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Record W4295093138 · doi:10.1177/17442591221121932

Drainage of infiltrated rainwater in wall assemblies: Test method, experimental quantification, and recommendations

2022· article· en· W4295093138 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

VenueJournal of Building Physics · 2022
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsDrainageRainwater harvestingCavity wallDurabilityWater retentionMaterials scienceGeotechnical engineeringEnvironmental scienceDrainage system (geomorphology)Composite materialSoil waterGeologySoil scienceEcology

Abstract

fetched live from OpenAlex

Drainage reduces the amount of water able to infiltrate toward the interior of wall assemblies. However, a portion of the infiltrated water remains in the assembly after drainage has occurred. The degree to which this retained portion of water affects the durability of the wall assembly can be evaluated by means of hygrothermal simulations. However, the number of studies reporting information on the retention percentage that can be applied as input for hygrothermal simulations and on the drainage performance of wall assemblies is, in general, quite limited. Therefore, an experimental study was developed, to assess governing test methods to evaluate drainage characteristics and to quantify retention of water in wall test specimens having various cavity widths and incorporating different drainage materials. It was concluded that apart from the absolute amount of retained water, the lateral spreading of water in the cavity and the overall wetted area, should also be considered, thereby resulting in reporting the retained amount relative to the wetted area. The latter values provide more detailed information on the behavior of water in the cavity. Additionally, it was concluded that a clear cavity of 1 mm can drain water more efficiently than a cavity of 10 mm. As well, the surface texture of drainage materials affected the spreading and retention of water within the cavity and the use of a drainage mat in the cavity resulted in an increased relative retention but a reduced lateral spreading of the water.

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)0.001
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 score0.046
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.289
Teacher spread0.262 · 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