Bibliographic record
Abstract
The current research investigation is focused on estimating the theoretical capacity of a rehabilitated steel marine pile. The old steel pile can be rehabilitated by installing new concrete encasement (jacket). The new concrete jacket can be easily connected to the old steel pile using shear friction between old pile and new concrete jacket or additional mechanical or welded connection. The under-water welding process is a very expensive task and considerable saving can be realized by eliminating this process. A previous experimental investigation was conducted to evaluate the behaviour of the rehabilitated steel pile. The maximum load and the load-slip deformation data were recorded for all of the tested specimens. The test results indicated that the marine pile can be efficiently rehabilitated by installing a concrete jacket using shear friction principles or the bolted connection to avoid the expense of welding under-water. The theoretical study included the investigation of surface friction, shear friction mechanism and cohesion on the bond capacity. The effect of the bolted anchor on increasing the effective cross section of the rehabilitated pile is examined. After investigating the predicted values of various equations developed by various researchers, the shear friction mechanical model developed by CSA 1994 is recommended to be used as the most effective formula that can provide an accurate prediction for the rehabilitated pile capacity.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".