Seismic Performance of Hybrid Corrosion-Free Self-Centering Concrete Shear Walls
Bibliographic record
Abstract
Reinforced concrete (RC) walls are extensively used in high-rise buildings to resist lateral loads, while ensuring an adequate level of ductility. Durability problems, including corrosion of conventional steel reinforcements, necessitate exploring alternative types of reinforcement. The use of glass fiber reinforced polymer (FRP) bars is a potential solution. However, these bars cannot be used in seismic applications because of their brittleness and inability to dissipate seismic energy. Superelastic shape memory alloy (SMA) is a corrosion-free material with high ductility and unique self-centering ability. Its high cost is a major barrier to use in construction projects. The clear advantage of utilizing both SMA and FRP to achieve durable self-centering structures has motivated the development of a composite SMA-FRP bar. This paper investigates the hybrid use of FRP bars and either SMA bars or composite SMA-FRP in concrete shear walls. An extensive parametric study was conducted to study the effect of different design parameters on the lateral performance of hybrid RC walls. The seismic behavior of the hybrid walls was then examined. The hybrid walls not only solved the durability problem but also significantly improved the seismic performance.
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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) | 0.001 | 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".