复合载荷作用下H型垂直轴风力机叶片结构多目标优化  

Multi-objective optimization of blade structure of H-type vertical axis wind turbine under composite load

作　　者：周兴明 周井玲[1] ZHOU Xingming;ZHOU Jingling(School of Mechanical Engineering,Nantong University,Nantong 226019,China)

机构地区：[1]南通大学机械工程学院,南通226019

出　　处：《现代制造工程》2024年第4期153-159,145,共8页Modern Manufacturing Engineering

基　　金：南通市科技项目(MS12021049)。

摘　　要：为改善气动力、离心力和重力等复合载荷作用下的H型垂直轴风力机叶片的结构性能,提出一种多目标优化方法。以质量和最大应力最小为目标,最大变形为约束建立优化模型。通过流固耦合(Fluid-Structure-Interaction,FSI)方法,实现叶片表面压力的实时准确提取,建立复合载荷作用下的叶片有限元模型;基于最优空间填充(Optimal Space-Filling,OSF)方法和Kriging模型建立各变量对应力、质量和变形的响应面模型,进行灵敏度和变化趋势分析;最后采用多目标遗传算法(Multi-Objective Genetic Algorithm,MOGA)获得各变量的最优解,并进行结果验证。结果表明,优化后叶片质量减少了14.7%,各方位角下的最大应力减幅最大为7.8%,最大变形减幅最大为16.7%。研究结果可为复合载荷作用下叶片的结构优化设计提供参考。In order to improve the structural performance of H-type vertical axis wind turbine blades under the combined loads of aerodynamic force,centrifugal force and gravity,a multi-objective optimization method was proposed.A mathematical optimization model was established with the minimum mass and maximum stress as the objective function and the maximum deformation as the constraint.Through the Fluid-Structure-Interaction(FSI)method,the real-time and accurate extraction of the blade surface pressure was realized,and the finite element model of the blade under the combined load was established.Based on Optimal Space-Filling(OSF)method and Kriging model,the response surface model of each variable to stress,mass and deformation was established,and the sensitivity and change trend were analyzed.Finally,the Multi-Objective Genetic Algorithm(MOGA)was used to obtain the optimal solution of each variable,and the results were verified.The results showed that the optimized blade mass was reduced by 14.7%,the maximum reduction of the maximum stress at each azimuth was 7.8%,and the maximum reduction of the maximum deformation was 16.7%.The research results can provide a reference for the structural optimization design of blades under combined loads.

关 键 词：垂直轴风力机 叶片 流固耦合 KRIGING模型 多目标遗传算法 

分 类 号：TK83[动力工程及工程热物理—流体机械及工程]