Data-driven chemical kinetic reaction mechanism for F-24 jet fuel ignition. (15th April 2021)

• Record Type: Journal Article
• Authors: Ryu, Je Ir; Kim, Keunsoo; Min, Kyungwook; Scarcelli, Riccardo; Som, Sibendu; Kim, Kenneth S.; Temme, Jacob E.; Kweon, Chol-Bum M.; Lee, Tonghun
• Is Part Of: Fuel. Volume 290(2021)
• Publication Date: 2021-04-15
• Subjects: Jet Fuel -- Jet A -- F-24 -- Genetic Algorithm -- ARLMech -- HyChem; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2020.119508
• Languages: English
• ISSNs: 0016-2361

Abstract

Abstract: A data-driven chemical kinetic mechanism for the military version of Jet A, F-24, is developed for numerical simulations of the ignition process. The main purpose of this study is to obtain a practical F-24 mechanism across wide temperature and equivalence ratio ranges, with a particular focus on the negative temperature coefficient and low temperature regions. The new mechanism (ARLMech-HC-F24) is based on the HyChem model of a similar fuel and optimized using a micro-genetic algorithm against an experimental ignition delay data set of the target fuel. The development and optimization processes include reaction selection, population creation, shuffled tournament implementation based on a merit function, and child-individual creation for the next generation. Several techniques and parameters are proposed to generate an accurate mechanism through an efficient process. The newly introduced data-driven mechanism based on these techniques shows better merit value convergence and represents the ignition behavior more accurately than that without the techniques. This practical mechanism is suitable for the numerical simulations of the F-24 or Jet A ignition problem, and the suggested strategies can be employed in similar problems of rate coefficients estimation.