Theoretical framework for large-strain shear resistance of Kaolin clays under chemo-mechanical loadings
Bibliographic record
Abstract
The normal stress, strain rate, and pore fluid chemistry significantly influence the large-strain shear response of clays and received great attention for engineering practice. The effect of inundation pressure, consolidation pressure, pH of aqueous solutions, and di-electric on the shear response of kaolin was experimentally investigated. The strain-softening behaviour was observed under normally consolidated (NC) conditions as observed in the past studies on different clays. However, this anomalous shear response with volumetric contraction is not understood. Thus, for the first time, the strain-softening behaviour of NC clays was addressed from an effective stress approach using physico-chemical analysis of kaolin. In this study, the drained shear strength response of NC kaolin was investigated under physico-chemical influence using ring shear tests. A theoretical framework was developed by including micromechanism of clay fabric evolution during shear and explicit expressions for electro-chemical forces. The proposed framework was used to estimate the shear resistance from the modified effective stress approach to interpret the experimental results. The proposed framework provides useful expressions for predicting the shear strength behaviour of kaolin clays, which were validated with experimental data from the present study and literature studies. The new conceptual framework satisfactorily explained the peak and residual shear strength variations under different chemo-mechanical loading for NC conditions. The proposed model adequately predicted the effective stress paths, peak, and residual envelopes in ring shear stress conditions for NC kaolin soils.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".