Longitudinal seismic response control of long-span cable-stayed bridges using shape memory alloy wire-based lead rubber bearings under near-fault records
Bibliographic record
Abstract
This article investigates the efficiency of a new generation smart isolation system, namely shape memory alloy wire-based lead rubber bearing, for the seismic response control of long-span cable-stayed bridge systems under near-fault ground motions. The constitutive model of shape memory alloy wire-based lead rubber bearings is coded and implemented into OpenSees as a new user element. This user element can accurately predict the re-centering capability and energy dissipation capacity of shape memory alloy wire-based lead rubber bearing under different excitations. The Sutong cable-stayed bridge in China, with a main span of 1088 m, is taken as an example. Results reveal that implementing shape memory alloy wires into lead rubber bearings can effectively increase the self-centering property and, as a result, reduce the residual deformation in shape memory alloy wire-based lead rubber bearings under near-fault ground motions. Shape memory alloy wires lead to an increase in the horizontal stiffness and energy dissipation capacity of shape memory alloy wire-based lead rubber bearings. The deck displacement is restricted effectively, and a superior structural performance is achieved in terms of the deck acceleration. Shape memory alloy wire-based lead rubber bearings can effectively reduce the base shear and base moment of the towers. However, it is observed that an increase in the shape memory alloy wire diameter may have negligible effect on the deck acceleration, tower base shear and moment, and in some cases, on the pier base shear and moment.
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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".