A simplified procedure is presented for the determination of the derivatives of eigenvectors of nth order algebraic eigensystems. The method is applicable to symmetric or nonsymmetric systems, and requires knowledge of only one eigenvalue and its associated right and left eigenvectors. In the procedure, the matrix of the original eigensystem of rank (/?-!) is modified to convert it to a matrix of rank /?, which then is solved directly for a vector which, together with the eigenvector, gives the eigenvector derivative to within an arbitrary constant. The norm of the eigenvector is used to determine this constant and complete the calculation. The method is simple, since the modified n rank matrix is formed without matrix multiplication or extensive manipulation. Since the matrix has the same bandedness as the original eigensystems, it can be treated efficiently using the same banded equation solution algorithms that are used to find the eigenvectors.

Simplified calculation of eigenvector derivatives

Methods for calculating sensitivity derivatives for discrete structural systems are surveyed, primarily covering literature published during the past two decades. Methods are described for calculating derivatives of static displacements and stresses, eigenvalues and eigenvectors, transient structural response, and derivatives of optimum structural designs with respect to problem parameters. The survey is focused on publications developed in nonstructural fields such as electronics, controls, and physical chemistry which are directly applicable to structural problems. Most notable among the nonstructural-based methods are the adjoint variable technique from control theory, and the Green's function and FAST methods from physical chemistry.

Sensitivity Analysis of Discrete Structural Systems

Uncertainties and dynamic problems of bolted joints and other fasteners

Recent developments are reviewed in two major areas of structural sensitivity analysis: sensitivity of static and transient response; and sensitivity of vibration and buckling eigenproblems. Recent developments from the standpoint of computational cost, accuracy, and ease of implementation are presented. In the area of static response, current interest is focused on sensitivity to shape variation and sensitivity of nonlinear response. Two general approaches are used for computing sensitivities: differentiation of the continuum equations followed by discretization, and the reverse approach of discretization followed by differentiation. It is shown that the choice of methods has important accuracy and implementation implications. In the area of eigenproblem sensitivity, there is a great deal of interest and significant progress in sensitivity of problems with repeated eigenvalues. In addition to reviewing recent contributions in this area, the paper raises the issue of differentiability and continuity associated with the occurrence of repeated eigenvalues.

/pdf/recent-developments-in-structural-sensitivity-analysis-23fy9nqyl5.pdf

Recent developments in structural sensitivity analysis

http://web.mae.ufl.edu/nkim/Papers/paper19.pdf

Review of options for structural design sensitivity analysis. Part 1: Linear systems

Two numerical methods are presented for computing the derivatives of eigenvalues and eigenvectors which do not require complete solution of the eigenvalue problem if only a few derivatives are sought. The 'iterative' method may be used to find the first derivative of one or all of the eigenvectors together with the second derivative of their eigenvalues in a self-adjoint system. If the left- and right-hand eigenvectors are known, the first derivative of the eigenvector corresponding to the largest eigenvalue and the second derivative of the largest eigenvalue may be obtained for a nonself-adjoint system. The 'algebraic' method may be used to find all orders of the derivatives, provided they exist, without requiring the left-hand eigenvectors.

Numerical methods for evaluating the derivatives of eigenvalues and eigenvectors

Expressions are obtained for the derivatives of the eigenvalues and eigenvectors which are expressions of only one left-hand and one right-hand eigenvector. The approach described makes use of a Choleski decomposition or some other decomposition method. The method may be extended to find any order of derivative of the eigenvalue and eigenvector. The expressions obtained for finding the derivatives of eigenvalues and eigenvectors for nonself-adjoint systems may be applied to self-adjoint systems.

Derivatives of Eigenvalues and Eigenvectors for a General Matrix

Aircraft structural parameters optimization satisfying flutter velocity constraint and minimum mass, applying to box beam design

Optimization of complex structures to satisfy flutter requirements

Equations for the second partial derivatives of the eigenvalues of the flutter equation along with the equations for finding the second partial derivatives of the flutter velocity of an aircraft structure with respect to the structural parameters are derived. These partial derivatives are used to develop expressions for the step size in a projected gradient search along a constant mass hyperlane. A projected gradient search along with a gradient mass and a gradient velocity search is used to minimize the mass of a box beam which supports a lifting surface.

Carl S. Rudisill

Papers

Numerical methods for evaluating the derivatives of eigenvalues and eigenvectors

Derivatives of Eigenvalues and Eigenvectors for a General Matrix

Optimization of complex structures to satisfy flutter requirements

Second derivatives of the flutter velocity and the optimization of aircraft structures.

Comment on "Rates of Change of Flutter Mach Number and Flutter Frequency"