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Analysis of the design of experiments of offshore wind turbine
fatigue reliability design with Kriging surfaces
Rui Teixei...
Outline
• Introduction
• Offshore wind turbine fatigue design methodology
• Probabilistic fatigue design of Offshore Wind ...
Why is Offshore Wind Turbines development important?
• Global warming is a scientific fact.
• Renewable energy needs to be...
Introduction
• Probabilistic analysis of the design of Offshore Wind Turbine (OWT)
towers
• OWT Towers fatigue design
• OW...
Offshore wind turbine fatigue design methodology
• Current methodology involves the
extrapolation of load cycles using a
P...
• Using Kriging surrogate models to design towers to fatigue
• Short term damage rate follows a
Lognormal distribution.
• ...
Probabilistic design of OWT towers methodology
Loads tower
sections.
NREL FAST
Monopile OWT
Rainflow
counting,
damage
summ...
Results - Analysis of the design of experiments of offshore wind turbine fatigue
reliability design with Kriging surfaces
...
Results - Analysis of the design of experiments of offshore wind turbine fatigue
reliability design with Kriging surfaces
...
Conclusions
• Preliminary assessment indicate that the short term damage rate surface is highly
non-linear.
• Above the ra...
Thank you!
Rui Teixeira rteixeir@tcd.ie
This project has received funding from the European Union’s Horizon 2020 research ...
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“Random variables in the Offshore Wind Turbine fatigue reliability design with Kriging surfaces” presented at ICSI2017 by Rui Teixeira

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Abstract: The fatigue design of Offshore Wind Turbines (OWT) is one of the most resource demanding tasks in the OWT design process. Techniques have been developed recently to simplify the amount of effort needed to design to structural fatigue. This is the example of the usage of Kriging surrogate models. These may be used in OWTs design not only, to reduce the computational effort needed to analyse an OWT, but also to allow their design to be robust. Due to the stress variability and its non-linear character, the short-term fatigue damage variability is high, and converging the stochastic field approached by the surrogate model in relation to the real observations is challenging. A thorough analysis of the different components that load an OWT and are more critical for the tower component fatigue life is required, and therefore, presented and discussed in the current paper. The tower, jointly with the foundation, are particular components of the OWT regarding the fatigue analysis process. Statistical assessments of the extrapolation of fatigue loads for the tower and the influence of the environmental parameters in the short-term damage are presented in this paper. This sets a support analysis for the creation of the Kriging response surfaces for fatigue analysis. NREL’s 5 MW monopile turbine is used due to its state of the art character. Five environmental variables are considered in the analysis. A sensitivity analysis is conducted to identify which variables are most prominent in the quantification of the short-term damage uncertainty in the tower. The decoupling of the different external contributions for the fatigue life is a major contribution of the work presented. Preliminary guidelines are drawn for the creation of surrogate models to analyse fatigue of OWT towers and the most relevant conclusions are presented in an industry-oriented design outline regarding the most critical random variables that influence OWT short-term fatigue calculation.

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“Random variables in the Offshore Wind Turbine fatigue reliability design with Kriging surfaces” presented at ICSI2017 by Rui Teixeira

  1. 1. Analysis of the design of experiments of offshore wind turbine fatigue reliability design with Kriging surfaces Rui Teixeira, Alan O’Connor and Maria Nogal Department of Civil, Structural and Environmental Engineering, Trinity College Dublin, Dublin James Nichols and Nandakumar Krishnan Lloyd’s Register, United Kingdom ICSI2017, 04th September 2017 This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 642453
  2. 2. Outline • Introduction • Offshore wind turbine fatigue design methodology • Probabilistic fatigue design of Offshore Wind Turbine towers based on Kriging surrogate models • Results • Conclusions
  3. 3. Why is Offshore Wind Turbines development important? • Global warming is a scientific fact. • Renewable energy needs to be “pulled” forward. • EU targets of 20% of Renewable Energy in total energy consumption by 2020 and 27% by 2030 (EU Commission). • Projections of >2°C increase in global temperature by 2100 compared with pre- industrial levels (Paris Agreement). Source: Siemens 2014 report
  4. 4. Introduction • Probabilistic analysis of the design of Offshore Wind Turbine (OWT) towers • OWT Towers fatigue design • OWT are highly complex systems that are affected by multiple sources of uncertainty. Demand a strong reliability background. Why?
  5. 5. Offshore wind turbine fatigue design methodology • Current methodology involves the extrapolation of load cycles using a Peak-Over-threshold approach and definition of load spectra. Below the threshold level loads are accounted deterministically (IEC 61400-3). • Computationally demanding task. • Substantial contribution to the life cumulated damage is generated by small amplitude loads for low SN slope (m) materials. • Blades made of composite; • Tower made of steel
  6. 6. • Using Kriging surrogate models to design towers to fatigue • Short term damage rate follows a Lognormal distribution. • Kriging is an interpolation model that considers Gaussian uncertainty in the interpolation. Probabilistic design of OWT towers methodology • Applied to decrease computational cost. • Potential of application for reliability is very high.
  7. 7. Probabilistic design of OWT towers methodology Loads tower sections. NREL FAST Monopile OWT Rainflow counting, damage summation and statistical characterization of short-term damage rate. Kriging surrogate model. Long term fatigue damage distribution. Statistically accurate? No Yes
  8. 8. Results - Analysis of the design of experiments of offshore wind turbine fatigue reliability design with Kriging surfaces • One of the main challenges is the characterization of the uncertainty of the short term damage. • The model should be kept as simple as possible. No further complexity should be considered in the model if it does not account for relevant uncertainty in the results. • This implies the need to analyse the Design of Experiments (Stochastically). • Five environmental variables for pre- assessment with One-Factor-At-Time analysis. Four energy states. • Uw; Hs; Tp; I, Θw
  9. 9. Results - Analysis of the design of experiments of offshore wind turbine fatigue reliability design with Kriging surfaces • Considered very significant changes per parameter - 20% in order to better cover the DoE. 50 simulations to characterize the distribution. 1138% 218% 130% 495%
  10. 10. Conclusions • Preliminary assessment indicate that the short term damage rate surface is highly non-linear. • Above the rated power the standard deviation is usually 25-30% of the mean. Below the rated power this ratio is in average 50%. • Among the parameters analysed: • Wind velocity and Turbulence intensity significantly influence the short term damage rates of the OWT tower. DoE should be at least 2. • The influence of the wind direction can be ignored when analysing fatigue design with Kriging models. • Wave variables have a limited effect on the short term damage rate and usually redundant compared with the uncertainty derived from changes in Uw and I. • Further work on extended global analysis. Checking the correlation between variables and more extended coverage of DoE (e.g. using Latin Hypercube sampling). Increase the confidence of distribution estimation is needed.
  11. 11. Thank you! Rui Teixeira rteixeir@tcd.ie This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 642453

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