MétaCan
Menu
Back to cohort
Record W3109061714 · doi:10.1201/9781003076155-93

Low-Velocity Impact Response of a Continuous Glass Fiber/Polypropylene Composite

2020· book-chapter· en· W3109061714 on OpenAlexaff
David Trudel‐Boucher, Martin Bureau, J. Denault, B. Fisa

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsPolypropyleneMaterials scienceComposite materialComposite numberGlass fiberFiber

Abstract

fetched live from OpenAlex

Low-velocity impact behavior of a continuous glass fiber/polypropylene composite molded in a [0/90]2s stacking configuration has been investigated. Optical microscopy and ultrasonic scanning were used to evaluate the impact-induced damage. The predominant damage mechanisms were found to be matrix cracking, delamination and a small amount of fiber breakage at the edge of the front face indentation. Analysis of the load-time signals recorded during impact showed that the load corresponding to the onset of delamination is independent of the impact energy in the range tested. Tensile and flexural tests performed on impacted specimens showed that the residual strengths and flexural modulus decrease with increasing incident impact energy, while the post-impact residual tensile modulus remains constant. The dynamic interlaminar fracture toughness was evaluated from the critical strain energy release rate during impact of specimens with a delamination simulated by an embedded insert. Results are then compared with interlaminar fracture toughness values obtained during steady crack growth.

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 score0.006

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 head0.014
GPT teacher head0.233
Teacher spread0.219 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicMechanical Behavior of CompositesFrench-language works237,207