Reliability-based calibration of resistance factors for static bearing capacity of driven steel pipe piles
Bibliographic record
Abstract
As part of a study to develop load and resistance factor design (LRFD) codes for foundation structures in South Korea, resistance factors for the static bearing capacity of driven steel pipe piles were calibrated in the framework of the reliability theory. A database of 52 static load test results was compiled, and the data from these load test piles were sorted into two cases: a standard penetration test (SPT) N-value at pile tip (i) less than 50 and (ii) equal to or more than 50. Reliability analyses and resistance factor calibration for the two static bearing capacity analysis methods adopted in the Korean Design standards for foundation structures were performed using the first-order reliability method (FORM) and the Monte Carlo simulation (MCS). Reliability indices and resistance factors computed by the MCS are statistically identical to those computed by FORM. Target reliability indices were selected as 2.0 and 2.33 for the group pile case and 2.5 for the single pile case. The resistance factors recommended from this study are specific for the pile foundation design and construction practice and the subsurface conditions in South Korea.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".