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Record W3116893468 · doi:10.1002/ese3.855

A comprehensive comparative investigation on solar heating and cooling technologies from a thermo‐economic viewpoint—A dynamic simulation

2020· article· en· W3116893468 on OpenAlexaff
Hassan Jafari Mosleh, Pooria Behnam, Maryam Abbasi Kamazani, Omid Mohammadi, Soheil Kavian, Pouria Ahmadi, Marc A. Rosen

Bibliographic record

VenueEnergy Science & Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsEnvironmental scienceMeteorologySolar air conditioningCooling loadSolar energyAtmospheric sciencesEngineeringMechanical engineeringAir conditioningGeographyElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

Abstract The yearly thermo‐economic performance is dynamically investigated for three solar heating and cooling systems: solar heating and absorption cooling (SHAC), solar heating and ejector cooling (SHEC), and heating and solar vapor compression cooling (HSVC). First, the effects of important design parameters on the thermo‐economic performance of the systems to supply the heating and cooling loads of the building are evaluated. The systems are parametrically analyzed with the weather conditions of Tehran, Iran. The results show that the life cycle costs (LCC) of the SHAC and HSVC systems are alike and much lower than those of the SHEC system. The HSVC system exhibits the best performance from exergetic and solar fraction viewpoints. The comparative analysis shows that the energy efficiencies of the SHAC and SHEC systems are higher in colder climatic conditions. However, the collector efficiency of the HSVC system declines in colder climates, mainly due to the lower solar intensities relative to in hotter climates. Further, the solar fraction of the SHAC system is higher than the SHEC technology under all climatic conditions. Moreover, higher values of solar fractions are obtained under colder weather conditions for the SHEC and HSVC systems. The best economic performance is observed for the SHAC and HSVC technologies, having significantly lower LCCs than the SHEC system. These lower LCCs under colder climatic conditions are due to the lower cost of supplying the heating load compared to the cooling load. Furthermore, all systems exhibit enhanced exergetic performance in colder weather conditions. The yearly thermo‐economic performance is dynamically investigated for three solar heating and cooling systems: SHAC, SHEC, and HSVC. In addition, the effects of important design parameters on the thermo‐economic performance of the systems to supply the heating and cooling loads of the building are evaluated.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.232
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2020
Admission routes1
Has abstractyes

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