Ocean Renewable Energy

Ultimate Limit State Model Basis for Assessment of Offshore Wind Energy Converters

[+] Author and Article Information
S. Thöns1

Division VII.2: Buildings and Structures  BAM Federal Institute for Materials Research and Testing, Unter den Eichen 87, 12205 Berlin, Germanysebastian.thoens@bam.de

M. H. Faber

DTU Civil Engineering, DTU Technical University of Denmark, Brovej, Building 118, DK - 2800 Kgs, Lyngby, Denmark mihf@byg.dtu.dk

W. Rücker

Division VII.2: Buildings and Structures  BAM Federal Institute for Materials Research and Testing, Unter den Eichen 87, 12205 Berlin, Germanywerner.ruecker@bam.de


Corresponding author. Contact address: BAM Federal Institute for Materials Research and Testing, Division VII.2 Buildings and Structures, Unter den Eichen 87, 12205 Berlin, Germany.

J. Offshore Mech. Arct. Eng 134(3), 031904 (Feb 22, 2012) (9 pages) doi:10.1115/1.4004513 History: Received July 26, 2009; Revised January 27, 2011; Published February 22, 2012; Online February 22, 2012

This paper establishes the model basis regarding the ultimate limit state consisting of structural, loading, and probabilistic models of the support structure of offshore wind energy converters together with a sensitivity study. The model basis is part of a risk based assessment and monitoring framework and will be applied for establishing the “as designed and constructed” reliability as prior information for the assessment and as a basis for designing a monitoring system. The model basis is derived considering the constitutive physical equations and the methodology of solving these which then in combination with the ultimate limit state requirements leads to the specific constitutive relations. As a result finite element models based on shell elements incorporating a structural and a loading model are introduced and described in detail. Applying these models the ultimate capacity of the support structure and the tripod structure are determined with a geometrically and materially nonlinear finite element analysis. The observed failure mechanisms are the basis for the definition of the ultimate limit state responses. A probabilistic model accounting for the uncertainties involved is derived on the basis of literature review and measurement data from a prototype Multibrid M5000 support structure. In combination with the developed structural and loading models, sensitivity analyses in regard to the responses are performed to enhance the understanding and to refine the developed models. To this end, as the developed models necessitate substantial numerical efforts for the probabilistic response analysis predetermined designs of numerical experiments are applied for the calculation of the sensitivities using the Spearman rank correlation coefficient. With this quantification of the sensitivity of the random variables on the responses including nonlinearity the refinement of the model is performed on a quantitative basis.

Copyright © 2012 by American Society of Mechanical Engineers
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Figure 1

Paper organization containing the model basis and analyses for model development

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Figure 2

Assessment and monitoring framework with an offshore Multibrid M5000 prototype installed onshore

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Figure 3

Interactions (thick line: major interaction; dashed line minor interaction) within the offshore wind energy converter and between the offshore wind energy converter and the environment (Ref. [3])

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Figure 4

Ultimate limit state model basis consisting of the support structure model (a) and a tripod model (b)

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Figure 5

Height varying wind pressure distribution and nacelle loading vector at the top of the support structure

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Figure 6

Von Mises equivalent stress ((a) to (c)) for three points of the load deflection curve (ANSYS printout)

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Figure 7

Equivalent plastic strains ((a) to (c)) for three points of the load deflection curve (ANSYS printout)

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Figure 8

von Mises equivalent stress (top) and equivalent strains (bottom) for three points of the load deflection curve

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Figure 9

Spearman rank correlation matrix for ultimate limit state random variables and responses




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