Constitutive Model for Fibre Reinforced Cemented Silty Sand
Bibliographic record
Abstract
In this study, a modified version of Severn–Trent constitutive model was used to simulate the mechanical behaviour of composite materials under drained and undrained triaxial compression loading conditions. Two additional parameters obtained from the laboratory tests were added to the standard Severn–Trent model to simulate the stress-strain behaviour of cement and fibre-reinforced Toyoura silty sand. The model parameters were derived based on the experimental results performed, parametric study, trial and error and by comparison with previous research studies. The comparisons covered ranges of material from 0% to 3% fibre, 0% to 3% cement, 20% to 60% relative densities, and silt contents of up to 75%. The experimental results and model simulations were compared in terms of deviatoric stress versus axial strain, volumetric strain versus axial strain, and stress path behaviour. A close agreement of model simulations with the experimental results is observed for many of the tests performed on pure Toyoura sand, cemented, fibre, and fibre-reinforced cemented Toyoura silty sand. The extracted parameters are used to predict the response of those experiments until a reasonable (e.g. ± 5–10% peak strength) comparison is obtained.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".