Hydraulic and Separation Characteristics of an Industrial Gas Centrifuge Calculated with Neural Networks

Hydraulic and Separation Characteristics of an Industrial Gas Centrifuge Calculated with Neural Networks

Detaylı Bibliyografya
Parent link:AIP Conference Proceedings
Vol. 1938 : Isotopes: Technologies, Materials and Application (ITMA-2017).— 2018.— [020019, 5 p.]
Müşterek Yazar: Национальный исследовательский Томский политехнический университет Инженерная школа ядерных технологий Отделение ядерно-топливного цикла
Diğer Yazarlar: Butov V. G. Vladimir Grigorievich, Timchenko S. N. Sergey Nikolaevich, Ushakov I. A. Ivan Alekseevich, Golovkov N. Nikita, Poberezhnikov A. D. Andrey Dmitrievich
Özet: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
Baskı/Yayın Bilgisi: 2018
Konular:
электронный ресурс
труды учёных ТПУ
гидравлические характеристики
разделительные характеристики
газовые центрифуги
нейронные сети
бинарные смеси
разделение
изотопы
Online Erişim:https://doi.org/10.1063/1.5027226
Materyal Türü: Elektronik Kitap Bölümü
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=658000

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