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Record W3011026595 · doi:10.55632/pwvas.v91i1.573

Reynolds-Averaged Navier-Stokes (RANS) simulation of a staged pressurized oxy-coal combustion (SPOC)

2019· article· en· W3011026595 on OpenAlexfundno aff
Gideon Ozioma Udochukwu, Akkerman V’yacheslav

Bibliographic record

VenueProceedings of the West Virginia Academy of Science · 2019
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsnot available
FundersCanada Excellence Research Chairs, Government of CanadaU.S. Department of Energy
KeywordsCoalReynolds-averaged Navier–Stokes equationsCombustorCombustionCoal combustion productsNuclear engineeringWaste managementChemistryEnvironmental scienceMechanicsThermodynamicsEngineeringComputational fluid dynamicsPhysics

Abstract

fetched live from OpenAlex

Staged pressurized oxy-coal combustion (SPOC), which is a promising technology being developed at the Washington University at St. Louis (WUSTL) aiming to be used for low-cost, low-emission, high-efficiency power generation, is investigated numerically using the ANSYS Fluent commercial package. The modelling supports the WUSTL experimental endeavors in a 100 kW lab-scale reactor, with 90% of energy coming from the coal and 10% originating from methane-air combustion. To be specific about the burner design, carbon dioxide is injected alongside the coal, for its carriage. In addition, a small amount of methane is also injected alongside the coal to maintain a steady flame. Steady and unsteady Reynolds-Averaged Navier-Stokes (RANS) simulations are performed resulting in an asymmetric flame shape. We propose several potential causes of such a flame asymmetry including peculiarities of the coal injection and the onset of the shear-layer instability occurring because the densities and velocities of the mixing streams. As a result, an influence of the presence of coal on the flame symmetry is demonstrated. In addition, a benchmark at which the further increase of coal would result in flame asymmetry has been found.This work is performed in cooperation with the Washington University at St. Louis (WUSTL). It is sponsored by the US Department of Energy (DoE) through the US-China Clean Energy Research Center – Advanced Coal Technology Consortium (CERC-ACTC).

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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