A nonlinear numerical computational study of the effect of groundwater infiltration on slope stability based on FLAC3D
Bibliographic record
Abstract
The stability of slopes is related to many factors, among which rainfall and water table fluctuation are the most common natural factors leading to slope damage. Based on a non-homogeneous slope, numerical simulation analysis using FLAC3D software and intensity discounting method was conducted in the article to discuss the stability of the slope under different morphologies, to explore the influence of diving surface height and pit water level line on the slope stability, to put forward the support scheme and to carry out the effect test. The analysis shows that the increase of slope gradient, step length and slope height negatively affects the slope stability, among which the effect of slope height is the most significant, and the stability coefficient decreases by 49.61% when the slope height increases by 60m under the action of groundwater. The height of diving surface and pit water level line are both inversely proportional to the slope stability, and the decrease of slope stability produced by the increase of both is 10.53% and 42.06%, respectively, and the latter’s influence on the slope safety coefficient is much larger than the former. In addition, the comprehensive landslide prevention and control program, which adopts the construction of drainage facilities, the selection of drainage scheme and the strengthening of support at the rock stratum interface area, effectively improves the safety coefficient of the slope.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".