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Effect of high-temperature high-speed airflow on the thermo-oxidative aging of epoxy polymer and composite: An experimental study

2025· article· en· W4415679175 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePolymer Testing · 2025
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsSafran Electronics (Canada)
FundersSafran Aircraft EnginesLabexAgence Nationale de la Recherche
KeywordsAirflowEpoxyPolymerFlow (mathematics)

Abstract

fetched live from OpenAlex

The objective of this study is to investigate the effect of the airflow on the thermo-oxidative aging of polymer matrix composites (PMCs). Understanding how airflow affects the aging process is crucial for designing composite parts subjected to airflow conditions, such as in aeronautics. We conducted tests in an oven at 150 °C and in wind tunnel at Mach 0.85 to compare static and dynamic aging conditions. The airflow conditions are determined using a Reynolds Averaged Navier–Stokes (RANS) Computional Fluid Dynamic (CFD) simulation to estimate the pressure and temperature conditions at any point of the air-polymer interface. The oxidation is characterized by colorimetric and roughness testing. Based on our experimental data and simulation results, we show that the compressibility effect of the airflow affects the pressure field at the interface and the thermal boundary layer affects the temperature of the samples. The samples aged in the wind tunnel are always more oxidized than those aged under oven conditions. The airflow accelerates the thermo-oxidation by mainly increasing the static pressure.

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.

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 score0.008
Threshold uncertainty score0.842

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 head0.263
Teacher spread0.253 · 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