TY - JOUR
T1 - Community Reaction Network Reduction for Constructing a Coarse-Grained Representation of Combustion Reaction Mechanisms
AU - Ji, Lin
AU - Li, Yue
AU - Wang, Jie
AU - Ning, An
AU - Zhang, Naixin
AU - Liang, Shengyao
AU - He, Jiyun
AU - Zhang, Tianyu
AU - Qu, Zexing
AU - Gao, Jiali
N1 - Publisher Copyright:
© 2022 American Chemical Society.
PY - 2022
Y1 - 2022
N2 - A community-reaction network reduction (CNR) approach is presented for mechanism reduction on the basis of a network-based community detection technique, a concept related to pre-equilibrium in chemical kinetics. In this method, the detailed combustion mechanism is first transformed into a weighted network, in which communities of species that have dense inner connections under the critical ignition conditions are identified. By analyzing the community partitions in different regions, we determine the effective functional groups and driving processes. Then, a skeletal model for the overall mechanism is deduced according to the network centrality data, including transition pathway identification and reaction-path flux. The CNR method is illustrated on the hydrogen autoignition system which has been extensively investigated, and a new reduced mechanism involving seven processes is proposed. Dynamics simulations employing the present CNR model show that the computed ignition time and distribution of major species on a wide range of temperature and pressure conditions are in accord with the experiments and results from other methods.
AB - A community-reaction network reduction (CNR) approach is presented for mechanism reduction on the basis of a network-based community detection technique, a concept related to pre-equilibrium in chemical kinetics. In this method, the detailed combustion mechanism is first transformed into a weighted network, in which communities of species that have dense inner connections under the critical ignition conditions are identified. By analyzing the community partitions in different regions, we determine the effective functional groups and driving processes. Then, a skeletal model for the overall mechanism is deduced according to the network centrality data, including transition pathway identification and reaction-path flux. The CNR method is illustrated on the hydrogen autoignition system which has been extensively investigated, and a new reduced mechanism involving seven processes is proposed. Dynamics simulations employing the present CNR model show that the computed ignition time and distribution of major species on a wide range of temperature and pressure conditions are in accord with the experiments and results from other methods.
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U2 - 10.1021/acs.jcim.2c00240
DO - 10.1021/acs.jcim.2c00240
M3 - Article
C2 - 35442657
AN - SCOPUS:85129236946
SN - 1549-9596
JO - Journal of Chemical Information and Modeling
JF - Journal of Chemical Information and Modeling
ER -