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Background <p>Offshore wind turbines (OWTs) play a key role in the shift toward renewable energy. Most fixed-bottom turbines rely on monopile foundations, making their structural behavior critical to overall system performance. One of the main challenges is predicting natural frequencies accurately, since resonance with environmental loads can lead to fatigue damage and reduced service life.</p> Objective <p>The goal of this study is to develop and validate a coupled analytical–computational approach for estimating the natural frequencies of monopile-supported OWTs, while reducing the need for computationally expensive numerical models.</p> Methods <p>Three approaches were used and compared in this study: a simplified analytical model based on a coupled-spring representation of the foundation, a custom finite element model developed in Python, and a high-fidelity model built in COMSOL Multiphysics. The analytical results were further checked using Rayleigh’s method and compared with a reference 5 MW wind turbine.</p> Results <p>The results from all three approaches are in close agreement. The difference between the analytical model and the numerical simulations (Python FE and COMSOL) stays below 3% across cases, indicating that the simplified model captures the dominant dynamic behavior of the system with good accuracy.</p> Conclusion <p>The proposed framework offers a practical balance between accuracy and efficiency. It avoids the cost of full-scale simulations while remaining more reliable than overly simplified approaches. As such, it can be used effectively for early-stage design, optimization, and dynamic evaluation of offshore wind turbines.</p>

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A Hybrid Analytical–Numerical Framework for Efficient and Accurate Natural Frequency Prediction of Offshore Wind Turbine Towers

  • 期刊论文

  • 发表日期：

    2026年3月23日

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  • Aref Aasi,
  • Sahar Ebrahimi Bajgani,
  • Roohollah Javahersaz,
  • Zahra Nazariharavani

摘要

Background

Offshore wind turbines (OWTs) play a key role in the shift toward renewable energy. Most fixed-bottom turbines rely on monopile foundations, making their structural behavior critical to overall system performance. One of the main challenges is predicting natural frequencies accurately, since resonance with environmental loads can lead to fatigue damage and reduced service life.

Objective

The goal of this study is to develop and validate a coupled analytical–computational approach for estimating the natural frequencies of monopile-supported OWTs, while reducing the need for computationally expensive numerical models.

Methods

Three approaches were used and compared in this study: a simplified analytical model based on a coupled-spring representation of the foundation, a custom finite element model developed in Python, and a high-fidelity model built in COMSOL Multiphysics. The analytical results were further checked using Rayleigh’s method and compared with a reference 5 MW wind turbine.

Results

The results from all three approaches are in close agreement. The difference between the analytical model and the numerical simulations (Python FE and COMSOL) stays below 3% across cases, indicating that the simplified model captures the dominant dynamic behavior of the system with good accuracy.

Conclusion

The proposed framework offers a practical balance between accuracy and efficiency. It avoids the cost of full-scale simulations while remaining more reliable than overly simplified approaches. As such, it can be used effectively for early-stage design, optimization, and dynamic evaluation of offshore wind turbines.