By Danielle Fretwell
The Francis College of Engineering Department of Mechanical and Industrial Engineering, invites you to attend the doctoral dissertation defense by Valentin Boutrouche on “Computational Modeling and Characterization a Self-sustained Atmospheric Pressure Glow Discharges.”
Candidate Name: Valentin Boutrouche
Defense Date: Monday, April 3, 2023
Time: 10 a.m. to noon
Location: Southwick 240. Those interested in attending virtually via Zoom should contact the student (Valentin_Boutrouche@student.uml.edu) and committee advisor (Juan_Trelles@uml.edu) at least 24 hours prior to the defense to request access to the meeting.
- Advisor Juan Pablo Trelles, Associate Professor, Mechanical and Industrial Engineering, UMass Lowell
- Juan Pablo Trelles, Associate Professor, Mechanical and Industrial Engineering, University of Massachusetts Lowell
- Maria Carreon, Assistant Professor, Department of Mechanical and Industrial Engineering, UMass Lowell
- Ofer Cohen, Associate Professor, Department of Physics and Applied Physics, UMass Lowell
- Noah Van Dam, Assistant Professor, Department of Mechanical and Industrial Engineering, UMass Lowell
The electrification of manufacturing processes using renewable energy is regarded as essential for sustainable development, by mitigating greenhouse gas emissions driving global warming while stimulating economic growth. Low-temperature atmospheric pressure plasma sources provide highly reactive environments at relatively mild operating conditions, making them appealing to an increasingly wider range of applications in materials processing, chemical synthesis, water treatment, and medicine. Among the different types of plasma sources, the Atmospheric Pressure Glow Discharge (APGD) is a relatively simple and versatile plasma source whose efficacy has been demonstrated in various applications. Stable APGD operation at high currents is generally challenging due to instabilities leading to glow-to-arc transition. However, controlled cathode cooling has been recently demonstrated as an effective approach to limit such transition. Moreover, APGDs depict the formation of self-organized patterns over the electrodes, which can affect discharge performance. This doctoral dissertation research consists of the computational modeling and characterization of a self-sustained APGD. The APGD model is comprised of the conservation equations for total mass, chemical species, momentum, thermal energy of heavy-species and of free electrons, and electric charge. The computational model is implemented in the transport problems solver, TPORT, which is based on a nonlinear Variational Multi-Scale Finite Element Method. The computational studies are based on previously published experimental investigations of a pin-to-plate APGD in helium within a 10 mm interelectrode gap. The computational simulations adopt a time-dependent and three-dimensional description of the evolution of the discharge. The validation of the model and numerical characterization of the APGD were carried over a range of currents from 4 to 40 mA. Simulation results show good agreement with the experimentally-measured voltage drop and the same trend but higher values of positive column temperature. The results reveal that, with increasing total current, the discharge transitions from depicting a monotonically increasing current density distribution away from the cathode to presenting a minimum near the center of the interelectrode gap. The model is subsequently used to investigate the stability of the APGD as a function of two control parameters: the total electric current across the discharge and the level of cooling of the cathode. Particularly, the range of cooling levels encompasses conditions spanning from a thermally-insulated cathode to a perfectly-cooled one. Moreover, the study includes establishing the role of ambipolar diffusion on the discharge’s properties. Simulation results reveal the spontaneous formation of ring patterns along the cathode for the high current and low cathode cooling cases. The computational models and results in this dissertation advance the effort towards the predictive modeling of AGPDs for improved understanding and design of plasma devices and processes.