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Investigation of Hydrogen and Methane Production from Flue Gas Released from the Steel Industry

2021· article· en· W3188937960 on OpenAlexaff
Merve Öztürk, İbrahim Dinçer

Bibliographic record

VenueEnergy & Fuels · 2021
Typearticle
Languageen
FieldEngineering
TopicChemical Looping and Thermochemical Processes
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsFlue gasMethaneCombustionHydrogen productionHydrogenChemistryBrayton cycleEnvironmental scienceWaste managementNuclear engineeringThermodynamicsHeat exchangerOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

This paper concerns a potential multigeneration system where the flue gas is generated to be utilized for power, hydrogen and methane production, and an additional subsystem where the blending of 20% hydrogen into the methane is accomplished for residential usages. The proposed system mainly involves combined Brayton and organic Rankine cycles, water–gas shift reactor, Sabatier reactor, and combustion chamber. The Aspen Plus simulations are performed for the development and assessment of the presented multigeneration system. When the flue gas temperature is 815 °C, the work rate generated is 41.6 MW. As another beneficial output, the Sabatier reactor’s CH4 production rate is 0.26 kg/s, and a part of it is sent to blend with hydrogen at amolar fraction of 0.20 in the blend for household applications. It is observed that when combustion temperature of the blend increases from 800 °C to 1200 °C, the CO2 emissions decrease from 2.63 kmol/h to 1.42 kmol/h, and the net released heat from the combustion reactor decreases from 1175 kW to 944 kW. Furthermore, the overall energetic and exergetic efficiencies of the system are calculated as 52.1% and 68.9%, 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)0.000
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 score0.011
Threshold uncertainty score0.304

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 head0.014
GPT teacher head0.194
Teacher spread0.180 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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