Effect of plastic fine particles on shear strength at the critical state of sand–clay mixture
Bibliographic record
Abstract
A large number of engineering cases have shown that there is significant presence of the sand–clay mixtures during the engineering geological accidents. Static liquefaction or loss of bearing capacity is frequently observed due to the rise in pore water pressure from large deformation in such engineering geology. This study investigates the static behavior of sand–clay mixtures with varying fines contents and various plasticity indices of fines by means of the monotonic drained consolidation triaxial shear tests in conjunction with the binary packing model. Factors influencing the active fines content ( b) of the sand–clay mixtures are examined based on the mixtures’ critical state. This study also discusses the reasons for variations in the critical friction angle ( M) of the sand–clay mixtures using environmental scanning electron microscope tests. Results indicated that the changes of fines content and the plastic index of fines have a certain effect on the static behavior, active fines content ( b), and the friction angle ( M) of the sand–clay mixture. This study presents an equation with reliable predictive results. These findings hold considerable importance for a deeper understanding of the mechanical properties of the sand–clay mixture with and the influencing mechanisms of different plasticity index of fines.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".