Bibliographic record
Abstract
This paper presents an experimental investigation on the influence of embedment depth on the anchor failure mode. It is widely understood that a deep anchor will behave differently compared to a shallow anchor. A test set-up is developed in this research to capture soil deformation during anchor uplifting, which consists of a camera, a loading frame, a Plexiglas mould, and a computer. A series of model tests are performed to investigate the influence of the anchor embedment depth on soil deformation. A set of images are captured while a semicircular anchor is being uplifted against the Plexiglas window. A soil displacement field is calculated from two images using the Digital Image Correlation (DIC) method. The failure surface is studied by locating the maximum shear strains deduced from the soil displacement field. Based on this study, it is found that the anchor behaviour is substantially influenced by the anchor embedment depth. A similar punching failure mode is observed in loose sand regardless of the anchor depth. However, in dense sand a restrained failure mode is observed in a deep anchor opposite to the mode with failure plane extending to ground surface in a shallow anchor. This study improves the understanding of soil-anchor interaction and helps to design an efficient anchor system.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".