Bibliographic record
Abstract
The large temperature gradients experienced by crude oil emulsions in pipelines found in colder environments can lead to the precipitation, deposition and build-up of wax-like species from the crude oil onto the pipe wall that result in flow assurance problems. The objective of this thesis was to understand the rheological behaviour of model water-in-oil emulsions stabilized by wax crystals. The microstructure, phase transitions and rheology of model emulsions constisting of water, mineral oil, parrafin wax and the emulsifier polyglycerol polyricinoleate (PgPr) were investigated. Changes in emulsion flow begaviour (steady state and dynamic) as a function of composition, termperature and passage through a laboratory-scale flowloop were investigated, with these parameters significantly affecting shear flow, yield stress and viscoelasticity. The gelation temperature of wax-containing ('waxy') oil was slightly lower than that of its equivalent emulsion due to differences in the structure of the gelled emulsion network. Overall, this study successfully showed that there exist significant differences in the microstructure and flow behaviour of model crude oil emulsions when wax and a dispersed aqueous phase are present.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".