Investigation of small- to large-strain moduli correlations of rockfill materials — application to Romaine-2 dam
Bibliographic record
Abstract
The establishment of relationships between the shear wave velocity (Vs) and other geotechnical parameters of rockfills under large strains (e.g., oedometer-constrained modulus, Moedo, and tangent elastic modulus, Et) is a significant step toward precise modeling of earth structure stress–strain behavior. In this study, four specimens reconstituted from the rockfill used for Romaine-2 dam construction were investigated experimentally to correlate small-strain to large-strain moduli. The development of Moedo and Vs with consolidation was measured in a laboratory using the piezoelectric ring-actuator technique (P-RAT) incorporated in a large oedometer cell. A correlation between Moedo and the small-strain shear modulus (Go) was proposed. Moreover, numerical simulations were performed using the Duncan–Chang hyperbolic model to correlate Vs and the Duncan–Chang initial elastic modulus (Ei), which depends on the minor principal stress (σ3). Based on the experimental and numerical data, a relationship between the Ei and Vs of the rockfill specimens was established. Verification studies were also performed using in situ measurements obtained from the Romaine-2 dam construction, and the ability of the proposed relationships to predict Ei from in situ Vs measurements was demonstrated. The proposed correlations can help geotechnical designers estimate the deformation characteristics of rockfill materials from in situ Vs measurements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".