Prediction of remaining fatigue life of welded joints in wind turbine support structures considering strain measurement and a joint distribution of oceanographic data

Reassessing the remaining fatigue life of the wind turbine support structures becomes more and more crucial for operation, maintenance, and life extension when they are reaching the end of their design service life. By using measured oceanographic and strain data, each year, remaining fatigue life c...

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Published inMarine structures Vol. 66; pp. 307 - 322
Main Authors Mai, Quang A., Weijtjens, Wout, Devriendt, Christof, Morato, Pablo G., Rigo, Philippe, Sørensen, John D.
Format Journal Article Web Resource
LanguageEnglish
Published Barking Elsevier Ltd 01.07.2019
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Abstract Reassessing the remaining fatigue life of the wind turbine support structures becomes more and more crucial for operation, maintenance, and life extension when they are reaching the end of their design service life. By using measured oceanographic and strain data, each year, remaining fatigue life can be updated to adapt the operation to real loading conditions. Previous works have not put attention to address the complexity of offshore loading combinations and as-constructed state of the structure in estimating structural responses for fatigue behaviour to stochastically predict the remaining fatigue life. The present paper links the oceanographic data to fatigue damage by using measured strain, and uses the Bayesian approach to update the joint distribution of the oceanographic data. Consequently, the failure probability of the support structure can be updated and so the predicted fatigue life. The year-to-year variation of the 10-min mean wind speed, the unrepresentativeness of measured strain, the measurement uncertainty, and corrosion are considered together with uncertainties in Miner′s rule and S–N curves. The present research shows that the real oceanographic data can be used to adjust the predicted remaining fatigue life and eventually give decision support for the wind turbine operation. •Wind and wave are included in the stress-life (S-N) fatigue damage calculation of existing structures.•Wind speed distribution is updated using Bayesian approach and included in the limit state function.•Effect of year-to-year variation of annual mean wind speed is considered•The estimated fatigue life is very sensitive to the accuracy of the method used to derive stresses at the interested location from the measuring location.•The most probable hot-spot location is found by combining measured strain data of different wind directions.
AbstractList Reassessing the remaining fatigue life of the wind turbine support structures becomes more and more crucial for operation, maintenance, and life extension when they are reaching the end of their design service life. By using measured oceanographic and strain data, each year, remaining fatigue life can be updated to adapt the operation to real loading conditions. Previous works have not put attention to address the complexity of offshore loading combinations and as-constructed state of the structure in estimating structural responses for fatigue behaviour to stochastically predict the remaining fatigue life. The present paper links the oceanographic data to fatigue damage by using measured strain, and uses the Bayesian approach to update the joint distribution of the oceanographic data. Consequently, the failure probability of the support structure can be updated and so the predicted fatigue life. The year-to-year variation of the 10-min mean wind speed, the unrepresentativeness of measured strain, the measurement uncertainty, and corrosion are considered together with uncertainties in Miner′s rule and S–N curves. The present research shows that the real oceanographic data can be used to adjust the predicted remaining fatigue life and eventually give decision support for the wind turbine operation.
Reassessing the remaining fatigue life of the wind turbine support structures becomes more and more crucial for operation, maintenance, and life extension when they are reaching the end of their design service life. By using measured oceanographic and strain data, each year, remaining fatigue life can be updated to adapt the operation to real loading conditions. Previous works have not put attention to address the complexity of offshore loading combinations and as-constructed state of the structure in estimating structural responses for fatigue behaviour to stochastically predict the remaining fatigue life. The present paper links the oceanographic data to fatigue damage by using measured strain, and uses the Bayesian approach to update the joint distribution of the oceanographic data. Consequently, the failure probability of the support structure can be updated and so the predicted fatigue life. The year-to-year variation of the 10-min mean wind speed, the unrepresentativeness of measured strain, the measurement uncertainty, and corrosion are considered together with uncertainties in Miner′s rule and S–N curves. The present research shows that the real oceanographic data can be used to adjust the predicted remaining fatigue life and eventually give decision support for the wind turbine operation. •Wind and wave are included in the stress-life (S-N) fatigue damage calculation of existing structures.•Wind speed distribution is updated using Bayesian approach and included in the limit state function.•Effect of year-to-year variation of annual mean wind speed is considered•The estimated fatigue life is very sensitive to the accuracy of the method used to derive stresses at the interested location from the measuring location.•The most probable hot-spot location is found by combining measured strain data of different wind directions.
Author Devriendt, Christof
Sørensen, John D.
Rigo, Philippe
Weijtjens, Wout
Mai, Quang A.
Morato, Pablo G.
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Cites_doi 10.1016/j.ress.2006.12.008
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10.1115/1.4009458
10.1016/S0951-8320(01)00087-4
10.1016/S0951-8339(01)00031-4
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10.1061/(ASCE)0733-9445(1984)110:10(2340)
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Keywords Measurement
Welded joints
Measured strain
Offshore
Remaining life
Inspection
Fatigue
Wind turbines
Reliability
Support structures
Monitoring
SCADA
Language English
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Snippet Reassessing the remaining fatigue life of the wind turbine support structures becomes more and more crucial for operation, maintenance, and life extension when...
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StartPage 307
SubjectTerms Bayesian analysis
Civil engineering
Corrosion
Crack propagation
Distribution
Engineering, computing & technology
Fatigue
Fatigue failure
Fatigue life
Ingénierie civile
Ingénierie, informatique & technologie
Inspection
Joints (timber)
Life extension
Life prediction
Measured strain
Measurement
Monitoring
Oceanographic data
Offshore
Offshore construction
Offshore engineering
Offshore structures
Probability theory
Product design
Reliability
Remaining life
SCADA
Service life
Strain measurement
Support structures
Turbine engines
Turbines
Uncertainty
Welded joints
Wind power
Wind speed
Wind turbines
Title Prediction of remaining fatigue life of welded joints in wind turbine support structures considering strain measurement and a joint distribution of oceanographic data
URI https://dx.doi.org/10.1016/j.marstruc.2019.05.002
https://www.proquest.com/docview/2245650005
http://orbi.ulg.ac.be/handle/2268/235724
Volume 66
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