Uniaxial Compressive Behavior of Concrete Columns Confined with Superelastic Shape Memory Alloy Wires
Bibliographic record
Abstract
Superelastic shape memory alloy (SMA) exhibits the ability to undergo large deformations before reverting back to its undeformed shape following the removal of the load. This unique property underlies its great potential in the seismic design and retrofitting of structure members. In this paper, superelastic SMA wires were utilized to confine concrete cylinders to enhance their axial compressive behavior. The axial carrying and deformation capacities of SMA-confined concrete cylinders are assessed by uniaxial compression testing on a total of eight SMA-confined concrete columns and one unconfined column. The influence of the amount of SMA and the prestrain level of SMA wires, as well as the reinforcing mode, on the axial carrying and deformation capacity of confined concrete columns were considered. The analysis focuses on the axial carrying capacity and deformation performance of concrete columns reinforced with superelastic SMA under different loading conditions. Based on the experimental data and analysis results, it is found that superelastic SMA wires can increase the axial loading capacity and enhance deformation performance of concrete columns. Under the same loading condition, the ultimate bearing capacity of SMA-confined concrete columns increases as the increasing of the amount of SMA wire. The results of this study verify the effectiveness of superelastic SMA in enhancing the loading capacity and deformation behavior of concrete cylinders.
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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".