Nonlinear formulations of the meshless local Petrov-Galerkin （MLPG） method are presented for geometrically nonlinear problems. The method requires no mesh in computation and therefore avoids mesh distortion difficul...Nonlinear formulations of the meshless local Petrov-Galerkin （MLPG） method are presented for geometrically nonlinear problems. The method requires no mesh in computation and therefore avoids mesh distortion difficulties in the large deformation analysis. The essential boundary conditions in the present formulation axe imposed by a penalty method. An incremental and iterative solution procedure is used to solve geometrically nonlinear problems. Several examples are presented to demonstrate the effectiveness of the method in geometrically nonlinear problems analysis. Numerical results show that the MLPG method is an effective one and that the values of the unknown variable are quite accurate.展开更多
研究时变结构模态参数辨识,基于泛函矢量时变自回归模型(Functional series vector time-dependent AR model,FS-VTAR)提出一种改进的移动最小二乘法的时变结构模态参数辨识方法。该方法源于无网格法中构造形函数进行局部近似的思想,引...研究时变结构模态参数辨识,基于泛函矢量时变自回归模型(Functional series vector time-dependent AR model,FS-VTAR)提出一种改进的移动最小二乘法的时变结构模态参数辨识方法。该方法源于无网格法中构造形函数进行局部近似的思想,引入带权正交基函数对移动最小二乘(Moving least square,MLS)的基函数进行改进,使得在辨识时间域内构造形函数矩阵过程中不再出现数值条件问题,从而提高了计算精度。把时变系数在形函数上线性展开,利用最小二乘法得到形函数的系数,从而得到时变系数。把时变模型特征方程转换为广义特征值问题提取出模态参数。利用时变刚度系统非平稳振动信号验证该方法,结果表明:改进的移动最小二乘法相比于传统的FS-VTAR模型能有效地避免基函数形式的选择和很高的基函数阶数且更加高效,相比于移动最小二乘法能有效地避免辨识过程中的数值问题,具有更高的模态参数辨识精度。展开更多
基金Project supported by the National 973 Program (No.2004CB719402), the National Natural Science Foundation of China (No. 10372030)the Open Research Projects supported by the Project Fund of the Hubei Province Key Lab of Mechanical Transmission & Manufacturing Engineering Wuhan University of Science & Technology (No.2003A16).
文摘Nonlinear formulations of the meshless local Petrov-Galerkin （MLPG） method are presented for geometrically nonlinear problems. The method requires no mesh in computation and therefore avoids mesh distortion difficulties in the large deformation analysis. The essential boundary conditions in the present formulation axe imposed by a penalty method. An incremental and iterative solution procedure is used to solve geometrically nonlinear problems. Several examples are presented to demonstrate the effectiveness of the method in geometrically nonlinear problems analysis. Numerical results show that the MLPG method is an effective one and that the values of the unknown variable are quite accurate.
文摘研究时变结构模态参数辨识,基于泛函矢量时变自回归模型(Functional series vector time-dependent AR model,FS-VTAR)提出一种改进的移动最小二乘法的时变结构模态参数辨识方法。该方法源于无网格法中构造形函数进行局部近似的思想,引入带权正交基函数对移动最小二乘(Moving least square,MLS)的基函数进行改进,使得在辨识时间域内构造形函数矩阵过程中不再出现数值条件问题,从而提高了计算精度。把时变系数在形函数上线性展开,利用最小二乘法得到形函数的系数,从而得到时变系数。把时变模型特征方程转换为广义特征值问题提取出模态参数。利用时变刚度系统非平稳振动信号验证该方法,结果表明:改进的移动最小二乘法相比于传统的FS-VTAR模型能有效地避免基函数形式的选择和很高的基函数阶数且更加高效,相比于移动最小二乘法能有效地避免辨识过程中的数值问题,具有更高的模态参数辨识精度。
