Enhancing Seismic Resilience of Existing Reinforced Concrete Building Using Non-Linear Viscous Dampers: A Comparative Study
Bibliographic record
Abstract
After the catastrophic destruction of the October 2005 Kashmir earthquake, the first building code of Pakistan was developed in 2007. The sole purpose of the building code of Pakistan (BCP) was to incorporate advancements in earthquake-resistant design to fortify structures and ensure the safety of citizens against future seismic events. After 2007, the BCP was not revised till 2021 to include the changes over time. However, the recently updated version of BCP 2021 highlights that the seismicity of many regions in Pakistan is high, which is not truly reflected in the BCP 2007. Therefore, the advancements in earthquake-resistant design due to the growing concerns about the potential risks of seismicity in the region have been incorporated into the updated version of the BCP. However, there are concerns among researchers that many structures designed on the 2007 code may need seismic fortification. Therefore, the current study focuses on the seismic fortification of existing systems that were developed using previous codes. Non-linear viscous fluid dampers are used to improve the seismic resilience of existing structures. This study compares the seismic performance of an existing reinforced concrete building with and without non-linear viscous dampers and subjected to a non-linear dynamic analysis. The performance of the building is evaluated in terms of story displacement, story drift, story acceleration, and energy dissipation mechanisms. Adding the non-linear fluid viscous dampers in the structure caused a decrease in the inter-story drift by around 31.16% and the roof displacement was reduced by around 36.58%. In addition to that, in a controlled structure, more than 70% of energy was dissipated by the fluid viscous dampers. These results indicate that adding the non-linear fluid viscous dampers to the existing structure significantly improved the vibration performance of the system against undesirous vibrations. The outcomes of this study also provide a very detailed insight into the usage of non-linear viscous dampers for improving the seismic performance of existing buildings and can be used to develop effective strategies to mitigate the impact of seismic events on already built structures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".