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Record W2147859994 · doi:10.1177/0021998311418850

Thermal insulation by heat resistant polymers for solid rocket motor insulation

2011· article· en· W2147859994 on OpenAlexafffund
Ashraf Fathy Ahmed, Suong V. Hoa

Bibliographic record

VenueJournal of Composite Materials · 2011
Typearticle
Languageen
FieldEngineering
TopicFiber-reinforced polymer composites
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaConcordia University
KeywordsMaterials scienceComposite materialAramidAmmonium polyphosphateKevlarThermal insulationEpoxyAir permeability specific surfaceCuring (chemistry)Solid-fuel rocketFire retardantFiberPropellant

Abstract

fetched live from OpenAlex

A new method for the development (design, fabrication, and characterization) of asbestos-free rubbers for use as rocket motor insulators is presented. Such insulation is based on chopped carbon fiber (CCF) and aramid fiber in pulp form asreinforcement for ethylene propylene diene monomer (EPDM) along with ammonium polyphosphate (AP) flame retardant agent. Six millimeters long CCFs and/or Kevlar pulp (KP) are dispersed in the EPDM polymeric matrix to obtain a homogenous master batch for curing. The new method involves the development of two types of prepregs andthe lamination of these types of prepregs. The first one consists of CCF/EPDM/AP (50 phr CCF) and the second type of prepreg KP/EPDM/AP (30 phr KP). Laminates composed of six alternative layers of these prepregs have been shown to exhibit better thermal, mechanical, physical, and ablative properties than their non-laminated counterparts.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.012
GPT teacher head0.215
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), 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

Citations90
Published2011
Admission routes2
Has abstractyes

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