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Record W2155305469 · doi:10.1520/jai102034

Tests of a Novel Ceiling Panel for Maintaining Space Relative Humidity by Moisture Transfer from an Aqueous Salt Solution

2009· article· en· W2155305469 on OpenAlexaff
Melanie Fauchoux, Carey J. Simonson, David A. Torvi

Bibliographic record

VenueJournal of ASTM International · 2009
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis of Composite Materials
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCeiling (cloud)Relative humidityMaterials scienceAqueous solutionMoistureHumiditySalt (chemistry)Salt solutionEnvironmental scienceComposite materialThermodynamicsStructural engineeringChemistryEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract Radiant ceiling panels are used to heat and cool occupied spaces as they satisfy comfort conditions better than all-air systems. Radiant panels also consume less energy as fan size and heating and cooling loads are reduced. A disadvantage of radiant ceiling panels is the lack of control of the relative humidity (RH) in the space, which can affect comfort. The goal of this research is to create a new ceiling panel that can transfer both heat and moisture to maintain temperature and RH in a space. The heat and moisture transfer panel (HAMP) is constructed from a porous membrane and uses a salt solution as the transfer media. Tests have been run on the HAMP using different salt solutions and temperatures in order to determine the amount of moisture transferred between the HAMP and the air. Given initially dry air, the HAMP is able to increase the RH of the air up to 15 % RH with water and up to 7.8 % RH with a salt solution. This results in a change in humidity ratio of 2.7 g/kg with water and 1.3 g/kg with a salt solution.

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 score0.006

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)0.0020.000

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 head0.019
GPT teacher head0.268
Teacher spread0.249 · 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

Citations14
Published2009
Admission routes1
Has abstractyes

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