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Record W4386141824 · doi:10.3390/min13091115

Dense Medium Cyclone Separation of Fine Coal: A Discussion on the Separation Lower Limit

2023· article· en· W4386141824 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMinerals · 2023
Typearticle
Languageen
FieldEngineering
TopicCyclone Separators and Fluid Dynamics
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaUniversity of AlbertaNatural Science Foundation of Shanghai
KeywordsCyclone (programming language)Separation (statistics)CoalSettlingLimit (mathematics)Environmental scienceProcess engineeringMechanicsMeteorologyComputer scienceWaste managementEnvironmental engineeringPhysicsEngineeringMathematics

Abstract

fetched live from OpenAlex

The separation of fine coal has been widely discussed in the coal preparation industry due to its high economic potential. Dense medium cyclone (DMC) is the most efficient equipment available for fine coal separation. However, the industrial application of DMC is far from satisfactory due to operational difficulties and maintenance. In this research, particle settling behavior in a dense medium cyclone was analyzed for improved separation. The calculation result about feed pressure and separation lower limit, which fits the experimental data well, might be a guidance for industrial DMC design and operation. According to the calculation result, it is highly recommended that the separation lower limit be set at 0.2 mm rather than 0.1 mm, because the feed pressure head required for the latter (50 D) is three times higher than the former (15 D).

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.379

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 head0.016
GPT teacher head0.264
Teacher spread0.248 · 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