Peak punch-through capacity of spudcan in sand with interbedded clay: numerical and analytical modelling
Bibliographic record
Abstract
The presence of a thin soft clay layer inside a bed of sand may significantly reduce the bearing capacity of the sand layer, imposing a risk of punch-through failure. In this paper, finite element (FE) simulations are reported using a hardening soil (HS) model for sand. The FE model has been verified against centrifuge tests involving loose and dense sand layers overlying clay soil. The effects of sand stiffness, foundation roughness, sand friction angle, undrained clay strength, clay strength nonhomogeneity, and sand and clay layer geometries on the foundation peak capacities have been studied. Punch-through failure is initiated with an inclined sand plug being sheared and pushed into the underlying soft clay. During punch-through, the clay layer fails due to significant radial squeezing. Existing analytical models do not capture the combined failure mechanism of sand shearing and clay radial squeezing. A new analytical model is developed to estimate the peak punch-through capacity of a spudcan in sand with an interbedded clay layer, showing improved performance over the current industry guidelines.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".