MétaCan
Menu
Back to cohort

Flexible Polyurethane Foams Filled with Coconut Coir Fibres and Recycled Tyre - Part II: Compression and Energy Absorption

2012· article· en· W2092787840 on OpenAlexaff
Chan Wen Shan, Maizlinda Izwana Idris, Imran H. Ghazali

Bibliographic record

VenueAdvanced materials research · 2012
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsImpact
Fundersnot available
KeywordsMaterials scienceCompressive strengthComposite materialPolyurethaneCoirCompression (physics)Composite numberFiller (materials)ModulusAbsorption (acoustics)

Abstract

fetched live from OpenAlex

The mechanical properties of flexible PU foams filled with coconut coir fibres and recycled tyre were investigated. The densities of foam composites are slightly increase as 2.5 wt% filler loading to foams. Among all, the highest density value is 54.048 kg/m 3 as compared with pure foam which is 52.69kg/m3. In compression test, the compressive response of foam composites was presented in three different regions which are elastic, plateau, and densification. The compressive results show the foams filled with 2.5wt% (50F50P) offered the greatest properties. It shows an increment of 10.784% for compressive modulus whereas an increment of 9.329% for compressive strength as compared with pure PU foam. This result may attribute to its varying cellular structure. The compressive results also indicated that there was no any contribution from tyre particles to the foam’s compressive properties unless it is added as the composition described above. Nevertheless, the results of energy analysis show added fillers can enhanced the foam’s energy absorption characteristic. The energy absorbability is found increased on composite which having good compressive properties as well as having cellular structure of possess smaller cell size.

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)0.000
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 score0.012
Threshold uncertainty score0.705

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.037
GPT teacher head0.323
Teacher spread0.286 · 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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueAdvanced materials researchSame topicPolymer composites and self-healingFrench-language works237,207