Generalized effective stress of dual-porosity geomaterials considering thermochemical effects
Bibliographic record
Abstract
The accurate calculating effective stress is crucial to predicting soil deformation and ensuring structural safety under complex mechanical, thermal, and chemical loads. In this study, the thermodynamic pressures of the solid phase, and liquid phases in macropores and micropores of dual-porosity geomaterials are determined on the basis of thermodynamics and conservation equations with considering for the impact of temperature and solute concentration on soil–water interactions. In particular, thermal pressurization related to temperature and generalized osmotic pressure related to solute concentration were incorporated into the liquid-phase thermodynamic pressure equations. Thereafter, an equation for the generalized effective stress that could be applied specifically to dual-porosity geotechnical materials with consideration for environmental loads was derived from the definition of the stress tensor. The deformation behavior of clay under mechanical, thermal, and chemical coupling loading conditions was predicted using the newly proposed generalized effective stress. Predicted results revealed a stronger correlation between the generalized effective stress and void ratio, thereby confirming the accuracy and effectiveness of the proposed approach. The derived equation establishes a solid theoretical foundation for designing impermeable buffer barriers in geotechnical engineering and geo-environmental engineering safety assessments.
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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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".