Systems and Control Transactions.
(pp. pp. 1228-1236).
PSE Press
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Abstract
Reaction processes require optimization to enhance key performance indicators (KPIs) such as yield, conversion, and selectivity. Techniques like Bayesian Optimization (BO), Model-Based Design of Experiments (MBDoE), and Goal-Oriented Optimal Experimental Design (GOOED) play pivotal roles in achieving these objectives. BO efficiently explores the design space to identify optimal conditions, while MBDoE maximizes the information gain by reducing kinetic model uncertainty. In contrast, GOOED focuses solely on maximizing the KPIs without considering the system uncertainty, identifying reactor conditions in the design space guaranteeing optimal performance. This study compares BO, MBDoE, and GOOED in optimizing methane oxidation in an automated flow reactor. Performance is assessed based on optimal methane conversion, reduced system uncertainty and minimal experimental efforts to achieve maximum conversion. BO quickly identifies high-conversion conditions, MBDoE minimizes experimental runs while providing insights into parameter sensitivities, and GOOED prioritizes conversion efficiency. The findings highlight trade-offs between convergence speed, robustness, and information gain, providing valuable insights for designing data-driven, physics-informed experiments..
| Type: | Proceedings paper |
|---|---|
| Title: | Optimizing Methane Conversion in a Flow Reactor System Using Bayesian Optimization and Model-Based Design of Experiments Approaches: A Comparative Study |
| Event: | The 35th European Symposium on Computer Aided Process Engineering |
| Dates: | 6 Jul 2025 - 9 Jul 2025 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.69997/sct.148204 |
| Publisher version: | https://doi.org/10.69997/sct.148204 |
| Language: | English |
| Additional information: | © 2025 by the authors. Licensed to PSEcommunity.org and PSE Press. This is an open access article under the creative commons CC-BY-SA licensing terms. Credit must be given to creator and adaptations must be shared under the same terms. See https://creativecommons.org/licenses/by-sa/4.0/ |
| Keywords: | Bayesian Optimization, Model-Based Design of Experiments, Methane Conversion |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10211086 |
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