Performance evaluation of Composite Caisson-Pile Foundation (CCPF) in sand using finite element model
Bibliographic record
Abstract
Caisson (Well) foundation has been widely used in South Asian countries like Nepal, India for construction of bridge piers and abutments. Generally, the caisson is cast in the ground and slowly sunk to the desired depth by gravity. But, due to sinking difficulties, designers are discarding it despite its several advantages. To overcome such a peculiar situation by taking advantage of caisson foundation, a composite caisson-pile foundation (CCPF) has been recently proposed and used to construct a bridge foundation in Nepal. This study aims to investigate the load-settlement behaviour of CCPFs resting on sand subjected to vertical load using three-dimensional finite element analyses. Through other numerical and experimental studies, the accuracy of the finite element analysis was proven to be correct and valid. A detailed parametric study is conducted, which includes the influence of pile length, number of piles and friction angle on the performance of CCPF embedded in sand.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".