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Record W2958507418 · doi:10.1139/cjce-2019-0223

Effect of rain leakage on hygrothermal performance of highly insulated wood-framed walls: a stochastic approach

2019· article· en· W2958507418 on OpenAlexaffvenue
Lin Wang, Hua Ge

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsConcordia University
Fundersnot available
KeywordsRainwater harvestingMoistureInfiltration (HVAC)Building envelopeEnvironmental scienceLeakage (economics)Materials scienceComposite materialMeteorologyThermal

Abstract

fetched live from OpenAlex

Wind-driven rain is one of the most important moisture sources that may lead to moisture damage risks of building envelopes, particularly when the rainwater unintentionally infiltrates into the envelope assembly through defects of the wall components. This paper proposes a stochastic modelling approach to evaluate the impact of rain infiltration on hygrothermal performance of highly insulated wood-framed walls, including an I-joist deep cavity wall, two exterior insulated walls, and a conventional 2×6 stud wall as the baseline wall. The stochastic hygrothermal models of the walls are created based on the uncertainties of material properties and rain deposition factor under different scenarios with rain infiltration deposited at different locations of the wall assembly. The stochastic simulation results show that the rainwater deposited on a water resistive barrier does not cause any moisture damage risk, but there is a significant risk when the rainwater is directly deposited on the exterior or interior surface of wood sheathing, and the interior deposition has the highest risk.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.005
GPT teacher head0.166
Teacher spread0.161 · 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 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

Citations15
Published2019
Admission routes2
Has abstractyes

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