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Record W4281479427 · doi:10.32920/19852495.v1

Mode II Interlaminar fracture toughness of flax and glass epoxy hybrid composites

2022· preprint· en· W4281479427 on OpenAlexaff
Wilfred Stephen Ekeoseye

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceFracture toughnessComposite materialEpoxyDelamination (geology)Composite numberFinite element methodFracture (geology)ToughnessFailure mode and effects analysisStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Delamination is a significant mode of failure in composite materials during service; It prevents the adequate dissemination of load between plies lowering the strength of the material, which could consequently lead to a cascading effect of failure. Providing more data on the delamination properties of composite material during loading will increase the adoption of composite materials in more industries. This study aims to characterize the mode II interlaminar fracture toughness of hybrid composites – hybrid one [0G/0F]8S, hybrid two [04G/04F]S and hybrid three [04G/ (90/0)2F]S. Furthermore, this study explores the application of Finite Element Analysis as a tool to assess the damage in a composite material during delamination. In this study, mode II fracture toughness of three hybrids of flax and glass epoxy is characterized according to the ASTM standard D7905 standard. Finite Element Analysis is applied to assess the failure in the flax plies of the respective hybrid.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.010
GPT teacher head0.258
Teacher spread0.248 · 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
Published2022
Admission routes1
Has abstractyes

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