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Flutter suppression using eigenspace freedoms to meet requirements

A constrained optimization methodology has been developed which allows specific use of eigensystem freedoms to meet design requirements. A subset of the available eigenvector freedoms was employed. The eigenvector freedoms associated with a particular closed-loop eigenvalue are coefficients of basis vectors which span the subspace in which that closed-loop vector must lie. Design requirements are included as a vector of inequality constraints. The procedure was successfully applied to develop an unscheduled controller which stabilizes symmetric flutter of an aeroelastic vehicle to a dynamic pressure 44 percent above the open-loop flutter point. The design process proceeded from full-state feedback to the inclusion of a full-order observer to the selection of an eighth-order controller which preserved the full-state sensitivity characteristics. Only a subset of the design freedoms was utilized (i.e., assuming full-state feedback only four out of 26 eigenvectors were used, and no variations were made in the closed-loop eigenvalues). Utilization of additional eigensystem freedoms could further improve the controller.

Adams, William M., Jr.↗

A Lanczos algorithm for vibration, suckling and termal analysis

This paper reviews an eigensolver algorithm based on the Lanczos Method for vibration, buckling and thermal analysis. The original code was written for inclusion in the Computational Mechanics Testbed (COMET), a general purpose finite element code. A portable version of the Lanczos code that is optimized for high-performance supercomputers has been developed. Special features of the algorithm include the capability to compute rigid body modes, thermal modes and Lanczos vectors that are derived from the applied load vector. The latter is necessary when using the Lanczos vectors as reduced-basis vectors in transient structural response and transient heat conduction calculations. The modularity of the code allows the user the option of including the most up-to-date utilities, such as the equation solver best suited for the application. The algorithm is discussed in detail and results of several applications are presented. Timing results for a vibration application indicate that the Lanczos algorithm is twenty times faster than the subspace iteration method which has been extensively used in the past.

Bostic, Susan W.↗