Solids Deposition during “Cold Flow” of Wax−Solvent Mixtures in a Flow-loop Apparatus with Heat Transfer
Bibliographic record
Abstract
“Cold flow” refers to the pipeline flow of a “waxy” crude oil at a temperature, which is below its wax appearance temperature (WAT) and above its pour point temperature (PPT), whereby precipitated wax crystals remain suspended in the flowing crude oil. It has been suggested as an alternative technology for decreasing solids deposition (Merino-Garcia, D.; Correra, S. Pet. Sci. Technol . 2008, 26, 446). An experimental investigation was undertaken to study solids deposition under cold flow in a flow-loop apparatus, incorporating a small double-pipe heat exchanger. The experiments were performed using 3 and 6 mass % mixtures of a petroleum wax dissolved in Norpar13 (a paraffinic solvent comprising C 9 −C 16 ) at different wax−solvent mixture temperatures, T h, and two flow rates over a deposition time of 1 h. Two sets of deposition experiments were performed: cold flow with {WAT ≥ T h > PPT} and “hot flow” with { T h > WAT}. The deposit mass decreased with a decrease in wax concentration and with an increase in the coolant temperature. However, the deposit mass decreased with a decrease in the mixture temperature, under cold flow, but it increased with a decrease in the mixture temperature, under hot flow. Also, the deposit mass, under cold flow, was not affected by flow rate. Predictions from a pseudosteady-state heat-transfer model were in good agreement with experimental results, indicating the deposition process to be thermally driven. The liquid−deposit interface temperature in all cases was equal to the WAT of the liquid phase. Variations in both the wax content and the carbon number distribution in deposit samples are discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".