Automated computational thermochemistry for butane oxidation: A prelude to predictive automated combustion kinetics

• Published in: Proceedings of the Combustion Institute Vol. 37; no. 1; pp. 363 - 371
• Main Authors: Keçeli, Murat, Elliott, Sarah N., Li, Yi-Pei, Johnson, Matthew S., Cavallotti, Carlo, Georgievskii, Yuri, Green, William H., Pelucchi, Matteo, Wozniak, Justin M., Jasper, Ahren W., Klippenstein, Stephen J.
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 2019
• Subjects: Ab Initio thermochemistry; Butane oxidation; Computational thermochemistry; Workflow; Workflow; Computational thermochemistry; Butane oxidation; Ab Initio thermochemistry
• ISSN: 1540-7489; 1873-2704
• DOI: 10.1016/j.proci.2018.07.113

Large-scale implementation of high level computational theoretical chemical kinetics offers the prospect for dramatically improving the fidelity of combustion chemical modeling. As a first step toward this goal, we developed a procedure for automatically generating the thermochemical data for combustion of an arbitrary fuel. The procedure begins by producing a list of combustion relevant species from a specification of the fuel and combustion conditions of interest. Then, for each element in the list of species, the procedure determines an internal coordinate z-matrix description of its structure, the optimal torsional configuration via Monte Carlo sampling, key rovibrational properties for that optimal geometry (including anharmonic corrections from torsional mappings and/or vibrational perturbation theory), and high level estimates of the electronic and zero-point energies via arbitrarily defined composite methods. This dataset is then converted first to partition functions, then to thermodynamic properties, and finally to NASA polynomial representations of the data. The end product is an automatically generated database of electronic structure results and thermochemical data including representations in a format appropriate for combustion simulations. The utility and functioning of this predictive automated computational thermochemistry (PACT) software package is illustrated through application to the automated generation of thermochemical data for the combustion of n-butane. Butane is chosen for this demonstration as its species list is of reasonably manageable size for debugging level computations, while still presenting most of the key challenges that need to be surmounted in the consideration of larger fuels. Furthermore, its low temperature chemistry is representative of that occurring with larger alkanes.