Open AccessAutomatic Optimization of Vertical Long-shaft Fire Pump Overload Based on Particle Swarm Optimization Algorithm
Author(s) -
Jinfeng Zhang,
Zhijun Yang,
Liangqing Lai,
Haiqing Song,
Chengming Jing
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1081/1/012017
Subject(s) - particle swarm optimization , impeller , latin hypercube sampling , global optimization , engineering , computer science , algorithm , mechanical engineering , mathematics , statistics , monte carlo method
As a typical large-flow high-head pump, the vertical long-axis fire pumps have the advantages of rapid startup, superior structure, and strong applicability in multiple occasions. In order to shorten the non-overload optimization cycle, CFturbo, ICEM and CFX are integrated by writing batch processing commands to achieve automatic multi-load and no-load optimization of vertical long-axis fire pumps based on Isight’s multi-disciplinary optimization platform. With the objective of achieving the non-overload characteristics of vertical long-axis fire pumps, the optimal Latin hypercube design is used to spatially sample the design variables of the impeller. After sampling, the particle swarm optimization (PSO) algorithm is used to optimize the design. The results show that, vertical long-axis fire pumps achieve non-overload characteristics within 1.5 Q 0 after optimization, while the head and efficiency at the rated operating point are almost unchanged.