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Record W4396967134 · doi:10.1177/14658011241255060

Low-velocity impact behavior of woven fabric-reinforced natural rubber composites

2024· article· en· W4396967134 on OpenAlex
Xin Wang, Shing‐Chung Wong, Xiaosheng Gao, Soon Won Moon

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePlastics Rubber and Composites Macromolecular Engineering · 2024
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsSyncrude (Canada)
Fundersnot available
KeywordsComposite materialMaterials scienceNatural rubberWoven fabric

Abstract

fetched live from OpenAlex

The progressive damage behaviors of woven fabric-reinforced natural rubber panels under low-velocity impact were studied by the drop-weight tests. The woven fabrics considered include nylon, Kevlar, and carbon. The impact force, impact energy, and delamination area were analyzed, and the damaged samples were observed using an optical microscopy and an X-ray scanner to investigate the damage mechanisms. The results show that the peak force of impact increases while the absorbed energy decreases as the fiber strength/stiffness and fiber content increase. Based on the peak force and the delamination area results, the natural rubber/Carbon/2 specimen, which consists of two carbon fabric layers inside the natural rubber, displays the best impact performance among the composites considered in this study.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.176
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.004
GPT teacher head0.219
Teacher spread0.215 · 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