A New Hollow Cylinder Torsional Shear Device for Stress/Strain Path Controlled Loading
Bibliographic record
Abstract
Abstract An automated hollow cylinder torsional (HCT) shear device has been commissioned at Carleton University to enable research on stress rotation and partial drainage. The design incorporates elements to arrest undesirable runaway strains and enable the capture of post peak strain softening in different directions, and the ability to closely follow prescribed loading paths. This device is capable of applying both static and cyclic loading under stress and displacement controlled loading modes. This is one of the first HCT devices built specifically to study the partially drained response of soils under three dimensional loading. Test results demonstrating various capabilities of this device, and the level of confidence in the measurements are presented in this paper. The presented results highlight the importance of drainage boundary conditions, and principal stress rotation on liquefaction susceptibility. The partial drainage condition in soils reveals that a small expansive volumetric deformation due to unfavorable drainage boundary conditions can trigger strain softening and flow in soils that may be stable and strain hardening under undrained loading. Tests along different total stress paths under three-dimensional generalized loading show that the uniqueness of undrained effective stress path can be extended to generalized three dimensional loading.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".