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Record W4395681648 · doi:10.1016/j.egyr.2024.04.030

Performance evaluation of a novel fuel cell and wind-powered multigeneration system

2024· article· en· W4395681648 on OpenAlexaff
Farbod Esmaeilion, M. Soltani, Faraz Forutan Nia, Mohammad Hatefi, Alireza Taklifi, Maurice B. Dusseault, Marc A. Rosen

Bibliographic record

VenueEnergy Reports · 2024
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsUniversity of Ontario Institute of TechnologyUniversity of WaterlooBalsillie School of International Affairs
Fundersnot available
KeywordsExergyEnvironmental sciencePayback periodExergy efficiencyWork (physics)Internal rate of returnWind powerProcess engineeringAutomotive engineeringEnvironmental economicsWaste managementEnvironmental engineeringEngineeringMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

The introduction of promising energy sources to satisfy human desires is extremely crucial. The present work studies the performance of an original solid oxide fuel cell-wind-based polygeneration system for producing hydrogen, sodium hypochlorite, potable water, heating, cooling, and electrical power. In the methodological concept, energy, exergy, economic, and exergoenvironmental assessments are carried out to evaluate the system performance concerning different parameters. The technical outcomes depict that the system can produce 363 kW of electrical power, 162 kW of cooling, and 46.5 kW of heating at the design operating settings while the energy and exergy efficiencies are 55.5% and 38.1%, respectively. Moreover, over a year of operation, the system can provide 19.9 × 10 4 m3 gaseous hydrogen, 50.9 ×‎ 103 m3 potable water, and 5.31 tonnes of sodium hypochlorite to increase the gained benefits from this efficient and cost-effective system. To evaluate the prevalence of the designed system, the economic outcomes demonstrate that the payback period is 1.5 years while the internal rate of return is 0.70. Moreover, the system presents relatively proper environmental benefits based on the obtained outcomes from the exergoenvironmental study; the exergoenvironmental factor, exergy stability factor, and sustainability index are 0.50, 0.56, and 1.6, respectively.

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 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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.929

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 communication0.0000.000
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 head0.020
GPT teacher head0.240
Teacher spread0.221 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations7
Published2024
Admission routes1
Has abstractyes

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