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Proceedings Paper

Nonlinear dynamic model for magnetically-tunable Galfenol vibration absorbers
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Paper Abstract

This paper presents a single degree of freedom model for the nonlinear vibration of a metal-matrix composite manufactured by ultrasonic additive manufacturing that contains seamlessly embedded magnetostrictive Galfenol alloys (FeGa). The model is valid under arbitrary stress and magnetic field. Changes in the composite’s natural frequency are quantified to assess its performance as a semi-active vibration absorber. The effects of Galfenol volume fraction and location within the composite on natural frequency are quantified. The bandwidth over which the composite’s natural frequency can be tuned with a bias magnetic field is studied for varying displacement excitation amplitudes. The natural frequency is tunable for all excitation amplitudes considered, but the maximum tunability occurs below an excitation amplitude threshold of 1 × 10−6 m for the composite geometry considered. Natural frequency shifts between 6% and 50% are found as the Galfenol volume fraction varies from 25% to 100% when Galfenol is located at the composite neutral axis. At a modest 25% Galfenol by volume, the model shows that up to 15% shifts in composite resonance are possible through magnetic bias field modulation if Galfenol is embedded away from the composite midplane. As the Galfenol volume fraction and distance between Galfenol and composite midplane are increased, linear and quadratic increases in tunability result, respectively.

Paper Details

Date Published: 29 March 2013
PDF: 11 pages
Proc. SPIE 8690, Industrial and Commercial Applications of Smart Structures Technologies 2013, 869002 (29 March 2013); doi: 10.1117/12.2010114
Show Author Affiliations
Justin J. Scheidler, The Ohio State Univ. (United States)
Marcelo J. Dapino, The Ohio State Univ. (United States)


Published in SPIE Proceedings Vol. 8690:
Industrial and Commercial Applications of Smart Structures Technologies 2013
Kevin M. Farinholt; Steven F. Griffin, Editor(s)

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