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基于自由变形型面的轴流涡轮叶片离散伴随优化

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针对涡轮机械单级气动优化问题,发展了基于自由变形型面技术的离散伴随CFD优化方法。对二维涡轮静叶与涡轮单级进行了优化分析,给出了叶型在约束条件下的最优形状。静叶优化得到的叶片前缘半径显著减小,厚度减小。在优化前后总压恢复系数减小了 12。44%,而流动出口角约束在-74。66°,改变幅度为0。047%。对涡轮单级优化问题,考虑旋转效应后的动叶弯度提高,总效率提高了 0。79%。而流动出口角约束在-70°,改变幅度为0。068%。结果表明所提方法在涡轮级气动性能优化问题上的有效性。与传统的有限差分方法,离散伴随方法对单级优化时间仅为有限差分的3%。
Discrete-adjoint optimization of axial turbine blade using free-form deformation
A discrete-adjoint CFD method based on the free-form deformation was developed for aerodynamic performance optimization of the axial turbine stage.Optimization analysis of the two-dimensional turbine stator and single turbine stage was carried out,and the optimal shape of the blade shape under the constraints was given.In the stator blade optimization,the leading edge radius and thickness of the blade obtained were significantly reduced.The total pressure recovery coeffiicient decreased by 12.44%after optimization,while the flow outlet angle was constrained to-74.66° with the variance of 0.047%during the optimization.For the single-stage turbine optimization problem,the camber of the rotor blade was enhanced,and the total efficiency was improved by 0.79%considering the rotation effect.The constraint condition lied in the flow outlet angle with the variance of 0.068%during the optimization.The results showed the effectiveness of the proposed method on the aerodynamic performance optimization of turbine stage.Compared with the traditional finite difference method,the discrete adjoint method costed only 3%CPU time for single-stage optimization.

axial turbineCFD methoddiscrete-adjoint optimizationfree-form deformationaerodynamic performance

康伟、王彦清、徐全勇、胡仕林

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西北工业大学航天学院,西安 710072

清华大学航空发动机研究院,北京 100084

轴流涡轮 计算流体力学方法 离散伴随优化 自由变形型面 气动性能

2024

航空动力学报
中国航空学会

航空动力学报

CSTPCD北大核心
影响因子:0.59
ISSN:1000-8055
年,卷(期):2024.39(11)