Development of a Miniature Cone Penetrometer for Calibration Chamber Testing
Bibliographic record
Abstract
Abstract Cone penetration testing (CPT) has become the industry standard for in situ testing of cohesionless soils, and in particular, field liquefaction evaluation. The empirical methods for the interpretation of CPT data are either based on field data or the observation of CPT measurements in laboratory samples. In this study, a miniature cone penetrometer (with a diameter of 6 mm) is developed for understanding the response of loose to medium-dense sands. A modified triaxial cell is used for sample preparation and containment of the sample during cone penetration. The miniature cone can measure cone tip resistance, sleeve friction, and excess pore water pressure developed at the cone tip. While cone tip resistance is measured by a separate load cell, sleeve friction is obtained by subtracting cone tip resistance from a combined measurement of tip resistance and sleeve frictional force. Due to the free-draining nature of the sand tested in this study, no excess pore water pressure is developed during cone penetration. The measured data from the miniature cone are verified by comparison with CPT resistances measured in several other calibration chamber experiments on similar sands. Compared to a large calibration chamber with a standard size cone, the miniature cone allows quicker and less expensive CPT experiments in a more uniform sample.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".