Coupled effects of principal stress rotation, temperature, and suction on the cyclic behaviour of unsaturated loess
Bibliographic record
Abstract
Principal stress rotation (PSR) significantly affects the cyclic behaviour of subgrade soil. Previous studies on PSR have been generally limited to saturated and isothermal conditions despite subgrade soil experiencing daily and seasonal variations in temperature and suction. This study incorporated temperature- and suction-controlled units into existing hollow cylinder apparatus to conduct cyclic shear tests, both with and without PSR, while maintaining identical cyclic deviatoric stress. The study considered different temperatures (5 °C, 20 °C, and 40 °C) and suctions (0, 10, and 30 kPa). The permanent strain increases and resilient modulus decreases as temperature rises and suction decreases. Furthermore, the incorporation of PSR results in increased permanent strain and decreased resilient modulus, with these changes being influenced by temperature and suction. At zero suction, the permanent strain increases by 130% and 230% at 5 °C and 40 °C when PSR is incorporated. As suction increases to 10 kPa, these values are 50% and 80%. These coupled effects are likely due to the decrease in the overconsolidation ratio (OCR) with increasing temperature and decreasing suction, with PSR effects being more pronounced at lower OCRs. Furthermore, a new semi-empirical equation was proposed to model these coupled effects on resilient modulus, a critical parameter in pavement design.
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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".