Development of an Instrumented Settling Column for Use in a Geotechnical Centrifuge
Bibliographic record
Abstract
A geophysically and geotechnically instrumented settling column is used in conjunction with a geotechnical centrifuge, to monitor changing physical properties during the self-weight consolidation of a kaolin clay slurry. The column was equipped to monitor changes in excess pore pressure, bulk density and compressional wave velocity. The kaolin sample discussed in this paper was subject to an acceleration field of 100 g. The sample achieved 100% primary consolidation within 3 hours, excess pore pressures dissipating in a manner similar to that reported for 1 g settling column experiments. During this time the sample settled from a 0.865 m thick suspension to a 0.150 m thick soil deposit. The compressional wave velocity and density data, collected at one point in the sample, provided insight into the development of the soil during the centrifugation process. These data showed that below 1200 kg/m3 the sample behaved as a suspension, which is comparable to the results of other researchers and consistent with suspension theory. Above this density, the experimental data indicates that the sample begins to develop a fabric and, as a consequence, the compressional wave velocity increases to values greater than those predicted by suspension theory. There are some issues which need to be resolved through further data analysis or centrifuge tests, but the principle aim of the experiment was successfully achieved. That is to demonstrate that the instrumented settling column for use in geotechnical centrifuge is an extremely useful technology for evaluating soft soil properties and behaviour in a time efficient and cost effective manner.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".