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Record W2031606420 · doi:10.1115/detc2012-71272

Active Aerodynamic System to Improve the Safety and Handling of Race Cars in Lane Change and Wet Road Maneuvers

2012· article· en· W2031606420 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsAerodynamicsAutomotive engineeringController (irrigation)Vehicle dynamicsControl systemEngineeringActive safetyComputer scienceAeronauticsSimulationControl engineeringAerospace engineering

Abstract

fetched live from OpenAlex

Motor vehicle racing is usually supported by advanced engineering technologies considering every attempt to improve the performance of the car. A major objective of the engineering support is to enhance the handling and safety of race cars. The normal force on every tire has important effects on the handling properties, longitudinal dynamic and the safety of vehicle. Therefore, developing technologies to control and adjust these forces is highly desirable. The capability of active aerodynamic system to compensate the overall downward force of the vehicle has been widely published in literature. This paper shows the effectiveness of an actively controlled aerodynamic system to improve the handling and safety of a small-size race car in a lane-change maneuver and driving on wet roads. The analyses of a nonlinear vehicle model with active aerodynamic system, the controller structure and the control law have been presented. Computer simulations were carried out to verify the model and evaluate the performance of the control system.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score0.297

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)

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.

Opus teacher head0.006
GPT teacher head0.184
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations7
Published2012
Admission routes1
Has abstractyes

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