Effect of Lime and Fly Ash Soil Treatment on Pore Water Pressure Response in Earth Dams under Rapid Drawdown
Bibliographic record
Abstract
Rapid drawdown is one of the most critical conditions in a dam's lifespan, as sudden reservoir drainage induces pore pressure imbalances that may threaten upstream slope stability.Therefore, ensuring slope stability through proper design remains a key safety consideration.This study investigates how variations in permeability affect the pore water pressure response in treated earth dams subjected to rapid drawdown.A physical model of an earth dam was constructed, with core soil was treated with varying limefly ash ratios (M-1 to M-4) and compared to an untreated control.Rapid drawdown was simulated by reducing the upstream water level from 36 cm to 5 cm within 5 min, while pore water pressures were monitored using ten sensors distributed across the dam section.Results indicate that the untreated control model exhibited rapid pore pressure dissipation due to high core and shell permeability.In contrast, treated models showed delayed dissipation, proportional to the additive content, with M-4 presenting the slowest response and most significant pressure dissipation delay.Nonetheless, the highpermeability shell zone effectively mitigated adverse effects on upstream slope stability.Numerical validation demonstrated excellent agreement with experimental data (coefficient of determination, R² > 0.95).Seepage analysis further confirmed that seepage towards the downstream direction decreased progressively with treatment, while exit gradients were effectively reduced to zero on the downstream slope at higher treatment levels.
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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".