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Strain rate effects for aluminum and magnesium alloys in finite element simulations of steering wheel armature impact tests

2002· article· en· W2030943477 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

VenueFatigue & Fracture of Engineering Materials & Structures · 2002
Typearticle
Languageen
FieldMaterials Science
TopicHigh-Velocity Impact and Material Behavior
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsArmature (electrical engineering)Magnesium alloyMaterials scienceFinite element methodMagnesiumStrain rateAluminiumMetallurgyStructural engineeringAlloyComposite materialMechanical engineeringEngineeringMagnet

Abstract

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ABSTRACT This paper addresses the strain rate effects for aluminum and magnesium steering wheel armatures when they are subjected to dynamic impact tests. Two geometrically different steering wheel armatures, a three spoke proprietary aluminum alloy armature and a four spoke magnesium alloy (AM50A) armature, underwent experimental impact testing. The testing conditions for each armature were different; testing with the aluminum alloy armature involved impacts with a deformable chestform and the magnesium armature experienced impact tests with a rigid plate. Finite element models of all testing apparatuses were developed for both testing conditions and numerical simulations were conducted based on the experimental method employed. Strain rate effects for the aluminum alloy were considered using the Cowper–Symonds constitutive relation and a Johnson–Cook material law was utilized for the magnesium alloy. Simulations were conducted with and without strain rate effects considered. The comparison between the experimental and numerical methods illustrate that there is only a minor change in the numerical testing results with the inclusion of strain rate effects, however, a better correlation between experimental and numerical methods occurs.

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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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.273
Teacher spread0.258 · 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