Numerical study of soil conditions under which matric suction can be maintained
Bibliographic record
Abstract
The effect of negative pore-water pressure is often ignored in slope stability studies. There is a perception among geotechnical engineers that negative pore-water pressures will dissipate with rainfall infiltration and cannot be relied upon in design considerations. The objective of this paper is to illustrate that under certain conditions soil suction can be maintained. Based on the theory of infiltration and seepage through a saturatedunsaturated soil system, steady state and transient finite element seepage analyses were conducted using Seep/W on a 20 m high slope inclined at 30°. The results of the analysis showed that under steady state conditions, the most important factor influencing the permanency of matric suction in the soil is the magnitude of rainfall flux expressed as a percentage of the saturated coefficient of permeability of soil. For the analysis under transient seepage conditions, the results showed that the pore-water pressure profile depends on the magnitude of the rainfall flux, the saturated coefficient of permeability, the soil-water characteristic curve, and the water storage function. For a soil with a low coefficient of permeability and a large water storage capacity, the matric suction needs a substantial amount of time to dissipate and thus may be maintained over a longer time period than the rain is likely to fall, even if the ground surface flux is equal to or greater than the saturated coefficient of permeability. Engineers should address more appropriate engineering design assumptions that can be related to the permanence of matric suction in soil slopes based on the numerical analysis. Measures such as slope cover or surface recompaction can be taken into consideration to minimize the rainfall infiltration and thus maintain active matric suction in slopes.Key words: unsaturated soils, slope, rainfall infiltration, matric suction, permeability.
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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 | 0.001 | 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".