Model for prediction of resilient modulus incorporating matric suction for recycled unbound granular materials
Bibliographic record
Abstract
This paper presents experimental results on the effect of matric suction on the resilient modulus of four recycled unbound granular materials. The recycled materials were prepared at moisture contents ranging between 70% and 90% of optimum moisture content (OMC) and tested in a repeated load triaxial test (RLTT) apparatus under various stress regimes. Soil-water characteristic curves (SWCC) were established for each material by preparing samples at various moisture contents and measuring matric suction with filter papers. To obtain the wet end of the SWCC, further samples were conditioned on a tension plate at suctions controlled by the hanging water column method. Some published models for prediction of resilient modulus were applied to the experimental data, but the correlations were unsatisfactory generally, and so an improved model was sought. Subsequently, a model with four terms and six constants was developed, which followed the general power law. A single set of material constants was found for all recycled materials to provide satisfactory predictions of resilient modulus (R 2 = 0.88), over a wide range of stresses and moisture states.
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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".