Browsing by Author "21ad45de978b95d8e60582710d7dd206"
Now showing items 1-3 of 3
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Application of neural network and time-domain feature extraction techniques for determining volumetric percentages and the type of two phase flow regimes independent of scale layer thickness
Alanazi, Abdullah; Alizadeh, Seyed Mehdi; Nurgalieva, Karina; Nesic, Slavko; Grimaldo Guerrero, John William; Abo-Dief, Hala M.; Eftekhari-Zadeh, Ehsan; nazemi, ehsan; Igor, Narozhnyy (MDPI Multidisciplinary Digital Publishing InstituteSwitzerland, 2022-01-27)One of the factors that significantly affects the efficiency of oil and gas industry equipment is the scales formed in the pipelines. In this innovative, non-invasive system, the inclusion of a dual-energy gamma source and ... -
Applying data mining and artificial intelligence techniques for high precision measuring of the two-phase flow’s characteristics independent of the pipe’s scale layer
Mayet, Abdulilah; Salama, Ahmed S.; Alizadeh, Mehdi; Nesic, Slavko; Grimaldo Guerrero, John William; Eftekhari-Zadeh, Ehsan; nazemi, ehsan; Iliyasu, Abdullah (MDPI Multidisciplinary Digital Publishing InstituteSwitzerland, 2022)Scale formation inside oil and gas pipelines is always one of the main threats to the efficiency of equipment and their depreciation. In this study, an artificial intelligence method method is presented to provide the flow ... -
Introducing the effective features using the particle swarm optimization algorithm to increase accuracy in determining the volume percentages of three-phase flows
Chen, Tzu-Chia; Alizadeh, Mehdi; Albahar, Marwan; Thanoon, Mohammed; Alammari, Abdullah; Grimaldo Guerrero, John William; nazemi, ehsan; Eftekhari-Zadeh, Ehsan (MDPI AGSwitzerland, 2023-01-11)What is presented in this research is an intelligent system for detecting the volume percentage of three-phase fluids passing through oil pipes. The structure of the detection system consists of an X-ray tube, a Pyrex galss ...