期刊论文详细信息
Brazilian Journal of Chemical Engineering
Analysis and optimization of gas-centrifugal separation of uranium isotopes by neural networks
S.c.p. Migliavacca2  C. Rodrigues2  C.a.o. Nascimento1 
[1],Instituto de Pesquisa Energética e Nucleares
关键词: neural networks;    isotope separation;    gas centrifugation;    optimization;    uranium isotopes;    modeling;   
DOI  :  10.1590/S0104-66322002000300005
来源: SciELO
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【 摘 要 】
Neural networks are an attractive alternative for modeling complex problems with too many difficulties to be solved by a phenomenological model. A feed-forward neural network was used to model a gas-centrifugal separation of uranium isotopes. The prediction showed good agreement with the experimental data. An optimization study was carried out. The optimal operational condition was tested by a new experiment and a difference of less than 1% was found.
【 授权许可】

CC BY   
 All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License

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