A comprehensive kinetic modeling study of ethylene combustion with data uncertainty analysis. (1st September 2021)

• Record Type: Journal Article
• Authors: Wang, Hongxin; Slavinskaya, Nadezda; Kanz, Aziza; Auyelkhankyzy, Moldir; Gao, Yiting; Haidn, Oskar
• Is Part Of: Fuel. Volume 299(2021)
• Publication Date: 2021-09-01
• Subjects: Ethylene -- Chemical kinetic mechanism -- Uncertainty -- Auto-ignition -- Laminar flame; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2021.120833
• Languages: English
• ISSNs: 0016-2361

Abstract

Abstract: A revision and upgrade of the ethylene (C2 H4 ) oxidation kinetic sub-mechanism were carried as a next step in the optimization of the C<3 chemistry, which is a base for the upcoming PAH sub-model improvement. The main emphasis of the work was focused on the assessment of uncertainties of the thermo-kinetical and experimental data to involve that principally in the methodology of reaction model uncertainty. The principal targets of mechanism extension and update are: inspection of the reaction rate coefficients with accounting recently published pressure-dependent reactions and analysis of reaction paths related to the C2 H4 low-temperature oxidation and the formation of aromatic precursors. The experimental data (auto-ignition, premixed laminar flame speeds, and concentration profiles) with evaluated uncertainty and consistency were used for model optimization. The uncertainty bounds of the key reaction rate coefficients were evaluated from the statistical treatment of the published data, which provided constraints in the reaction rate parameters. The rate parameters of 57 reactions of C2 H4 and key intermediates were optimized. The revised reaction mechanism demonstrates a good agreement with the majority of the existing experimental data. Results of the sensitivity and rate of production analyses performed for several kinetic mechanisms from the literature were compared to visualize the variations and ambiguity in the importance of reaction paths and highlight the uncertainty problems in mechanism optimization and integration.