A family of modal methods for computing eigenvector derivatives with repeated roots are directly derived from the constraint generalized inverse technique which is originally formulated by Wang and Hu. Extensions are ...A family of modal methods for computing eigenvector derivatives with repeated roots are directly derived from the constraint generalized inverse technique which is originally formulated by Wang and Hu. Extensions are made to Akgun's method to allow treatment of eigensensitivity with repeated roots for general nondefective systems, and Bernard and Bronowicki's modal expansion approach is expanded to a family of modal methods.展开更多
On one hand, when the bridge stays in a windy environment, the aerodynamic power would reduce it to act as a non-classic system. Consequently, the transposition of the system’s right eigenmatrix will not equal its le...On one hand, when the bridge stays in a windy environment, the aerodynamic power would reduce it to act as a non-classic system. Consequently, the transposition of the system’s right eigenmatrix will not equal its left eigenmatrix any longer. On the other hand, eigenmatrix plays an important role in model identification, which is the basis of the identification of aerodynamic derivatives. In this study, we follow Scanlan’s simple bridge model and utilize the information provided by the left and right eigenmatrixes to structure a self-contained eigenvector algorithm in the frequency domain. For the purpose of fitting more accurate transfer function, the study adopts the combined sine-wave stimulation method in the numerical simulation. And from the simulation results, we can conclude that the derivatives identified by the self-contained eigenvector algorithm are more dependable.展开更多
An improved modal truncation method with arbitrarily high order accuracy is developed for calculating the second- and third-order eigenvalue derivatives and the first- and second-order eigenvector derivatives of an as...An improved modal truncation method with arbitrarily high order accuracy is developed for calculating the second- and third-order eigenvalue derivatives and the first- and second-order eigenvector derivatives of an asymmetric and non-defective matrix with repeated eigenvalues. If the different eigenvalues λ1, λ2,……, λs of the matrix satisfy ｜λ1｜ ≤... ≤｜λr｜ and ｜λs｜ 〈｜〈s＋1｜ （s ≤r-l）, then associated with any eigenvalue λi （i≤ s）, the errors of the eigenvalue and eigenvector derivatives obtained by the qth-order approximate method are proportional to ｜λi｜/λs＋1｜q＋l, where the approximate method only uses the eigenpairs corresponding to λ1, λ2,……,λs A numerical example shows the validity of the approximate method. The numerical example also shows that in order to get the approximate solutions with the same order accuracy, a higher order method should be used for higher order eigenvalue and eigenvector derivatives.展开更多
基金The project supported by the National Natural Science Foundation of China
文摘A family of modal methods for computing eigenvector derivatives with repeated roots are directly derived from the constraint generalized inverse technique which is originally formulated by Wang and Hu. Extensions are made to Akgun's method to allow treatment of eigensensitivity with repeated roots for general nondefective systems, and Bernard and Bronowicki's modal expansion approach is expanded to a family of modal methods.
基金supported by the State Key Program of National Natural Science Foundation of China (Grant No. 11032009)the National Natural Science Foundation of China (Grant No. 10772048)
文摘On one hand, when the bridge stays in a windy environment, the aerodynamic power would reduce it to act as a non-classic system. Consequently, the transposition of the system’s right eigenmatrix will not equal its left eigenmatrix any longer. On the other hand, eigenmatrix plays an important role in model identification, which is the basis of the identification of aerodynamic derivatives. In this study, we follow Scanlan’s simple bridge model and utilize the information provided by the left and right eigenmatrixes to structure a self-contained eigenvector algorithm in the frequency domain. For the purpose of fitting more accurate transfer function, the study adopts the combined sine-wave stimulation method in the numerical simulation. And from the simulation results, we can conclude that the derivatives identified by the self-contained eigenvector algorithm are more dependable.
基金supported by the National Natural Science Foundation of China(No.11101149)the Basic Academic Discipline Program of Shanghai University of Finance and Economics(No.2013950575)
文摘An improved modal truncation method with arbitrarily high order accuracy is developed for calculating the second- and third-order eigenvalue derivatives and the first- and second-order eigenvector derivatives of an asymmetric and non-defective matrix with repeated eigenvalues. If the different eigenvalues λ1, λ2,……, λs of the matrix satisfy ｜λ1｜ ≤... ≤｜λr｜ and ｜λs｜ 〈｜〈s＋1｜ （s ≤r-l）, then associated with any eigenvalue λi （i≤ s）, the errors of the eigenvalue and eigenvector derivatives obtained by the qth-order approximate method are proportional to ｜λi｜/λs＋1｜q＋l, where the approximate method only uses the eigenpairs corresponding to λ1, λ2,……,λs A numerical example shows the validity of the approximate method. The numerical example also shows that in order to get the approximate solutions with the same order accuracy, a higher order method should be used for higher order eigenvalue and eigenvector derivatives.
