Seismic fragility assessment of concrete bridge pier reinforced with shape memory alloy considering residual displacement
Bibliographic record
Abstract
Post-earthquake rapid recovery of bridge is one of the prime objectives for performance based design. Shape Memory Alloy (SMA) has the unique ability to undergo large deformation, but can regain its undeformed shape through stress removal (i.e. superelasticity), which brings about an added advantage in seismic regions. In an attempt to reduce permanent damage of concrete bridges, a hybrid RC bridge pier configuration is presented here. In the proposed configurations of bridge piers, the plastic hinge region is reinforced with SMA and the remaining portion with regular steel. Residual displacement is a critical parameter for performance based earthquake engineering as it dictates the functionality of a member after an earthquake. This paper evaluates fragility-based seismic vulnerability of SMA reinforced concrete bridge pier considering residual displacement. Fragility curves have also been used to assess the relative performance of SMA with conventional steel RC bridge pier. Probabilistic Seismic Demand Model (PSDM) has been used in generating the fragility functions. The development of these fragility curves for bridge piers aid in expressing the potential impact of SMA on the bridge pier vulnerability.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".