MétaCan
Menu
Back to cohort
Record W1984271777 · doi:10.1021/ie0611913

Inline Bitumen Emulsification Using Static Mixers

2007· article· en· W1984271777 on OpenAlexaff
Jean-Philippe Gingras, Louis Fradette, Philippe A. Tanguy, Jacques Bousquet

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2007
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsEmulsionStatic mixerAsphaltPressure dropDrop (telecommunication)Materials scienceVolumetric flow ratePulmonary surfactantSpecific energyChromatographyComposite materialChemistryChemical engineeringAnalytical Chemistry (journal)MechanicsThermodynamicsViscosityMechanical engineeringOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Highly concentrated bitumen-in-water emulsions were produced with static mixers in continuous mode. The effect of the following process parameters on the average droplet size was studied: emulsion flowrate, static mixers configuration, and surfactant concentration as well as bitumen hardness, concentration, and temperature. Several static mixer configurations were investigated consisting of combinations of SMX (Sulzer Chemtech Ltd.) and helical elements with empty sections. The drop size results revealed that the mean droplet size could be scaled with the energy or the power draw depending on the static mixer configuration. Moreover, it was shown that the energy draw could capture the effect of emulsion flowrate and bitumen concentration on the mean droplet size, whereas the power draw (or the specific power) captured the effect of the emulsion flowrate and bitumen temperature. It was also demonstrated that the specific energy, or pressure drop, was minimized when SMX mixers were inserted after helical mixers.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.043
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.001
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 head0.129
GPT teacher head0.373
Teacher spread0.244 · 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

Citations27
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueIndustrial & Engineering Chemistry ResearchSame topicPetroleum Processing and AnalysisFrench-language works237,207