Implementation of a New Strain Softening Constitutive Model in the Material Point Method for the Simulation of Retrogressive Failure in Sensitive Clays
Bibliographic record
Abstract
Sensitive clays experience significant strain-softening behavior, that is, when subjected to large strains. They disintegrate into a remolded liquid with diminutive shear strength. When a slope begins to fail, the remolded clay keeps moving away from its original position causing subsequent failures, resulting in catastrophic aftermath. The capability to reproduce realistic strain-softening characteristics in the constitutive soil model is necessary for more accurate numerical slope analyses in sensitive clays. This paper illustrates a simple yet practical constitutive model specially developed for simulating the strain-softening behavior of sensitive clays. The model is then implemented in Anura3D, an open-source software that uses the material point method to simulate large deformations. The model is tested using the failure of a previously occurred retrogressive failure in sensitive clay. Finally, the model’s predictions have been compared with the actual post-failure run out of the landslide, and the results show that the model is reasonable and practical.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".