Bibliographic record
Abstract
Distinct element simulation was performed for direct shear box (DSB) tests on a dense and a loose two-dimensional (2D) sample of 3259 cylinders. Special attention was devoted to the effect that the frictional force between the inside surface of the upper shear box and the sample had on the measured shear strength in the DSB test. Some ways of minimizing this interface frictional force were introduced in the paper. Given that the deformation approximates simple shear within the deforming zone across the sample centre (referred to as the shear zone), a method was proposed to evaluate the overall strains in the DSB test. The numerically simulated data were used to interpret, on a microscopic scale, the angle of internal friction and a 2D stressdilatancy equation for the mobilized plane in granular material. It was found that the angle of internal friction in granular material is not directly related to the interparticle friction angle (ϕµ). Instead, it relates to the average interparticle contact angle ([Formula: see text]) on the mobilized plane and the ratio k/f0, representing the degree of the probability distribution of the interparticle contact forces that is biased toward the positive zone of the contact angle θ (along the shear direction), where k is the slope of the linear distribution of the average interparticle contact forces against the interparticle contact angle; and f0is the average interparticle contact force.Key words: angle of internal friction, direct shear box test, distinct element method, friction, granular material, stressdilatancy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".