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Record W2809094628 · doi:10.4271/09-06-01-0006

Wheel Chock Key Design Elements and Geometrical Profile for Truck Vehicle Restraint

2018· article· en· W2809094628 on OpenAlexafffund
Denis Rancourt, Charles Khazoom, Carl Blanchette, Laurent Giraud, Jacques Lemire, Yves St-Amant

Bibliographic record

VenueSAE International Journal of Transportation Safety · 2018
Typearticle
Languageen
FieldEngineering
TopicTransportation Safety and Impact Analysis
Canadian institutionsUniversité de Sherbrooke
FundersInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsTruckKey (lock)Automotive engineeringEngineeringComputer scienceComputer security

Abstract

fetched live from OpenAlex

Wheel chocks are rather simple compliant mechanisms for stabilizing vehicles at rest. However, chocks must be carefully designed given the complex interaction between the chock and the tire/suspension system. Despite their importance for safety, literature is surprisingly limited in terms of what makes a wheel chock efficient. Using simple but reliable quasi-static mechanical models, this study identifies mechanical requirements that help to avoid a number of failure modes associated with many existing wheel chocks. Given that chock grounding is not always possible, a chock’s maximum restraining capacity is only obtained when the wheel is completely supported by the chock. A generic chock profile is proposed to achieve this objective while mitigating undesirable failure modes. The profile is based on fundamental mechanical principles and no assumption is made on the load interaction between the chock and the wheel. A more specific clothoid chock profile is further proposed to minimize the tire dynamic contact force with the chock and its rate of variation when engaging a chock in a dynamic situation. The proposed chock design should be tested in the future to confirm its performance.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.810
Threshold uncertainty score0.576

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 head0.018
GPT teacher head0.271
Teacher spread0.253 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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