Vehicle roll-over stability in strong winds on long-span bridges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High-sided, lightly loaded vehicles are known to be prone to accidents in strong, gusty winds. While wind related accidents may occur anywhere on roads, vehicles are more sensitive to wind while passing over bridges given the higher road elevations, exposure and possible speed-up effects at various bridge locations compared to ground level roads. The paper presents an extended roll-over model for estimation of vehicle stability in strong, gusty winds. The study example is of a Double-Deck Suspension Bridge where four typical vehicles were investigated, including: a tractor-trailer truck; an intercity bus; a courier van; and a full-sized SUV. Using a sectional model of the bridge deck and vehicle models built in scale, six component force and moment coefficients were measured at various lanes for the full azimuth of wind directions. The effects of the road level were also investigated. Based on expected wind turbulence properties at the bridge site and measurements of wind flow modifications at various deck locations, vehicle stability against roll-over has been predicted for various wind and vehicle speeds. For calibration purposes comparative tests and analyses on the same vehicles were carried out for the Confederation Bridge, PEI, Canada, and the results compared with the adopted policy for traffic control in strong winds on that bridge. Recommendations for traffic management in strong winds on tested bridges were drawn.
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.
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 it