Hydraulic and Separation Characteristics of an Industrial Gas Centrifuge Calculated with Neural Networks; AIP Conference Proceedings; Vol. 1938 : Isotopes: Technologies, Materials and Application (ITMA-2017)

Podrobná bibliografie
Parent link:AIP Conference Proceedings
Vol. 1938 : Isotopes: Technologies, Materials and Application (ITMA-2017).— 2018.— [020019, 5 p.]
Korporativní autor: Национальный исследовательский Томский политехнический университет Инженерная школа ядерных технологий Отделение ядерно-топливного цикла
Další autoři: Butov V. G. Vladimir Grigorievich, Timchenko S. N. Sergey Nikolaevich, Ushakov I. A. Ivan Alekseevich, Golovkov N. Nikita, Poberezhnikov A. D. Andrey Dmitrievich
Shrnutí:Title screen
Single gas centrifuge (GC) is generally used for the separation of binary mixtures of isotopes. Processes taking place within the centrifuge are complex and non-linear. Their characteristics can change over time with long-term operation due to wear of the main structural elements of the GC construction. The paper is devoted to the determination of basic operation parameters of the centrifuge with the help of neural networks. We have developed a method for determining the parameters of the industrial GC operation by processing statistical data. In this work, we have constructed a neural network that is capable of determining the main hydraulic and separation characteristics of the gas centrifuge, depending on the geometric dimensions of the gas centrifuge, load value, and rotor speed.
Режим доступа: по договору с организацией-держателем ресурса
Jazyk:angličtina
Vydáno: 2018
Témata:
On-line přístup:https://doi.org/10.1063/1.5027226
Médium: Elektronický zdroj Kapitola
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=658000

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200 1 |a Hydraulic and Separation Characteristics of an Industrial Gas Centrifuge Calculated with Neural Networks  |f V. G. Butov [et al.] 
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330 |a Single gas centrifuge (GC) is generally used for the separation of binary mixtures of isotopes. Processes taking place within the centrifuge are complex and non-linear. Their characteristics can change over time with long-term operation due to wear of the main structural elements of the GC construction. The paper is devoted to the determination of basic operation parameters of the centrifuge with the help of neural networks. We have developed a method for determining the parameters of the industrial GC operation by processing statistical data. In this work, we have constructed a neural network that is capable of determining the main hydraulic and separation characteristics of the gas centrifuge, depending on the geometric dimensions of the gas centrifuge, load value, and rotor speed. 
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701 1 |a Timchenko  |b S. N.  |c physicist  |c Associate Professor of Tomsk Polytechnic University  |f 1980-  |g Sergey Nikolaevich  |3 (RuTPU)RU\TPU\pers\34267 
701 1 |a Ushakov  |b I. A.  |c physicist  |c engineer at Tomsk Polytechnic University  |f 1991-  |g Ivan Alekseevich  |3 (RuTPU)RU\TPU\pers\35544 
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