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Record W2807416441 · doi:10.4271/2018-01-1460

Analysis and Simulation of Low-Speed Collision of Car Front Bumpers

2018· article· en· W2807416441 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2018
Typearticle
Languageen
FieldEngineering
TopicSimulation and Modeling Applications
Canadian institutionsnot available
Fundersnot available
KeywordsCollisionFront (military)Computer scienceAerospace engineeringAutomotive engineeringPhysicsEngineeringComputer securityMeteorology

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">Bumper systems are vital to improving automotive passive safety and reducing the maintenance cost in low-speed collision. Automotive companies need to develop bumpers with adequate strength, high energy absorption rate, minimum weight and least expense. To shorten the product development period and lower the development cost, four evaluation conditions were proposed to assess the behaviors of car front bumpers based on the three main low-speed collision regulations of the US Part 581, the Canadian CFVSS215 and the European ECE-R42. A finite element method was put forward to model the car front bumper and to analyze the low-speed collision performance of the bumper system. A drop hammer impact test was carried out to verify the validity of the method, and experiment results indicated the correctness of the finite element model. The dynamic response and the energy absorption parameters of the bumper system were calculated, including structural deformation, collision force and energy absorption ratio. The maximum longitudinal deformation and the energy absorption ratio were chosen as the evaluation standards to determine whether the bumper meets the collision requirement or not. The influence of beam thickness on the collision performance of the bumper was also discussed, and a two-mm-thick beam was adopted after comparison.</div></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.

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 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 score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.261
Teacher spread0.249 · 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