Cyclic Shear Response of Fraser River Sand Using Cyclic Ring Shear
Bibliographic record
Abstract
Cyclic triaxial, direct simple shear, torsional shear, resonant column, and cyclic ring shear apparatuses have been used for evaluating cyclic shear strength and liquefaction resistance of cohesionless soils. In this study cyclic shear response of Fraser River sand is investigated using constant-volume cyclic ring shear tests. The effects of sample preparation method, vertical stress, number of loading cycles to liquefaction (NL), cyclic stress ratio (CSR), and relative density (Drc) on the liquefaction behavior of Fraser River sand are investigated. Fraser River sand specimens are prepared by different sample preparation methods and tested under stress-controlled, constant-volume, plane-strain shearing condition. The ring shear specimens are consolidated to vertical stresses of 100, and 200 kPa prior to the application of uniform, sinusoidal, shear stress cycles. The specimens are then subjected to cyclic shear stress ratios (CSR) of 0.08, 0.10, 0.12, 0.15 and 0.20. Cyclic shear strain and effective vertical stress respectively increase and decrease with increasing the number of loading cycles. Larger cyclic shear strains and greater reductions in effective vertical stress are also produced at higher CSR. It is found that saturated water-pluviated samples exhibit significantly higher cyclic shearing resistance compare to dry air-pluviated and saturated moist-tamped samples. Compared to cyclic direct simple shear tests, cyclic shearing resistance measured in ring shear experiments is higher due to the rigid boundaries of the specimen chamber which impose a perfect plane strain shearing condition.
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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".