Numerical investigation on the pullout capacity of suction caissons in silty sand-over-clay deposit
Bibliographic record
Abstract
This research offers an in-depth numerical analysis on the pullout capacity of suction caissons in sand-over-clay deposits. A validated finite element (FE) model is employed and cross-referenced with existing centrifuge tests and numerical data. A parametric analysis is conducted to examine the variables affecting the pullout capacity of suction caissons, including caisson’s length, pad-eye position, and layered deposits. The FE analysis yields some insights into the following key design components: (i) the optimal pad-eye locations; (ii) the ultimate horizontal and vertical bearing capacities; and (iii) the horizontal load estimation at various pad-eyes attachments. A straightforward guideline for calculating the caisson’s pullout capacities is then established for preliminary estimations for suction caissons in silty sand-over-clay deposit.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".