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Record W2071585061 · doi:10.1520/jai102924

Correlation Between Water Vapor and Air Permeability of Building Materials: Experimental Observations

2011· article· en· W2071585061 on OpenAlexaffabout
Phalguni Mukhopadhyaya, Devin Batcheller, Kumar Kumaran, John Lackey, David van Reenen, Nicole Normandin

Bibliographic record

VenueJournal of ASTM International · 2011
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsWater vaporPermeability (electromagnetism)Air permeability specific surfaceVapor pressureRelative humidityMaterials scienceHumidityDensity of airBuilding envelopeEnvironmental scienceVapour pressure of waterComposite materialChemical engineeringThermodynamicsChemistryEngineeringOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract Two fundamental properties of building materials that influence the hygrothermal performance of building envelope systems are water vapor permeability and air permeability. The driving forces for water vapor and air transmission through building materials are, respectively, partial water vapor pressure and total air pressure differentials. The theoretical similarity of the driving forces would suggest the possibility of a relationship between water vapor and air permeability. During past two decades, researchers at the National Research Council of Canada—Institute for Research in Construction have compiled a database of measured air permeability and water vapor permeability properties of building materials commonly used in North America. This material properties database was examined to identify the degree to which air permeability and water vapor permeability of the building materials might be functionally related. The database was segregated into categories for different material types. An approximately linear relationship could, within some categories, be observed between water vapor permeability and air permeability. There were however approximately as many categories within which no relationship between the parameters was apparent as there were categories within which functional relationships between the parameters were apparent. Within categories where functional relationships were apparent, the form of the relationships generally depended on the mean relative humidity at which water vapor permeability was measured. In most cases, a definitive functional form of the relationship between water vapor permeability and air permeability could not be established.

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 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 score0.053
Threshold uncertainty score0.885

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)0.0010.000

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 head0.047
GPT teacher head0.249
Teacher spread0.203 · 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 teacher head, 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

Citations16
Published2011
Admission routes2
Has abstractyes

Explore more

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