Explosive dynamics of bluff-body-stabilized lean premixed hydrogen flames at blow-off
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2022-09-19
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ArticleKAUST Department
Clean Combustion Research CenterComputational Reacting Flow Laboratory (CRFL)
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
Date
2020-09-19Online Publication Date
2020-09-19Print Publication Date
2020-09Embargo End Date
2022-09-19Submitted Date
2019-11-07Permanent link to this record
http://hdl.handle.net/10754/665336
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Two-dimensional direct numerical simulation (DNS) databases of bluff-body-stabilized lean hydrogen flames representative of complicated reactive–diffusive system are analysed using the combined approach of computational singular perturbation (CSP) and tangential stretching rate (TSR) to investigate chemical characteristics in blow-off dynamics. To assess the diagnostic approaches in flame and blow-off dynamics, Damköhler number and TSR variables are applied and compared. Four cases are considered in this study showing different flame dynamics such as the steadily stable mode, local extinction by asymmetric vortex shedding, convective blow-off and lean blow-out. DNS data points in positive explosive eigenvalue conditions were subdivided into four different combinations in TSR and extended TSR space and categorized in four distinct characteristic regions, such as kinetically explosive or dissipative and transport-enhanced or dissipative dynamics. The TSR analysis clearly captures the local extinction point in the complicated vortex shedding and allows an improved understanding of the distinct chemistry-transport interactions occurring in convective blow-off and lean blow-out events.Citation
Kim, Y. J., Song, W., Hernández Pérez, F. E., & Im, H. G. (2020). Explosive dynamics of bluff-body-stabilized lean premixed hydrogen flames at blow-off. Proceedings of the Combustion Institute. doi:10.1016/j.proci.2020.06.071Sponsors
This work was sponsored by King Abdullah University of Science and Technology (KAUST). Computational resources were provided by the KAUST Supercomputing Laboratory (KSL). The authors would like to thank Professor Mauro Valorani and his group at Sapienza University of Rome for providing the CSP analysis tools.Publisher
Elsevier BVAdditional Links
https://linkinghub.elsevier.com/retrieve/pii/S1540748920301267ae974a485f413a2113503eed53cd6c53
10.1016/j.proci.2020.06.071