Vibration Analysis of Axially Loaded Bridges Traversed by Accelerating Vehicles With Passenger Dynamics
Bibliographic record
Abstract
An investigation into the dynamics of vehicle-passenger-structure-induced vibration of suspension bridges traversed by accelerating vehicles is carried out. The vehicle including the driver and passengers is modeled as a half-car planer model with six degrees-of-freedom. In addition, the stiffness of compliant bushings at the connecting points of the shock absorbers to the body is considered. The bridge is assumed to obey the Timoshenko beam theory with axial load and arbitrary conventional boundary conditions. The roughness of the bridge is assumed as a differentiable function of location. Due to continuously moving the location of the variable loads on the bridge, and in the presence of damping force, the governing differential equations become complicated. The numerical simulations presented here are for the case of a vehicle traveling at a constant acceleration on a uniform bridge with rough surface and simply supported end conditions. The relationship between the bridge vibration characteristics, bridge roughness, and the vehicle speed and acceleration is rendered, which yields into search for a particular acceleration and speed that determines the maximum value of the dynamic deflection and the bending moment of the bridge. Results obtained from the Timoshenko beam theory are compared with those from the Euler-Bernoulli beam for which full agreements are found. Finally, the maximum deflection of the beam under moving loads is compared with that of the case with static loading.
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 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".