545465 An Automatically Generated Pressure-Dependent PAH Mechanism for Rich-Methane Combustion

Wednesday, June 5, 2019
Texas Ballroom Prefunction Area (Grand Hyatt San Antonio)
Te-Chun Chu1, Zachary J. Buras1, Patrick Oßwald2, Mengjie Liu1, Mark J. Goldman1 and William H. Green1, (1)Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, (2)Institute of Combustion Technology, German Aerospace Center (DLR), Stuttgart, Germany

The need for an accurate model for rich-methane combustion relevant to High Temperature Pyrolysis and partial oxidation processes has grown as the supply of natural gas has increased in recent years. In addition to the chemistry of forming dominant products (CO and H2) or valuable chemicals (acetylene and ethylene), the model must accurately predict formation of undesired incomplete combustion byproducts, e.g. polycyclic aromatic hydrocarbons (PAH) and soot. To meet this need, a detailed chemical mechanism has been generated in this work focusing on high-temperature combustion of rich-methane up to three-ring PAH formation.

The Reaction Mechanism Generator (RMG) software generated a pressure-dependent chemical mechanism for specified conditions to investigate chemistry in rich-methane combustion. Pressure-dependent rate coefficients are estimated by RMG using master equation methods from potential energy surfaces computed from first-principles. The accuracy of the new chemical kinetic model is tested against the experiments done by Köhler et al.,1 where major species along with intermediates and aromatics were measured by molecular beam mass spectrometry in a flow reactor between 1100-1800 K. The model predictions are in excellent agreement with the experimental results. Major species are predicted within the experimental uncertainties at various conditions. Acetylene, which is over-predicted by existing mechanisms like GRI 3.02 and USC-II3, is predicted more accurately by the new mechanism. The predictions of benzene, indene, naphthalene, and acenaphthylene are highly accurate in terms of both magnitude and temperature dependence, which is ideal for further modeling of soot formation. This new model, which can predict detailed natural gas chemistry of industrial relevance from first-principles calculations, and the process to develop it are valuable resources for the growing natural gas industry.

1. Köhler, M. et al., Chemical Engineering Science 2016, 139, 249-260.

2.Gregory P. Smith et al., GRI-Mech 3.0. http://www.me.berkeley.edu/gri_mech/.

3. Hai Wang, X. Y. et al., USC Mech Version II. High-Temperature Combustion Reaction Model of H2/CO/C1-C4 Compounds. 2007.

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