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Record W3198690841 · doi:10.3390/en14185648

Assessing the Energy, Indoor Air Quality, and Moisture Performance for a Three-Story Building Using an Integrated Model, Part Three: Development of Integrated Model and Applications

2021· article· en· W3198690841 on OpenAlexaffabout
Seyedmohammadreza Heibati, Wahid Maref, Hamed H. Saber

Bibliographic record

VenueEnergies · 2021
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsASHRAE 90.1Indoor air qualityEnvironmental scienceMoistureEfficient energy useAir quality indexSimulationMeteorologyEngineeringEnvironmental engineering

Abstract

fetched live from OpenAlex

The overall building performance depends mainly on the energy performance, indoor air quality, and moisture performance. In order to accurately calculate the building performance, the development of a model with the ability to integrate all three performances is required. In this research, a combination of three models namely EnergyPlus for energy, CONTAM for indoor air quality, and WUFI for moisture transport are used to develop an integrated model. The mechanism of this combination is based on the exchange of temperatures, airflows, and heating-cooling flows control variables between all three sub-models. By using the paired sample t-test, an integrated model is verified and its accuracy is validated. The accuracy of the integrated model is verified by the paired sample t-test. In order to analyze the accuracy of the integrated model in comparison with single models, four scenarios of airtight fan off, airtight fan on, leaky fan off, and leaky fan on are defined for a three-story-house subjected to three different climate cities of Montreal, Vancouver, and Miami. Percentage differences of simulated measures with the ASHRAE Standard are considered as the performance criteria. The simulated results by single and integrated models are compared and analyzed. Finally, the scenarios with the high performances are evaluated in terms of energy efficiency, indoor air quality, and moisture for Montreal, Vancouver, and Miami. Overall, it can be concluded that an integrated model should be developed.

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: none
Teacher disagreement score0.364
Threshold uncertainty score0.584

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 head0.048
GPT teacher head0.286
Teacher spread0.238 · 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

Citations15
Published2021
Admission routes2
Has abstractyes

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