Research on cooperative optimization of multiphase pump impeller and diffuser based on adaptive refined response surface method
Multiphase pumps play an important role in the exploitation of natural gas hydrate. Compared with ordinary pumps, they can handle fluids with higher gas volume fraction (GVF). Therefore, it is important to improve the performance of the pump under high GVF. A model pump is designed based on the desi...
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Published in: | Advances in mechanical engineering Vol. 14; no. 1 |
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Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
Published: |
London, England
SAGE Publications
01-01-2022
Sage Publications Ltd SAGE Publishing |
Subjects: | |
Online Access: | Get full text |
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Summary: | Multiphase pumps play an important role in the exploitation of natural gas hydrate. Compared with ordinary pumps, they can handle fluids with higher gas volume fraction (GVF). Therefore, it is important to improve the performance of the pump under high GVF. A model pump is designed based on the design theory of axial flow pump and centrifugal pump inducer. The hydraulic performance of the model pump is verified by numerical simulation and experiment. The Sparse Grid method is applied to the design of experiment (DOE), and three different adaptive refined response surface methods (RSM) are applied to the build the approximate model. Refinement points and verification points are used to improve and verify the precision of the response surface, respectively. The model with high precision and high computational efficiency is obtained through comparison and analysis. The multi-objective optimization of the optimal response surface model is carried out by MOGA (Multi-Objective Genetic Algorithm) method. The pressure increment of the optimized model is increased by 38 kPa. The efficiency is significantly improved under large mass flow conditions. The hydraulic performance of the optimized model is compared with that of the basic model. And the reasons that affect the performance of the multiphase pump are analyzed. |
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ISSN: | 1687-8132 1687-8140 |
DOI: | 10.1177/16878140211072944 |