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Record W2618701320 · doi:10.6028/nist.ir.7238

Investigation of the impact of commercial building envelope airtightness on HVAC energy use

2005· report· en· W2618701320 on OpenAlexaff
Steven J. Emmerich, Tim McDowell, Wagdy Anis

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsThinkpath Engineering Services (Canada)
FundersU.S. Department of Energy
KeywordsHVACBuilding envelopeEnvelope (radar)Architectural engineeringEnvironmental scienceEngineeringMechanical engineeringMeteorologyAerospace engineeringGeographyAir conditioning

Abstract

fetched live from OpenAlex

This report presents a simulation study of the energy impact of improving envelope airtightness in U.S. commercial buildings. Despite common assumptions, measurements have shown that typical U.S. commercial buildings are not particularly airtight. Past simulation studies have shown that commercial building envelope leakage can result in significant heating and cooling loads. To evaluate the potential energy savings of an effective air barrier requirement, annual energy simulations were prepared for three nonresidential buildings (a two-story office building, a one-story retail building, and a four-story apartment building) in 5 U.S. cities. A coupled multizone airflow and building energy simulation tool was used to predict the energy use for the buildings at a target tightness level relative to a baseline level based on measurements in existing buildings. Based on assumed blended national average heating and cooling energy prices, predicted potential annual heating and cooling energy cost savings ranged from 3 % to 36 % with the smallest savings occurring in the cooling-dominated climates of Phoenix and Miami. In order to put these estimated energy savings in context, a cost effectiveness calculation was performed using the scalar ratio methodology employed by ASHRAE SSPC 90.1.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.991

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)0.0010.000

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 head0.048
GPT teacher head0.283
Teacher spread0.235 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations74
Published2005
Admission routes1
Has abstractyes

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