Three Dimensional Aerodynamic Optimization for an Ultra-Low Aspect Ratio Transonic Turbine Stator Blade

Author:

Hasenja¨ger Martina1,Sendhoff Bernhard1,Sonoda Toyotaka2,Arima Toshiyuki2

Affiliation:

1. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

2. Honda R&D Ltd., Wako-shi, Saitama, Japan

Abstract

A modern numerical stochastic optimization method, namely the evolution strategy (ES), was applied to an ultra-low aspect ratio transonic turbine stator blade in order to seek a new aerodynamic design concept for lower secondary flow losses. The low stator blade count is selected to avoid the direct viscous interaction of the stator wake with the downstream rotor blade. This led to the ultra-low aspect ratio stator blade. In the optimization, two kinds of objective functions were used, that is, (1) minimization of the “aerodynamic loss” (a single objective), (2) minimization of the “aerodynamic loss” and of the “variation of circumferential static pressure distribution” downstream of the stator blade (multi-objective optimization). In the case of the single objective, the aerodynamic loss is improved by an extreme aft-loaded airfoil with a noticeable bent part near the trailing edge, although the circumferential static distribution is slightly worse than that of the baseline. In the case of the multi-objective optimization, we observe a trade-off relation between aerodynamic loss and variation of static pressure distribution which is not easily resolved. A new design concept to achieve lower aerodynamic loss for ultra-low aspect ratio transonic turbine stator blades is discussed.

Publisher

ASMEDC

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. From Conceptual 1D Design Towards Full 3D Optimization of a Highly Loaded Turbine Stage;55th AIAA Aerospace Sciences Meeting;2017-01-05

2. Direct 3D Aerodynamic Optimization of Turbine Blades with GPU-Accelerated CFD;Computational Methods in Applied Sciences;2014-11-15

3. Interaction Detection in Aerodynamic Design Data;Intelligent Data Engineering and Automated Learning - IDEAL 2009;2009

4. Knowledge Extraction from Aerodynamic Design Data and its Application to 3D Turbine Blade Geometries;Journal of Mathematical Modelling and Algorithms;2008-12

5. Effect of End Wall Contouring on Performance of Ultra-Low Aspect Ratio Transonic Turbine Inlet Guide Vanes;Journal of Turbomachinery;2008-11-10

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