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Record W1977851743 · doi:10.1504/ijex.2013.052544

Dynamic exergetic performance assessment of an integrated solar pond

2013· article· en· W1977851743 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.

Bibliographic record

VenueInternational Journal of Exergy · 2013
Typearticle
Languageen
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsOntario Tech University
FundersUniversity of Ontario Institute of Technology
KeywordsExergySolar pondEnvironmental scienceSolar energyExergy efficiencyEnvironmental engineeringAtmospheric sciencesProcess engineeringNuclear engineeringMeteorologyEngineeringGeologyPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

In this paper, we present an experimental investigation of the exergetic performance of a solar pond integrated with solar collectors (with a surface area of 2096 m² and a depth of 2 m, and four flat–plate collectors with dimensions of 1.90 m × 0.90 m). A data acquisition device is used to measure and record the temperatures hourly at various locations in the pond. An exergy model is developed to study the dynamic exergetic performance of the solar pond integrated with solar collectors in terms of exergy efficiencies which are then compared with the corresponding energy efficiencies. Thus, the energy efficiencies are found to be 21.33%, 23.59%, 24.28% and 26.52%; the exergy efficiencies are found to be 20.02%, 21.66%, 22.24% and 23.84% for using 1, 2, 3 and 4 collectors, respectively. The energy efficiencies are compared with the corresponding exergy efficiencies.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.320
Teacher spread0.307 · 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