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Record W3008353656 · doi:10.1002/pc.25549

Open hole tension and compression behavior of 3D braided composites

2020· article· en· W3008353656 on OpenAlexaff
Shuangqiang Liang, Qihong Zhou, Chen Ge, Frank Ko

Bibliographic record

VenuePolymer Composites · 2020
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceComposite materialBraidTension (geology)Ultimate tensile strengthCompression (physics)Composite numberTransverse planeComposite laminatesFiberCompressive strengthTensile testingStructural engineering

Abstract

fetched live from OpenAlex

Abstract The damage tolerant behavior of 3D braided composites is evaluated in terms of the open‐hole notch strength test under tensile and compressive loading. The influence of fiber architecture is evaluated by comparing 3D braid with and without axial yarns as well as laminated composites based on ASTM quasi‐static tension and compression testing standard. The results show that the notched and un‐notched properties of the two types of 3D braided composites are similar under tension and compression loading. Comparing to laminates, both types of 3D braided composites demonstrated superior notch insensitivity than laminated composites. For the failure behavior of the 3D braided composites, under tension loading, crack of both notched specimens tends to propagate along the notch and finally render the specimen to failure. Clear cracks usually presented on the samples without axial yarns, while not for the specimens with axial yarn. Under compression loading, the two types of 3D braided composite are also macroscopically similar, showing transverse fracture. The modified Fabric Geometry Model is used to predict the tensile properties of 3D braided composite. The predicted and experimental results are shown to be in good agreement.

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 head0.029
GPT teacher head0.258
Teacher spread0.229 · 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

Citations26
Published2020
Admission routes1
Has abstractyes

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