Soil flow mechanisms around and between stiffeners of caissons during installation in clay
Bibliographic record
Abstract
Structural stiffeners placed inside caissons have created significant uncertainty regarding soil flow mechanisms, side friction, and end bearing, and consequently in the prediction of the underpressure required for installation. This paper describes centrifuge modelling of the penetration of stiffened skirts in overconsolidated clay, identifying the soil flow mechanisms around and between stiffeners and the penetration resistance. The effects of stiffener width and spacing as well as soil strength ratio are discussed. The present guidelines for predicting the point of soil backflow in the gap that forms between the stiffeners are shown to be invalid and a new expression, based on a stability factor (su/γ′B, where su and γ′ are the undrained shear strength and effective unit weight of the soil, respectively, and B is the combined width of the skirt and stiffener close to the caisson tip) is proposed. End bearing at the skirt tip and base stiffener are seen to dominate installation resistance. The normalized installation resistance stabilizes at a value of ∼17.5 at deep penetrations and is shown to be independent of whether the cavity between the stiffeners remains open or is backfilled with a soil–water mixture. This factor of 17.5 is shown to be in good agreement with reported field data and centrifuge test data and hence may be used to obtain a first-order estimate of the installation resistance of a caisson with stiffeners.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".