Model Pile Pull-Out Tests Using Polyethylene Sheets to Reduce Downdrag on Cast In Situ Piles
Bibliographic record
Abstract
Abstract Low-density polyethylene sheets (LDPE) were used in this study to investigate its effectiveness in reducing downdrag on cast in situ piles. Eight model pile pull-out tests were conducted using three reinforced concrete circular model piles with different surface conditions (smooth, smooth with necking and bulging, and rough) in combination with three different LDPE sheet arrangements (one-sheet, two-sheet, and three-sheet). The pile was embedded partially in Ottawa sand with a surcharge of 19.3 kPa on sand surface. The test results showed that an arrangement with 3 pieces of 0.25-mm thick LDPE sheet was most effective in reducing side friction up to an average of 89 %. It was also found that the effectiveness of LDPE sheets is independent of the concrete surface roughness. However, the presence of necking and bulging was found to increase the side resistance up to 40 % for the plain pile without LDPE sheets.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".