Experimental comparative study on novel flexural strengthening systems for seismically deficient RC piers: Prestressed Fe-SMA plates vs. externally bonded CFRP sheets
Bibliographic record
Abstract
This study explores an innovative method for enhancing the seismic performance of deficient RC bridge piers through a novel flexural strengthening system incorporating prestressed Iron-based Shape Memory Alloy (Fe-SMA) plates. The novelty of this system lies in implementing a robust anchorage technique, effectively addressing challenges typically accompanied by enhancing the flexural performance of RC piers using prestressed systems. Three RC circular columns were built representing 1/3 to scale bridge piers. The first column remained unstrengthened, while the second was strengthened in flexure using prestressed Fe-SMA plates. The third column was strengthened using vertical externally bonded (EB) Carbon Fibre-Reinforced Polymer (CFRP) sheets – a passive system chosen for comparison with the prestressed Fe-SMA system. The columns were simultaneously subjected to a constant axial and a lateral cyclic loading applied at their tops. The results showed that the Fe-SMA strengthened column exhibited the most stable hysteretic response with only 13.88 % strength degradation at 8.84 % drift, in addition to witnessing a significant increase of 35.32 % and 72.60 % in its lateral strength and energy dissipation, respectively. Also, the vertical Fe-SMA plates successfully mitigated the column’s extensive damage and reduced its residual displacements by 17.79 %, thereby preserving the column’s concrete core and preventing the buckling of its reinforcements. • Fe-SMA plates and CFRP sheets stabilized the columns’ hysteretic behaviour. • Fe-SMA plates and CFRP sheets slowed the strength and stiffness degradation. • Fe-SMA plates and CFRP sheets increased the columns’ energy dissipation capacity. • Fe-SMA plates were superior than CFRP sheets in reducing residual displacements.
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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 | 0.000 |
| 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) | 0.002 | 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".