Implementation of a Simplified Method in Design of Hysteretic Dampers for Isolated Highway Bridges
Bibliographic record
Abstract
Using seismic isolation systems for highway bridges modifies the structure’s principal vibration modes and effectively reduces the seismic base shear conveyed from the superstructure to the substructure. However, for some low-damping rubber isolation bearings, large displacements can be a problem. Supplemental hysteretic dampers can be introduced into the base-isolated bridge, which might nevertheless increase the structure base shear, and the merit of adding dampers has to be evaluated properly. In this paper, a simplified method was implemented for the design of a low-cost hysteretic damper, and the resulting isolator-damper system was tested experimentally. The design method used is based on an equivalent linearization approach. A full-scale elastomeric isolation bearing was characterized and used in the design of a hysteretic damper. Both the isolator and the damper went through cyclic testing and real-time dynamic substructuring (RTDS) methods to verify the capacity of the method to design base isolation-damping systems. The study was further extended to extreme seismic loading by nonlinear time-history analysis. The results reveal that the simplified method is adequate for use in the performance optimization of isolated-damped bridges.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".