@article {2134,
	title = {Proposing a gamma radiation based intelligent system for simultaneous analyzing and detecting type and amount of petroleum by-products},
	journal = {Nuclear Engineering and Technology},
	year = {2020},
	type = {Research regular paper},
	abstract = {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 {\texttimes} 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.},
	author = {Mohammadmehdi Roshani and Giang Phan and Rezhna Hassan Faraj and Nhut-Huan Phan and Gholam Hossein Roshani and Enrico Corniani and Ehsan Nazemi}
}
