Large deformation analysis of suction caisson installation in clay
Bibliographic record
Abstract
Large deformation finite element (LDFE) analyses were performed to study the installation of caissons by suction and jacking in normally consolidated clay. The penetration of the caisson wall was modelled between depths of one and four diameters using an axisymmetric LDFE approach, which falls in the category of arbitrary Lagrangian–Eulerian (ALE) methods. The results allowed quantification of differences in the behaviour of caissons installed entirely by jacking compared with a combination of self-weight and suction as is used in the field. For jacked installation, over the penetration range of one to four diameters, the proportion of caisson wall accommodated by inward soil flow reduced from around 45% at the start to zero at about four diameters embedment; by contrast, the proportion for suction installation stayed essentially constant, oscillating around 65% through the depth of penetration. This difference was also evident in the local incremental displacements of the soil beneath the caisson tip. During continuous penetration, the induced increases in radial and mean total stresses around the caisson wall are some 10%–15% smaller for suction installation than for jacked installation, with the difference growing with increasing penetration. In addition, an obvious difference was found in the caisson tip resistance between these two installation methods.Key words: suction caisson, clay, large deformation finite element, soil plug, total stress changes, penetration resistance, factor of safety.
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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 | 0.000 |
| 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".