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Design and analysis of an ocean current turbine performance assessment system
- 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 |
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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. |
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Subject(s): |
Marine turbines -- Mathematical models Fluid dynamics Structural dynamics Stochastic processes Rotors -- Design and construction -- Testing |
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Persistent Link to This Record: | http://purl.flvc.org/FAU/3359164 | |
Use and Reproduction: | http://rightsstatements.org/vocab/InC/1.0/ | |
Host Institution: | FAU |