Designing a simple radiometric system to predict void fraction percentage independent of flow pattern using radial basis function

• Autorzy: Roshani G. H. , Nazemi E. , Shama F. , Imani M. A. , Mohammadi S.

Identyfikatory

DOI

10.24425/119560

• Języki publikacji: EN

Abstrakty

EN

The void fraction is one of the most important parameters characterizing a multiphase flow. The prediction of the performance of any system operating with more than single phase relies on our knowledge and ability to measure the void fraction. In this work, a validated simulation study was performed in order to predict the void fraction independent of the flow pattern in gas-liquid two-phase flows using a gamma ray ⁶⁰Co source and just one scintillation detector with the help of an artificial neural network (ANN) model of radial basis function (RBF). Three used inputs of ANN include a registered count under Compton continuum and counts under full energy peaks of 1173 and 1333 keV. The output is a void fraction percentage. Applying this methodology, the percentage of void fraction independent of the flow pattern of a gas-liquid two-phase flow was estimated with a mean relative error less than 1.17%. Although the error obtained in this study is almost close to those obtained in other similar works, only one detector was used, while in the previous studies at least two detectors were employed. Advantages of using fewer detectors are: cost reduction and system simplification.

Słowa kluczowe

EN

two-phase flow; gamma-ray attenuation; scintillation detector; void fraction; artificial neural network

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2018
• Tom: Vol. 25, nr 2
• Strony: 347--358
• Opis fizyczny: Bibliogr. 33 poz., rys., tab., wykr., wzory

Twórcy

autor

Roshani G. H.

• Kermanshah University of Technology, Electrical Engineering Department, Kermanshah, Iran

autor

Nazemi E.

• Nuclear Science and Technology Research Institute, Tehran, Iran

autor

Shama F.

• Islamic Azad University, Department of Electrical Engineering, Kermanshah Branch, Kermanshah, Iran

autor

Imani M. A.

• Kermanshah University of Medical Sciences, Medical Biology Research Centre, Kermanshah, Iran

autor

Mohammadi S.

• Islamic Azad University, Young Researchers and Elite Club, Kermanshah Branch, Kermanshah, Iran

Bibliografia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).