An artificial neural network based approach for estimating the density of liquid applied in gamma transmission and gamma scattering techniques.

Autor: Sang TT; Faculty of Physics, Ho Chi Minh City University of Education, Ho Chi Minh City, Viet Nam; Faculty of Physics and Engineering Physics, University of Science, Ho Chi Minh City, Viet Nam; Vietnam National University, Ho Chi Minh City, Viet Nam., Chuong HD; Nuclear Technique Laboratory, University of Science, Ho Chi Minh City, Viet Nam; Vietnam National University, Ho Chi Minh City, Viet Nam., Tam HD; Faculty of Physics, Ho Chi Minh City University of Education, Ho Chi Minh City, Viet Nam. Electronic address: tamhd@hcmue.edu.vn.
Jazyk: angličtina
Zdroj: Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine [Appl Radiat Isot] 2021 Mar; Vol. 169, pp. 109570. Date of Electronic Publication: 2020 Dec 24.
DOI: 10.1016/j.apradiso.2020.109570
Abstrakt: The study presents a new ANN-based approach to determine the density of a liquid applied in the gamma transmission and gamma scattering techniques. This approach used the Monte Carlo simulation combined with an artificial intelligence technique and experimental data to estimate the density of liquids. Two advantages of the proposed approach: (1) it is able to determine the density of a liquid by only measuring the gamma spectrum (transmission spectrum or scattering spectrum) without knowing the composition of the liquid, and (2) it is able to determine the density of a liquid when it is contained in a tube of various diameters. The artificial neural network model was trained by data obtained from simulation and then was used to predict the density of seven liquids with density in the range of 0.6 g cm -3 to 2.0 g cm -3 for the purpose of validating the proposed approach. For the gamma transmission technique, there are 25/28 samples with relative deviations between reference and predicted densities of less than 5%. The remaining three samples have deviations in the range from 5.2% to 6.3%. For the gamma scattering technique, there are 17/21 samples with a relative deviation of less than 5%. The remaining four samples have a deviation in the range from 5.2% to 6.9%. The results proved that the artificial intelligence technique combined with Monte Carlo based on gamma transmission and gamma scattering techniques is an effective approach for estimating the density of a liquid.
(Copyright © 2020 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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