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Record W2093392975 · doi:10.1115/1.2770754

Comparison of the Performance of a Forced-Air and a Radiant Floor Residential Heating System Connected to Solar Collectors

2007· article· en· W2093392975 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 Solar Energy Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsRadiant heatingSolar energyEnvironmental scienceRadiant energyBuilding envelopeMeteorologyThermalEngineeringElectrical engineeringOpticsRadiationPhysicsThermodynamics

Abstract

fetched live from OpenAlex

A detailed building energy analysis tool is used to model the performance of a forced-air system and a radiant floor system. These two systems use a low-temperature tank to store solar energy from a solar collector array. An electrically heated tank at a higher temperature is used to provide any additional heat needed to meet the space heating load. The simulation models developed are then used to compare the performance of the forced-air and radiant floor systems based on maintaining the same operative temperature inside the space. It is found that the portion of the heating load that comes from solar energy is higher in the case of the radiant system. This portion from solar energy increases even further when the operating temperature of the radiant floor is lowered. The results also show that the energy performance of the radiant floor relative to the forced-air system improves for houses with higher envelope R-values and infiltration rates. Given the many different interacting factors that influence the performance of the solar-assisted systems studied, it is very important to use detailed simulation models to help assess which system is more energy efficient for a particular application.

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 score0.296
Threshold uncertainty score0.432

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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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