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Record W2887442882 · doi:10.36487/acg_rep/1363_11_yuan

Development of success criteria for high density fluid fine tailings flocculation in the oil sand industry

2013· article· en· W2887442882 on OpenAlexaboutno aff
Xuehong Yuan, Barry Bara, Renato Ribeiro Siman

Bibliographic record

VenuePaste/˜Pœaste · 2013
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsFlocculationCentrifugeDewateringTailingsFast Fourier transformMaterials scienceLift (data mining)Process engineeringEnvironmental scienceGeotechnical engineeringEngineeringComputer scienceEnvironmental engineeringMetallurgyPhysics

Abstract

fetched live from OpenAlex

Syncrude Canada Ltd. is currently developing multi-pronged technologies to treat its legacy fluid fine tailings (FFT). FFT centrifugation, thin-lift and thick-lift (Accelerated Dewatering with rim ditch) are three key technologies. They all require proper mixing and flocculation of high density FFT with a polymeric flocculant. It was found that the previously developed criteria to determine the flocculation performances for the well-diluted tailings systems used in thickeners were not valid for the flocculation of high density FFT due to high viscosity of FFT. The success criteria for high density FFT flocculation were identified as a technical gap that must be closed before FFT centrifuge commercialisation. This paper deals with the development of the success criteria to benchmark the mixing and flocculation performances of high density FFT. The instruments and methodologies used to determine the success criteria will be presented and discussed. It was concluded that four criteria, i.e. yield stress, capillary suction time (CST), lab centrifuge index and visual floc structures of the flocculated materials, were successfully established to determine the performances of high density FFT flocculation. These four criteria are all related to each other. Yield stress indicates the strength of the flocculated material, CST shows the relative dewatering capacity, the lab centrifuge index quickly determines the processibility of solids-liquid separation at a given centrifugal force and time, and the floc structures visually demonstrate the floc sizes and networks. In general, for a good flocculation the flocculated material exhibits a higher yield stress, a lower CST, a clearer centrifuge centrate, and a larger visual floc size. They are just vice versa for a poor flocculation of high density FFT. A few case studies will be used to verify the applicability of the four criteria for high density FFT flocculation. These criteria have been used to gauge the FFT flocculation performances in Syncrude 2010 and 2011 FFT centrifuge pilot tests.

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 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 score0.168
Threshold uncertainty score0.548

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 head0.015
GPT teacher head0.250
Teacher spread0.235 · 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 teacher head, 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

Citations0
Published2013
Admission routes1
Has abstractyes

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