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Ventilation Control Strategy Using the Supply CO <sub>2</sub> Concentration Setpoint

2005· article· en· W2110953376 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

VenueHVAC&R Research · 2005
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsSetpointVentilation (architecture)AirflowEnvironmental scienceOccupancyAir quality indexIndoor air qualityComputer scienceAutomotive engineeringSimulationEngineeringEnvironmental engineeringArchitectural engineeringMeteorologyMechanical engineering

Abstract

fetched live from OpenAlex

This paper proposes a new ventilation control strategy applied to multiple spaces subject to variable occupancy. The strategy specified for real-time, online ventilation control takes advantage of uninitiated air from some overventilated spaces to be used as fresh outdoor air in order to reduce system energy use while maintaining the indoor air quality (IAQ) in each space. This proposed strategy maintains a supply CO2 concentration setpoint low enough to dilute CO2 generated by full occupancy in critical zones. The supply CO2 concentration setpoint could be determined online using the monitored zone airflow rates. It is tested and evaluated by making comparisons with other known control strategies. An existing VAV system installed at the École de technologie supérieure is used to evaluate this new strategy. The outdoor air fraction and associated energy use of investigated ventilation control strategies are calculated using the VAV system component models that are developed and validated against the monitored data.

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)0.001
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 score0.044
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.045
GPT teacher head0.316
Teacher spread0.271 · 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