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Record W2996745486 · doi:10.1111/ina.12633

In situ efficiency of filters in residential central HVAC systems

2019· article· en· W2996745486 on OpenAlexafffund
Tianyuan Li, Jeffrey A. Siegel

Bibliographic record

VenueIndoor Air · 2019
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaAmerican Society of Heating, Refrigerating and Air-Conditioning Engineers
KeywordsElectretHVACFiltration (mathematics)Environmental scienceAir conditioningFilter (signal processing)Forced-airVentilation (architecture)Materials scienceEnvironmental engineeringProcess engineeringEngineeringComposite materialElectrical engineeringMechanical engineeringMathematics

Abstract

fetched live from OpenAlex

High-efficiency filtration in residential forced-air heating, ventilation, and air conditioning (HVAC) systems protects equipment and can reduce exposure to particulate matter. Laboratory tests provide a measure of the nominal efficiency, but they may not accurately reflect the in situ efficiency of the filters because of variations in system conditions and changes in filter performance over time. The primary focus of this paper is to evaluate the effective filtration efficiency, which is inclusive of any loading and system impacts, in 21 occupied residential homes through in-duct concentration measurements. We considered the role of filter media by testing both electret and non-electret media, as well as the role of loading by considering new and used filters. The results show that filters with higher nominal efficiency generally had higher effective filtration efficiency in the same home. In terms of performance change, there is no significant difference in efficiency between initial and 3-month non-electret filters, but the efficiency of electret filters generally decreased over time. However, both nominal efficiency and performance change were vastly overshadowed by the wide variety in loading and system conditions across homes, making it hard to predict filter efficiency in a given home without in situ measurements.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.236

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 head0.004
GPT teacher head0.183
Teacher spread0.180 · 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 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

Citations20
Published2019
Admission routes2
Has abstractyes

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