Experimental Investigation of Suction Installation Behavior of Caissons in Loose Saturated Sands
Bibliographic record
Abstract
With the continuous expansion of global offshore wind power, suction caissons are increasingly becoming a significant foundation form due to their advantages such as low installation noise, convenient construction, and reusability. However, localized seepage induced soil disturbance and strength changes during their installation remain underexplored, leading to uncertainties in their capacity assessment. This paper presents a series of experimental investigations in loose saturated sand, comparing suction and embedded installations for caissons with varying length-to-diameter (L/D) ratios coupled with Cone Penetration Tests (CPT) to evaluate soil strength changes inside and outside the caissons. For both installations, the results reveal similar lateral load-bearing capacities (0.12 kN) for shorter caissons (L = 120 mm), whereas for longer suction installed caissons (L = 240 mm), the capacity was reduced by approximately 80%, due to internal soil weakening and an upward shift of the rotation centre. CPT data further revealed compaction enhancement outside and seepage-induced reduction in soil strength inside the caisson, jointly affecting failure behavior. Based on these findings, the conventional bearing capacity formula for fully embedded caissons was modified to account for partial embedment and external-internal soil strength differences, and a novel mechanically-derived failure criterion was proposed, accurately capturing non-linear load responses and improving prediction of suction caisson capacity for various load eccentricities and L/D ratios, thus supporting optimized offshore foundation design.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".