Time Integration of the Chemistry of Combustion Processes in Industrial Furnaces, using Julia

Time Integration of the Chemistry of Combustion Processes in Industrial Furnaces, using Julia

Bachelor Thesis (2023)
Author(s)

J.J. Van der Meer (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Domenico Lahaye – Mentor (TU Delft - Mathematical Physics)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2023 Jochem Van der Meer
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Jochem Van der Meer
Graduation Date
07-07-2023
Awarding Institution
Delft University of Technology
Programme
['Applied Mathematics']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Combustion is and remains for the foreseeable future an essential chemical process. The physical and mathematical modelling of such processes can help to optimise the design and operation of combustion furnaces which is critical for fuel efficiency. Given the combined complexity and interaction of the gas flow dynamics and the reaction processes however, such modelling can become time consuming and demanding when it is comes to computational capacity. It is for this reason that alternative modelling and computational techniques are of interest. This paper serves as a thorough introduction to modelling this process using Chemical Reactor Networks (CRN) – which is known to be a relatively efficient model and computational approach.

It provides a step-by-step explanation of the CRN approach, as well as a hands-on implementation for a One-Step Mechanism, ie. a combustion process involving only a single stage oxidisation of the fuel. It also introduces the reader to the industry standard CHEMKIN format and the GRI 3.0 data-base, and investigates the possibility of incorporating the state-of-the-art GRI 3.0 database into Chemical Reactor Networks. Following on from this work it is recommended to validate CRN based results against experimental data and modelling results using different techniques such as Computational Fluid Dynamics to gauge both accuracy and computational efficiency.

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