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Bartkowicz, Theodore J.

Publications and source records attributed to Bartkowicz, Theodore J..

Ares I-X In-Flight Modal Identification

Operational modal analysis is a procedure that allows the extraction of modal parameters of a structure in its operating environment. It is based on the idealized premise that input to the structure is white noise. In some cases, when free decay responses are corrupted by unmeasured random disturbances, the response data can be processed into cross-correlation functions that approximate free decay responses. Modal parameters can be computed from these functions by time domain identification methods such as the Eigenvalue Realization Algorithm (ERA). The extracted modal parameters have the same characteristics as impulse response functions of the original system. Operational modal analysis is performed on Ares I-X in-flight data. Since the dynamic system is not stationary due to propellant mass loss, modal identification is only possible by analyzing the system as a series of linearized models over short periods of time via a sliding time-window of short time intervals. A time-domain zooming technique was also employed to enhance the modal parameter extraction. Results of this study demonstrate that free-decay time domain modal identification methods can be successfully employed for in-flight launch vehicle modal extraction.

Bartkowicz, Theodore J.↗

Extraction of Modal Parameters from Spacecraft Flight Data

The modeled response of spacecraft systems must be validated using flight data as ground tests cannot adequately represent the flight. Tools from the field of operational modal analysis would typically be brought to bear on such structures. However, spacecraft systems have several complicated issues: 1. High amplitudes of loads; 2. Compressive loads on the vehicle in flight; 3. Lack of generous time-synchronized flight data; 4. Changing properties during the flight; and 5. Major vehicle changes due to staging. A particularly vexing parameter to extract is modal damping. Damping estimation has become a more critical issue as new mass-driven vehicle designs seek to use the highest damping value possible. The paper will focus on recent efforts to utilize spacecraft flight data to extract system parameters, with a special interest on modal damping. This work utilizes the analysis of correlation functions derived from a sliding window technique applied to the time record. Four different case studies are reported in the sequence that drove the authors understanding. The insights derived from these four exercises are preliminary conclusions for the general state-of-the-art, but may be of specific utility to similar problems approached with similar tools.

James, George H.↗

Structural Health Monitoring of Large Structures

This paper describes a damage detection and health monitoring method that was developed for large space structures using on-orbit modal identification. After evaluating several existing model refinement and model reduction/expansion techniques, a new approach was developed to identify the location and extent of structural damage with a limited number of measurements. A general area of structural damage is first identified and, subsequently, a specific damaged structural component is located. This approach takes advantage of two different model refinement methods (optimal-update and design sensitivity) and two different model size matching methods (model reduction and eigenvector expansion). Performance of the proposed damage detection approach was demonstrated with test data from two different laboratory truss structures. This space technology can also be applied to structural inspection of aircraft, offshore platforms, oil tankers, ridges, and buildings. In addition, its applications to model refinement will improve the design of structural systems such as automobiles and electronic packaging.

Kim, Hyoung M.↗