Experimental and numerical studies on lateral bearing characteristics of innovative gravel-filled canister-monopile (GCM) hybrid foundation
Bibliographic record
Abstract
In recent years, the monopile foundation is increasingly utilized to support offshore wind turbines (OWT). However, as the OWT becomes larger, a larger monopile diameter is always required to resist lateral loads, resulting in an increase in the construction cost and installation effort of the monopile. Therefore, an innovative gravel-filled canister-monopile (GCM) hybrid foundation is proposed to provide greater lateral bearing capacity of monopile without raising construction cost and minimizing installation effort. The hybrid foundation that integrates an additional canister filled with gravel alongside the monopile, can increase the horizontal bending stiffness and improve soil resistance as the soil beneath the canister. To evaluate the lateral bearing capacity of the GCM hybrid foundation and compare it with the conventional monopile, the model tests as well as the finite element analysis are conducted in this regard. The results show that the hybrid foundation outperforms the monopile in terms of increasing lateral bearing capacity, moment resistance and reducing lateral deformation. Furthermore, a thorough parametric study evaluating the effects of canister dimensions, backfill properties and loading eccentricity on the lateral bearing characteristics of a hybrid foundation are evaluated. Some design suggestions are provided for the further application of the hybrid foundation in OWT projects.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".