Experimental Study of Shear Zones Formed at Sand/Steel Interfaces in Axial and Torsional Axisymmetric Tests
Bibliographic record
Abstract
Abstract The interface shear behavior of granular materials is central to many engineering applications, including the performance of structures like deep foundations, landfills, and retaining walls. Consequently, it is paramount to understand the behavior of construction material-soil interfaces involved in these applications. Furthermore, it has been shown that the study of interface behavior, in the laboratory and in-situ, can provide robust information about the soil's properties and engineering performance. This paper presented laboratory evaluations of micro and meso-scale shear deformation of medium-sized sands aimed at developing an improved fundamental understanding of granular-continuum stress-strain behavior. A comparison of interface testing results from two different shear directions—axial and torsional—demonstrated that the evolution and progression of shear zone formation was affected differently by changes in the interface surface roughness and particle angularity. In particular, it was observed that torsional shear is a more dilative process that induces a larger degree of soil shearing and is greatly affected by particle angularity. Studies of shear-induced volume changes also revealed that the influence zone for torsional shearing is larger than that for axial shearing, with soil dilation occurring inside the shear zone in contact with the material counterface and soil contraction in a surrounding outer zone. Fundamental micromechanical processes that aim to explain the differences between the behavior of axial and torsional tests are proposed.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".