Effectiveness of granular columns in containing settlement
Bibliographic record
Abstract
Laboratory-based research studies and full-scale evaluations of the behaviour of ground improved with granular columns are ample regarding bearing capacity, but limited in respect to the settlement response. This paper presents a laboratory model study that considers the settlement performance of isolated pad footings bearing on reinforced sand deposits under the influence of a fluctuating groundwater table. This is a particularly onerous condition for loose sand deposits in coastal areas, which may undergo significant collapse settlement over time. Loose and dense experimental sand beds were constructed, and the performance of rigid footings under a maintained load and bearing on sand incorporating different column configurations was monitored under cycling of the water table over a period of 28 d, with one filling/empting cycle every 18 h. It was found that settlement, while greatly reduced compared with that for unreinforced footings, was ongoing, and typically occurred at a much greater rate for loose sand than for dense sand. Also, settlement rates were slightly higher for fully penetrating than partially penetrating columns, and also for footings reinforced by a column group rather than a single column. This was attributed to the migration of sand grains into the larger column voids.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".