节点文献

基于无限元的2.5维方法预测轨道交通混凝土桥梁低频噪声

A 2.5-dimensional infinite element based method for the prediction of structure-borne low-frequency noise from concrete rail transit bridges

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 宋晓东吴定俊李奇

【Author】 SONG Xiao-dong;WU Ding-jun;LI Qi;Department of Bridge Engineering,Tongji University;

【机构】 同济大学桥梁工程系

【摘要】 提出了一种基于无限元的2.5维方法,可以快速预测桥梁结构噪声且不失精度。首先,建立沿桥梁纵向截面均匀的二维无限元模型,进行声传递向量计算。然后,联合桥梁三维模态分析结果,通过空间波数变换获得三维桥梁模型的模态声传递向量,并采用三维直接边界元的计算结果验证了所提出的2.5维方法的正确性。最后,进行车轨桥耦合振动计算,将获得的桥梁模态坐标与声模态传递向量结合起来预测桥梁振动辐射噪声。以上海某轨道交通为背景进行噪声现场测试,将现场实测结果与计算结果对比。分析表明,计算结果在近场与实测值吻合较好,但是由于忽略了相邻跨桥梁的影响,在远场数值计算结果小于实测值。

【Abstract】 A two-and-a-half dimensional(2.5D)procedure based on infinite element method(IFEM)is proposed to predict the bridge-borne noise with higher efficiency,yet no loss of accuracy.The two-dimensional(2D)infinite element model of a bridge with a constant cross section is developed to calculate the acoustic transfer vectors.Then,spatial modal acoustic transfer vectors(MATVs)of the bridge are derived using the space-wavenumber transforms of its 3Dmodal shapes.The MATVs obtained from 2.5DIFEM and 3Dboundary element method are then compared to verify the accuracy of the 2.5Dmethod.The vehicletrack-bridge dynamic interaction analysis is then conducted,and the bridge-borne noise is finally computed through the MATVs and modal coordinate responses of the bridge.The 2.5Dprocedure is employed to simulate the sound pressure radiating from the concrete bridge in one of Shanghai rail transit lines,and the numerical results are compared with the measured counterparts from field tests.The simulated and measured results match well in both time and frequency domains at near-field points.Nevertheless,the numerical results are smaller than the measured ones for far-field points,mainly due to the neglect of sound pressure induced by adjacent spans.

【基金】 国家自然科学基金资助项目(50908178)
  • 【文献出处】 振动工程学报 ,Journal of Vibration Engineering , 编辑部邮箱 ,2015年06期
  • 【分类号】U441.3
  • 【被引频次】18
  • 【下载频次】325
节点文献中: 

本文链接的文献网络图示:

本文的引文网络