Effect of Specimen Size and Boundaries on the Results of Direct Simple Shear Tests
Bibliographic record
Abstract
Direct simple shear (DSS) tests are widely used to capture the shearing behavior of soils. A major concern with a DSS test is the non-uniform distributions of stress and strain on the horizontal platens of this device. A series of DSS simulations were carried out in this study using 3D discrete element analysis (DEM) to examine the effects of specimen size and boundary conditions. The gradation of a coarse sand was used to generate different sphere sizes, which were then uniformly spread throughout the model. While smooth lateral walls were used, the horizontal boundaries had a high coefficient of friction to minimize slippage. A constant-volume condition was imposed by controlling boundary displacements. Different specimen diameters were modeled to examine the effect of diameter-to-height ratio (D/H) on stress path, peak shear stress, and post peak behavior. Numerical simulations indicated that boundary effects became more prominent at higher consolidation stresses for a given D/H. Such boundary effects were, however, reduced by enlarging the sample diameter (i.e., raising D/H). Specimen boundary effects were minimized in specimens with a D/H ≥ 2.8, resulting in the same shearing behavior as those with larger D/H ratios.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".