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Record W1989072034 · doi:10.1002/er.1056

Energy and exergy analysis of Salihli geothermal district heating system in Manisa, Turkey

2005· article· en· W1989072034 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

VenueInternational Journal of Energy Research · 2005
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsUniversity of Ontario Institute of Technology
Fundersnot available
KeywordsExergyGeothermal gradientExergy efficiencyGeothermal energyHeat exchangerEnvironmental scienceEnvironmental engineeringWaste managementProcess engineeringEngineeringMechanical engineeringGeology

Abstract

fetched live from OpenAlex

This study deals with an energy and exergy analysis of Salihli geothermal district heating system (SGDHS) in Manisa, Turkey. In the analysis, actual system data are used to assess the district heating system performance, energy and exergy efficiencies, specific exergy index, exergetic improvement potential and exergy losses. Energy and exergy losses throughout the SGDHS are quantified and illustrated in the flow diagram. The exergy losses in the system, particularly due to the fluid flow, take place in the pumps and the heat exchanger, as well as the exergy losses of the thermal water (e.g. geothermal fluid) and the natural direct discharge of the system. As a result, the total exergy losses account for 2.22, 17.88 and 20.44%, respectively, of the total exergy input to the entire SGDHS. The overall energy and exergy efficiencies of the SGDHS components are also studied to evaluate their individual performances and determined to be 55.5 and 59.4%, respectively. Copyright © 2005 John Wiley & Sons, Ltd.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.030
GPT teacher head0.328
Teacher spread0.298 · 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