Moth-Flame Algorithm for Accurate Simulation of a Non-Uniform Electric Field in the Presence of Dielectric Barrier
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 te...
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| Format: | Article |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8587247/ |
| _version_ | 1818619180184764416 |
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| author | M. Talaat Abdulaziz S. Alsayyari M. A. Farahat Taghreed Said |
| author_facet | M. Talaat Abdulaziz S. Alsayyari M. A. Farahat Taghreed Said |
| author_sort | M. Talaat |
| collection | DOAJ |
| description | 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 <inline-formula> <tex-math notation="LaTeX">$\left ({\beta }\right)$ </tex-math></inline-formula>, which is dependant on three values, relative permittivity, barrier location, and barrier thickness. The MFO is working to minimize the error given by <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> using two new optimization factors in the <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> 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. |
| first_indexed | 2024-12-16T17:33:23Z |
| format | Article |
| id | doaj.art-935da854d06a4d6693d8cb181875a301 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T17:33:23Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-935da854d06a4d6693d8cb181875a3012022-12-21T22:22:52ZengIEEEIEEE Access2169-35362019-01-0173836384710.1109/ACCESS.2018.28891558587247Moth-Flame Algorithm for Accurate Simulation of a Non-Uniform Electric Field in the Presence of Dielectric BarrierM. Talaat0https://orcid.org/0000-0001-5976-7810Abdulaziz S. Alsayyari1M. A. Farahat2Taghreed Said3Electrical Power and Machines Department, Faculty of Engineering, Zagazig University, Zagazig, EgyptComputer Engineering Department, College of Engineering, Shaqra University, Dawadmi, Saudi ArabiaElectrical Power and Machines Department, Faculty of Engineering, Zagazig University, Zagazig, EgyptElectrical Engineering and Computers Department, Higher Technological Institute, 10th of Ramadan City, EgyptIn 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 <inline-formula> <tex-math notation="LaTeX">$\left ({\beta }\right)$ </tex-math></inline-formula>, which is dependant on three values, relative permittivity, barrier location, and barrier thickness. The MFO is working to minimize the error given by <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> using two new optimization factors in the <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> 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.https://ieeexplore.ieee.org/document/8587247/Artificial intelligencemoth-flame optimization (MFO)particle swarm optimization (PSO)genetic algorithm (GA)dielectric barrierelectric field simulation |
| spellingShingle | M. Talaat Abdulaziz S. Alsayyari M. A. Farahat Taghreed Said Moth-Flame Algorithm for Accurate Simulation of a Non-Uniform Electric Field in the Presence of Dielectric Barrier IEEE Access Artificial intelligence moth-flame optimization (MFO) particle swarm optimization (PSO) genetic algorithm (GA) dielectric barrier electric field simulation |
| title | Moth-Flame Algorithm for Accurate Simulation of a Non-Uniform Electric Field in the Presence of Dielectric Barrier |
| title_full | Moth-Flame Algorithm for Accurate Simulation of a Non-Uniform Electric Field in the Presence of Dielectric Barrier |
| title_fullStr | Moth-Flame Algorithm for Accurate Simulation of a Non-Uniform Electric Field in the Presence of Dielectric Barrier |
| title_full_unstemmed | Moth-Flame Algorithm for Accurate Simulation of a Non-Uniform Electric Field in the Presence of Dielectric Barrier |
| title_short | Moth-Flame Algorithm for Accurate Simulation of a Non-Uniform Electric Field in the Presence of Dielectric Barrier |
| title_sort | moth flame algorithm for accurate simulation of a non uniform electric field in the presence of dielectric barrier |
| topic | Artificial intelligence moth-flame optimization (MFO) particle swarm optimization (PSO) genetic algorithm (GA) dielectric barrier electric field simulation |
| url | https://ieeexplore.ieee.org/document/8587247/ |
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