Settlement characteristics and evaluation approach of embankment widening over soft clay
Bibliographic record
Abstract
Embankment widening alongside an existing embankment causes additional stress and differential settlement on the foundation beneath the embankment, which may have adverse effects on pavements. The settlement profiles of the existing and widened foundations beneath an embankment are governed by several geometric and physical parameters related to embankment widening. An accurate settlement evaluation method is essential for the determination of an appropriate ground improvement technique. In this paper, a simplified method for predicting the settlement of the soft foundation induced by embankment widening is proposed. A validated finite element method model was first employed to quantify the effect of geometric parameters and soil properties on the settlement characteristics. Furthermore, a simplified model based on the bi-Gaussian function was developed to illustrate the settlement profiles. The results obtained by the proposed model are in good agreement with previously reported centrifuge test results and a generated numerical database, demonstrating that the proposed model has satisfactory accuracy. The developed prediction model offers an alternative approach for the preliminary design of embankment widening.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".