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Record W2897747592 · doi:10.1016/j.ifacol.2018.09.399

Three-Phases Dynamic Modelling of Column Flotation Process

2018· article· en· W2897747592 on OpenAlexaff
Yahui Tian, Maryam Azhin, Xiaoli Luan, Fei Liu, Stevan Dubljević

Bibliographic record

VenueIFAC-PapersOnLine · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDiscretizationNonlinear systemPartial differential equationDiscrete systemApplied mathematicsMathematicsTransformation (genetics)Hyperbolic partial differential equationContinuous modellingDiscrete modellingMathematical analysisAlgorithmPhysics

Abstract

fetched live from OpenAlex

In this work, a three-phases discrete dynamic model of column flotation which accounts for the interface and froth regions is developed. The system is described by transport hyperbolic nonlinear partial differential equations (PDEs). The steady state profiles are utilized to linearize the original nonlinear system. The Cayley-Tustin time discretization transformation is applied to the linear hyperbolic PDEs system and maps the continuous infinite dimensional system to a discrete infinite dimensional system without spatial discretization. The final discretized model is structure preserving and does not imply any model reduction. Discrete model dynamics are compared with high fidelity numerical simulations of continuous linearized model in order to demonstrate applicability of the proposed discrete model development.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.026
GPT teacher head0.299
Teacher spread0.273 · 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 designSimulation or modeling
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

Citations15
Published2018
Admission routes1
Has abstractyes

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