Name
Title | ||
|---|---|---|
Community Reaction Network Reduction for Constructing a Coarse-Grained Representation of Combustion Reaction Mechanisms |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1021/acs.jcim.2c00240 | JOURNAL OF CHEMICAL INFORMATION AND MODELING |
DocType | Volume | Issue |
Journal | 62 | 10 |
ISSN | Citations | PageRank |
1549-9596 | 0 | 0.34 |
References | Authors | |
0 | 10 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lin Ji | 1 | 0 | 0.34 |
| Yue Li | 2 | 6 | 10.29 |
| Jie Wang | 3 | 3 | 7.20 |
| An Ning | 4 | 0 | 0.34 |
| Naixin Zhang | 5 | 0 | 0.34 |
| Shengyao Liang | 6 | 0 | 0.34 |
| Jiyun He | 7 | 0 | 0.34 |
| Tianyu Zhang | 8 | 0 | 0.34 |
| Zexing Qu | 9 | 0 | 0.34 |
| Jiali Gao | 10 | 60 | 18.14 |