对轴流压气机叶型流动损失和落后角模型进行了系统归纳与整理,并将其与逐排基元叶片模型相结合,建立了计算多级轴流压气机特性工程方法,并进一步将其与锦标赛式遗传算法相结合,发展了一种新的多级轴流压气机变几何扩稳多目标优化算法,并成功应用于某型8级轴流压气机扩稳分析,取得了明显成效.与单目标优化相比,多目标扩稳调节能明显改善压气机性能,其最大效率提高了近4个百分点,且静叶安装角调节范围也明显减小.
Practicable loss and deviation models to both transonic and subsonic axial compressors are determined by using detailed investigation.They are combined with the blade row-by-blade row cascade model.A method for calculating off-design performance of multi-stage axial compressors is developed,based on those models.The two-branch tournament genetic algorithm for multi-objective design is then used to optimize stator vane stagger setting.The methodology has been incorporated into computer program and validated using data from a eight-stage transonic axial compressor.Results have demonstrated that variable stator stagger setting through multi-objective optimization is a powerful method to rematch stages which can be used to enlarge aerodynamic stability range of multi-stage compressors.Compared to single-objective optimization,it is also remarkable that four 4 percent increment in compressor efficiency is obtained from Pareto optimal solution using multi-objective optimization.
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