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المؤلفRoshani, Mohammadmehdi
المؤلفPhan, Giang T.T.
المؤلفJammal Muhammad Ali, Peshawa
المؤلفHossein Roshani, Gholam
المؤلفHanus, Robert
المؤلفDuong, Trung
المؤلفCorniani, Enrico
المؤلفNazemi, Ehsan
المؤلفKalmoun, El Mostafa
تاريخ الإتاحة2024-07-21T06:24:19Z
تاريخ النشر2021
اسم المنشورAlexandria Engineering Journal
المصدرScopus
المعرّفhttp://dx.doi.org/10.1016/j.aej.2020.11.043
الرقم المعياري الدولي للكتاب11100168
معرّف المصادر الموحدhttp://hdl.handle.net/10576/56832
الملخصThe main objective of the present research is to combine the effect of scale thickness on the flow pattern and characteristics of two-phase flow that is used in oil industry. In this regard, an intelligent nondestructive technique based on combination of gamma radiation attenuation and artificial intelligence is proposed to determine the type of flow pattern and gas volume percentage in two phase flow independent of petroleum pipeline's scale layer thickness. The proposed system includes a dual energy gamma source, composed of Barium-133 and Cesium-137 radioisotopes, and two sodium iodide detectors for recording the transmitted and scattered photons. Support Vector Machine was implemented for regime identification and Multi-Layer Perceptron with Levenberg Marquardt algorithm was utilized for void fraction prediction. Total count in the scattering detector and counts under photo peaks of Barium-133 and Cesium-137 were assigned as the inputs of networks. The results show the ability of presented system to identify the annular regime and measure the void fraction independent of petroleum pipeline's scale layer thickness.
اللغةen
الناشرElsevier
الموضوعFlow pattern
Multi-layer perceptron
Oil pipeline
Scale layer
Support vector machine
العنوانEvaluation of flow pattern recognition and void fraction measurement in two phase flow independent of oil pipeline's scale layer thickness
النوعArticle
الصفحات1955-1966
رقم العدد1
رقم المجلد60
dc.accessType Open Access


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