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Title: Automated Kinetic Models to Predict the Flame Speeds of Halocarbons
Previous generations of halocarbon refrigerants and flame suppressants cause intolerable levels of ozone depletion and global warming, motivating the search for environmentally-friendly alternatives, but the complex flammability of proposed halocarbon compounds has proven to be a challenge. Because the combustion chemistry of these greener halocarbon refrigerants and suppressants is very condition-dependent, the flammability of potential alternatives need to be screened under a variety of operational conditions prior to marketing and further product development. To facilitate this screening, kinetic models can be generated automatically in Reaction Mechanism Generator (RMG) to predict the flammability. RMG, a software package that automates the generation of detailed reaction mechanisms, has recently been extended to predict the chemical kinetics involved in halocarbon combustion. Full kinetic mechanisms with kinetic, thermodynamic, and transport properties generated from RMG are then evaluated with Cantera to predict laminar flame speeds under different reacting conditions. Recent work developed an RMG model of flame suppressant 2-BTP (CH2=CBrCF3) in methane flames. Current work has advanced RMG’s 2-BTP model to achieve improved quantitative agreement with experimental flame speeds. We also use RMG to generate models of binary halocarbon blends to determine the importance of “cross reactions” that are not accounted for through simple concatenation of individual combustion mechanisms. Flame speeds of RMG-generated blend models and blend models comprised of concatenated mechanisms are compared, along with experimental flame speeds found in literature. As demonstrated in current and previous work, automating the generation of full halocarbon kinetic models through RMG expedites screening for the next generation of environmentally-friendly refrigerants and suppressants, a task that would be both time- and cost-intensive if conducted without automation.  more » « less
Award ID(s):
1751720
PAR ID:
10442368
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
13th U.S. National Combustion Meeting
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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