Effect of Rheological Properties of Yield Pseudoplastic Fluids on Slugs Characteristics in an Upward Vertical Pipe: Experiments and Modeling
Bibliographic record
Abstract
Abstract Two-phase flow of gas/yield Pseudoplastic fluids can be found in different industrial applications like the chemical processes, oil industry, and petroleum transport in pipelines. In this study, experimental and numerical investigation of the influence of Rheological properties of non-Newtonians fluids in two-phase flow (gas/yield Pseudoplastic fluids) on slug characteristics in an upward vertical flow were performed. Different concentrations of Xanthan gum solutions (0.05%, 0.10%, and 0.15%, by w/w), which are referred to as non-Newtonian, yield Pseudoplastic behavior used as the working liquids and air as a gas. The experiments were conducted in an open-loop re-circulating system has a total length of 65 m to ensure phase mixing, and authorize flow regime patterns to develop. The vertical pipe has a diameter of 76.3 mm. API-compliant 8-speed rotational viscometer model 800 was used to measure the rheological properties of non-Newtonian fluids. Flow visualization and recording videos were achieved by A high-speed camera to a comparison between behavior of Newtonian and non-Newtonian fluids in the two-phase model. Pressure transducers used to measure high-response pressure. Computational fluid dynamics software (ANSYS fluent 2019 R3) was used for the numerical investigation. The volume of fluid (VOF) model has been chosen for tracking immiscible fluids. CFD simulation results compared to the experimental data. The slug behavior and shape were noticed to be affected by changing the rheological properties of the liquid phase. with increasing XG concentration at the same operations conditions, we found that non-uniform and random distribution of small bubbles due to the effective viscous force of a liquid phase.
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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 | 0.000 | 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) | 0.000 | 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".