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Multi-objective optimization and loss analysis of multistage centrifugal pumps.

Authors :
Wu, TianXin
Wu, DengHao
Gao, ShuYu
Song, Yu
Ren, Yun
Mou, JieGang
Source :
Energy. Dec2023, Vol. 284, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

Multistage centrifugal pumps are widely used, and improving their efficiency is an indispensable part of energy conservation. A multi-objective optimization method combining experimental design, surrogate model, and optimization algorithm is proposed to re-design impellers and diffusers for improving pump performance. In the paper, nine variables were selected by the Plackett–Burman design with the head and minimum efficiency index (MEI) as the optimization objectives. The Gaussian process regression (GPR) was used to establish the surrogate model, and multi-objective optimization of the impeller and diffuser was carried out by non-dominated sorting genetic algorithm II (NSGA-II). The optimization results show that head and efficiency at the designed point 1.0 Q d increased by 8.8% and 2.8% respectively, and C MEI decreased by 1.34%. Meanwhile, the energy loss and flow characteristics of the original and optimization models were analyzed with the entropy production theory. Compared with the original model, the energy loss was reduced, and the flow in the interaction area between the impeller and diffuser becomes more stable for the optimized model. Moreover, the influencing mechanism of the pump geometrical parameters on the hydraulic performance and flow characteristics were discussed and analyzed. • A PB-GRP-GA multi-objective optimization method is proposed. • Internal energy losses were identified by Entropy Production Rate. • Influence mechanism of geometry on performance was revealed. • Higher MEI of pump model was achieved and verified by experiments. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03605442
Volume :
284
Database :
Academic Search Index
Journal :
Energy
Publication Type :
Academic Journal
Accession number :
173322018
Full Text :
https://doi.org/10.1016/j.energy.2023.128638