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Design and analysis of an ocean current turbine performance assessment system

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Date Issued:
2012
Summary:
This thesis proposes a sensor approach for quantifying the hydrodynamic performance of Ocean Current Turbines (OCT), and investigates the influence of sensor-specific noise and sampling rates on calculated turbine performance. Numerical models of the selected sensors are developed, and then utilized to add stochastic measurement error to numerically-generated, non-stochastic OCT data. Numerically-generated current velocity and turbine performance measurements are used to quantify the relative influence of sensor-specific error and sampling limitations on sensor measurements and calculated OCT performance results. The study shows that the addition of sensor error alters the variance and mean of OCT performance metric data by roughly 7.1% and 0.24%, respectively, for four evaluated operating conditions. It is shown that sensor error results in a mean, maximum and minimum performance metric to Signal to Noise Ration (SNR) of 48.6% and 6.2%, respectively.
Title: Design and analysis of an ocean current turbine performance assessment system.
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Name(s): Young, Matthew T.
College of Engineering and Computer Science
Department of Ocean and Mechanical Engineering
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Issued: 2012
Publisher: Florida Atlantic University
Physical Form: electronic
Extent: xi, 108 p. : ill. (some col.)
Language(s): English
Summary: This thesis proposes a sensor approach for quantifying the hydrodynamic performance of Ocean Current Turbines (OCT), and investigates the influence of sensor-specific noise and sampling rates on calculated turbine performance. Numerical models of the selected sensors are developed, and then utilized to add stochastic measurement error to numerically-generated, non-stochastic OCT data. Numerically-generated current velocity and turbine performance measurements are used to quantify the relative influence of sensor-specific error and sampling limitations on sensor measurements and calculated OCT performance results. The study shows that the addition of sensor error alters the variance and mean of OCT performance metric data by roughly 7.1% and 0.24%, respectively, for four evaluated operating conditions. It is shown that sensor error results in a mean, maximum and minimum performance metric to Signal to Noise Ration (SNR) of 48.6% and 6.2%, respectively.
Identifier: 835953159 (oclc), 3359164 (digitool), FADT3359164 (IID), fau:4062 (fedora)
Note(s): by Matthew T. Young.
Thesis (M.S.C.S.)--Florida Atlantic University, 2012.
Includes bibliography.
Mode of access: World Wide Web.
System requirements: Adobe Reader.
Subject(s): Marine turbines -- Mathematical models
Fluid dynamics
Structural dynamics
Stochastic processes
Rotors -- Design and construction -- Testing
Persistent Link to This Record: http://purl.flvc.org/FAU/3359164
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU