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Ocean Renewable Energy

Fatigue and Serviceability 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

1

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), 031905 (Feb 22, 2012) (10 pages) doi:10.1115/1.4004514 History: Received July 26, 2009; Revised January 27, 2011; Published February 22, 2012; Online February 22, 2012

This paper develops the models for the structural performance of the loading and probabilistic characterization for the fatigue and the serviceability limit states for the support structure of offshore wind energy converters. These models and a sensitivity study are 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 the design of monitoring systems. The constitutive physical equations are introduced in combination with the fatigue and serviceability limit state requirements as the starting point for the development of the structural performance and loading models. With these models introduced in detail, several modeling aspects for both limit states are analyzed. This includes analyses of the influence on the hot spot stresses by applying a contact formulation for the pile guide brace connection and the application of a finite element formulation using solid elements. Further, the comparison of the natural frequencies of a discrete rotor model with a continuous rotor model is documented. To account for uncertainties associated with the structural and loading models, a probabilistic model is derived on the basis of literature review and measurement data from a prototype Multibrid M5000 support structure. The sensitivity study is based on the calculation of a nonlinear coefficient of correlation in conjunction with predetermined designs of experiments. This is conducted by a systematic analysis of the influence of the random variables on limit state responses and hence on the structural reliability. Integrating the analyses and sensitivity studies of the fatigue and serviceability limit state models developed in this paper as well as the ultimate limit state models in Thöns (“Ultimate Limit State Model Basis for Assessment of Offshore Wind Energy Converters,” ASME J. Offshore Mech. Arct. Eng.), the model basis for the assessment is completed. The process of establishing and analyzing such a model basis contributes to a detailed understanding of the deterministic and probabilistic characteristics of the structure and provides valuable insights in regard to the significance of available data.

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Copyright © 2012 by American Society of Mechanical Engineers
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Figures

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Figure 1

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

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Figure 2

Paper organization containing the model basis and analyses for model development

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Figure 3

Fatigue and serviceability model basis consisting of overall combined shell/beam model (a), a tripod shell model (b), and a tripod solid model (c)

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Figure 4

Comparison of “contact” and “no contact” hot spot stresses

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Figure 5

Comparison of hot spot stresses calculated by a shell and a solid model

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Figure 6

Mode shapes of the discrete rotor model with colored displacement vector sum in ascending order

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Figure 7

Mode shapes in ascending order using the overall model with colored displacement vector

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Figure 8

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

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Figure 9

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

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