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Record W2330212396 · doi:10.1021/ef502640p

Inorganic Matter Behavior during Coal Gasification: Effect of Operating Conditions and Particle Trajectory on Ash Deposition and Slag Formation

2015· article· en· W2330212396 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnergy & Fuels · 2015
Typearticle
Languageen
FieldEngineering
TopicIron and Steelmaking Processes
Canadian institutionsUniversity of Alberta
FundersCanadian Centre for Clean Coal/Carbon and Mineral Processing Technologies
KeywordsSlag (welding)Deposition (geology)CoalFly ashParticle (ecology)Particle depositionViscosityMetallurgyParticle sizeMaterials scienceMineralogyCoal gasificationChemistryRange (aeronautics)Composite materialGeology

Abstract

fetched live from OpenAlex

Ash particle deposition and uncontrolled slag flow, which can lead to tap hole blockage, are some of the main issues during coal gasification. In this work, a special collector probe was used to collect ash deposition and analyze slag formation and blockage probability in terms of operating conditions and particle trajectories. Increasing the temperature led to the increase in the total deposition for all of the experiments. However, when the temperature was increased, the weight of produced slag flow increased, but it was observed that increasing the temperature could not guarantee the safe operation by preventing deposition blockage. Using two Canadian coal types proved that the ash composition of coal has a significant effect on the amount and thickness of deposition on the wall. For fuel with low ash viscosity, increasing the temperature increased slag flow and blockage never happened. However, for fuel with high bulk ash viscosity, when the temperature was increased, the blockage probability did not decrease. The reason might be related to the different effects of the temperature on particle stickiness and slag viscosity at a specific range of the temperature. Computer-controlled scanning electron microscopy (CCSEM) analysis showed that excluded iron-bearing minerals of the first coal and included calcium-bearing minerals of the second coal had a substantial effect on the deposition tendency of these fuels. Increasing the velocity of the particles by gas flow rate mostly resulted in reduction of deposition. Fuel with a higher particle size range at a low temperature and high gas flow has the lowest deposition tendency. To evaluate the effect of particle trajectory/aerodynamics, two different types of feeding configurations were used and the results showed that the feeder type has a significant effect on the deposition pattern and growth at different locations. One feeder by injecting the particles in a narrow area led to high inorganic accumulation near the feeding spot, resulting in severe depositions with a thickness of several centimeters. The other feeder caused more uniform deposition by producing a wider sticky surface with a lower deposition thickness on the wall of the furnace.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.298

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 head0.221
Teacher spread0.212 · 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