Numerical and experimental study on adaptive stiffness yaw damper for suppressing abnormal vibration of high-speed trains
Bibliographic record
Abstract
The mismatch between the parameters of the yaw damper and the equivalent conicity of wheel rail contact can lead to abnormal vibration of rail vehicles, while the stiffness variation range of traditional yaw dampers is very small, covering a limited range of equivalent conicity of wheel rail contact, resulting in the risk of carbody hunting at low conicity and bogie hunting at high conicity. To overcome the abovementioned shortcomings of traditional yaw dampers and reduce the abnormal vibration of high-speed trains under various operating conditions, this study proposes an adaptive stiffness yaw damper. The effectiveness of this solution was confirmed through roller testing rig and multi-body dynamic simulations. The results show that the device can dynamically adjust the stiffness according to the operating conditions of the vehicle, effectively reducing the carbody and bogie hunting under extreme wheel rail contact conditions, and thereby reducing the abnormal vibration of high-speed trains. At the same time, this device helps reconcile the trade-off between the curve negotiation performance and stability of vehicle, indirectly lessening the requirement for wheel–rail maintenance and reducing operational and maintenance expenses.
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 | 0.000 |
| 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) | 0.000 | 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".