CFD simulation of annular oil flow wrapped with water
Bibliographic record
Abstract
Abstract The transport of heavy oil in tubes is energy intensive since the oil viscosity can reach values of 10 500 000 cP. This study focuses on the transport of oil in a piping system by an annular flow of oil wrapped with water, since this alternative reduces head loss. The piping system was comprised of horizontal tubes, curves, and vertical tubes. The assumptions for the CFD simulation were the following: 3D geometry, turbulent flow, and isothermal system as well as incompressible, steady‐state, and transient flow. A mesh convergence study was carried out. The residue for pressure and velocity dropped at least three orders of magnitude. The inter‐phase‐slip Algorithm (IPSA), algebraic slip model (ASLP), scalar equation method (SEM), and Phoenics models were applied to calculate the interaction between the phases. Turbulence was modelled with default k‐ϵ and k‐ω models and the LES strategy by using a Smagorinsky sub‐grid scale model. The density profiles generated in the CFD simulation were compared with experimental data and a resemblance was observed. The transient simulation showed a swirling flow that was experimentally observed, which was a result of synergy of multiphase flow, horizontal tube, curve, and vertical tube.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".