Thermodynamic-based cross-scale model for structural soil with emphasis on bond dissolution
Bibliographic record
Abstract
The immersion weakening effect of natural soil has always been a difficult problem encountered in geotechnical engineering practice. The bond dissolution is a common cause of soil strength deterioration, which is not yet fully understood. In this study, a thermodynamic-based constitutive model of structural soils based on the α model is first established, considering the bond strength by modifying the yield surface size and gradually reducing the bond strength with the development of plastic strain. Furthermore, by taking the meso-mechanisms of bond dissolution into account, the evolution rule of the free energy during the bond dissolution process is derived based on a homogenization approach, and a thermodynamic-based constitutive model of structural soil with bond dissolution is thereafter developed. By comparing with the results of one-dimensional compression tests and conventional triaxial tests, the model is verified to be capable of reflecting the gradual destructuration process of soil while loading. The comparison with triaxial test results of completely decomposed granite after different immersion durations and parametric studies show that based on the cross-scale energy equivalence, the model can well reflect the strength deterioration characteristics of completely decomposed granite with bond dissolution mechanisms at the mesoscale fully considered.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".