Near-surface soils: self-supported unconfined drained sand specimens
Bibliographic record
Abstract
Knowledge about soil behaviour in the near surface is fundamental to a broad range of military strategic research efforts. The prevailing mathematical representations of near-surface shear strength do not necessarily reflect the observed shear strengths. This paper presents an experimental procedure for testing self-supported, unconfined-drained specimens to investigate the shear strength of a poorly graded sand with the inferred unsaturated behaviour from typical effective stress expressions. The impact of soil suction is quantified from the soil–water characteristic curve obtained from a modified, unsaturated, one-dimensional oedometer device: Fredlund’s device. Seventy-seven unconfined tests illustrate that while individual or discrete states can be explained by effective stress relationships, those expressions do not accurately quantify the observed shear strength from one state to the next. Saturation failure is observed when the degree of saturation is between 70.5% and 76.5%, well below the assumed threshold. The results show that the dry shear resistance is a function of the initial density state, but as the degree of saturation increases, the shear resistance becomes independent of the initial density, and converges to the saturation failure. These findings expose the limitations of effective stress expressions and suggest a revised nonlinear, three-dimensional, unconfined Mohr failure envelope based on an applied external stress.
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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 | 0.000 |
| 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) | 0.001 | 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".