Impact of the fines content on stress fluctuations in bi-disperse granular mixtures during triaxial tests
Bibliographic record
Abstract
In this experimental study, the influence of fines content and specimen preparation method on the mechanical behavior of granular mixtures have been explored by studying stress fluctuations that occur when the mixtures are subjected to drained triaxial tests. The magnitude and distribution of stress fluctuations are related to the changes in the microstructure of the ensemble. Bi-disperse granular mixtures of glass beads with a size ratio of 8.8, over the entire range of fines content F c (0% to 100%) were considered. The specimen were prepared using two standard specimen preparation techniques, dry deposition and moist tamping to recreate two distinct microstructures. It is found that in the under-filled regime where the stress transmission is mainly governed by the coarse particles, a significant increase in the magnitude of fluctuations is observed as the fines content, F c , increases, and on the contrary in the overfilled regime, where the load bearing structures are mainly made up of fines, fluctuations are found to decrease with further increase in F C which suggests that larger the interplay between coarse and fine particles, larger the fluctuations. Further investigation of these fluctuations in the context of critical avalanche dynamics or Self Organized Criticality (SOC) is performed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".