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Record W2035956552 · doi:10.1177/1744259109355729

More Sustainable Masonry Façades: Preheating Ventilation Air Using a Dynamic Buffer Zone

2009· article· en· W2035956552 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

VenueJournal of Building Physics · 2009
Typearticle
Languageen
FieldEngineering
TopicSolar Energy Systems and Technologies
Canadian institutionsUniversity of TorontoToronto Metropolitan University
Fundersnot available
KeywordsMasonryVentilation (architecture)Environmental scienceThermalStructural engineeringEngineeringMechanical engineeringMeteorology

Abstract

fetched live from OpenAlex

During sunny conditions, surface temperatures on masonry façades can rise to over 40°C above the ambient temperatures. Conventional wall designs minimize the benefits of this solar heat through the use of thermal insulation. However, air that is drawn from the outdoors, between the façade and sheathing, can be used to recover heat from the masonry. The system, which utilizes a dynamic buffer zone (DBZ), acts as a solar air collector. This system can provide an effective way to preheat ventilation air at little to no extra cost, while not compromising the architectural features of the masonry wall system. A numerical model was developed to predict the amount of heat recovery possible using a DBZ. The numerical model was verified by comparing results with a commercial computational fluid dynamics software package and by conducting laboratory experiments. Preliminary results indicate that the DBZ as a solar air collector can achieve as high as 33% daily solar efficiency and seasonal solar efficiencies of up to 27%. Since this system is low-cost, yet effective, it may offer designers an opportunity to build more sustainable masonry wall systems.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.527

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 head0.008
GPT teacher head0.246
Teacher spread0.237 · 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