A thermomechanical model for saturated soil at small and large strains
Bibliographic record
Abstract
Many elastoplastic models have been developed for simulating thermomechanical behaviour of saturated soil. Although the yield surface of these models shrinks with temperature, its shape is always assumed to be independent of temperature. This simplification may induce errors in predicting thermal effects on shear behaviour. Furthermore, existing models tend to focus on thermomechanical behaviour at large strains. Behaviour such as the degradation of the shear modulus with strain at small strains (<1%) is often ignored. To address these issues, a new thermomechanical model is developed using the bounding surface plasticity theory. Both the size and shape of the bounding surface are allowed to change with temperature. The new model is able to predict elastoplastic response of saturated soil at small strains, even when stress path is within the bounding surface. Using this new model, thermomechanical behaviour of four different soils having different overconsolidation ratios is simulated. Comparisons between measured and computed results reveal that the new model is able to capture many vital aspects of thermomechanical behaviour, including volume changes during heating and cooling, and thermal effects on drained and undrained shear behaviour. In particular, it predicts a gradual degradation of the shear modulus at small strains. By incorporating thermal effects on the shape of the bounding surface, the modelling of thermomechanical behaviour, especially the effective stress path during undrained shearing, is improved.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".