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Record W2789304101 · doi:10.1177/0731684418754360

Mechanical characterisation and modelling of randomly oriented strand architecture and their hybrids – A general review

2018· review· en· W2789304101 on OpenAlexaff
Swaroop B Visweswaraiah, Marina Selezneva, Larry Lessard, Pascal Hubert

Bibliographic record

VenueJournal of Reinforced Plastics and Composites · 2018
Typereview
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsMcGill University
Fundersnot available
KeywordsFormabilityMaterials scienceAerospaceStiffnessComposite materialAutomotive industryIsotropyMechanical engineeringFibre-reinforced plasticStructural engineeringEngineering

Abstract

fetched live from OpenAlex

A comprehensive review of the mechanical characterisation and modelling of randomly oriented strand material architecture and their hybrids with laminates is presented. Randomly oriented strand composites are long discontinuous fibre systems that exhibit excellent formability characteristics and stiffness properties comparable to quasi-isotropic laminates, allowing their use in the manufacture of intricate geometric parts for automotive and aerospace industries. Randomly oriented strand architecture complements out-of-autoclave methods such as compression moulding, thermostamping and resin-transfer moulding leading to cost-reduction. Their applicability is limited to non-structural and low-load bearing applications due to their low strength properties. Continuous fibre aerospace preforms exhibiting excellent mechanical performance possess low formability characteristics and are confined to simple shell-like geometries with minimal curvatures, while incurring high-costs and long manufacturing times. Hybridisation of randomly oriented strand and with other material architectures represents trade-off solutions of formability and performance characteristics often yielding synergistic effects. Seemingly simple, randomly oriented strand architecture is a complex material system that poses several structural and process challenges. This work categorises the pertinent research work from the literature on the mechanical characterisation into the framework of a formal characterisation environment of composite structures that includes the coupon, the part and structural levels. The manufacturing, dispersion methods and measurement techniques are qualitatively assessed with reference to the mechanical properties. The discussion on modelling involves the identification of crucial characteristics of significant analytical and numerical modelling techniques devised for the prediction of the mechanical behaviour of randomly oriented strand composites and their hybrids. Emphasis is on the methods of stiffness and strength prediction. Our perspectives on the effective use of randomly oriented strand composites and their hybrids are discussed. Process characterisation and process modelling of randomly oriented strand composites and their hybrids are beyond the scope of this article.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.024
GPT teacher head0.243
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 designNot applicable
Domainnot available
GenreReview

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

Citations77
Published2018
Admission routes1
Has abstractyes

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