Streamer Discharge Simulation for Plasma-Assisted Combustion
Year: 2025
Type: dissertation
Abstract: A common and successful method to achieve atmospheric pressure fuel-air plasma-assisted combustion is through repetitive ns pulsed discharges and dielectric-barrier discharge. The transient phase in these discharges is dominated by transport influenced by strong space charges produced by ionization fronts, this can be best represented by the streamer model. The function of non-thermal plasma in these discharges is to excite the species in the fuel-air mixture to produce radicals which accelerate the chemical conversion reactions which directly lead to temperature rise, ultimately culminating in ignition. Therefore, the characterization of the streamer and its energy partitioning is essential to developing a predictive model. In this thesis a numerical platform is developed to study important characteristics of streamers that influence combustion and develop a set of macroscopic parameters useful for combustion. We examined plane-plane and point-plane electrode geometries for hydrogen-air, methane-air, and ammonia-air mixtures. The results showed that radical production efficiency for a fixed applied field is nearly independent of time and the radical density production depends only on the electrical energy density coupled to the plasma. We compared the electric field and energy density of the streamer model for different electrode geometries and the impact on radical production. We also compared the results of the streamer model to the zero-dimensional uniform field Townsend-like discharge, and our results showed a significant difference. Zero-dimensional combustion models were developed to study the effect of streamer radical production on the ignition characteristics of hydrogen-air and methane-air fuel mixtures. The results showed a strong dependence of the electrical energy density on the ignition delay.
DOI: 10.25777/atbb-vx91
Author: Reyes, Stuart Jairo
Institution: Old Dominion University
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6908422357
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