Evaluation of ultimate limit state design of piles subjected to drag force based on Canadian Highway Bridge Design Code and AASHTO LRFD Bridge: field study and numerical modeling
Bibliographic record
Abstract
Consideration of drag force in the geotechnical ultimate limit state (ULS) design of piled foundations influenced by ground settlement has posed a challenge due to inconsistencies across different codes. This study compares the geotechnical ULS design provisions of two widely used North American bridge design codes, AASHTO and Canadian Highway Bridge Design Code (CHBDC), through a case study of a production steel H-pile subjected to embankment-induced loading. The investigation includes direct field measurements, pile dynamic analysis, and numerical simulations. AASHTO incorporates drag force in geotechnical ULS design, leading to conservative estimates, whereas CHBDC omits it from ULS calculations. However, due to differing load and resistance factors and the magnitude of the drag force, CHBDC's design provisions were found to yield more conservative results in this study. Furthermore, adopting pile capacity derived from restrike measurements versus end of initial driving in dynamic analysis was found to provide higher resistance in geotechnical ULS design due to shaft setup.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".