A physics-based approach for predicting time-dependent progression length of backward erosion piping
Bibliographic record
Abstract
The progression length at various stages of backward erosion piping (BEP) in levee systems can serve as a key engineering demand parameter for reliability and risk assessments. The main goal of this study is to put forward a reliable and computationally efficient technique for predicting the progression length during BEP. Many existing modeling approaches for predicting progression lengths of BEP are either computationally expensive or consider a constant, time-independent amplification factor for the permeability coefficient. In contrast, the model developed here considers the underlying physical phenomena to properly capture the amplification of the permeability coefficient during the progression of BEP. The proposed model is derived considering the rolling threshold condition, which is obtained from the moment equilibrium of erodible particles. This modeling approach with time-varying permeability coefficients has been implemented in FLAC3D, and the derived BEP paths are validated for three flume experiments. The impact of material properties including porosity, tortuosity, and coefficient of uniformity on the amplification factor are investigated. These analyses show that the permeability amplification factor and the progression length increase with low rates at the initial stages of piping. Following the formation of the piping path, they both increase at a generally greater rate over time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".