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contributor authorSclavounos, Paul D.
contributor authorZhang, Yu
contributor authorMa, Yu
contributor authorLarson, David F.
date accessioned2019-03-17T09:38:28Z
date available2019-03-17T09:38:28Z
date copyright1/22/2019 12:00:00 AM
date issued2019
identifier issn0892-7219
identifier otheromae_141_03_031904.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4255584
description abstractThe development of an analytical model for the prediction of the stochastic nonlinear wave loads on the support structure of bottom mounted and floating offshore wind turbines is presented. Explicit expressions are derived for the time-domain nonlinear exciting forces in a sea state with significant wave height comparable to the diameter of the support structure based on the fluid impulse theory (FIT). The method is validated against experimental measurements with good agreement. The higher order moments of the nonlinear load are evaluated from simulated force records and the derivation of analytical expressions for the nonlinear load statistics for their efficient use in design is addressed. The identification of the inertia and drag coefficients of a generalized nonlinear wave load model trained against experiments using support vector machine learning algorithms is discussed.
publisherThe American Society of Mechanical Engineers (ASME)
titleOffshore Wind Turbine Nonlinear Wave Loads and Their Statistics
typeJournal Paper
journal volume141
journal issue3
journal titleJournal of Offshore Mechanics and Arctic Engineering
identifier doi10.1115/1.4042264
journal fristpage31904
journal lastpage031904-8
treeJournal of Offshore Mechanics and Arctic Engineering:;2019:;volume( 141 ):;issue: 003
contenttypeFulltext


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