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Record W3034741473 · doi:10.18280/ijdne.150302

Thermo-Exergetic Assessment of the Steam Boilers Used in a Cuban Thermoelectric Facility

2020· article· en· W3034741473 on OpenAlexvenueno aff
Yoalbys Retirado–Mediaceja, Yanán Camaraza-Medina, Andrés A. Sánchez-Escalona, Héctor Luis Laurencio-Alfonso, Marcelo Fabián Salazar-Corrales, Carlos Zalazar-Oliva

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Control Systems Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsNuclear engineeringThermoelectric effectEnvironmental scienceEngineeringWaste managementMechanical engineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

In this work, was made a thermo-exergy evaluation of four steam boilers that are used in the thermoelectric power plant belong to a Cuban productive company, which, have not been sufficiently studied from the energy point of view.The methodology for the estimation of the thermal and exergy efficiency values of these facilities is established and systematized in an algorithm.For this purpose, in this paper the GOST method is used in the assess evaluation of the steam boilers (direct and indirect method).The final results show a high correspondence between the gross thermal efficiency values obtained by the direct and indirect methods, their difference does not exceed 2.7% in the 87.5% of each variant calculated and the average value was 1.89%.The use of the thermal energy and the exergy in the boilers compute values near of 90.14 and 46.42% respectively.The application of proposal procedure shows a favorable behavior of the facilities object of study in this paper.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.234
Teacher spread0.226 · 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 designObservational
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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