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Title

Utilization of Artificial Neural Network in optimizing square cascades for separation of tellurium ۱۳۰ isotope

Year: 1399
COI: IRCCE08_060
Language: EnglishView: 164
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Authors

Morteza Imani - Engineering Department, Shahid Beheshti University, G.C., P.O. Box: ۱۹۸۳۹۶۳۱۱۳, Tehran, Iran
Mohammademad Adelikhah - Engineering Department, Shahid Beheshti University, G.C., P.O. Box: ۱۹۸۳۹۶۳۱۱۳, Tehran, Iran
Mehdi Aghaie - Engineering Department, Shahid Beheshti University, G.C., P.O. Box: ۱۹۸۳۹۶۳۱۱۳, Tehran, Iran

Abstract:

Separation of stable isotopes has been considered today due to their widespread use. The separation of the isotope ۱۳۰Te is important for medical applications, and the production of radioisotopes up to high concentrations. In this paper, square cascade optimization to achieve ۹۹.۹% concentration of this isotope by the gray wolf optimization algorithm is presented. In the optimization, instead of solving nonlinear equations of concentration distribution in the cascade, a trained neural network is used to predict the value of the objective function. To train the neural network, ۴۰۰ randomly generated data from the simulation results were used. Predicting the objective function using a neural network leads to a ۹۸% reduction in optimization execution time. Using this method, the optimal cascade separates ۳۴۰۹ g of ۱۳۰Te with ۹۹.۹% concentration from ۱۰ kg of natural tellurium during one year.

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This Paper COI Code is IRCCE08_060. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/1197852/

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Imani, Morteza and Adelikhah, Mohammademad and Aghaie, Mehdi,1399,Utilization of Artificial Neural Network in optimizing square cascades for separation of tellurium ۱۳۰ isotope,8th International Conference on Chemistry, Chemical Engineering and Petroleum,Tehran,https://civilica.com/doc/1197852

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Type of center: دانشگاه دولتی
Paper count: 21,581
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