Miniature cone tip resistance of sand with fly ash using triaxial setup
Bibliographic record
Abstract
In a continuation of the authors’ recent work, the ultimate tip resistance of a miniature cone using triaxial equipment was determined for samples of dry sand mixed with dry fly ash. The effect of (i) the proportion of fly ash, (ii) the relative density of samples, and (iii) the vertical overburden pressure was examined. It was noted that an addition of fly ash in sand for the same range of relative density leads to a significant reduction in the ultimate tip resistance of the cone (qcu). This occurs due to a decrease in the friction angle (ϕ) of the sample with an increase in the fly ash content for a given relative density. For ϕ greater than about 30°, two widely used correlation curves from published literature, providing the relationships between qcuand ϕ for cohesionless soils, were found to provide satisfactory predictions, even for sand – fly ash mixtures. As was expected, the values of qcuincrease continuously with an increase in the relative density of the soil mass and the vertical effective (overburden) stress on the 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".