Seismic Retrofitting of Reinforced Concrete Structures: A Comparative
Bibliographic record
Abstract
One of the main goals of retrofitting reinforced concrete (RC) structures is to enhance their safety against natural disasters like earthquakes. A significant number of RC buildings in Canada were constructed several decades ago and may be vulnerable to earthquakes due to the absence of modern design considerations. Therefore, seismic retrofitting of RC buildings is essential to minimize earthquake damage. This study compares two of the most popular techniques used for retrofitting such structures. A six-story RC building located in a high-seismicity zone is retrofitted using a base isolator and a tuned mass damper. The retrofitting systems are designed using routine methods, and their ability to reduce earthquake damage is evaluated. Buildings upgraded with two different retrofitting systems are modeled in the OpenSees software package and subjected to several seismic events. According to the results, the routine methods used for designing the optimal linear TMD and base isolation may not be sufficient to ensure highly efficient performance, as their effectiveness depends on the intensity of seismic excitation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".