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The modeling and use of syntactic foams for passive control of fluid-borne noise

Syntactic foams-composite materials consisting of hollow particles embedded in a host matrix-have many applications for manufactured products, including weight reduction, thermal insulation, and noise reduction. In this thesis, a certain variety of syntactic foam is investigated with regards to reducing fluid borne noise in hydraulic systems. Such a foam maintains stiffness at low hydrostatic pressures and becomes compressible as pressure increases. With this compressibility, the foam is potentially useful as a liner for a reactive noise control device, much like compressed gas style devices currently in use; but the syntactic foam additionally adds significant damping to the system. In order to predict device performance, a linear multimodal model is developed of a hydraulic suppressor, constructed as an expansion chamber lined with a syntactic foam insert. Material models are developed for various compositions of the foam liners, based on an inverse analysis matching the model to experimental results. Two model simplifications are considered, and it is found that a simplified bulk modulus model gives sufficiently accurate results to make approximate predictions of suppressor performance. Several optimizations are performed to predict the optimal material composition for hydraulic excavator work cycles. To help compare the prototype suppressor against commercially available bladder style suppressors, a model is developed for the bladder style silencer and is validated experimentally. Overall, this work both demonstrates the current and potential utility of syntactic foam as a device lining material, and contributes new models to the hydraulics noise control community.

Identiferoai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/53122
Date12 January 2015
CreatorsMarek, Kenneth A.
ContributorsCunefare, Kenneth A.
PublisherGeorgia Institute of Technology
Source SetsGeorgia Tech Electronic Thesis and Dissertation Archive
Languageen_US
Detected LanguageEnglish
TypeDissertation
Formatapplication/pdf

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