Assessment of the unified design method for piles subjected to negative skin friction using field studies and numerical modeling
Bibliographic record
Abstract
This study presents field measurements and numerical simulations to evaluate drag force and downdrag as a result of negative skin friction on an H-pile driven into clay till stratigraphy subjected to embankment loading. The validated numerical model results with field measurement data as well as pile dynamic test results are compared with predictions from the unified design method. The comparison is made for two pile positions in the cap, the most and the least critical, based on axial force along the shaft. Findings indicated that both methods demonstrated the neutral plane at nearly the same depth. However, the unified design method overestimated the maximum axial force along the shaft, as well as drag force and downdrag, in both pile scenarios. This method also indicated a smaller difference in maximum axial force between the most and least critical pile locations compared to the numerical modeling. Finally, the unified design method may neglect the shaft setup effect in calculating the target resistance of piles in soils with this potential. Considering the setup effect in evaluating the pile resistance subjected to negative skin friction can lower the neutral plane, reduce downdrag estimates, and increase drag force capacity, leading to a more efficient design.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".