Hands-on-experience on seismic retrofit in four different countries
Bibliographic record
Abstract
There are various different seismic vulnerability assessment procedures and seismic retrofit methods that have been applied to existing buildings in seismic regions.After the analytical assessment and design phase, it is of critical importance that the retrofit design is properly applied on-site.Conventional parties such as local authorities, construction culture, construction companies, quality of workmanship and availability of materials play a crucial role in the construction of seismic resistant buildings and in the selection of retrofit method and application.Furthermore there is a lack of experience on the performance of buildings subjected to earthquakes.Authors assessed and retrofitted eight reinforced concrete buildings and one masonry building from one to six stories in Nepal, Djibouti, Turkmenistan and Haïti, respectively, in 2011, 2013, 2015 and 2016.Retrofitted buildings in Nepal were subjected to 7.8 magnitude earthquake in April 2015, which gave authors the opportunity to document the seismic performance.This paper summarizes the hands-on-experience gained from four different seismic assessment and retrofitted projects conducted in four different countries.Performance of the retrofitted buildings subjected to a 7.8 magnitude earthquake and difficulties in the application of retrofit are present.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".