摘要
建立了基于NSGA-Ⅱ算法的叶片多目标水力优化设计系统,该系统以叶片的形状参数为优化变量,以能量性能和空化性能为目标函数,将NSGA-Ⅱ遗传算法引入作为优化工具以实现叶片的多目标优化设计.对某电站水轮机模型活动导叶的水力性能进行了优化设计,优化后导叶流道的进出口总压损失减小了26.97%,导叶表面上的最低静压力值上升了34.176%.结果表明,优化后的导叶不仅减小了流动损失,而且具有更好的空化性能.所提出的优化方法能以较少的变量控制叶片几何形状,且能有效分析各设计变量对目标函数的影响程度和范围,缩小优化问题的规模,得到满意的优化结果,可作为一种有效的水力机械叶片优化设计工具.
The multi-object optimization method for hydraulic machinery blades was proposed based on NSGA-Ⅱ algorithm.In the method,shape parameters of the blades were used as optimization variables,energy and cavitation performances were used as objective functions,and the multi-object optimization for the guide vane blade surface in a water power plant was carried out.The obtained results showed that the total pressure loss reduced by 26.97%,and the minimal pressure in guide vane increased by 34.176%.For the optimized guide vanes,the loss was reduced,and the cavitation performance was improved.It is concluded that the multi-object optimization method presented can control the blade profiles by using fewer variables and is available for both effectively analyzing the influence of every design variable on objective function and reducing the scale of the optimization question.So it is a valid optimization design tool for hydraulic machinery blades.
出处
《排灌机械工程学报》
EI
2010年第5期369-373,共5页
Journal of Drainage and Irrigation Machinery Engineering
基金
国家自然科学基金资助项目(50979091)
国家863计划项目(2009AA05Z202)
关键词
水轮机导叶
参数化
计算流体动力学
NSGA-Ⅱ算法
多目标优化设计
hydraulic turbine guide vane
parameterize
computational fluid dynamics
NSGA-Ⅱ algorithm
multi-object optimum design
