Abstract
Global Pathway Selection/Analysis (GPSA) algorithm helps in analyzing the chemical kinetics of complex combustion systems by identifying important global reaction pathways that connects a source and a sink species. The present work aims to extend the application of GPSA to plasma assisted combustion systems in order to identify the dominant global pathways that govern the plasma and combustion kinetics at various conditions. The reaction cycles involving the excitation of nitrogen to its vibrational and electronic states and the subsequent de-excitation to its ground state are found to control the reactivity of plasma assisted systems. Provisions are made in the GPSA algorithm to capture the dominant reaction pathways and cycles of plasma assisted combustion (i.e., p-GPSA). Further, the analysis of plasma assisted ammonia combustion are presented as an example, which includes the results obtained using both the traditional path flux analysis and p-GPSA. The dominant pathways for the plasma assisted combustion of ammonia are identified along with the dominant excitation–de-excitation loops and their importance are ascertained and verified using path flux analysis.
Original language | English (US) |
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Title of host publication | AIAA SciTech Forum 2022 |
Publisher | American Institute of Aeronautics and Astronautics Inc, AIAA |
ISBN (Print) | 9781624106316 |
DOIs | |
State | Published - 2022 |
Event | AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022 - San Diego, United States Duration: Jan 3 2022 → Jan 7 2022 |
Publication series
Name | AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022 |
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Conference
Conference | AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022 |
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Country/Territory | United States |
City | San Diego |
Period | 1/3/22 → 1/7/22 |
Bibliographical note
Funding Information:S. Yang acknowledges the grant support from NSF CBET 2002635. P.N. Johnson acknowledges the graduate fellowship support from the Department of Mechanical Engineering at University of Minnesota. T.S. Taneja acknowledges the support from the UMII MnDrive Graduate Assistantship Award. The authors acknowledge Prof. Graham V. Candler and the Minnesota Supercomputing Institute (MSI) for the computational resources.
Publisher Copyright:
© 2022, American Institute of Aeronautics and Astronautics Inc.. All rights reserved.