Effect of plastic and silty fines on the shear behavior and pore water pressure generation in sands
Bibliographic record
Abstract
The purpose of this study was to investigate the influence of plastic and silty fines on the shear strength and the porewater pressure (PWP) response of Ottawa Sands. The sands have been mixed with both plastic and silty soils at different percentages. The fines were added ranging from 5% up to a threshold value by weight for constant dry unit weight and sheared in consolidated undrained triaxial compression (CU) test at a constant small strain rate. The advantages of using skeletal void ratio in cases where fines are present within pure sand samples are also discussed. The properties of plastic fines such as the plasticity of the fines, the percentage of fines content, and the clay mineralogy are studied to understand the influence on the undrained behavior of sands. In order to have a better understanding of the generation and dissipation of PWP during undrained shearing in sandy and sandy soils with plastic and non-plastic fines, a novel PWP measurement system was designed to measure PWP at the center of a triaxial specimen. Factors influencing the development of PWP such as strain rates, the relative density of the sands and the percentage of fines content along with their plasticity index were investigated. Results from the study indicated that the effect the fines on the soil response varies on the amount and type of fines and also on the initial relative density of the host sand.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".