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Record W2419301264 · doi:10.1051/meca/2015099

Thermo-economic assessment of three-stage combined cycle power system using ammonia-water mixture

2016· article· en· W2419301264 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

VenueMechanics & Industry · 2016
Typearticle
Languageen
FieldEngineering
TopicThermodynamic and Exergetic Analyses of Power and Cooling Systems
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsExergyExergy efficiencyProcess engineeringSortingGenetic algorithmOrganic Rankine cycleMulti-objective optimizationComputer scienceWorking fluidSensitivity (control systems)Optimization problemEnvironmental scienceMathematical optimizationPower (physics)MathematicsEngineeringElectricity generationThermodynamicsMechanical engineeringAlgorithm

Abstract

fetched live from OpenAlex

Thermo-economic modeling and multi-objective optimization studies are performed for a three-stage combined cycle system using ammonia water mixture as working fluid. This combined cycle plant is composed of three main subsystems, Brayton cycle, Rankine and Kalina cycles. Energy and exergy analyses and multi-objective optimization are included. In order to optimize the system, a multi-objective optimization method based on a fast and elitist non-dominated sorting genetic algorithm is applied to determine the best design parameters of the system. The two objective functions considered for the optimization purpose are the total cost rate of the system including equipment costs, and the second objective function is the system exergy efficiency. The total cost rate of the system is minimized while the cycle exergy efficiency is maximized using an evolutionary algorithm. In order to convey a deeper understanding and identify the necessary trade-offs within the optimized objectives in a multifaceted fashion, multi-objective optimizations are conducted in the study. Moreover, a closed form equation is derived to provide the relationship between the exergy efficiency and total cost rate. Finally, sensitivity analyses are performed to better understand the effects of various key design parameters on the total exergy destruction rate, exergy efficiency and total cost rate of the system.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.836
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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