Shaking table tests and stability analysis of steep nailed slopes
Bibliographic record
Abstract
Shaking table tests were performed on five model slopes to examine the effects of the angle and length of the nails and the frequency of excitation on the seismic resistance and failure mechanism of the slopes. Seismic excitation was also applied to slopes at various angles. Experimental results showed that nails markedly improved the seismic resistance of all model steep slopes. Additionally, nailed slopes exhibit characteristics of ductility under strong excitation. The angle of the nails influences the deformation of the slope but only slightly affects seismic resistance. An increase in the length of the nails increased the seismic resistance of the slope and reduced the displacement of the facing only when subjected to strong excitation. The slope at an angle of 90° to the horizontal has a markedly lower seismic resistance than that at 80°. The rocking of the model slope was strong for the slope with inclined nails and the slope at 90° to the horizontal. The failure surface of the soil mass is approximately a bilinear surface; the pullout of nails from the lower rows of nails caused total slope failure. The seismic resistance of a nailed slope is categorized viz. response of the models by three stages: stable, seismic resistance, and incipient collapse phases. Critical seismic acceleration coefficients of all models are evaluated and compared with values predicted by a developed pseudo-static, limit-equilibrium-based slope stability approach, which postulates a two-wedge failure mechanism.Key words: shaking table test, steep nailed slope, seismic resistance, pseudo-static approach.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".