Evaluation of Tuned Mass Damper for Offshore Wind Turbine Using Coupled Fatigue Analysis Method

This study proposes an integrated fatigue life assessment methodology to accurately evaluate the time-domain evolution in tubular joint fatigue damage in offshore wind turbine (OWT) jacket structures under long-term combined wind and wave actions. A customized post-processing module was developed via secondary development on the MLife platform, employing a conditional probability distribution model to perform joint probabilistic modeling of measured marine environmental data, thereby establishing a long-term joint wind–wave distribution database. The reconstruction of hotspot stress time histories at the tubular joints was achieved through a hybrid analytical–numerical approach, integrating analytical formulations of nominal stress with a multi-axial stress concentration factor (SCF) matrix. Long-term fatigue damage assessment was implemented using the Palmgren–Miner linear cumulative damage hypothesis, where a weighted summation methodology based on joint wind–wave probability distributions rigorously accounted for the statistical contributions of individual design load cases. An ultimate bearing capacity analysis was also conducted based on S-N fatigue endurance characteristic curves. This research specifically investigates the influence mechanisms of tuned mass dampers (TMDs) on the time-domain-coupled fatigue performance of tubular joints subjected to long-term combined wind and wave loads. Numerical simulations demonstrate that parametrically optimized TMD systems significantly enhance the fatigue life metrics of critical joints in jacket structures.

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Publication Details

Journal
Energies
Published
2025-09-09
DOI
https://doi.org/10.3390/en18184788
Citations
1
Primary Topic
Wind and Air Flow Studies
Type
article
Field-Weighted Citation Impact
0.80

Funders

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Evaluation of Tuned Mass Damper for Offshore Wind Turbine Using Coupled Fatigue Analysis Method

Xinyun Wu, Yongqing Lai, Yanwen Zhang, Xin Li et al.
1 citations
Energies
Wind and Air Flow Studies
0.80
article

Evaluation of Tuned Mass Damper for Offshore Wind Turbine Using Coupled Fatigue Analysis Method

Xinyun Wu, Yongqing Lai, Yanwen Zhang, Xin Li, Bin Wang, Wenhua Wang
article en
1 citations

Abstract

This study proposes an integrated fatigue life assessment methodology to accurately evaluate the time-domain evolution in tubular joint fatigue damage in offshore wind turbine (OWT) jacket structures under long-term combined wind and wave actions. A customized post-processing module was developed via secondary development on the MLife platform, employing a conditional probability distribution model to perform joint probabilistic modeling of measured marine environmental data, thereby establishing a long-term joint wind–wave distribution database. The reconstruction of hotspot stress time histories at the tubular joints was achieved through a hybrid analytical–numerical approach, integrating analytical formulations of nominal stress with a multi-axial stress concentration factor (SCF) matrix. Long-term fatigue damage assessment was implemented using the Palmgren–Miner linear cumulative damage hypothesis, where a weighted summation methodology based on joint wind–wave probability distributions rigorously accounted for the statistical contributions of individual design load cases. An ultimate bearing capacity analysis was also conducted based on S-N fatigue endurance characteristic curves. This research specifically investigates the influence mechanisms of tuned mass dampers (TMDs) on the time-domain-coupled fatigue performance of tubular joints subjected to long-term combined wind and wave loads. Numerical simulations demonstrate that parametrically optimized TMD systems significantly enhance the fatigue life metrics of critical joints in jacket structures.

EnergiesVol. 18(18)
Dalian University of Technology (CN), Powerchina Huadong Engineering Corporation (China) (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 25%
Wind and Air Flow Studies
0.80
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