Recently Reaction Mechanism Generator (RMG) was released as an open source software http://sourceforge.net/projects/rmg/. This version of RMG is able to generate mechanisms with high pressure rate rules using the rate-based mechanism generation algorithm [3]. The rules to generate thermochemistry and rate rules for reactions are stored in a easily expandable and modifiable database. Capability to perform sensitivity analysis and reaction flux analysis is also included in this version of RMG so that the user can easily understand and analyze the mechanisms generated by RMG. Since this last release, work has been done on RMG so that it can generate pressure dependent networks. The pressure dependent rate constants calculated using QRRK theory and reaction rates are given in the chebyshev format. This can be important for generating mechanisms at higher temperatures (> 800 K) [4]. The algorithm used to generate pressure dependent networks is based on the activated species algorithm[2]. A brief description of the algorithm will be presented. Experiments were performed by Charles McEnally et al. in which hexadiene doped (2000 ppm) methane flames were examined and C3 to C12 hydrocarbon concentrations were measured on the centerline of the flame. RMG was used to generate a mechanisms for the decomposition of each of the 9 hexadienes used in this study. Sensitivity analysis was used to identify imporatnt reactions and species in each of these mechanisms. The thermochemistry of these important species and transition states were evaluated using high level ab-initio calculations. The pressure dependent rates of important pressure dependent networks were evaluated using master chemical equation approach. The undoped methane flame used in this study was modeled by Bennett et al. [1] and the results from this study were used to solve the concentration of hexadiene and its primary products perturbatively. The methodology and results used will be presented in detail. The new open-source software described allows any one to rapidly generate quantitatively accurate models for pyrolytic chemistry and ongoing work to generate accurate models for other types of chemistry will be briefly outlined.

References

[1] B. A. V. Bennett, C. S. McEnally, L. D. Pfefferle, M. D. Smooke, and M. B. Colket. Computational and experimental study of axisymmetric coflow partially premixed ethylene/air flames. Combustion and Flame, 127:2004- 2022, Oct. 2001.

[2] D. M. Matheu, T. A. Lada, W. H. Green, A. M. Dean, and J. M. Grenda. Rate-based screening of pressure-dependent reaction networks. Computer Physics Communications, 138:237-249, Aug. 2001.

[3] R. Susnow, A. Dean, W. Green, P. Peczak, and L. Broadbelt. Rate-based construction of kinetic models for complex systems. Journal of Physical Chemistry A, 101(20):3731-3740, 1997.

[4] B. Wong, D. Matheu, and W. Green. Temperature and molecular size dependence of the high-pressure limit. Journal of Physical Chemistry A, 107(32):6206-6211, 2003

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