Influence of specimen nonuniformity and end restraint conditions on drained triaxial compression test results in sand
Bibliographic record
Abstract
Drained triaxial compression tests on sand are common in geotechnical engineering due to their application in determining strength and critical state properties, and calibration of constitutive models. However, questions around reliability of test results due to strain localization and specimen nonuniformity have sparked debate around the adequacy of various specimen preparation techniques and configuration of top cap and bottom pedestal, among other variables. A rigorously calibrated and validated three-dimensional finite element model using an advanced constitutive model, NorSand, was used to address some of these concerns. The results generally confirmed that common specimen preparation techniques, moist tamping, and (air or water) pluviation, if done properly, can reasonably estimate the properties of a perfectly uniform specimen with the same density. Unsurprisingly, it was also confirmed that the post-peak response of dense specimens is by far the most sensitive part of sand behaviour characterized by these tests. It was suggested that for two-to-one height-to-diameter ratio specimens, end platen lubrication does not necessarily improve test results and can cause concentration of localized deformations near the platens. A fixed cap appeared to enforce a better boundary condition than a free-to-rotate one by preventing cap rotation driven by the formation of a single failure plane.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| 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 | 0.001 |
| 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".