Seismic Response of Monopile-Supported OWT Structure Considering Effect of Long-Term Cyclic Loading
Bibliographic record
Abstract
Offshore wind turbine (OWT) structures are subject to wave, wind, and seismic loading. Due to the cyclic nature of these loads, OWT foundations can be vulnerable to cumulative deformation and liquefaction triggered by waves and earthquakes. The effects of cumulative deformation and liquefaction on the monopile-supported OWT are not fully appreciated. This paper develops a three-dimensional numerical model for analyzing the seismic performance of large monopile-supported OWT under the long-term effect of cyclic loading. The numerical model was established employing FLAC3D and utilizing SANISAND constitutive model to simulate the soil behavior. The numerical model was validated by comparing its predictions with the results of dynamic triaxial tests and centrifuge tests. A simplified densification and subsidence site model was integrated into the numerical model to facilitate considering the long-term effect of cyclic loading. The numerical model was then used to conduct a comprehensive study to evaluate the influence of long-term cyclic loading on the natural frequency and seismic response of OWT structure. The results demonstrated that the densified subsidence zone around monopile increased the liquefaction resistance. However, the horizontal displacement of pile and the response acceleration of tower-top increased due to soil subsidence around monopile.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".