A method to assess the suffusion susceptibility of low permeability core soils in compacted dams based on construction data
Bibliographic record
Abstract
Suffusion, as one of the main internal erosion processes in earth structures and their foundations, may increase their failure risks. The paper aims at presenting a general method to assess the suffusion susceptibility of core soil samples belonging to zoned hydraulic embankment dams. On one hand, the suffusion susceptibility of the soil samples is evaluated by an erosion resistance index. Thanks to existing statistical analyses, the erosion resistance index is estimated from several soil parameters that can be easily measured in situ or in laboratory during the construction of a dam. On the other hand, the saturated hydraulic conductivity of the soil samples is evaluated based on the amount of fines content and on available construction data. Moreover, the power dissipated by the flow is inferred based on the saturated hydraulic conductivity and simplified fluid boundary conditions. The combined consideration of the erosion-resistant index and of the power dissipated by the flow permits to identify zones characterised with a relatively larger suffusion potential (lower erosion resistance index and larger power than their respective average). Throughout, the method is applied to a particular zoned dam with a till core, from Northern Quebec, as a proof of concept.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".