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Record W2890010922 · doi:10.1177/026248931503400601

Investigating the Mechanical Response of Soy-Based Polyurethane Foams with Glass Fibers under Compression at various Rates

2015· article· en· W2890010922 on OpenAlex

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

VenueCellular Polymers · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceComposite materialPolyurethaneViscoelasticityModulusCompressive strengthGlass fiberFiberCompression (physics)Stress (linguistics)

Abstract

fetched live from OpenAlex

Polyurethane foams have very diverse mechanical properties making them suitable for a wide range of applications. Their dependence on petroleum-based constituents, however, has prompted research in the preparation and investigation of foams made from bio-based components, such as polyol derived from soybean oil. Short fiber reinforcement has been found to improve the compressive modulus and plateau stress of the foams. In this study, elastic glass fibers were used to reinforce viscoelastic polyurethane foams; the compressive behaviour of the resulting foam was observed at various strain rates. At all strain rates, the fibers reinforced the foams, improving the modulus and plateau stress when compared to the properties of neat foam. A coupling between the fiber content and strain rate-dependence was observed in the modulus and plateau stress of the foams. Lastly, despite the increase in strength and stiffness of the foams, addition of fibers did not reduce the energy absorption of the foams.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.017
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.027
GPT teacher head0.249
Teacher spread0.222 · 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