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Record W3192522105 · doi:10.3390/buildings11080334

Hygrothermal Characteristics of Cold Roof Cavities in New Zealand

2021· article· en· W3192522105 on OpenAlexaboutno aff
S. Rupp, Stephen McNeil, Manfred Plagmann, Greg Overton

Bibliographic record

VenueBuildings · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Heat Island Mitigation
Canadian institutionsnot available
Fundersnot available
KeywordsRoofDurabilityBuilding envelopeCivil engineeringGuidelineBenchmark (surveying)Ventilation (architecture)EngineeringStructural engineeringArchitectural engineeringEnvironmental scienceForensic engineeringComputer scienceGeologyMeteorologyMechanical engineeringGeography

Abstract

fetched live from OpenAlex

The New Zealand Building Code contains minimum durability requirements for components. For roof structures the requirement is 50 years if the component is structural or 15 years if it is not. Metal roof claddings are very common in New Zealand, and roof spaces are typically not deliberately ventilated. Recently, a number of roofs are failing to meet their durability requirement, and the lack of deliberate ventilation is a contributory factor in some cases. In this paper, we consider roof failures and analyse them using the hygrothermal simulation software WUFI® 2D (version 4.1). Using the National Research Council of Canada’s Guideline on Design for Durability of Building Envelopes, we evaluate to what extent the guideline can be used for such more complex models. Experimental data from a residential dwelling where excessive roof moisture issues were discovered shortly after occupancy are presented. A novel remedial solution using daytime-only ventilation to the roof cavity was trialled, and the data were used to benchmark a two-dimensional numerical simulation of the roof space using WUFI® 2D. A larger hygrothermal data set for 71 dwellings is presented together with relevant climatic conditions. The study works towards evidence-based building code changes for roof ventilation and is an example of using the guideline document for more complicated building envelope assemblies.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.833

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 head0.007
GPT teacher head0.199
Teacher spread0.192 · 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 designObservational
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

Citations5
Published2021
Admission routes1
Has abstractyes

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