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Study on flow field characteristics of regulator in uranium enrichment centrifugal cascade

  • Er-bing Shi EMAIL logo , Qing-cheng Zeng , Jun Che , Hang Li , Zheng-guo Cui and Jia-qi Han
Published/Copyright: March 4, 2025
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Abstract

The regulator is one of the most important equipment in the uranium enrichment centrifugal cascade, of which the main function is to automatically control the pressure and flowrate within the certain range. The regulator must operate under a low-pressure vacuum condition. Compression and expansion as well as the transonic and supersonic flow of gaseous Uranium hexafluoride (UF6) in the low-pressure vacuum are drastic and complicated, which makes it difficult and significant to analyze the flow field in the regulator. The computational fluid dynamics (CFD) technique has been introduced in the analysis of complex flow in recent years. The flow field characteristics in the regulator of six opening ratio under high and low inlet pressure conditions were studied based on the flow field numerical simulation. The transonic and supersonic flow field characteristics as well as the flow separation (boundary layer separation) were studied utilizing standard k-ε turbulence model. The results show that the velocity and Mach number oscillate when the opening ratio is Greater than or equal to 40 % for high inlet pressure condition, which indicates the opening ratio range of stable flow. The flow separation near the boundary layer emerges downstream of the nozzle at 20 % opening ratio for both high and low inlet pressure conditions. The regulator has piecewise linear characteristic. The research can provide guidance for design and application of the regulator in the uranium enrichment centrifugal cascade.


Corresponding author: Er-bing Shi, CNNC No. 7 Research and Design Institute Co., Taiyuan 030000, China, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interests: The author states no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Received: 2024-11-02
Accepted: 2025-02-10
Published Online: 2025-03-04
Published in Print: 2025-06-26

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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