Modelling the stress–dilatancy behavior of carbonate sand in Abu Dhabi
Bibliographic record
Abstract
Carbonate sands are the primary material used in the construction of reclaimed islands in the United Arab Emirates (UAE). Their stress–strain behavior exhibits unique characteristics due to strong particle interlocking, which arises from their naturally angular platy shapes. This interlocking effect contributes to the distinctive dilatancy of carbonate sands and poses challenges in modeling their stress–dilatancy response using the conventional NorSand constitutive model. To address this, the NorSand model was extended by incorporating an additional material parameter to better capture their dilatancy behavior. The extended model was validated through consolidated drained triaxial compression tests conducted on carbonate sand collected from an artificial island in Abu Dhabi, UAE. Additionally, variations in model parameters were investigated by collecting experimental results of carbonate sands from various geographical regions. To assess parameters uncertainties, a Monte Carlo simulation was performed using conditional multivariate normal distributions. A systematic assessment demonstrates that the newly introduced material parameter plays a crucial role in accurately capturing the stress–strain response and regional behavior of carbonate sands.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".