Field tests on large-scale instrumented piles driven in chalk: results and interpretation
Bibliographic record
Abstract
The design of large open steel piles driven at chalk sites suffers from considerable uncertainty, leading to major difficulties in many significant onshore and offshore projects. This paper describes recent instrumented driving, monotonic testing to failure, and restrike tests conducted on large open steel piles driven in primarily low- to medium-density chalk at a site in North-western France. The experiments are described and interpreted with reference to a high-quality site characterisation, dynamic and static methods of test analysis, and alternative predictive design approaches. Important new conclusions flow regarding driving behaviour, the set-up that took place over up to 65 days after installation and the resistances available under compression and tension loading. Surprisingly large differences are shown between tension and compression shaft capacity, which are postulated to be due to Poisson straining in the steel pile shaft and its interaction with the surrounding chalk mass. The field tests contribute to building a high-quality dataset that allows proposed axial capacity design methods to be tested and potentially refined to provide reliable and representative design tools.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".