Characterization of layered seabed soil spatial variability and its effect on the bearing capacity of offshore monopile foundations
Bibliographic record
Abstract
Due to the lack of knowledge of site-specific data and corresponding pile test results, the reliability of random finite element analysis (RFEM) on monopile and its findings remain questionable. This paper performed an RFEM on monopile in a specific offshore wind farm. The spatial variability of soil parameters in each seabed layer was carefully characterized based on both laboratory test results and calibrated in situ CPTU data. Statistical results demonstrated substantial variability in undrained shear strengths of two silty clay layers and insignificant variability in friction angles of three sandy soil layers, and all soil properties following lognormal distribution. RFEM incorporating the spatial variability of two silty clay layers was conducted to examine the probability distribution of monopile's bearing capacities. The monopile was wished-in-place to overcome the convergence difficulty induced by the deep penetration of pipe piles in the layered seabed. Monte Carlo simulation findings suggest that the spatial variability of soil strength resulted in an overprediction of the vertical bearing capacity, comparison between the statistical results of monopile capacities from RFEM and 43 pile test data in the field proves the reliability of the numerical method. Finally, a quantitative relationship between the safety factor and failure probability was developed to improve monopile design.
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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 | 0.001 | 0.001 |
| 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".