Low-temperature effect on seismic performance of isolated highway bridges with high damping rubber bearings
Bibliographic record
Abstract
The high damping rubber (HDR) bearing and lead high damping rubber (LHDR) bearing have been proven to be temperature-sensitive bearings in previous research, especially at low temperatures. However, this characteristic may affect the seismic performance of isolated bridges with HDR and LHDR bearings at low ambient temperatures. Due to the absence of explanations for the temperature-dependent mechanisms of rubber bearings, current seismic design codes for isolated bridges in Japan do not consider low-temperature environmental factors. To thoroughly evaluate the seismic performance of isolated bridges with HDR and LHDR bearings at low ambient temperatures and provide a reference for current seismic design codes, a nonlinear bridge model is established to conduct dynamic analysis at ambient temperatures of −20℃, 0℃, and 23℃. The multi-layer thermo-coupled Bouc-Wen (MTBW) model is adopted to replace the bilinear model and simulate the behavior of the HDR and LHDR bearings in the bridge model to account for the low-temperature effect. The ductility of the bridge pier and the shear strain of the isolation bearing are selected as two engineering demand parameters. The corresponding damage states are defined in incremental dynamic analysis (IDA) and seismic fragility analysis. The research outcomes show that low temperatures have significant effects on the seismic performance of isolated bridges, with a reduction in the maximum shear strain and energy dissipation of bearings and an increase in displacement of the pier. The effectiveness of the isolation system is weakened at low ambient temperatures. Moreover, the failure probability becomes higher at low ambient temperatures for both the bridge pier and bearing at each damage state. At low ambient temperatures, the probability of pier damage occurring before bearing damage increases, which becomes the dominant damage mode in most cases. The low-temperature effect is recommended to be thoroughly assessed for isolated highway bridges in cold earthquake-prone regions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".