Publication Date
2010
Document Type
Dissertation
Committee Members
Richard Cobb (Committee Member), Ramana Grandhi (Advisor), Steven Olson (Committee Member), Ravi Penmetsa (Committee Member), Joseph Slater (Committee Member)
Degree Name
Doctor of Philosophy (PhD)
Abstract
Air vehicles flying at hypersonic speeds encounter extreme thermal, aerodynamic and acoustic loads. To maintain the structural integrity of the flight vehicle, a thermal protection system shields the main structure from these loads. Therefore, maintaining the health of the thermal protection system is critical for a successful mission and vehicle safety. One of the more common types of failure in a mechanically attached thermal protection system is fastener failure. Since reducing vehicle turnaround between flights is desired, creating an automated system to perform structural health monitoring on the fastener health of the thermal protection system is needed. This can be completed by analyzing changes in the dynamic characteristics of the system due to fastener failure.
While much of the recent experimental research focuses on using sensors to detect high-frequency dynamic changes in the system to detect damage, this research focuses on investigating fastener failure damage where only low-frequency dynamics are available. This involves validating a finite element model with low-frequency experimental dynamic tests to ensure the geometry, boundary conditions, material properties, and finite element mesh properly capture the physical characteristics of the structure. The damage states are then simulated with the finite element model to obtain a better understanding of how the damages cause low-frequency dynamic changes without requiring a vast amount of experimental data. The damage detection metrics include previously developed modal parameters-the MAC, PMAC, and COMAC-in addition to two newly developed damage metrics-the normalized coordinate modal assurance criterion and the normalized coordinate modal assurance criterion summation. The new damage metrics investigate how mode shape normalization can provide a distributed prediction for where damage is located.
Page Count
170
Department or Program
Ph.D. in Engineering
Year Degree Awarded
2010
Copyright
Copyright 2010, all rights reserved. This open access ETD is published by Wright State University and OhioLINK.
