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Cross-wind effects on road and rail vehicles

2009· article· en· 189 citations· W2084938823 on OpenAlex· 10.1080/00423110903078794

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
Meta-epidemiology (narrow)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Simulation or modelingConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.704
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.005
GPT teacher head0.231
Teacher spread
0.226 · how far apart the two teachers sit on this one work
Validation status
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

Abstract

This paper presents a review of recent research that has been carried out on the cross-wind effects on road and rail vehicles. After a brief introduction to the issues involved, the risk analysis framework is set out. All risk analysis methods require some knowledge of cross-wind aerodynamic force and moment coefficients, and methods of obtaining these through full scale and wind tunnel testing and through Computational Fluid Dynamics methods are then described. The picture of the flow fields around vehicles that is suggested by these measurements and calculations is then presented, and the steady and the unsteady aerodynamic force characteristics described. The detailed methodology for using this information to predict accident risk is then set out, including details of the vehicle dynamics system models that can be used. Finally potential alleviation methods are described and suggestions made for further works.

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.

The record

Venue
Vehicle System Dynamics
Topic
Aerodynamics and Fluid Dynamics Research
Field
Engineering
Canadian institutions
Bombardier (Canada)
Funders
not available
Keywords
AerodynamicsWind tunnelEngineeringComputational fluid dynamicsSet (abstract data type)Moment (physics)Aerodynamic forceVehicle dynamicsMarine engineeringComputer scienceAerospace engineering
Has abstract in OpenAlex
yes