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Multiphysics surrogate-based model updating of a jacket-supported offshore wind turbine using measured vibration and SCADA data
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DOI：10.3389/fenrg.2026.1847071.png)
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Abstract
En 中文
Multiphysics models are often utilized for structural design; condition assessment; and response prediction of a system; such as the support structure of offshore wind turbines. Although multiphysics models are considered to be of high fidelity; discrepancies are often observed between the model predictions and actual data measurements from the real structure. The model updating process reduces the model parameter uncertainty by minimizing the differences between the model and the measured data through an optimization procedure. In this paper; such a procedure is applied to an instrumented GE Haliade 6-MW jacket-supported offshore wind turbine by updating the tower and substructure modulus of Elasticity (E) to minimize differences between modal parameters identified from 1 month of measurements and those obtained from the OpenSees model or predicted from surrogate models. Surrogate models; including a neural network and a polynomial regression fit; are used to replace the OpenFAST simulations. The results indicate that the fully coupled OpenFAST model provides a more physically consistent representation in the medium power range (0.5–4.5 MW) by reducing variability in the updated E; whereas the OpenSees model is more suitable for low and high categories; where pitch control and reduced aerodynamic loading limit the influence of aero-hydro-servo-elastic effects.
Keywords:
structural health monitoring
multiphysics modeling
model updating
Block Island Wind Farm (BIWF)
offshore wind turbine (OWT)
Journal
IF:
2.4
Papers:
923
Citations:
1.4W
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