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Record W4306252955 · doi:10.6000/1929-5995.2022.11.05

The Influence of Density on the Mechanical Response of Reinforced High-Density Polyurethane Foams: A Statistical Approach

2022· article· en· W4306252955 on OpenAlexvenueno aff
Eduardo Fischer Kerche, Joziel Aparecido da Cruz, Sandro Campos Amico

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2022
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsMaterials sciencePolyurethaneComposite materialComposite numberCompression (physics)StiffnessLinear densityCellulose

Abstract

fetched live from OpenAlex

In this work, rigid polyurethane foams (RPUF) reinforced by micro fibrillated cellulose (MFC) were manufactured using the free rising method and also under confinement inside a closed mould, aiming to increase apparent density and improve mechanical response. Neat RPUF were also manufactured for comparison. The mechanical response, evaluated by compression (following ASTM D1621 standard) tests were correlated with the final composite apparent density (evaluated following ASTM D1622 standard). Simple linear regression statistical models, based on F-test, were developed using stat graphics software, aiming to understand and correlate the increment in density and its influence on the improvement in mechanical response. Different models were developed to describe the foam behavior. The main results show a more significant influence of the density on strength than stiffness for the neat RPUF, unlike the MFC-reinforced RPUF, which presented an opposite response. These effects could be caused by the lower content of voids when the foams were produced under confinement, and by the greater crosslink density, when MFC was added.

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)0.034
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
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 score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
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 head0.029
GPT teacher head0.329
Teacher spread0.300 · 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.

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

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