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Sulfur as a Fuel Source in a Combined Power Cycle Equipped with a Dry Flue Gas Desulfurization System

2016· article· en· W2523485667 on OpenAlexafffund
Yasmine M. Hajar, Kimberley B. McAuley, Frank Zeman

Bibliographic record

VenueEnergy & Fuels · 2016
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsRoyal Military College of CanadaQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFlue-gas desulfurizationFlue gasCombined cycleChemistryFlue-gas emissions from fossil-fuel combustionSulfurWaste managementAnhydriteHeat recovery steam generatorHeat of combustionPower stationCoalIntegrated gasification combined cycleElectricity generationCombustionThermal power stationTurbineMaterials scienceSyngasMetallurgyThermodynamicsOrganic chemistryEngineeringGypsumMechanical engineeringPower (physics)

Abstract

fetched live from OpenAlex

This paper investigates the novel use of elemental sulfur as a fuel in a combined cycle power plant, wherein sulfur is oxidized in the combustion chamber to produce work from a gas turbine. Produced sulfur dioxide is then reacted with calcite to produce anhydrite (CaSO 4 ) in a flue gas desulfurization unit. The desulfurization reaction is exothermic, producing heat that can be converted to electricity by passing the exhaust gas through a heat recovery steam generator. The cases studied in this work are a 410 MW natural gas combined cycle, used as a reference case, a sulfur combined cycle (SCC) consisting of a typical industrial gas turbine with heat recovery followed by desulfurization, and a third case of a SCC followed by desulfurization before the heat recovery, thereby producing power from the exothermic desulfurization reaction. Energy calculations of the last case show promising results for converting sulfur to anhydrite through a combined cycle that produces 615 MW of electrical power with CO 2 emission of 0.584 kg/kWh, a value lower than the representative value of a new, supercritical coal power plant.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.181
Teacher spread0.177 · 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 designBench or experimental
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

Citations2
Published2016
Admission routes2
Has abstractyes

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