A skeletal mechanism for n-dodecane/ammonia combustion and an open-source reaction scheme optimization tool
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2024-10-01
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Language
en
Pages
19
Series
Fuel, Volume 373
Abstract
The significance of ammonia (NH3) as an alternative fuel is increasing due to its potential as a carbon-free energy carrier. However, ammonia is known for its difficult combustion characteristics. One possible solution is to blend it with a high reactivity diesel fuel. In this work, n-dodecane has been chosen as the diesel surrogate. In order to investigate the combustion of ammonia blends with n-dodecane, a new skeletal chemical kinetic mechanism is developed. The proposed model consists of 75 species and 451 reactions, making it the most concise state-of-the-art mechanism. For the mechanism development, (a) experimental data from literature has been gathered, (b) 8 objectives have been defined for 17 experimental data sets, (c) sensitive reactions for the objectives have been identified with the open-source Cantera software, (d) the pre-exponential factors pertaining to 86 sensitive reactions have been optimized within the relevant uncertainty ranges, and (e) the JAYA algorithm has been utilized for the optimization. The optimized mechanism shows roughly a 70% improvement for the specified objectives, such as ignition delay times, laminar burning velocities, and species profiles, compared to the unoptimized starting mechanism. Additionally, very good agreement is observed with literature data for a wide range of operating conditions during validation. The proposed mechanism is accompanied by an open source graphical user interface for efficient mechanism optimization.Description
Publisher Copyright: © 2024 The Author(s)
Keywords
Ammonia, Chemical kinetic mechanism, Combustion, JAYA algorithm, n-dodecane, Optimization
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Citation
Kurumus, A T, Bhattacharya, A, Tamadonfar, P & Kaario, O 2024, ' A skeletal mechanism for n-dodecane/ammonia combustion and an open-source reaction scheme optimization tool ', Fuel, vol. 373, 132168 . https://doi.org/10.1016/j.fuel.2024.132168