Bearing Capacity of a Group of Stone Columns in Soft Soil Subjected to Local or Punching Shear Failures
Bibliographic record
Abstract
The use of stone columns is a viable, cost-effective, and environmentally friendly ground improvement technique. Columns are made of compacted aggregate and installed in soft soil as reinforcements to increase the bearing capacity and to reduce foundation settlement. In the literature, the methods available to estimate the bearing capacity of soil reinforced with stone columns assumed bulging and general shear as the only modes of failure. However, ground reinforced with stone columns may also fail by local or punching shear mechanisms, depending on the soil, columns, and geometry of the system. This paper presents analytical models to estimate the bearing capacity of the foundation on a soft soil reinforced with stone columns that are subjected to local or punching shear failure mechanisms. The models were based on a limit equilibrium technique and the composite soil properties. The proposed theories were validated with experimental and analytical data available in the literature. Design charts are presented for practical purposes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".