Analysis of Seepage Influence on High Slopes Based on Multi-dimensional Measured Data
Bibliographic record
Abstract
This paper aims to disclose the influence of seepage on high slope during the operation phase. Multiple techniques were adopted to disclose how the clogging rate of drain holes affects slope stability, including but not limited to in-situ probe test, close-range photogrammetry, indoor test, and numerical simulation. Firstly, the groundwater was monitored by digital level meter and pore osmometer. The monitoring results show that, when the clogging rate surpassed 80%, the groundwater level in the slope rose by 13m, the porewater pressure grew by 25kPa at the maximum. Next, the rebar stress and anchor cable axial force were measured, revealing that, when the clogging rate surpassed 80%, the shear force on the main rebar of the anti-slide pile increased by 20%, and the axial force of the anchor cable climbed up by 30kN. After that, the slope surface deformation was evaluated by close-range photogrammetry. The evaluation indicates that the surface deformation was 44mm, about 30mm above the alarm value, i.e. the slope faces the risk of instability. Furthermore, the changes in groundwater level and mechanical response of supporting structures were analyzed at different clogging rates, through numerical simulation and finite-element calculation based on strength reduction theory. The numerical results show that: the stress on supporting structures and slope deformation increased linearly, when the clogging rate grew below 60%, while the stress on supporting structures surged up, once the clogging rate exceeded 80%. The finite-element results indicate that, when the clogging rate exceeded 60%, the safety factor of the slope plunged deeply, an evidence of the instability risk. The research results provide new insights into the slope protection in engineering practices.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".