Assessment of Potential for Seepage-Induced Unraveling Failure of Flow-Through Rockfill Dams
Bibliographic record
Abstract
A purely numerical parametric study of 24 flow-through rockfill dam geometries was conducted. The nonlinear nature of the p-LaPlacian–like partial differential equation was dealt with using a finite-difference scheme that directly incorporated the exponent of a power law that replaced Darcy’s law. Convergence, use of specialty nodes, nodal density, and boundary condition effects were quantitatively investigated. The flow-field angle of the toe was found to be a useful starting point in studying the potential for unraveling failure. Factors of safety (FS) against this type of failure are then presented for a range of downstream slopes, thus showing which combinations of slope and particle diameter are unsafe. It is shown that the FS tends to drop below unity under the seepage face primarily because of the strength of the exit gradient near the toe of the structure and secondarily because of the overflow velocity. It is hoped that the techniques and results presented will facilitate the design and assessment of flow-through rockfill structures.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".