Introduction to a Novel Approach for Modeling Wax Deposition in Fluid Flows. 1. Taylor−Couette System
Bibliographic record
Abstract
A novel approach for modeling wax deposition in fluid flows is developed. Particle diffusion and inertia, shear removal, molecular diffusion, shear dispersion, and aging are considered as possible mechanisms in the wax deposition process. Among these mechanisms, particle diffusion/deposition plays the most significant role in formation of the deposit at the realistic transport conditions. The model parameters are estimated using some experimental data obtained by the organic solids deposition cell (OSDC) that was designed based on the Taylor−Couette system. The model predictions are then compared with the deposition data at other conditions. The effect of each parameter on the model predictions is also discussed. The estimated model parameters can then be used in the pipeline deposition model to predict the deposition rates under actual flow conditions in production and transportation pipelines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".