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Comparison of a Variable Refrigerant Flow Heat Pump Model in Cooling Mode to Data from ASHRAE HQ

2022· article· en· W4297497456 on OpenAlexafffund
Aziz Mbaye, Massimo Cimmino

Bibliographic record

VenueASHRAE/IBPSA-USA Building Simulation Conference · 2022
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaHydro-Québec
KeywordsASHRAE 90.1RefrigerantEnvironmental scienceMean squared errorEnergy consumptionCoefficient of performanceHeat pumpApproximation errorStatisticsSimulationComputer scienceMeteorologyMathematicsEngineeringHeat exchangerGeographyMechanical engineering

Abstract

fetched live from OpenAlex

This paper presents the development of a variable refrigerant flow (VRF) heat pump model aimed towards multi-year simulations. The model is modular and allows the simulation of any number of indoor and outdoor units. Model parameters are inferred from a parameterestimation procedure on available manufacturer data. The model is compared against data recorded from the VRF system that serves the first floor of the ASHRAE Headquarters Building in Atlanta, comprised of 22 indoor units and 2 outdoor units. Comparison results show that the model predicts, for a daily time scale, the total energy consumption during a 2 months cooling period with a relative error, a normalised mean bias error (NMBE) and a coefficient of variation of the root mean square error (CVRMSE) of 4.1%, 7.9% and 20.9%, respectively. The relative error between simulation results and measured data for daily energy consumption varies from 0.2% to 43% during weekdays.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.529
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 communication0.0000.001
Open science0.0010.000
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 head0.076
GPT teacher head0.336
Teacher spread0.260 · 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 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

Citations0
Published2022
Admission routes2
Has abstractyes

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