期刊文献+

The Development of Highly Loaded Turbine Rotating Blades by Using 3D Optimization Design Method of Turbomachinery Blades Based on Artificial Neural Network & Genetic Algorithm 被引量:3

采用基于神经网络及遗传算法的叶轮机械叶片三维优化设计方法开发高载荷透平动叶片(英文)
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摘要 In order to improve turbine internal efficiency and lower manufacturing cost, a new highly loaded rotating blade has been developed. The 3D optimization design method based on artificial neural network and genetic algorithm is adopted to construct the blade shape. The blade is stacked by the center of gravity in radial direction with five sections. For each blade section, independent suction and pressure sides are constructed from the camber line using Bezier curves. Three-dimensional flow analysis is carried out to verify the performance of the new blade. It is found that the new blade has improved the blade performance by 0.5%. Consequently, it is verified that the new blade is effective to improve the turbine internal efficiency and to lower the turbine weight and manufacturing cost by reducing the blade number by about 15%. In order to improve turbine internal efficiency and lower manufacturing cost, a new highly loaded rotating blade has been developed. The 3D optimization design method based on artificial neural network and genetic algorithm is adopted to construct the blade shape. The blade is stacked by the center of gravity in radial direction with five sections. For each blade section, independent suction and pressure sides are constructed from the camber line using Bezier curves. Three-dimensional flow analysis is carried out to verify the performance of the new blade. It is found that the new blade has improved the blade performance by 0.5%. Consequently, it is verified that the new blade is effective to improve the turbine internal efficiency and to lower the turbine weight and manufacturing cost by reducing the blade number by about 15%.
出处 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2003年第4期198-202,共5页 中国航空学报(英文版)
基金 Project G19990 2 2 3 0 7supported by 973
关键词 optimization design highly loaded rotating blades artificial neural network genetic algorithm optimization design highly loaded rotating blades artificial neural network genetic algorithm
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参考文献5

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同被引文献28

  • 1赵桂杰,陈浮,宋彦萍,王仲奇.Experimental Study on the Aerodynamic Performance of Swept-Curved Blade[J].Chinese Journal of Aeronautics,2004,17(3):136-141. 被引量:5
  • 2宁方飞,刘晓嘉.一种新的响应面模型及其在轴流压气机叶型气动优化中的应用[J].航空学报,2007,28(4):813-820. 被引量:11
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