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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".