Degree centrality of combustion reaction networks for analysing and modelling combustion processes
Authors: Ahmad Saylam, Kamal Hadj Ali, and Mustapha Fikri
Document type: Published journal article
Journal: Combustion Theory and Modelling
Publication details: Volume 24, Issue 3, pages 442–459, 2020
Published online:
Hosted version: Author Accepted Manuscript
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Independent technical summary
The study applies graph-theoretic degree centrality to detailed combustion reaction networks in order to identify principal species during a combustion process.
A principal or central species is defined through its connectivity within the reaction network at a particular simulation time step or computational cell. Species with larger degree-centrality values are interpreted as being more strongly connected to other species under the local thermochemical conditions.
The degree-centrality criterion is incorporated into an adjusted dynamic adaptive chemistry workflow. Principal species are identified locally and dynamically, and the resulting information is used with a directed-relation-graph mechanism-reduction approach.
The study also shows that a species classified as highly active or highly connected in a combustion reaction network is not necessarily identical to a species that must be retained for accurate predictive simulation. Network centrality and predictive importance therefore need to be distinguished.
Technical contribution
The work introduces a network-based diagnostic for analysing large combustion mechanisms and for supporting locally adaptive chemistry reduction. Its principal contribution is the explicit use of time- or cell-dependent reaction-network structure rather than a single globally fixed species ranking.
This approach is relevant to detailed-chemistry simulations in which the dominant thermochemical state and reaction pathways change across time, space or operating conditions.
Scope and application boundary
Degree centrality is a structural network measure. A large centrality value does not by itself prove that a species controls a target observable such as ignition delay, flame speed, pollutant formation or heat release.
Use of the method for a new fuel, mechanism, reactor or CFD problem requires validation against the intended operating domain and target quantities. The selected network definition, edge weighting, threshold criteria, reduction method and error controls can materially affect the resulting reduced chemistry.
Author Accepted Manuscript
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This is an Accepted Manuscript of an article published by Taylor & Francis in Combustion Theory and Modelling on 6 December 2019, available online at: https://doi.org/10.1080/13647830.2019.1699167 .
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Citation
Saylam, A., Hadj Ali, K., & Fikri, M. (2020). Degree centrality of combustion reaction networks for analysing and modelling combustion processes. Combustion Theory and Modelling, 24(3), 442–459. https://doi.org/10.1080/13647830.2019.1699167