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

作     者：周凡贞 冯国泰 蒋洪德 ZHOU Fan-zhen;FENG Guo-tai;JIANG Hong-De

作者机构：Academy of Energy Science and Engineering Harbin Institute of technologyHarbin 150001 China Institute of Engineering Thermophysics Academia Sinica Beijing 100080 China 

基　　金：Project G19990 2 2 3 0 7supported by 973 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2003年第16卷第4期

页      码：198-202页

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%.

主 题 词：optimization design highly loaded rotating blades artificial neural network genetic algorithm 

学科分类：082502[082502] 08[工学] 0825[工学-环境科学与工程类] 

核心收录：

D　O　I：10.1016/S1000-9361(11)60184-2

馆 藏 号：203259647...