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Record W2063699197 · doi:10.1115/smasis2008-318

Design, Fabrication and Mechanical Characterization of Pyramidal Periodic Cellular Metal/Polyurethane Foam Hybrid Materials

2008· article· en· W2063699197 on OpenAlexaff
J. E. Campbell, G.D. Hibbard, Hani E. Naguib

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPolyurethaneMaterials scienceComposite materialFabricationResilience (materials science)Metal foamStiffnessCompressive strengthComposite numberCharacterization (materials science)NanotechnologyPorosity

Abstract

fetched live from OpenAlex

A new type of hybrid material was designed and fabricated by reinforcing periodic cellular metals (PCMs) with rigid polyurethane (PU) foams. A pyramidal PCM geometry and various densities of two-phase rigid polyurethane foam were used to fabricate three different hybrid materials. These novel hybrid materials may find useful application as cores in sandwich structures. By increasing the density of the polyurethane foam used in the PCM/PU foam hybrids, the stiffness of the hybrid increased allowing the stiffness to be tailored for a specific application. Furthermore, the strength of the hybrids was greater than that of the PCM or foam alone, and in most configurations the strength was greater than the sum of the strength of the PCM and the polyurethane foam. Next, the resilience of the hybrids was greater than that of the PCM or foam alone and was also greater than the sum of the resilience of the PCM and foam. Finally, the impact energy at which surface failure would occur was greater in the hybrid samples than the foams or the PCM and was found to increase with increasing foam density.

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)0.000
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 score0.224
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.010
GPT teacher head0.175
Teacher spread0.165 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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