June 19, 2024
Gholam Hossein Roshani

Gholam Hossein Roshani

Academic rank: Associate professor
Education: Ph.D in Nuclear Engineering
Faculty: Faculty ofٍٍ Electrical Engineering


Proposing a gamma radiation based intelligent system for simultaneous analyzing and detecting type and amount of petroleum by-products
Type Article
Petroleum by-products;Artificial intelligence;Online monitoring;Dual energy; source;Poly-pipelines
Researchers M. M. Roshani، giang phan، rezhna hassan faraj، Nhut-Huan Phan، Gholam Hossein Roshani، Behrooz Nazemi، Enrico Corniani، Ehsan Nazemi


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.