University of Bahrain
Scientific Journals

Optimization of Equatorial Dipole-Dipole Antenna Geometry Using Evolutionary Computing for Subsurface Imaging

Show simple item record Concepcion, Ronnie Baun, Jonah Jahara Janairo, Adrian Genevie Alipio, Melchizedek Relano, R-Jay Española, Jason Vicerra, Ryan Rhay Bandala, Argel Dadios, Elmer Dungca, Jonathan 2023-07-18T03:01:54Z 2023-07-18T03:01:54Z 2023-07-18
dc.identifier.issn 2210-142X
dc.description.abstract Efficient mapping of buried utilities requires vital subsurface imaging. However, traditional galvanic dipole antennas suffer from current leakage due to suboptimal geometry and necessitate destructive borehole methods. To address this, an evolutionary computing approach optimizes a single-pair equatorial dipole-dipole antenna for high-frequency capacitive ground coupling at 38 MHz with 1.2 m skin depth. By minimizing the induction number (β) to 0 and maximizing the electrostatic geometric factor (K) to 1, quasi-static condition is achieved. Multigene genetic programming constructs fitness functions using antenna geometry parameters: dipole spacing, dipole length, and plate elevation. The optimization utilizes a genetic algorithm (GA) and evolutionary strategy (ES) to find the optimal parameter combination. GA enables faster exploration, while ES facilitates faster exploitation. Results indicate that an optimized equatorial antenna design requires plate elevation to be ≤ 2.24% of the combined dipole spacing and length. The ES-optimized antenna exhibits minimal power loss, high efficiency, isotropic gain, and direct radiation of the electric field on the pipe surface. This study eliminates trial and error in dipole design by presenting an effective technique for antenna optimization in subsurface imaging. The proposed approach achieves the global best solution, improving the cost-effectiveness and efficiency of subsurface mapping. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.subject Antenna Geometry Optimization en_US
dc.subject Dipole Antenna en_US
dc.subject Machine Learning en_US
dc.subject Subsurface Imaging en_US
dc.subject Underground Imaging en_US
dc.title Optimization of Equatorial Dipole-Dipole Antenna Geometry Using Evolutionary Computing for Subsurface Imaging en_US
dc.volume 14 en_US
dc.issue 1 en_US
dc.pagestart 1 en_US
dc.pageend xx en_US
dc.contributor.authorcountry Philippines en_US
dc.contributor.authoraffiliation De La Salle University en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US

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