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Record W3201343160 · doi:10.11575/prism/38799

Viscosity and Stability of Visbroken Fractionated Oils

2021· dissertation· en· W3201343160 on OpenAlexaboutno aff
Amirabbas Abbaspourmehdiabadi

Bibliographic record

VenuePRISM (University of Calgary) · 2021
Typedissertation
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsViscosityStability (learning theory)ThermodynamicsChemistryChromatographyPetroleum engineeringPhysicsEngineeringComputer science

Abstract

fetched live from OpenAlex

One challenge facing Western Canada is the limited capacity to transport bitumen through pipelines. Bitumen has a high density and viscosity that both exceed pipeline specifications. It must be diluted for transport, but the diluent occupies a capacity that would otherwise be available for the bitumen. One possible solution is to reduce the amount of diluent by decreasing the density and viscosity of the bitumen through a combination of de-asphalting and visbreaking processes. Visbreaking reduces the viscosity of the oil, however, if carried too far, this process can destabilize the oil (cause asphaltene precipitation and coke formation). De-asphalting decreases the oil density and can allow more intensive visbreaking without destabilizing the oil. These processes can be applied to both bitumen and vacuum bottom feeds. In all cases, it is necessary to predict the product properties and stability to optimize the process design. This thesis aims to measure and model the effect of visbreaking on the density, viscosity, and stability of a bitumen, a vacuum bottom, and a de-asphalted oil. Each oil was visbroken at two different severities (combinations of temperature and residence time) in an in-house continuous visbreaker. The feeds and their products were separated into distillates, saturates, aromatics, resins, and asphaltenes, and the properties (molecular weight, density, viscosity, and solubility) of each fraction were measured. Previously developed correlations for molecular weight, density model parameters, viscosity model parameters, and solubility parameters were updated. The density of the oils was determined with a volumetric mixing rule and their viscosity with the Expanded Fluid viscosity model. Their stability versus asphaltene precipitation was determined with the Modified Regular Solution phase equilibrium model. The average deviation of the modelled densities and viscosities were 2 kg/m³ and 19%, respectively. The average deviation in the modelled onset of asphaltene precipitation (solvent content at which precipitation first occurred) was 4.4 wt% n-heptane. The average deviation of the modeled asphaltene yield (mass of precipitated asphaltenes divided by the mass of feed oil) was 2.3 wt%.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.079
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.195
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), 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
Published2021
Admission routes1
Has abstractyes

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