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Record W3121127686 · doi:10.21608/bfemu.2021.140384

The Efficiency of Window Design and Orientation on Long-Cycle Passive Solar Heating Demands in Residential Buildings.(Dept.A)

2021· article· en· W3121127686 on OpenAlexaboutno aff
Amjed Maghrabi

Bibliographic record

VenueMEJ Mansoura Engineering Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsUpgradeWindow (computing)Window of opportunityEnvironmental scienceCost reductionEngineeringComputer scienceAerospace engineeringBusiness

Abstract

fetched live from OpenAlex

This paper describes research conducted to evaluate the efficiency of various window components with respect to solar heating demands of a prototype residential house in Waterloo, Canada. A number of proposed high performance window types are compared against base-case conventional windows in attempt to trace the long cycle cutback in heating demands. Three window orientations including South, North and West facing were considered. RetScreen passive solar heating project model was used for this purpose. The upgrade of windows has shown a dramatic cutback in passive solar heating demands with preference in South facing direction. Initial cost of window upgrade is reimbursed, due to reduction of active solar heating cost, in less than ten years depending on the type of window selected. it is concluded that the economical upgrade of a window depends on the initial installation cost required for the upgrade and the project life.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.004
GPT teacher head0.189
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2021
Admission routes1
Has abstractyes

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