Caractérisation multiaxiale des interfaces multimatériaux. Application aux assemblages collés
Bibliographic record
Abstract
Si bon nombre de moyens expérimentaux existent afin de caractériser les assemblages collés, obtenir le comportement intrinsèque de zones aussi minces reste une difficulté majeure car bien souvent les résultats dépendent de la géométrie du système expérimental adopté. Cet article décrit le système Arcan-Mines conçu pour une caractérisation multiaxiale des interfaces entre différents substrats. Néanmoins on se limitera dans le contexte de cette étude à son utilisation aux assemblages collés. Ce montage permet leur caractérisation sous sollicitations complexes de traction-cisaillement ou de compression-cisaillement aussi bien en statique que sous des grandes vitesses de déformations. Il permet de déterminer les fonctions seuil de plasticité ou de rupture des zones de liaison. Une formulation originale de ces fonctions est proposée avec des critères exprimés en fonction du premier et du second invariant des contraintes. On présente les résultats d'essais selon différentes configurations de sollicitations
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".