Identification of failure mechanisms of road embankments due to liquefaction: optimal corrective measures at seismic sites
Bibliographic record
Abstract
Road embankments are infrastructures usually made of granular material that may suffer liquefaction if saturated and subjected to dynamic loading. If pavement rests on the embankment, longitudinal cracks parallel to the road axis are frequently observed at the road surface after the occurrence of an earthquake. This paper presents the application of a new constitutive model that can simulate this type of problem. A new flow rule, related to a degradation state parameter of the soil, is incorporated in the constitutive law to represent the dilative soil behaviour. By so doing, both contraction and dilation of the soil are modelled jointly. The constitutive law has been implemented in a coupled two-dimensional finite element code developed by the authors, which permits identification of the failure mechanisms of road embankments under seismic loadings. Some remedial measures consisting of densifying the soil and (or) improving the drainage at some locations within the embankment are numerically explored, and the optimal measure is determined.Key words: soil dynamics, coupled model, constitutive law, earthquake, road construction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".