MétaCan
Menu
Back to cohort
Record W174418009 · doi:10.17077/etd.93fnz13i

An investigation of the combustion of oil sand derived bitumen-in-water emulsions

2009· dissertation· en· W174418009 on OpenAlexaboutno aff
Timothy Robert Kennelly

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsAsphaltPetroleum engineeringCombustionEnvironmental scienceOil sandsWaste managementEngineeringChemistryMaterials scienceComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Dwindling conventional oil resources has caused exploration efforts to focus elsewhere. Bitumen from oil sands has emerged as one of the primary unconventional oil resources in use today. Quadrise Canada Corporation has harnessed this unconventional oil by developing their bitumen-in-water emulsion known as MSAR (Multi-Phase Superfine Atomized Residue). Fuel-in-water emulsions are linked to a combustion phenomenon known as micro-explosion, which are associated with an increase in combustion efficiency and decrease in harmful emissions. A study has been conducted of the MSAR fuel to help advance the optimization and modeling of its use in spray combustors so as to best harness the potential. Quantitative and qualitative data has been obtained during combustion experiments of the fuel that will attribute to this end. Additionally, a simplified statistical model is presented based on the governing equations to describe the atomization that occur as a result of micro-explosions of the MSAR fuel as well as a simple model to represent internal force needed for a micro-explosion to occur. The results of this study continue to reinforce the understanding that micro-explosions cannot be attributed to one overriding physical principal, but rather are th result from variations in turbulent, dynamic, and thermal forces.

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 score0.285
Threshold uncertainty score0.431

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 head0.006
GPT teacher head0.214
Teacher spread0.208 · 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
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicCombustion and flame dynamicsFrench-language works237,207