Effects of inclusion contents on resilient modulus and damping ratio of unsaturated track-bed materials
Bibliographic record
Abstract
For the French conventional railway lines, a layer, namely interlayer, was created in the substructure mainly by the interpenetration of ballast grains and subgrade soils. The in situ investigation indicated that the content of coarse grains decreases over depth. In this study, the resilient modulus and damping ratio of the unsaturated lower part of the interlayer soil were investigated at six different volumetric inclusion contents fv (volumetric ratio of dry coarse grains to the whole sample) by carrying out cyclic triaxial tests following a multi-step loading procedure. The results show that the two dynamic parameters (resilient modulus and damping ratio) change significantly at the beginning of loading and the variation rate decreases as the number of cycles increases. Besides, a mean characteristic volumetric inclusion content fv–cha ranging from 27.8% to 28.9% was identified, separating two zones with different inclusion effects. To verify this observation, X-ray microcomputed tomography (μCT) scans were conducted on as-compacted samples. The results obtained strongly support the existence of fv–cha: when fv ≤ fv–cha, the matrix of fines constitutes the skeleton of the sample with inclusions floating in it, leading to slight changes of the two dynamic parameters with fv. By contrast, when fv > fv–cha, the inclusions dominate the skeleton of the sample, giving rise to significant changes of the two dynamic parameters with fv.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".