Damage of a concrete gravity dam under the effect of the hydrodynamic loads
Bibliographic record
Abstract
For the proper design of vital structures as a dam, in order to avoid considerable damage in downstream of the structure, a deepen study must be established. The hydrodynamic behavior is very important for the determination of the damages through the dam body, which have effects on the failures and consequences on the internal resistance and the stability of the structure. This work attempts to elucidate the effect of seismic loading and inertia through the variation of Peak Ground Acceleration (PGA) and the time of seismic recording. A damage model based on a continuous approach and taking into account the tensile strength of the concrete and the elastic deformations is applied. The Koyna dam situated in India with a height of 103 m, which experienced in 1967 a considerable earthquake causing the rupture of the structure is taken as an example of application for our study, two seismic records are applied, the first is that of Koyna in December 1967 with a duration of 10 seconds, and the other that of Saguenay in Canada in November 1988 of a duration of 15 seconds with intensities less than the first. We noted that the acceleration considerably induces the horizontal displacements at the crest dam which lead to more important damages going from downstream to upstream causing the rupture of the structure, on the other hand the duration of the recording with weak intensities does not cause significant damage.
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 | 0.000 |
| 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 | 0.000 |
| 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".