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Record W3155127739

The Generation of Extremely Fine Water-in-Bitumen emulsions via the Satellite Drop Formation Mechanism

2018· dissertation· en· W3155127739 on OpenAlexfundno aff
Anas Ettahiri

Bibliographic record

VenueTSpace · 2018
Typedissertation
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of TorontoSyncrude
KeywordsDrop (telecommunication)Mechanism (biology)SatelliteAsphaltEnvironmental scienceMeteorologyPetroleum engineeringProcess engineeringEngineeringMaterials scienceAerospace engineeringMechanical engineeringPhysicsComposite material
DOInot available

Abstract

fetched live from OpenAlex

This thesis is concerned with the generation of fine water-in-bitumen emulsions through drop fracture during the bitumen froth treatment process. Due to their negative economic and environmental impact, the stability of these emulsions has received tremendous attention; however, little work has been conducted on the manner through which they form. In this study, we use a novel microfluidic platform to study the satellite drop generation mechanism via drop fracture. Using this technique, satellite drops several orders of magnitude smaller than the mother drop were generated and characterized. The smallest satellite drops observed were below 2μm in radius. The range of satellite. The effects of industrially relevant parameters, namely, water pH, solvent dilution and capillary number, are investigated. The satellite drop volume and number of drops were found to increase with the capillary number and dilution while process water pH was found to have a smaller effect.

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 score0.074
Threshold uncertainty score0.536

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 head0.018
GPT teacher head0.275
Teacher spread0.257 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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