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Record W4403805825 · doi:10.1080/17480272.2024.2415975

Phase change materials to improve the energy savings of wood building envelopes in Quebec

2024· article· en· W4403805825 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueWood Material Science and Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaMinistère de l'Éducation et de l'Enseignement supérieurChina Scholarship Council
KeywordsPhase changeMaterials scienceBuilding envelopeEnvironmental sciencePhase (matter)Energy (signal processing)Architectural engineeringEngineeringCivil engineeringForensic engineeringComposite materialEngineering physicsMeteorologyPhysics

Abstract

fetched live from OpenAlex

A large amount of energy is used to heat and cool buildings in the construction industry. Moreover, wood frame buildings’ relatively low thermal mass limits energy efficiency and thermal comfort. Thermal energy storage via latent heat can effectively increase the thermal inertia of the building envelope, minimising the indoor temperature fluctuations and improving the occupant thermal comfort. This paper evaluated the energy efficiency and thermal comfort of an air-conditioned wood frame building by using biobased phase change materials (PCM) as the middle layer of a building envelope. Numerical simulations were conducted to investigate the effect of different factors (PCM melting point, surface area, thickness, and position) by adding a PCM layer into building walls to reduce annual heating and cooling energy consumption. The results of the numerical simulations showed that a phase change material layer can effectively decrease the energy demand of buildings, especially in cold areas. Based on the conditions investigated, the optimum solution can reduce the cooling, heating and annual energy consumption by 47%, 34% and 38%, respectively, compared to a reference building without a PCM layer. Moreover, an economic and environmental study of buildings containing biobased PCM is presented.

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 score0.009
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.021
GPT teacher head0.273
Teacher spread0.253 · 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