Nonnodal Condensation of Eigenvalue Problems

Non Nodal Condensation of Eigenvalue Problems

We generalize the Guyan condensation of large symmetric eigenvalue problems to allow general degrees of freedom to be master variables. On one hand useful information from other condensation methods (such as Component Mode Synthesis) thus can be incorporated into the method. On the other hand this opens the way to iterative reenement of eigenvector approximations. Convergence of such a procedur...

General masters in parallel condensation of eigenvalue problems

In the dynamic analysis of structures using nite element methods very often prohibitively many degrees of freedom are required to model the structure suuciently accurate. Condensation methods are often used to reduce the number of unknowns to manageable size. Substructuring and choosing the master variables as the degrees of freedom on the interfaces of the substructures yields data structures ...

Interior and modal masters in condensation methods for eigenvalue problems

In the dynamic analysis of structures condensation methods are often used to reduce the number of degrees of freedom to manageable size. Substruc-turing and choosing the master variables as the degrees of freedom on the interfaces of the substructures yields data structures which are well suited to be implemented on parallel computers. In this paper we discuss the additional use of interior mas...

Improving Condensation Methods for Eigenvalue Problems via Rayleigh Functional

The dynamic analysis of structures using the nite element method leads to very large eigenvalue problems. Condensation is often required to reduce the number of degrees of freedom of these problems to manageable size. The (statically or dynamically) condensed problem can be considered as linearization of a matrix eigenvalue problem which is nonlinear with respect to the eigenparameter. As a con...

Derivation of Eigenvalue Problems