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Record W2081180839 · doi:10.1177/0021998308338079

Design of New Hybrid Composites using Metal Embedded in Polymer Foam and Foam Composite

2009· article· en· W2081180839 on OpenAlexaff
Ahsan Ahmed, Atef Fahim, Hani E. Naguib

Bibliographic record

VenueJournal of Composite Materials · 2009
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsMaterials scienceComposite materialComposite numberSandwich-structured compositePolyurethaneMetal foamFlexural strengthFracture toughnessSyntactic foamDeflection (physics)Aluminium foam sandwichFinite element methodToughnessStructural engineeringAluminium

Abstract

fetched live from OpenAlex

Adhesion and loading bearing properties of polyurethane (PU) foams and sandwich composite with metallic inserts are studied. Metal or solid polymer anchors are used as the load transfer components for PU foam and sandwich composites when they are used as the structural element in design. The traditional method of fixation of these components in foams is gluing and fastening. In this work, the anchors are in the form of inserts and are imbedded in the PU during the foaming process. Flexural testing was conducted on PU with and without metallic inserts to establish typical interaction trends. The load-deflection response, mode of failure, and fracture stresses of the PU structures are elucidated. Results show that long taper and leaf inserts imbedded in foam and sandwich composite provide better load carrying capacity. Comparisons between the taper and leaf inserts are documented. Leaf inserts inside a foam and sandwich composite show better results as compared to taper inserts in terms of adhesion and failure stresses. A linear elastic fracture model is also developed for the foam beam, and the fracture toughness is calculated. FEA analyses of the interaction between the inserts and the PU and sandwich composites under different loads were carried out. The FEA modeling results coincide with the experimental ones, hence validating the model.

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 categoriesMeta-epidemiology (narrow)
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 score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.029
GPT teacher head0.277
Teacher spread0.248 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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