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Record W1973377557 · doi:10.1177/0040517510388547

Characterizing the performance of a single-layer fabric system through a heat and mass transfer model - Part I: Heat and mass transfer model

2010· article· en· W1973377557 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

VenueTextile Research Journal · 2010
Typearticle
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMass transferMoistureHeat transferMaterials scienceThermalMechanicsBoundary layerWater vaporEvaporative coolerLayer (electronics)Air layerAir gap (plumbing)ThermodynamicsComposite materialMeteorologyPhysics

Abstract

fetched live from OpenAlex

A mathematical model was developed to study the coupled heat and moisture transfer through a fabric system that consists of a single layer of fabric and an air gap. Properties of air and moisture are sensitive to temperature and, hence, were assumed to be functions of local temperature. Therefore, the model is applicable to a broad range of boundary conditions. A numerical scheme was proposed to solve the distributions of temperature and water vapor concentration throughout the layers, from which the thermal and evaporative resistances of the fabric system were evaluated. Experiments were conducted for two particular fabrics using a sweating guarded hotplate, and the data show good agreement with the model predictions, suggesting that the heat and mass transfer model is capable of accurately predicting thermal and evaporative resistances for the single-layer fabric system.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.122
GPT teacher head0.337
Teacher spread0.215 · 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