Specimen size effects on behavior of loose sand in triaxial compression tests
Bibliographic record
Abstract
Triaxial tests are often used to determine the behavior and strength characteristics of soils without due attention to the differences in specimen size. Several drained and undrained monotonic triaxial compression shear tests are performed in this study on three different specimen sizes of the same sand to investigate the influence of specimen size and scale effect on sand compression and shear behavior. The behavior of a sand specimen is strongly influenced by shear banding and specimen boundary conditions, which are manifested as specimen size effects in the test results of this study. The measured sand compressibility and shear strength parameters are employed to describe scale effects, and investigate specimen size effects in liquefaction triggering analysis. The results show that while larger specimens exhibit a less compressible behavior during isotropic compression, larger shear strengths and effective friction angles are mobilized in the smaller specimens during shearing. A number of geotechnical analyses can be significantly affected by variations in strength parameters of the same soil determined from different specimen sizes. While using small size specimens for determining shear strength parameters might result in an unconservative design, a large specimen size provides a more accurate representation of different soil strength conditions and field deformations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".