|Name:||Deborah F. Pilkey|
|Title:||Computation of a Damping Matrix for Finite Element Model Updating|
|Degree:||Doctor of Philosophy|
|Department:||Engineering Science & Mechanics|
|Committee Chair:||Dr. Daniel J. Inman and Dr. Calvin J. Ribbens|
|Chair's email:||firstname.lastname@example.org, email@example.com|
|Committee Members:||Dr. Christopher Beattie|
|Dr. Romesh Batra|
|Dr. Mehdi Ahmadian|
|Keywords:||damping, model updating, model reduction, high performance computing|
|Date of defense:||April 21, 1998|
|Availability:||Release the entire work immediately worldwide.|
The characterization of damping is important in making accurate predictions of both the true response and the frequency response of any device or structure dominated by energy dissipation. The process of modeling damping matrices and experimental verification of those is challenging because damping can not be determined via static tests as can mass and stiffness. Furthermore, damping is more difficult to determine from dynamic measurements than natural frequency. However, damping is extremely important in formulating predictive models of structures. In addition, damping matrix identification may be useful in diagnostics or health monitoring of structures.
The objective of this work is to find a robust, practical procedure to identify damping matrices. All aspects of the damping identification procedure are investigated. The procedures for damping identification presented herein are based on prior knowledge of the finite element or analytical mass matrices and measured eigendata. Alternately, a procedure is based on knowledge of the mass and stiffness matrices and the eigendata. With this in mind, an exploration into model reduction and updating is needed to make the problem more complete for practical applications. Additionally, high performance computing is used as a tool to deal with large problems. High Performance Fortran is exploited for this purpose. Finally, several examples, including one experimental example are used to illustrate the use of these new damping matrix identification algorithms and to explore their robustness.
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