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Record W2092223132 · doi:10.1177/0040517508093415

Improving Heat Transfer Models of Air Gaps in Bench Top Tests of Thermal Protective Fabrics

2009· article· en· W2092223132 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTextile Research Journal · 2009
Typearticle
Languageen
FieldEngineering
TopicFire dynamics and safety research
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Saskatchewan
KeywordsEnclosureHeat transferMaterials scienceConvectionTest benchThermalMechanicsConvective heat transferNatural convectionThermal radiationIsothermal processThermodynamicsMechanical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

An improved model has been developed to simulate heat transfer in horizontal air spaces between thermal protective fabrics and test sensors in bench top tests, such as the thermal protective performance test. This model calculates the radiation and convection heat transfer from the test specimen to the test sensor. Radiation heat transfer is calculated by treating the bottom boundary of the enclosure as a series of isothermal rectangular pieces. Convection heat transfer is calculated using an empirical correlation and by assuming that convection only occurs over a portion of the cross-section of the enclosure. Predicted times required to exceed the Stoll second degree burn criterion were found to be within 3 % of those measured during actual bench top tests of steel shimstock using air gaps from 6.4 mm (1/4 in.) to 19.1 mm (3/4 in.).

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.027
GPT teacher head0.303
Teacher spread0.276 · 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