Stiffness-proportional foundation damping to linearise soil-monopile interaction models for wind turbines
Bibliographic record
Abstract
The structural design of offshore wind turbines must account for numerous design load cases to capture various scenarios, including power production, parked conditions, and emergency or fault conditions under different environmental conditions. Given the stochastic nature of these external actions, deterministic analyses using characteristic values and safety factors, or Monte Carlo Simulations, are necessary. This process involves a large number of simulations, ranging from ten to a hundred thousand, to achieve a reliable and optimal structural design. To reduce computational complexity, practitioners can employ low-fidelity models where the soil-foundation system is either neglected or simplified using linear elastic models. However, medium to large cyclic soil-pile lateral displacements can induce soil hysteretic behaviour, potentially mitigating structural and foundation vibrations. A practical solution at the preliminary design stage entails using stiffness-proportional viscous damping to capture the damping generated by the soil-pile hysteresis. This paper investigates the efficacy of this simplified approach for the IEA 15 MW reference wind turbine on a large-diameter monopile foundation subjected to several operational and extreme wind speeds. The soil-pile interaction system is modelled through lateral and rotational springs in which a constant stiffness-proportional damping model is applied. The results indicate that the foundation damping generated by the nonlinear soil-pile interaction is significant and cannot be neglected. When fast analyses are required, the stiffness-proportional viscous damping model can be reasonably used to approximate the structural response of the wind turbine. This approach enhanced the accuracy of the computed responses, including the maximum bending moment at the mudline for ultimate limit design and damage equivalent loads for fatigue analysis, in comparison to methods that disregard foundation damping. • The stiffness-proportional foundation damping can be effectively used for simplified offshore wind turbine models. • A nonlinear translational and rotational soil-pile interaction model is calibrated for the IEA 15MW Reference Wind Turbine. • Key responses, such as mudline bending moment and Damage Equivalent Load, are strongly affected by the foundation damping. • Comparison between the nonlinear model and the linearized model demonstrates that foundation damping cannot be ignored. • Stiffness-proportional damping is a viable approach for preliminary design, reducing the computational demands.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".