Analytical Evaluation of Seismic Performance of RC Frames Rehabilitated Using FRP for Increased Ductility of Members
Bibliographic record
Abstract
Many reinforced concrete (RC) frame structures designed according to pre1970 strength-based codes are susceptible to abrupt strength deterioration once the shear capacity of the columns is reached. Fiber composites are used to increase the shear strength of existing RC columns and beams by wrapping or partially wrapping the members. Increasing the shear strength can alter the failure mode to be more ductile with higher energy dissipation and interstorey drift ratio capacities. The objective of this study was to analytically evaluate the effect of varying distributions of fiber-reinforced polymer (FRP) rehabilitation on the seismic performance of three existing RC frames with different heights when subjected to three types of scaled ground motion records. The FRP wrapping is designed to increase the displacement ductility of frame members to reach certain values representing moderate ductility and high ductility levels. These values were assumed based on previous experimental work conducted on members wrapped using FRP. The study also investigates the effect of the selected element’s force–displacement backbone curve on the capacities of the structures with respect to maximum interstory drift ratio, maximum peak ground acceleration, or peak ground velocity resisted by the frames, maximum storey shear-to-weight ratio and maximum energy dissipation. It was found that for low-rise buildings, the FRP rehabilitation of columns only was effective in enhancing the seismic performance; while for high-rise ones, rehabilitation of columns only was not as effective as rehabilitation of both columns and beams. Ignoring representing the postpeak strength degradation in the hysteretic nonlinear model of FRP-rehabilitated RC members was found to lead to erroneous overestimation of the seismic performance of the structure.
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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 | 0.000 | 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".