A review of heat‐transfer mechanism for solid deposition from “waxy” or paraffinic mixtures
Bibliographic record
Abstract
Abstract Summarized in this review are a large number of experimental and modelling studies for advancing the heat‐transfer‐based mechanism for solid deposition from “waxy” or paraffinic oils and mixtures. This comprehensive heat‐transfer approach is entirely different from a more popular molecular‐diffusion mechanism. It has evolved from numerous publications, over three decades, which explored topics related to thermodynamic, rheological, crystallization, solid deposition, and shutdown and deposit‐aging behaviour of prepared multicomponent paraffinic mixtures of varying compositions to simulate “waxy” crude oils. These investigations covered a wide range of compositions, temperatures, and cooling rates—under static, sheared, laminar and turbulent conditions—in both the hot and cold flow regimes. The heat‐transfer mechanism for wax deposition is based on (partial) freezing or liquid‐to‐solid phase transformation process, for which steady‐state and unsteady‐state mathematical models have been developed and validated with extensive laboratory data. Furthermore, a shear‐induced deformation model for the deposit aging phenomenon has been developed and validated; it is based on a partial release of the liquid phase from the incipient gel, thereby causing an enrichment of heavier alkanes and a corresponding depletion of lighter alkanes in the deposit. A successful analogy with the ice deposition process has confirmed the wax deposition process to be also controlled by heat transfer, without involving any other mechanism for wax deposition. All of these previous studies confirm that wax deposition is predominantly a thermally driven process.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".