Pile driveability in low- to medium-density chalk
Bibliographic record
Abstract
Pile driving in low- to medium-density chalk is subject to significant uncertainty. Predictions of “chalk resistance to driving” (CRD) often vary considerably from field driving behaviour, with both pile refusals and free falls under zero load being reported. However, recent field studies have led to better understanding of the processes that control the wide range of behaviour seen in the field. This paper describes the primary outcomes of the analysis of dynamic tests at an onshore and an offshore site and uses the results to propose a new method to predict CRD. The method is based on phenomena identified experimentally: the relationship between cone penetration resistance and CRD, the attenuation of local stresses as driving advances, and the operational effective stress interface shear failure characteristics. The proposed method is evaluated through back-analyses of driving records from independent pile installation cases that were not included in developing the method, but involved known ground conditions, hammer characteristics, and applied energies. The proposed method is shown to lead to more reliable predictions of CRD than the approaches currently applied by industry.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".