Advanced numerical simulation of collapsible earth dams
Bibliographic record
Abstract
This paper presents a methodology for advanced numerical analysis of earth dams, considering all design stages. It also includes transient analysis of safety factors and can be applied to general three-dimensional conditions, considering unsaturated materials and the interrelation between hydraulic and mechanical phenomena by simultaneously solving equilibrium and continuity conditions. The methodology has been successfully implemented in a finite element program and applied to the analysis of earth dams with sections composed of soils at optimum, dry of optimum, and mixed compaction conditions. The dry section is intended to simulate the so-called “Alka-Seltzer” dams, constructed with poorly compacted and dry material, thus resulting in a meta-stable and collapsible structure. The results show that it is possible to design a less expensive mixed section with approximately the same behavior and in some cases even better performance when compared with the homogeneous section at optimum conditions. This is achieved by strategically placing the optimum materials in the most stressed zones of the earth fill. The safety factor analyses show the importance of considering coupled effects in collapsible dams. In such cases, failure can be simulated in the upstream slope during the first reservoir impounding, as has been observed in some actual cases.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".