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Record W2025600087 · doi:10.1533/ijcr.2004.0284

Quasi-static crushing of S-shaped aluminum front rail

2004· article· en· W2025600087 on OpenAlexfundno aff
Zheng Li, Tomasz Wierzbicki

Bibliographic record

VenueInternational Journal of Crashworthiness · 2004
Typearticle
Languageen
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsnot available
FundersUniversity of Waterloo
KeywordsFinite element methodStructural engineeringDeflection (physics)CrashworthinessStatic testingUltimate tensile strengthQuasistatic processAluminiumEngineeringMaterials scienceComposite materialPhysics

Abstract

fetched live from OpenAlex

A combined experimental, analytical and numerical/FEM study on the quasi-static axial crushing of thin-walled aluminum S-rails is presented. Quasi-static test was performed on S-rails with a prescribed cross-head speed 10 mm/sec. Finite element models were developed and found to reproduce the crushing response to a significant degree of accuracy with respect to the onset of collapse, the subsequent localization of plastic deformation and the overall energy absorbing capability. With the failure parameters calibrated from uniaxial tensile tests, FEM simulation can also be used to predict the fracture onset. Based on a simplified model, an analytical solution for the force-deflection response was developed, which can be applied to an early design stage of the ȁSȁ frame. Finally, the same problem was solved by means of CrashStudio and comparisons were made with some known solutions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), 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

Citations22
Published2004
Admission routes1
Has abstractyes

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