Elastic visco-plastic consolidation modelling of clay foundation at Berthierville test embankment
Bibliographic record
Abstract
This paper applies for the first time a highly non-linear One-Dimensional Elastic Visco-Plastic (1-D EVP) model to the consolidation analysis of the clay layer underneath Berthierville test embankment in Quebec, Canada. This paper firstly gives a brief description of the main equations of the Finite Element (FE) consolidation modelling incorporating the 1-D EVP model. Special issues encountered in the consolidation modelling of the field problem are addressed. Water head fluctuations at the upper and lower boundaries of the clay are considered by giving an appropriate definition of excess porewater pressure. An optimization procedure is suggested for the determination of the 1-D EVP model parameters. The determination of initial strains in the field is explained. The FE model can consider (a) multi-layered soil profile, (b) time-dependent loading and hydraulic boundary conditions and (c) different constitutive models for different soils (1-D EVP model for clay and Terzaghi's model for silty sand). A parametric FE modelling study is carried out to determine two uncertain parameters of the silty sand layer underlying the clay layer. It is found that the parameter m(v) affects the compressibility of the silty sand layer, but has no influence on the consolidation behaviour of the clay. However, the parameter k can affect the compression of the silty sand layer and the clay layer. FE consolidation modelling of the soils underneath Berthierville test embankment is carried out using the model parameters determined. It is found that the compression of the clay layer computed from the FE model is in good agreement with field measured values. Porewater pressures from the FE modelling are close to the measured values except for the values at the initial loading stage. This discrepancy at this initial stage is discussed in this paper.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".