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Record W4236531835 · doi:10.5383/ijtee.08.02.006

Some Aspects of the Rheological Behaviour of Coal Water Slurries

2014· article· en· W4236531835 on OpenAlexvenueno aff
Sunita Panda, R Swain, Igit Sarang

Bibliographic record

VenueInternational Journal of Thermal and Environmental Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicCoal Combustion and Slurry Processing
Canadian institutionsnot available
Fundersnot available
KeywordsRheologySlurryCoal waterCoalMaterials scienceEnvironmental sciencePetroleum engineeringWaste managementEngineeringComposite material

Abstract

fetched live from OpenAlex

Initially coal-slurry fuels were based on coal-oil mixtures.Now the emphasis is largely on coal-water fuels.Since most of the studies have been done with coals available in the western countries having low ash content, an attempt has been made in this paper to study some aspects of the rheological behaviour of coal slurries prepared out of coals having high ash content.Crisis in the volatile oil markets experienced in the seventies have promoted renewed interest in coal-based fuel technologies.Coal-slurry fuels have emerged as viable technical alternatives for oil and gas in utility and industrial boilers.Despite current low prices and the abundance of oil, concerns over its long-term availability and price, as well as strategic considerations make coal-slurry technology attractive.In this paper an empirical relationship has been established among apparent viscosity and volume fraction of solids for coal having high ash content.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.174
Teacher spread0.169 · 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 source (direct Gemma or distilled Codex), 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
Published2014
Admission routes1
Has abstractyes

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Same venueInternational Journal of Thermal and Environmental EngineeringSame topicCoal Combustion and Slurry ProcessingFrench-language works237,207