Examinando por Autor "ELDOSOUKY, A.M."

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Bio-inspired Computational Intelligence Metaheuristic-Based Optimization and Sensitivity Analysis Approach to Determine Techno-Economic Feasibility of Hydrogen Refueling Stations for Fuel Cell Vehicles
(Springer, 2025-04-11) OKONKWO, P.C.; NWOKOLO, S.C.; ALARIFI, S.S.; EKWOK, S.E.; ORJI, R.; UDO, S.O.; ELDOSOUKY, A.M.; BARHOUMI, E.M.; DAS, B.K.; GOMEZ-ORTIZ, D.; ABDELRAHMAN, K.; AKPAN, A.E:
This study presents a comprehensive economic and technological evaluation of renewable hybrid power systems for hydrogen refueling stations (HRS) in Nizwa, Oman, leveraging cutting-edge optimization algorithms to determine the most cost-effective and efficient hybrid energy syst configurations. Three hybrid energy systems of photovoltaic-wind turbine-battery (PV-WT-B), photovoltaic-wind-fuel cell-battery (PV-WT-FC-B), and wind turbine-battery (WT-B) were evaluated based on net present cost (NPC), levelized cost of energy (LCOE), and levelized cost of hydrogen (LCOH). The study employs advanced optimization techniques, including the Mayfly Algorithm, Genetic Algorithm, CUKO Search, Gray Wolf Optimizer (GWO), Constrained Particle Swarm Optimization (CPSO), Harmony Search (HS), and Flower Pollination Algorithm to determine the most viable hybrid energy system for the HRS in Nizwa. The results indicate that CPSO consistently achieves the lowest NPC, LCOE, and LCOH, whereas HS and GWO yield higher costs due to convergence inefficiencies Sensitivity analysis reveals a strong inverse correlation between PV capacity and cost metrics, highlighting the economic advantage of increased solar generation. Additionally, hybrid configurations integrating PV and wind turbine (P -WT-B, PV-WT-FC-B) significantly reduce NPC compared to WT-B, reinforcing the role of solar energy in optimizing economic costs. Furthermore, fuel cell integration (PV-WT-FC-B) imposes additional economic burdens, making PV-WT-B the most viable solution for HRS deployment in Oman. More so, the annual worth and return-on-investment analysis demonstrated that the PV-WT-B is the preferred energy system to meet the needs of the HRS in terms of investment. The findings underscore the importance of renewable energy fraction and capacity factor in energy economics, demonstrating that higher PV integration enhances sustainability and cost-efficien . This study provides a transformative framework for decarbonizing Oman’s transportation sector, offering insights into optimal hydrogen production strategies to advance the global clean energy transition.
Investigating the applicability of the Social Spider Optimization for the inversion of magnetic anomalies caused by dykes
(Elsevier, 2023-04) UBONG, C.B.; MBONU, C.C.; THOMPSON, C.E.; EKWOK, S.E.; AKPAN, A.E.; AKPABIO, I.; ELDOSOUKY, A.M.; ABDELRAHMAN, K.; ALZAHRANI, H.; GOMEZ-ORTIZ, David; THANH PHAM, L.
Dipping dykes are geologically important structures since they are very important structures for hydrogeological, geothermal and hydrocarbon research. Many methods have been introduced by researchers to interpret dykes from magnetic anomaly data, but each of these methods have limitations. Therefore, new techniques are constantly being developed to achieve better results. This study introduces a novel method based upon the Social Spider Optimization algorithm and tests the method using synthetic examples. The algorithm developed to decipher the source body properties, is presented in detail. The test data consists of synthetic anomalies corrupted by different levels of random noise and field anomalies from mining records in China and Turkey. The obtained results have showed that Social Spider Optimization is a reliable, stable and efficient tool for deciphering the physical properties of deep and shallow located dykes from magnetic data. In addition, the proposed method is recommended for inversion of other geophysics data such as self-potential and gravity data.