Configurational mechanics in granular media
Bibliographic record
Abstract
Abstract Granular materials belong to the class of complex materials within which rich properties can emerge on large scales despite a simple physics operating on the microscopic scale. Most notable is the dissipative behaviour of such materials mainly through non-linear frictional interactions between the grains which go out of equilibrium. A whole variety of intriguing features thus emerges in the form of bifurcation modes in either patterning or un-jamming. This complexity of granular materials is mainly due to the geometrical disorder that exists in the granular structure. Diverse configurations of grain collections confer to the assembly the capacity to deform and adapt itself against different loading conditions. Whereas the incidence of frictional properties in the macroscopic plastic behavior has been well described for long, the role of topological reorganizations that occur remains much more elusive. This paper attempts to shed a new light on this issue by developing ideas following the configurational entropy concept within a proper statistical framework. As such, it is shown that contact opening and closing mechanisms can give rise to a so-called configurational dissipation which can explain the irreversible topological evolutions that granular materials undergo in the absence of frictional interactions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".