Improving the seismic performance of post-tensioned self-centering connections using SMA angles or end plates with SMA bolts
Bibliographic record
Abstract
Abstract Cyclic performance of self-centering post-tensioned (PT) steel beam-column connections has been investigated numerically by introducing stiffened angle connection, shape memory alloy (SMA) angle connection and SMA bolted end plate connection. Results show that stiffened angle connection can significantly improve the seismic performance in terms of moment capacity (up to 40% increase), post-decompression stiffness (up to 58% increase) and energy dissipation capacity (up to 67% increase) compared to the corresponding connections with top and seat angles by accumulating permanent strain in the angle and stiffener. On the other hand, SMA angle connection has robust self-centering behavior which eliminates the need for replacement of energy dissipating element at the end of a strong earthquake. The limit states of other structural components, such as bolts and beam flanges, can be higher due to stress concentration which has been demonstrated in this study by presenting plasticity index (PI) and rupture index (RI) of the bolts. The use of an SMA bolted end plate connection can remove damage or residual deformation in connection components where the SMA bolts are responsible for energy dissipation and PT strands help re-center the connection. A full factorial analysis has been conducted by considering four important parameters such as end plate length, gage length, SMA bolt diameter, and pretension forces in the bolts to evaluate the seismic performance of this connection. A prediction equation has been presented to estimate the connection response and verified through further finite element analyses.
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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".