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Record W2044300731 · doi:10.1155/2007/48238

Modelling of the Separation Process in a FerrohydrostaticSeparator Using Discrete Element Method

2007· article· en· W2044300731 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.

Bibliographic record

VenuePhysical Separation in Science and Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsDe Beers (Canada)
Fundersnot available
KeywordsAlgorithmComputer science

Abstract

fetched live from OpenAlex

This paper presents a model of the separation process in a ferrohydrostatic separator (FHS) which has been designed and developed at DBGS, De Beers, South Africa. The model was developed using special discrete element method software package called Particle Flow Code in 3D (PFC 3D ). Special attention has been paid to the selection of the simulation parameters in order to achieve the required feed rates. The simulation was carried out using spherical particles and density tracers of different sizes and densities ranging between 0.004 and 0.008 m and 2700 and 3800 kg/m 3 , respectively. The tracers were used to set the apparent density of the ferrofluid (the cut‐point) and to provide a measurement of the efficiency of the separation. The model is replacing the ferrofluid by imposing a drag force on the particle. The results of the simulation were presented in the form of the distribution of the density tracers into the sink fraction. These results are realistic and show the advantages of DEM to understand the complex flow behavior of granular materials.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.338

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 studies0.0000.000
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 head0.031
GPT teacher head0.350
Teacher spread0.319 · 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