Abstract
The process of plasma discharge in dielectric barrier discharge (DBD) plasma actuators can occur under two different regimes, namely uniform discharge regime and filamentary discharge regime. When the discharge becomes filamentary, the induced flow velocity and consequently, the performance of the actuator starts to decrease. Therefore, it is crucial to prevent the transition to filamentary discharge. In this paper, a model is developed to predict the formation of filamentary regime. For this purpose, the full factorial design of experiments is applied to investigate the effects of geometrical variables and electrical variables on induced flow velocity and power consumption. Then, artificial neural network (ANN) is employed to develop two models for velocity and power consumption. The models are validated both experimentally and statistically. The models show that every variable has a different effect on the start of the filamentary discharge. Finally, the Sequential quadratic programming (SQP) optimization algorithm have been applied to obtain critical value for each variable, in which the plasma discharge begins to become filamentary for any given set of other variables. The results show that the predicted data are in good agreement with the experimental values. Thus, the ANN model can effectively identify the start of filamentary regime.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.