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Record W1604151765

Heat recovery in building envelopes

2003· article· en· W1604151765 on OpenAlexfundno aff
Iain S. Walker, Max H. Sherman

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2003
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryUniversity of AlbertaU.S. Department of Energy
KeywordsInfiltration (HVAC)Péclet numberBuilding envelopeHeat transferMechanicsEnvironmental scienceMaterials scienceThermodynamicsThermalPhysics
DOInot available

Abstract

fetched live from OpenAlex

Infiltration has traditionally been assumed to contribute to the energy load of a building by an amount equal to the product of the infiltration flow rate and the enthalpy difference between inside and outside.Some studies have indicated that application of such a simple formula may produce an unreasonably high contribution because of heat recovery within the building envelope.The major objective of this study was to provide an improved prediction of the energy load due to infiltration by introducing a correction factor that multiplies the expression for the conventional load.This paper discusses simplified analytical modeling and CFD simulations that examine infiltration heat recovery (IHR) in an attempt to quantify the magnitude of this effect for typical building envelopes.For comparison, we will also briefly examine the results of some full-scale field measurements of IHR based on infiltration rates and energy use in real buildings.The results of this work showed that for houses with insulated walls the heat recovery is negligible due to the small fraction of the envelope that participates in heat exchange with the infiltrating air.However; there is the potential for IHR to have a significant effect for higher participation dynamic walls/ceilings or uninsulated walls.This result implies that the existing methods for evaluating infiltration related building loads provide adequate results for typical 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.

How this classification was reachedexpand

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0010.000
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 head0.009
GPT teacher head0.152
Teacher spread0.143 · 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 teacher head, not a consensus.

Study designObservational
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

Citations11
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueUniversity of North Texas Digital Library (University of North Texas)Same topicHygrothermal properties of building materialsFrench-language works237,207