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Record W4306409614 · doi:10.1177/00952443221133240

Experimental evaluation of utilizing synthetic continuous fiber reinforcements for thermoplastics as an alternative to steel-based analogs

2022· article· en· W4306409614 on OpenAlexaff
Nabeel Ahmed Syed, Utkarsh Utkarsh, Muhammad Rizwan Tariq, Amir Hossein Behravesh, Qingping Guo, Ghaus Rizvi, Remon Pop‐Iliev

Bibliographic record

VenueJournal of Elastomers & Plastics · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsMaterials scienceComposite materialEpoxySynthetic fiberKevlarCuring (chemistry)CoatingCompression moldingFiberMold

Abstract

fetched live from OpenAlex

Despite being inexpensive and robust, steel cord reinforcements are often prone to pose risks to user health and safety in some industrial applications such as escalator handrails and rubber conveyor belts. Steel cords can reduce the overall stability and performance of the application over time due to their inherent creep accompanied by cyclic thermal expansion and contraction. In this context, this research focuses on replacing steel cords in some critical thermoplastic polyurethane (TPU) composite applications with continuous sustainable alternate synthetic fibers that possess high specific strength (e.g. carbon, glass, and Kevlar fibers). The first part of this research characterizes the effect of epoxy coating on synthetic fibers alone by studying their mechanical properties before and after modification, whereas the second half of the research involves reinforcing a TPU matrix with raw and epoxy-coated synthetic fibers to fabricate fiber-reinforced composites by compression molding. The effect of the curing temperature of epoxy on the end performance of the manufactured specimen was also tested. An in-depth analysis of mechanical and morphological studies showed that, at almost the same volume fraction of fibers, the TPU reinforced composites with modified carbon fibers showed higher load-bearing capacities than steel cord-based analogs. Conversely, a wide variety of other relevant industrial and commercial applications can potentially draw significant benefits by implementing these modified carbon/TPU composites instead of steel cords.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.330
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.031
GPT teacher head0.320
Teacher spread0.289 · 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 teacher head, 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Elastomers & PlasticsSame topicNatural Fiber Reinforced CompositesFrench-language works237,207