Magnetostrictive Particle Tagging of Epoxy and Epoxy Composites for Self Assessment of Damage
Li, Jin
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Permalink
https://hdl.handle.net/2142/85085
Description
Title
Magnetostrictive Particle Tagging of Epoxy and Epoxy Composites for Self Assessment of Damage
Author(s)
Li, Jin
Issue Date
2004
Doctoral Committee Chair(s)
White, Scott R.
Department of Study
Aerospace Engineering
Discipline
Aerospace Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Aerospace
Language
eng
Abstract
"This study is a comprehensive look at the feasibility of using magnetostrictive tags to detect damage in a structural composite. The brittle nature of the failure process of polymer matrix composite poses a technical challenge for their introduction in structural applications. Thus, there is a critical need to develop new techniques to monitor the health of structural composites on a continuous basis. Inspired by diagnostic techniques used in biomedicine, a new approach to health monitoring is proposed based on the technique of tagging. Magnetostrictive tagging refers to the incorporation of a small concentration of magnetostrictive particles into a host material to provide damage detection capability. Tag particles are typically less than 2% of the total volume and below 40 mum in size. This thesis focuses on the use of Terfenol-D, a giant magnetostrictive material, for tagging of polymer and polymer matrix composites. Their manufacture and magnetomechanical behavior is assessed using a variety of experimental procedures. The performance of tagged materials for damage detection is assessed in several ""simulate damage"" test specimens. Magnetic flux concentrations are observed to localize in the vicinity of induced damage and scale in proportion to the size of the damage zone. Micromechanical models are developed to analyze the experimental results. Tagging of polymers and polymer composites using Terfenol-D is shown to yield materials with unique health monitoring capabilities. Their behavior is predictable and is highly sensitive to damage state."
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