Moth-Flame Algorithm for Accurate Simulation of a Non-Uniform Electric Field in the Presence of Dielectric Barrier

Autor: M. Talaat, Abdulaziz S. Alsayyari, M. A. Farahat, Taghreed Said
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: IEEE Access, Vol 7, Pp 3836-3847 (2019)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2018.2889155
Popis: In this paper, a proposed moth-flame optimization (MFO) technique has been investigated for obtaining an accurate simulation of the non-uniform electric field represented by a needle-to-plane gap configuration. The needle electrode is connected to the high-voltage (HV) terminal, while the earthed terminal is connected to the plane electrode. In addition to the non-uniformity of the field, a transverse dielectric barrier has been presented and investigated along the gap with a different thickness and location. The MFO works to optimize the error given by a numerical equation published before for calculating this field problem in the presence of a transverse barrier. This numerical equation was based on a correction coefficient called $\left ({\beta }\right)$ , which is dependant on three values, relative permittivity, barrier location, and barrier thickness. The MFO is working to minimize the error given by $\beta $ using two new optimization factors in the $\beta $ equation. To ensure the accurate validation of MFO with a minimum error for field problem simulation, various artificial intelligence (AI) optimization techniques have been compared with the MFO obtained results. The comparative study shows that MFO is more effective, especially at 30% of the gap length from the HV electrode which represents the region of highly non-uniform field along the gap configuration. The numerical results of the field simulation that are held by different types of AI techniques are compared with those obtained from the accurate simulation results using the finite-element method. The value of the error between the numerical and simulation results shows that MFO is the most effective optimization techniques that can be used in the numerical equation to obtain the best value of the correction factor. With MFO, good agreement has been reached between the proposed numerical equation and the accurate simulation values of the electric field problem.
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