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Predictive Modeling of Acoustic Signals from Thermoacoustic Power Sensios (Taps)

Vipperman, JS and Dumm, Christopher and Carvajal, Jorge and Runane, Amy and Walter, Melissa and Czerniak, Luke and Heibel, Michael (2016) Predictive Modeling of Acoustic Signals from Thermoacoustic Power Sensios (Taps).

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Abstract

Thermoacoustic Power Sensor (TAPS) technology offers the potential for self-powered, wireless measurement of nuclear reactor core operating conditions. TAPS are based on thermoacoustic engines, which harness thermal energy from fission reactions to generate acoustic waves by virtue of gas motion through a porous stack of thermally nonconductive material. TAPS can be placed in the core, where they generate acoustic waves whose frequency and amplitude are proportional to the local temperature and radiation flux, respectively. TAPS acoustic signals are not measured directly at the TAPS; rather, they propagate wirelessly from an individual TAPS through the reactor, and ultimately to a low-power receiver network on the vessel's exterior. In order to rely on TAPS as primary instrumentation, reactor-specific models which account for geometric/acoustic complexities in the signal propagation environment must be used to predict the amplitude and frequency of TAPS signals at receiver locations. The reactor state may then be derived by comparing receiver signals to the reference levels established by predictive modeling. In this paper, we develop and experimentally benchmark a methodology for predictive modeling of the signals generated by a TAPS system, with the intent of subsequently extending these efforts to modeling of TAPS in a liquid sodium environment.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Vipperman, JSjsv@pitt.eduJSV0000-0001-5585-954X
Dumm, Christopher
Carvajal, Jorge
Runane, Amy
Walter, Melissa
Czerniak, Luke
Heibel, Michael
Date: 2016
Schools and Programs: Swanson School of Engineering > Mechanical Engineering and Materials Science
Refereed: Yes
Article Type: Research Article
Date Deposited: 21 Sep 2018 19:18
Last Modified: 21 Aug 2024 16:43
URI: http://d-scholarship.pitt.edu/id/eprint/35343

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