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Fatigue Damage Assessment of Offshore Wind Turbine Foundation Under Coupled Wind–Wave Loading Using Surrogate Modeling.

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Title: Fatigue Damage Assessment of Offshore Wind Turbine Foundation Under Coupled Wind–Wave Loading Using Surrogate Modeling.
Authors: Dai, Chong1 (AUTHOR), Zhao, Jinhai1,2 (AUTHOR) zhaojinhai87@126.com, Sun, Rui1 (AUTHOR)
Source: Energies (19961073). May2026, Vol. 19 Issue 10, p2383. 24p.
Subject Terms: *Machine learning, *Prediction models, *Offshore wind power plants, *Finite element method, *Soil-structure interaction, *Structural dynamics, *Wind waves, *Fatigue cracks
Abstract: This study develops an efficient fatigue prediction framework for offshore wind turbine (OWT) monopile foundations under coupled wind–wave conditions using four surrogate models: XGBoost, Random Forest (RF), Support Vector Regression (SVR), and Gaussian Process Regression (GPR). A finite element model (FEM) incorporating soil–pile interaction is established to accurately capture structural responses under realistic environmental loading. Fatigue damage is evaluated through time-domain simulations based on this model. A surrogate modeling approach is employed to capture the nonlinear mapping between environmental variables and fatigue damage using 60 representative samples. Results show that the proposed framework significantly improves computational efficiency while maintaining predictive reliability. Among the models evaluated, GPR yields the highest prediction accuracy, while SVR shows comparable performance. In contrast, XGBoost and RF exhibit relatively larger deviations. Parametric analysis reveals that fatigue damage is positively correlated with wind speed and significant wave height, but inversely correlated with peak wave period. Further, wind-induced loading dominates fatigue accumulation, and conventional load superposition methods underestimate fatigue damage due to nonlinear wind–wave coupling effects. Furthermore, fatigue damage exhibits pronounced circumferential variation, with maximum values occurring in the fore-aft directions. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 194141498
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Fatigue Damage Assessment of Offshore Wind Turbine Foundation Under Coupled Wind–Wave Loading Using Surrogate Modeling.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Dai%2C+Chong%22">Dai, Chong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhao%2C+Jinhai%22">Zhao, Jinhai</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> zhaojinhai87@126.com</i><br /><searchLink fieldCode="AR" term="%22Sun%2C+Rui%22">Sun, Rui</searchLink><relatesTo>1</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. May2026, Vol. 19 Issue 10, p2383. 24p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink><br />*<searchLink fieldCode="DE" term="%22Offshore+wind+power+plants%22">Offshore wind power plants</searchLink><br />*<searchLink fieldCode="DE" term="%22Finite+element+method%22">Finite element method</searchLink><br />*<searchLink fieldCode="DE" term="%22Soil-structure+interaction%22">Soil-structure interaction</searchLink><br />*<searchLink fieldCode="DE" term="%22Structural+dynamics%22">Structural dynamics</searchLink><br />*<searchLink fieldCode="DE" term="%22Wind+waves%22">Wind waves</searchLink><br />*<searchLink fieldCode="DE" term="%22Fatigue+cracks%22">Fatigue cracks</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study develops an efficient fatigue prediction framework for offshore wind turbine (OWT) monopile foundations under coupled wind–wave conditions using four surrogate models: XGBoost, Random Forest (RF), Support Vector Regression (SVR), and Gaussian Process Regression (GPR). A finite element model (FEM) incorporating soil–pile interaction is established to accurately capture structural responses under realistic environmental loading. Fatigue damage is evaluated through time-domain simulations based on this model. A surrogate modeling approach is employed to capture the nonlinear mapping between environmental variables and fatigue damage using 60 representative samples. Results show that the proposed framework significantly improves computational efficiency while maintaining predictive reliability. Among the models evaluated, GPR yields the highest prediction accuracy, while SVR shows comparable performance. In contrast, XGBoost and RF exhibit relatively larger deviations. Parametric analysis reveals that fatigue damage is positively correlated with wind speed and significant wave height, but inversely correlated with peak wave period. Further, wind-induced loading dominates fatigue accumulation, and conventional load superposition methods underestimate fatigue damage due to nonlinear wind–wave coupling effects. Furthermore, fatigue damage exhibits pronounced circumferential variation, with maximum values occurring in the fore-aft directions. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/en19102383
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 24
        StartPage: 2383
    Subjects:
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Prediction models
        Type: general
      – SubjectFull: Offshore wind power plants
        Type: general
      – SubjectFull: Finite element method
        Type: general
      – SubjectFull: Soil-structure interaction
        Type: general
      – SubjectFull: Structural dynamics
        Type: general
      – SubjectFull: Wind waves
        Type: general
      – SubjectFull: Fatigue cracks
        Type: general
    Titles:
      – TitleFull: Fatigue Damage Assessment of Offshore Wind Turbine Foundation Under Coupled Wind–Wave Loading Using Surrogate Modeling.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Dai, Chong
      – PersonEntity:
          Name:
            NameFull: Zhao, Jinhai
      – PersonEntity:
          Name:
            NameFull: Sun, Rui
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 05
              Text: May2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 19961073
          Numbering:
            – Type: volume
              Value: 19
            – Type: issue
              Value: 10
          Titles:
            – TitleFull: Energies (19961073)
              Type: main
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