Empirical relationships for estimating the crest settlement of earth-core rockfill dams subjected to earthquakes
Bibliographic record
Abstract
In this study, new empirical predictive relationships for earthquake-induced crest settlement of earth-core rockfill dams (ECRDs) were developed. A case history database of 19 dams that had been subjected to earthquakes was utilized. The presented relationships correlate the intensity measure (IM) of the earthquake records with the observed settlements, and thus, employing IMs that appropriately describe the severity of ground motion is of vital importance. It is well known that the dynamic properties of an ECRD can change significantly depending on the severity of an earthquake, and that this phenomenon can substantially impact the dynamic responses of dams. Accordingly, two IMs were suggested, taking into account the essential characteristics of ground motions affecting the nonlinear behaviour of ECRDs. The results indicate that the proposed relationships effectively address the limitations of the existing ones, and that they are practical tools that efficiently predict the seismic settlements of ECRDs.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".