摘要
在弹性空腔上敷设多孔介质和约束层阻尼可以有效地抑制结构的振动和噪声。考虑流体和结构的耦合作用,以及层间的连续性条件,采用Hypermesh建立了此类复合层空腔的有限元模型,并通过声学实验验证有限元模型的有效性。为了提高数值分析的效率,基于径向基神经算法(RBF)法建立了复合声腔的近似模型,并利用带精英策略的非支配排序遗传算法(NSGA-Ⅱ)对复合结构厚度进行了优化。结果表明,优化后的声压和复合结构的重量均有所降低,达到了降噪和轻量化的目的。
Laying porous media and constrained layer damping on the elastic cavity can effectively suppress the vibration and noise of the structure.Considering the coupling effect of fluid and structure,and the continuity conditions between layers,the finite element model of the composite cavity is established by Hyper mesh software.The acoustic experiment has verified the accuracy of the finite element model.In order to improve the efficiency of numerical analysis,an approximate model of the composite acoustic cavity is proposed based on the Radial Basis Function Neural Algorithm(RBF),and the thicknesses of the composite structure are optimized using the NSGA-Ⅱ method.The results show that the sound pressure and the weight of the optimized composite structure have been reduced,achieving the purpose of noise reduction and light weight.
作者
陈莎
陆静
王青
CHEN Sha;LU Jing;WANG Qing(School of Mechanical and Transportation Engineering,Guangxi University of Science and Technology,Liuzhou Guangxi 545006,China;Guangxi Key Laboratory of Automobile Components and Vehicle Technology,Guangxi University of Science and Technology,Liuzhou Guangxi 545006,China)
出处
《装备制造技术》
2020年第11期7-11,共5页
Equipment Manufacturing Technology
基金
国家自然科学基金项目(51665006)
广西科技大学研究生教育创新计划项目(GKYC202001)。
关键词
复合空腔
有限元
RBF法
NSGA-Ⅱ法
厚度优化
Composite Cavity
Finite Element Method
RBF Method
NSGA-ⅡMethod
Thickness Optimization
