Effects of stress paths on the small-strain stiffness of completely decomposed granite
Bibliographic record
Abstract
Research on the small-strain (0.001%1%) characteristics of sedimentary soils and sands has advanced to the stage where it has been utilized in engineering analysis and design for some time. Despite the progress, the stiffness characteristics of weathered materials such as completely decomposed granite (CDG) at small strains have still attracted relatively little research attention. This paper describes a systematic laboratory investigation of the small-strain characteristics of intact CDG subjected to various triaxial stress paths, including drained compression and extension tests. The small-strain stiffness was measured using bender elements and internal local transducers. Measurements from bender elements illustrate that the elastic shear modulus of CDG increases as the mean effective stress increases and the void ratio decreases. Significant nonlinear shear stiffness shear strain and bulk modulus volumetric strain relationships were observed. At 0.01% shear strain, the measured average shear stiffness obtained from the extension tests was about 60% higher than that from the compression tests. The average shear stiffness for the tests with a 90° rotation of the stress path was about 50%70% higher than that of tests without a change in the direction of the stress path after saturation.Key words: completely decomposed granite, nonlinearity, small strains, extension, compression, recent stress history.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".