Hydro-mechanical coupling effect on water permeability of intensely weathered sandstone
Bibliographic record
Abstract
The combined effect of stress and seepage is an important reason of engineering geological problems such as landslides, dam failures, and tunnel collapse. However, due to the limitations of the test apparatus, the existing studies rarely consider the stress effect in the seepage process. In this study, a soil column apparatus based on the wetting front advancing method was developed to explore the permeability properties of intensely weathered sandstone in a wide range of suction (10∼10 6 kPa). The results suggest that the wetting front advancing velocity decreased as the vertical stress increased during infiltration, which indicates that the stress changes the infiltration channel and affects the infiltration rate. On the other hand, due to the water sensitivity of intensely weathered sandstone, the soil column deformation before and after wetting is significantly different, indicating that water infiltration further exacerbates the deformation. When vertical stress is applied to the soil column, the permeability coefficient–suction curves at different sections are paralleled in general, which is affected by the variation in dry density and the non-uniform distribution of stresses inside the soil column. Moreover, as the initial dry density increases, the influence of the vertical stress on the permeability coefficient gradually decreases.
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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) | 0.000 | 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".