A numerical investigation of cryogenic cavitation flow in LNG submerged pump

The cryogenic centrifugal submersible pump is one of the core equipment of the technology and serves to pressurize and transport the fluid with the centrifugal force generated from the impeller by rotation. Due to the structural characteristics of the working fluid and multi-stage, problems such as...

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Bibliographic Details
Published in:Journal of physics. Conference series 2022-04, Vol.2217 (1), p.12051
Main Authors: Suh, Jun-Won, Yang, Hyeon-Mo, Lee, Kyoung-Yong, Hong, Jin-Hee, Choi, Young-Seok
Format: Article
Language:English
Subjects:
Cavitation
Cavitation flow
Centrifugal force
Centrifugal pumps
Cryopumping
Fluid flow
Impellers
Internal flow
Low pressure
Numerical analysis
Performance prediction
Physics
Reliability analysis
Reynolds averaged Navier-Stokes method
Turbulence models
Working fluids
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Summary:The cryogenic centrifugal submersible pump is one of the core equipment of the technology and serves to pressurize and transport the fluid with the centrifugal force generated from the impeller by rotation. Due to the structural characteristics of the working fluid and multi-stage, problems such as cavitation and axial thrust negatively affect the life, noise, vibration, and performance of the pump, so it must be considered. For this reason, this research aimed to investigate a low-pressure LNG pump for an LNG fuel supply system with a general specific speed. The main components were designed based on the previous studies and CFturbo. The numerical analysis method was established and the performance prediction was conducted using commercial CFD packages. The three-dimensional Reynolds-averaged Navier-Stokes equations were discretized to analyze the internal flow field. First, the reliability of the turbulence model was proved through Hord’s experiment in the 0.357-inch ogive. Second, the steady and unsteady simulations were conducted between the single-passage and full-passage conditions in the inducer. Third, the corresponding analysis was investigated to identify problems with existing model features and find improvement directions.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2217/1/012051