Seismic Damage Mechanism of CRTS-II Slab Ballastless Track Structure on High-Speed Railway Bridges
Bibliographic record
Abstract
China Railway Track System II (CRTS II) slab ballastless track structure is one of commonly adopted track systems on the high-speed railway bridge, which has been found seismically vulnerable under strong earthquakes. To investigate the earthquake-induced damage mechanism of the CRTS II slab ballastless track structure, a nonlinear numerical model of typical 7-span simply supported bridge–track system was established by the finite element software OpenSees and well calibrated by the test data and relative literatures. The nonlinear time history analysis was employed to calculate seismic responses of bridge and track parts under a suite of 10 seismic records. Results demonstrate that the sliding layer in the track structure is the most damage-prone component, especially at the bridge-subgrade transition section, and the shear alveolar may also sustain earthquake-induced fail. By analyzing the seismic damage mechanism of the track structure, this paper reveals that the nonuniform displacement responses of the girders and friction plate at the bridge-subgrade transition section are main factors that result in the extensive damage of the sliding layer and failure of the shear alveolar. However, the damage of these two components are beneficial to reduce the seismic responses of other components in the track structure and protect them from being damaged. From the perspective of engineering safety, the sliding layer and shear alveolar should be rigorously designed because the residual displacement of the sliding layer increases along with the maximum displacement and the failure of the shear alveolar may make the whole track structure failed.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".