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Record W2261583883 · doi:10.4271/2008-01-1121

Responses of the Q3, Hybrid III and a Three Year Old Child Finite Element Model Under a Simulated 213 Test

2008· article· en· W2261583883 on OpenAlexafffund
Tanya Kapoor, William Altenhof, Miroslav Tot, Andrew Howard, Jim Rasico, Fuchun Zhu, Koji Mizuno

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2008
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsHospital for Sick ChildrenUniversity of Windsor
FundersAUTO21 Network of Centres of Excellence
KeywordsTest (biology)Finite element methodComputer scienceStructural engineeringEngineeringBiologyEcology

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">This research focuses on the response of the Q3, Hybrid III 3-year-old dummy and a child finite element model in a simulated 213 sled test. The Q3 and Hybrid III 3-year old child finite element models were developed by First Technology Safety Systems. The 3-year-old child finite element model was developed by Nagoya University by model-based scaling from the AM50 (50 percentile male) total human model for safety. The child models were positioned in a forward facing, five-point child restraint system using Finite Element Model Builder. An acceleration pulse acquired from an experimental 213 sled test, which was completed following the guidelines outlined in the Federal Motor Vehicle Safety Standard 213 using a Hybrid III 3-year-old dummy, was applied to the seat buck supporting the child restraint seat. The numerical simulations utilizing the Q3, Hybrid III 3-year-old and the child finite element model were conducted using the explicit non-linear finite element code LS-DYNA. The main objective of this paper is to present the response behaviour of the child dummies in terms of head and neck injury potential in a simulated 213 test. Peak values of the neck injury criteria, calculated at the upper neck load cell for the Q3 and Hybrid III child dummies were approximately 1.21 and 0.96 respectively. Values for the head injury criteria, calculated using a 36 ms window, were observed to be 272 for the Hybrid III dummy, 260 for the child FE model and 337 for the Q3 child dummy.</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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.023
GPT teacher head0.260
Teacher spread0.238 · 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.

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

Citations6
Published2008
Admission routes2
Has abstractyes

Explore more

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