摘要
将遗传算法与流场正问题计算相结合,构造轴流风机叶型自动优化设计软件。利用遗传算法可并行特质,实现局域网多CPU并行优化,大幅度缩短寻优耗时。应用所研制的软件,对一低压轴流风机5个型面进行优化设计、沿径向积叠构成三维叶片,并运用NUMECA软件对设计叶轮进行数值验算。结果表明:优化叶轮基本达到给定压升、流量并具有较高的全压效率和较大的稳定工作裕度。
A genetic algorithm, combined with direct flow computational method, is applied to develop the software used for the automatic optimization design of axial-flow fan profiles. With the ability of parallel computing, the genetic algorithm can minimize the optimization time substantially. The software is used to design profiles on five radial surfaces of a low-pressure axial-flow fan rotor, and the rotor is tested with NUMECA software, which shows high efficiency and large stability margin.
出处
《流体机械》
CSCD
北大核心
2013年第6期42-45,共4页
Fluid Machinery
关键词
轴流风机
正问题设计
数值优化
axial-flow fan
direct design method
numerical optimization
