Discrete Element Modelling of Undrained Consolidated Triaxial Test on Cohesive Soils
Bibliographic record
Abstract
Microparameters of the clay component of an earth fill dam need to be identified in order to develop a reliable discrete element landslide model. To characterize clay microparameters, a calibration process of matching the simulated and actual undrained consolidated triaxial test results were performed. Linear parallel-bond model was used to describe the interactions of clay particles. The microparameters calibrated to match the real clay behavior were particle stiffness, friction, bond stiffness, and bond strength. Sensitivity analysis revealed that bond stiffness and bond strength dictate the peak stress behavior of the numerical model, while particle stiffness and friction influence its critical-state stress behavior. The designed calibration methodology based from the sensitivity analysis results was able to identify a suitable set of microparameters that can simulate the real behavior of clay. Integrating the calibrated microparameters to the numerical model yielded good agreement between the measured and simulated stress-strain relationships of clay at different consolidation pressures.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".