Predicting the long-term performance of a wide embankment on soft soil using an elastic–viscoplastic model
Bibliographic record
Abstract
This paper presents modelling of the consolidation of foundation soil under a wide embankment constructed over soft soil. An elastic–viscoplastic (EVP) constitutive model is used to represent the foundation soil for the coupled finite element analysis (FEA). A unit-cell analysis is carried out to capture the maximum settlement and the development of excess pore-water pressure with time below the centreline of the embankment for a long period (9 years). A new function for capturing the varying nature of the creep or secondary compression coefficient is proposed and used in association with the EVP model. The input material parameters for this study were determined from extensive laboratory experiments except for the equivalent horizontal permeability, which was systematically estimated by using vertical permeability data obtained from one-dimensional consolidation tests and by back-analysing the first 12 months of field settlement data. Comparisons are made among the predictions obtained adopting an elastoplastic modified Cam clay model and the EVP model with constant and varying creep coefficients for the foundation soil and the corresponding field data. The predictions with the EVP model are found to be better than those with the elastoplastic model and the use of a varying creep coefficient for the EVP model seems to further improve its predicting ability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.002 |
| 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 teacher head, 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".