Nuclear Engineering and Technology (Apr 2021)

Proposing a gamma radiation based intelligent system for simultaneous analyzing and detecting type and amount of petroleum by-products

  • Mohammadmehdi Roshani,
  • Giang Phan,
  • Rezhna Hassan Faraj,
  • Nhut-Huan Phan,
  • Gholam Hossein Roshani,
  • Behrooz Nazemi,
  • Enrico Corniani,
  • Ehsan Nazemi

Journal volume & issue
Vol. 53, no. 4
pp. 1277 – 1283

Abstract

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It is important for operators of poly-pipelines in petroleum industry to continuously monitor characteristics of transferred fluid such as its type and amount. To achieve this aim, in this study a dual energy gamma attenuation technique in combination with artificial neural network (ANN) is proposed to simultaneously determine type and amount of four different petroleum by-products. The detection system is composed of a dual energy gamma source, including americium-241 and barium-133 radioisotopes, and one 2.54 cm × 2.54 cm sodium iodide detector for recording the transmitted photons. Two signals recorded in transmission detector, namely the counts under photo peak of Americium-241 with energy of 59.5 keV and the counts under photo peak of Barium-133 with energy of 356 keV, were applied to the ANN as the two inputs and volume percentages of petroleum by-products were assigned as the outputs.

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