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Development of a Comprehensive Desig...
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Suzuki, Takuya.
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Development of a Comprehensive Design Methodology and Fatigue Life Prediction of Composite Turbine Blades under Random Ocean Current Loading.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Development of a Comprehensive Design Methodology and Fatigue Life Prediction of Composite Turbine Blades under Random Ocean Current Loading./
作者:
Suzuki, Takuya.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:
229 p.
附註:
Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.
Contained By:
Dissertation Abstracts International79-07B(E).
標題:
Ocean engineering. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10683998
ISBN:
9780355676105
Development of a Comprehensive Design Methodology and Fatigue Life Prediction of Composite Turbine Blades under Random Ocean Current Loading.
Suzuki, Takuya.
Development of a Comprehensive Design Methodology and Fatigue Life Prediction of Composite Turbine Blades under Random Ocean Current Loading.
- Ann Arbor : ProQuest Dissertations & Theses, 2017 - 229 p.
Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.
Thesis (Ph.D.)--Florida Atlantic University, 2017.
A comprehensive study was performed to overcome the design issues related to Ocean Current Turbine (OCT) blades. Statistical ocean current models were developed in terms of the probability density function, the vertical profile of mean velocity, and the power spectral density. The models accounted for randomness in ocean currents, tidal effect, and ocean depth. The proposed models gave a good prediction of the velocity variations at the Florida Straits of the Gulf Stream.
ISBN: 9780355676105Subjects--Topical Terms:
660731
Ocean engineering.
Development of a Comprehensive Design Methodology and Fatigue Life Prediction of Composite Turbine Blades under Random Ocean Current Loading.
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Development of a Comprehensive Design Methodology and Fatigue Life Prediction of Composite Turbine Blades under Random Ocean Current Loading.
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Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.
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Adviser: Hassan Mahfuz.
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Thesis (Ph.D.)--Florida Atlantic University, 2017.
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A comprehensive study was performed to overcome the design issues related to Ocean Current Turbine (OCT) blades. Statistical ocean current models were developed in terms of the probability density function, the vertical profile of mean velocity, and the power spectral density. The models accounted for randomness in ocean currents, tidal effect, and ocean depth. The proposed models gave a good prediction of the velocity variations at the Florida Straits of the Gulf Stream.
520
$a
A novel procedure was developed to couple Fluid-Structure Interaction (FSI) with blade element momentum theory. The FSI effect was included by considering changes in inflow velocity, lift and drag coefficients of blade elements. Geometric non-linearity was also considered to account for large deflection. The proposed FSI analysis predicted a power loss of 3.1 % due to large deflection of the OCT blade. The method contributed to saving extensive computational cost and time compared to a CFD-based FSI analysis.
520
$a
The random ocean current loadings were calculated by considering the ocean current turbulence, the wake flow behind the support structure, and the velocity shear. The random ocean current loadings had large probability of high stress ratio. Fatigue tests of GFRP coupons and composite sandwich panels under such random loading were performed. Fatigue life increased by a power function for GFRP coupons and by a linear-log function for composite sandwich panels as the mean velocity decreased. To accurately predict the fatigue life, a new fatigue model based on the stiffness degradation was proposed. Fatigue life of GFRP coupons was predicted using the proposed model, and a comparison was made with experimental results.
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As a summary, a set of new design procedures for OCT blades has been introduced and verified with various case studies of experimental turbines.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10683998
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