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The influence of moisture on the energy performance of retrofitted walls

2020· article· en· W3208821929 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

VenueMATEC Web of Conferences · 2020
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTransmittanceMoistureTransient (computer programming)Water contentThermalEnvironmental scienceMaterials scienceThermal transmittanceEnergy performanceEfficient energy useComposite materialMeteorologyGeotechnical engineeringEngineeringComputer scienceThermal resistance

Abstract

fetched live from OpenAlex

The renovation of old building facades should be performed mainly considering the building energy demand reduction. For this purpose, it is necessary to select retrofitted solutions that should be able of minimizing heat losses through walls. However, it is not only the nominal thermal transmittance that influences the amount of heat transported through the wall, but also the moisture content within the walls under in- service conditions. The main objective of this paper is the evaluation of the influence of the moisture content on the energy performance of retrofitted walls. A numerical study using the software WUFI Pro was carried out to quantify the influence of wind driven rain on the thermal transmittance of different wall assemblies exposed to different climates and orientations. This study reports the transient thermal transmittance of different retrofitted wall solutions as a function of moisture content.

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)0.000
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 score0.021
Threshold uncertainty score0.225

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 head0.014
GPT teacher head0.188
Teacher spread0.174 · 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