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Record W2125984309 · doi:10.1177/1744259112444021

Numerical modeling and experimental investigations of thermal performance of reflective insulations

2012· article· en· W2125984309 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 · 2012
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAtticStack (abstract data type)Heat transferThermalMaterials scienceThermal insulationRoofSample (material)MetreConvectionNuclear engineeringMechanical engineeringMechanicsEngineeringComposite materialStructural engineeringComputer scienceThermodynamicsLayer (electronics)

Abstract

fetched live from OpenAlex

Reflective insulations are being used in attics, flat roof, and wall systems. Numerical modeling and experimental investigations were conducted to assess the thermal performance of assemblies with reflective insulations. In this article, the present model was used to verify the use of the ASTM C-518 test method for measuring the effective thermal resistances (R-values) of sample stacks comprising reflective insulations. Two tests were conducted on sample stacks using heat flow meter apparatus. The sample stack consists of two expanded polystyrene layers and a reflective insulation installed in between. The model predictions agreed with the measured heat fluxes within ±1%. The article also discusses the combined effect of heat transfer by convection and radiation in the airspace facing the reflective insulation, showing that the derived R-value from the test data resulted in underestimation of the effective R-value of the sample stack.

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 score0.117
Threshold uncertainty score0.223

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 head0.021
GPT teacher head0.252
Teacher spread0.231 · 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