MétaCan
Menu
Back to cohort
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 OpenAlexaff
Dan Ding, Tian Tang, Guowen Song, André McDonald

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.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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

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 designSimulation or modeling
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

Citations51
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueTextile Research JournalSame topicTextile materials and evaluationsFrench-language works237,207