Plausible failure mechanisms of wildlife-damaged earth levees: insights from centrifuge modeling and numerical analysis
Bibliographic record
Abstract
Earth levees are subject to a wide range of wildlife intrusion patterns that cause mass removal and subsequent serious deformations. Such invasive activities leave the body of an earth embankment with burrow systems too complex to map and model using conventional techniques. This study investigates the impact of different idealized configurations of animal burrows on the geotechnical performance of levees. For this purpose, centrifuge testing was conducted on homogenous scaled-down 1 horizontal : 1 vertical (1H:1V) levee models built from silty sand material. Modeling involved introducing horizontal cylinder-shaped waterside and landside burrows at different elevations within the levee section. The reference (intact) and deteriorated levee models were subject to a centrifugal acceleration of 35g, which was kept constant as the water level behind the levee model was gradually increased. The deformation profile of the model was tracked, and the crest displacements were concurrently measured. Miniature pore pressure transducers (PPTs) embedded within the levee body provided pore pressure measurements. A three-dimensional finite element model was developed to investigate the hydraulic performance and verify the failure patterns of the deteriorated levees. Compared with an intact levee, the presence of animal intrusions was found to increase the exit hydraulic gradient for both waterside and landside intrusions. Lower animal burrows appeared to cause larger exit gradients than higher ones. Similarly, waterside burrows exhibited a notably higher pore pressure and larger hydraulic gradient. Waterside damage resulted in a quicker and more violent failure than landside burrows. The failure mechanisms for both the waterside and landside burrows are dissimilar despite their similarly abrupt nature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".