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Record W2589059572 · doi:10.1016/j.aej.2017.01.033

Inclusive analysis and performance evaluation of solar domestic hot water system (a case study)

2017· article· en· W2589059572 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAlexandria Engineering Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsNatural Resources Canada
FundersOffice of Energy Research and DevelopmentNatural Resources Canada
KeywordsEnvironmental scienceGreenhouse gasEnvironmental engineeringRoofEnergy performanceSolar energyEngineeringGreenhouseEnergy consumptionMeteorologyCivil engineeringGeographyElectrical engineering

Abstract

fetched live from OpenAlex

In recent years Solar Domestic Hot Water systems have increased significantly their market share. In order to better understand the real-life performance of SDHW systems, a single detached house was selected for extensive monitoring. Two solar panels were installed on the house roof to provide thermal energy to the Domestic Hot Water (DHW) system. The house was equipped with data logging system and remotely monitored with performance data collected and analyzed over one year. The paper presents the inclusive analysis and performance evaluation of SDHW system, including DHW recirculation loop, under Canadian weather conditions for average family occupancy (two adults and two kids) with daily average DHW, draws of 246 L. Moreover, the study is carried out a significant recommendation to improve the SDHW performance, decrease the gas energy consumption and reduce greenhouse gas (GHG) emissions. The SDHW performance depends mainly on DHW flow rate, draw time and duration, city water temperature, DHW recirculation loop control strategy and system layout. The performance analysis results show that 91.5% of the collected solar energy is transferred to the DHW heating load through the solar tank. The contribution to DHW heating load is about 69.4% from natural gas and 30.6% from solar. The recirculation loop is responsible for close to 34.9%, of DHW total energy.

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 score0.042
Threshold uncertainty score0.416

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 head0.010
GPT teacher head0.239
Teacher spread0.229 · 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