Local Strengthening of Reinforced Concrete Structures as a Strategy for Seismic Risk Mitigation at Regional Scale
Bibliographic record
Abstract
Recent earthquakes have clearly shown the high vulnerability of existing reinforced concrete (RC) structures. There is a crucial need to find cost‐effective and efficient strategies and methods to strengthen a large number of buildings (i.e., at a regional scale) before future major earthquakes occur. A viable strategy to prevent potential damage caused by earthquakes could be to selectively upgrade local capacity of individual structural components. In the aftermath of the 6 April 2009 L'Aquila earthquake, local retrofit work based on the use of fiber polymer reinforcement (FRP) were executed to increase the seismic capacity of lightly damaged public and private buildings. According to theoretical analyses carried out on six reinforced concrete (RC) school buildings in L'Aquila, a seismic safety level of about 60% of that requested in the design of a new building can be achieved in most cases by FRP‐based strengthening of exterior joints.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".