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Record W4403465518 · doi:10.1016/j.tsep.2024.102991

Enhancing building energy efficiency: Innovations in glazing systems utilizing solid-solid phase change materials

2024· article· en· W4403465518 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThermal Science and Engineering Progress · 2024
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsGlazingPhase (matter)Phase changeMaterials scienceSolid surfaceProcess engineeringArchitectural engineeringEnvironmental scienceEngineering physicsComposite materialEngineeringChemistryChemical physics

Abstract

fetched live from OpenAlex

This study investigates the energy efficiency of a double-glazing window (DGW) integrating a solid–solid phase change material (SSPCM) with limited thickness, applied to the inner glass pane within the air gap. Numerical model, validated against experimental data, is developed using a finite volume method in ANSYS Fluent. In this model, the Discrete Ordinates (DO) model is applied to simulate radiation, while the enthalpy-porosity approach is used to capture the solidification and melting processes in the phase change material . With this model, the energy performance of the system is analyzed under various transient temperature values (10 to 30 °C) and ranges (1 to 5 °C) during the coldest and hottest days of the year, as well as during cloudy and sunny days in Montreal (Dfb), Vancouver (Cfb), and Miami (Aw). According to the obtained results in Montreal, the DGW-SSPCM system consistently saves energy under summer sunny conditions, with optimal performance when the SSPCM remains transparent. However, it incurs energy losses in cloudy days, where the energy lost is 2.3 times greater than the energy saved in sunny days. In Vancouver, the system shows consistent energy savings, particularly at T c = 30 °C, with average savings of 20.5 kJ (23 %) under summer sunny conditions. The system is most beneficial in Vancouver, where winter energy savings in cloudy days (50.6 kJ) are 7.1 times greater than the losses in sunny days (7.1 kJ). In Miami, the system results in energy losses by 60 % and 5 % (at T c = 30 °C) under both summer sunny and cloudy conditions, respectively, indicating unsuitability for its climate. During winter sunny conditions, all three cities experience energy losses, with Vancouver showing the lowest of 7.1 kJ (3 %) and Montreal the highest of 64.4 kJ (19 %) at T c = 30 °C. In winter cloudy conditions, the system saves energy in all cities, with the highest savings in Miami of 54.5 kJ (26 %) at T c = 30 °C. Overall, the SSPCM-DGW system has proven to be beneficial in Vancouver across various conditions in terms of energy and visual performance. These findings highlight the necessity of considering localized climate factors when designing and implementing energy-efficient glazing systems. Finally, the SSPCM-DGW system has provided complete visual clarity during office hours, making it more suitable for commercial buildings.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.281
Teacher spread0.263 · 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