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Record W2616364523 · doi:10.1111/str.12220

A consistent experimental protocol for the strain rate characterization of thermoplastic fabrics

2017· article· en· W2616364523 on OpenAlexaff
Fabien Coussa, Jacques Renard, Sébastien Joannès, Jean-Christophe Teissedre, Rémy Bompoint, Nicolas Feld

Bibliographic record

VenueStrain · 2017
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsSafran Electronics (Canada)
FundersPermitting, Siting and AnalysisDuPont
KeywordsCharacterization (materials science)Strain rateMaterials scienceNonlinear systemUltimate tensile strengthConsistency (knowledge bases)Structural engineeringComposite materialStrain (injury)Tensile testingConstitutive equationRange (aeronautics)Computer scienceEngineeringArtificial intelligenceFinite element methodNanotechnology

Abstract

fetched live from OpenAlex

Abstract This paper introduces an experimental procedure aiming at performing a consistent mechanical characterization of textile composites behavior, under static and dynamic loadings, and particularly their macroscopic strain rate‐dependent mechanisms. The procedure includes the design and validation of a reduced specimen adapted to dynamic testing, which guarantees the consistency of the identified macroscopic properties under a wide range of strain rates. An interrupted high speed tensile apparatus was also developed to investigate the strain rate sensitivity of the nonlinear constitutive behavior from = 10 − 4 s − 1 to 102 s − 1. The originality of this experimental device lies in its ability to stop high speed loadings before ultimate failure, at adjustable, accurate strain levels. Finally, an extensive characterization campaign was performed. Results reveal a high strain rate dependency of the linear and nonlinear behavior. The procedure therefore generates consistent characterization data that may trustworthily be used for modeling purposes.

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)0.002
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.049
GPT teacher head0.314
Teacher spread0.265 · 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
GenreMethods

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

Citations9
Published2017
Admission routes1
Has abstractyes

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