MétaCan
Menu
Back to cohort
Record W2177461088 · doi:10.1177/0040517515581582

Mechanical behavior of airbag fabrics under quasi-static loading: an experimental evaluation of macro- and meso-scopic properties

2015· article· en· W2177461088 on OpenAlexaff
S. Zacharski, Frank Ko, Reza Vaziri

Bibliographic record

VenueTextile Research Journal · 2015
Typearticle
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceComposite materialAirbagCrimpYarnNonlinear systemStructural engineeringCoatingEngineering

Abstract

fetched live from OpenAlex

In this paper the current generation of 350 dtex airbag coated and uncoated fabrics are examined experimentally under a multitude of simple and complex deformations. The geometric dimensions of the fabric architecture and the load–elongation behavior of the yarn constituents are studied. Furthermore, deformational shear behavior of airbag fabrics, which have not previously been investigated, are examined here. The stress–strain behavior of the yarn as well as the fabrics with and without coating are found to be highly nonlinear. Under uniaxial loading, nonlinearities of the fabric occur at lower strains due to crimp of the fabric, whereas under biaxial loading, the nonlinearity occurs at low and intermediate strain levels resulting from a combination of the inherent nonlinear material response of the yarn and geometric changes in the fabric structure. The data generated not only provide the basis for structural analysis of the airbag, but can also be used to develop more sophisticated definitions of the constitutive behavior of the fabric.

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 score0.007

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 head0.419
GPT teacher head0.475
Teacher spread0.057 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueTextile Research JournalSame topicTextile materials and evaluationsFrench-language works237,207