Global Pathway Analysis of Plasma Assisted Ammonia Combustion

Praise Noah Johnson, Taaresh Sanjeev Taneja, Suo Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish (US)
Title of host publicationAIAA SciTech Forum 2022
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624106316
DOIs
StatePublished - 2022
EventAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022 - San Diego, United States
Duration: Jan 3 2022Jan 7 2022

Publication series

NameAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022

Conference

ConferenceAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022
Country/TerritoryUnited States
CitySan Diego
Period1/3/221/7/22

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.

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