Computational Issues in Damping Identification for Large Scale Problems

Abstract

Damage detection and diagnostic techniques using vibration responses that depend on analytical models provide more information about a structure’s integrity than those that are not model based. The drawback of these approaches is that some form of a workable model is required. Typically, models of practical structures and their corresponding computational effort are very large. One method of detecting damage in a structure is to measure excess energy dissipation, which can be seen in damping matrices. Calculating damping matrices is important because there is a correspondence between a change in the damping matrix and the change in the health of a structure. The objective of this research is to investigate the numerical problems associated with computing damping matrices using inverse methods. Two damping identification methods are tested for efficiency in large-scale applications. One is an iterative routine, and the other a least squares method. Numerical simulations have been performed on multiple degree-of-freedom models to test the effectiveness of the algorithm and the usefulness of parallel computation for the problems. High Performance Fortran is used to parallelize the algorithm.