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Record W3128053792 · doi:10.3390/en14030724

Reviewing the Exergy Analysis of Solar Thermal Systems Integrated with Phase Change Materials

2021· article· en· W3128053792 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

VenueEnergies · 2021
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsExergyProcess engineeringExergy efficiencyThermal energy storageThermalSolar energyPhase-change materialThermodynamicsHeat transferEnvironmental scienceHeat transfer fluidPhotovoltaic thermal hybrid solar collectorNuclear engineeringMaterials scienceEngineeringPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

The application of thermal storage materials in solar systems involves materials that utilize sensible heat energy, thermo-chemical reactions or phase change materials, such as hydrated salts, fatty acids paraffin and non-paraffin like glycerol. This article reviews the various exergy approaches that were applied for several solar systems including hybrid solar water heating, solar still, solar space heating, solar dryers/heaters and solar cooking systems. In fact, exergy balance was applied for the different components of the studied system with a particular attention given to the determination of the exergy efficiency and the calculation of the exergy during charging and discharging periods. The influence of the system configuration and heat transfer fluid was also emphasized. This review shows that not always the second law of thermodynamics was applied appropriately during modeling, such as how to consider heat charging and discharging periods of the tested phase change material. Accordingly, the possibility of providing with inappropriate or not complete results, was pointed.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.062
GPT teacher head0.289
Teacher spread0.228 · 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