Application of a Simplified Anisotropic Constitutive Model for Soft Structured Clay on Embankment Failure
Bibliographic record
Abstract
The design and maintenance of embankments is still a challenge in practical geotechnical engineering because of some features of soft sensitive soil behavior that are not considered in conventional methods. These features originate from the soil structure, including soil anisotropy, interparticle bonding, and decay as a result of the loading and deformation process. In recent years, many efforts have been made to incorporate the aforementioned features in various soil constitutive models. However, their application in practical geotechnical engineering is limited, owing to the complexity of the models, a number of parameters, and difficulties in the implementation in a computer code. The aim of this study is to modify a simple anisotropic constitutive model (SANICLAY) in order to take into account destructuration, named SANICLAY-D, and its implementation in computer code with a simple and robust algorithm. The capability of the proposed soil model in simulating the effects of the aforementioned soil features on the behavior of the well-known Test Embankment A constructed at Saint-Alban, Quebec, Canada, is explored. This model predicts, with sufficient accuracy, the effect of anisotropy on embankment failure behavior, especially the height and the failure surface, despite its simplicity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".