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Record W3039531246 · doi:10.1051/e3sconf/202017202002

Resilience of Canadian homes and small buildings to the effects of climate change - Risk of deterioration due to condensation within wall assemblies

2020· article· en· W3039531246 on OpenAlexafffundabout
Maurice Defo, Michael Lacasse

Bibliographic record

VenueE3S Web of Conferences · 2020
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsNational Research Council Canada
FundersInfrastructure Canada
KeywordsRelative humidityEnvironmental scienceCladding (metalworking)Thermal insulationMoistureForensic engineeringMaterials scienceComposite materialMeteorologyEngineeringGeography

Abstract

fetched live from OpenAlex

The objective of this study was to assess the potential effects of climate change on the moisture performance and durability of typical Canadian wood-frame walls using hygrothermal simulations, with a particular attention to the risk of condensation. To reduce the risk of condensation, the National Building Code of Canada (NBCC) recommends a maximum air leakage rate of 0.10L/sm 2 at 75 Pa in buildings with interior relative humidity not greater than 55%. This leakage rate was evaluated in five cities across Canada for a wood-frame wall having brick cladding, with and without outdoor insulation and both walls meeting the minimum insulation requirements given in NBCC. It is found that the risk of condensation will be reduced in the future in all 5 cities analysed. The reduction in the risk of condensation is slightly higher for the wall with no exterior insulation than for the wall with exterior insulation. This reduction in the risk of condensation means that the limit of 0.10L/(sm 2 ) for building having a warm side relative humidity of less than 55% may be reconsidered in the future. There may however be some risks associated with the increase in rain in some cities.

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 score0.050
Threshold uncertainty score0.995

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)0.0000.000

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 head0.023
GPT teacher head0.213
Teacher spread0.190 · 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

Citations3
Published2020
Admission routes3
Has abstractyes

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Same venueE3S Web of ConferencesSame topicHygrothermal properties of building materialsFrench-language works237,207