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Record W1567084427 · doi:10.4271/2009-01-0073

Evaluating Self-Unlocking Doors in Rollover Accidents using a Shock Testing Machine

2009· article· en· W1567084427 on OpenAlexaff
Andrew Gilberg, Jeremy Buckingham, Richard Clarke

Bibliographic record

VenueSAE International Journal of Passenger Cars - Mechanical Systems · 2009
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsTekna Plasma Systems (Canada)
Fundersnot available
KeywordsDoorsRollover (web design)Shock (circulatory)EngineeringAutomotive engineeringForensic engineeringStructural engineeringComputer scienceAeronauticsMedicineWorld Wide Web

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">Automotive manufacturers often rely upon features such as automatic locking to enhance the security and crashworthiness of doors in rollover accidents. This can be verified in warnings conveyed to vehicle owners through some owner's manuals. At the present time, there are no requirements on the dynamic performance of door locking systems within the Federal Motor Vehicle Safety Standards (FMVSS), although some static inertia requirements exist for latch systems.</div> <div class="htmlview paragraph">Field accident investigation and laboratory testing has revealed that some locked doors can self-unlock in rollover accidents when a vehicle sustains a roof impact. Using standard laboratory shock testing machinery, the acceleration boundaries required to trigger self-unlocking have been mapped for some sample doors. Impact pulses of surprisingly low levels of acceleration, when combined with sufficient duration have been found to trigger this response.</div> <div class="htmlview paragraph">Furthermore, two entirely different failure mechanisms have been identified and documented thus far. One failure mode results directly from inertial triggering of the locking system; this mode is anticipated by FMVSS. The second failure mode is the unexpected consequence of the vibratory response of the lock system linkage. This failure mode has not yet been recognized in the safety literature.</div> <div class="htmlview paragraph">This paper presents the findings of a field accident investigation where self-unlocking was believed to have occurred as well as test data from doors exhibiting the two different self-unlocking mechanisms.</div>

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.912
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.084
GPT teacher head0.393
Teacher spread0.309 · 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 designBench or experimental
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

Citations1
Published2009
Admission routes1
Has abstractyes

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