The velocity field characteristics of high‐viscosity fluids falling film flow down clamped channels
Bibliographic record
Abstract
Abstract The complexity of falling film flow has been studied in many industrial applications. In this work, the velocity field of high‐viscosity fluids falling film flow down clamped channels was investigated numerically and experimentally. The results show that the numerical simulation results are consistent with the experimental results, and the characteristics of the velocity field are related to the fluid properties, operating conditions, and structure of the clamped channels. When the fluid viscosity is greater than or equal to 10 Pa ⋅ s, the type of velocity field changes into I shape, U shape, and V shape. While the fluid viscosity drops to 0.89 Pa ⋅ s, the viscous force cannot resist the inertial force and gravity, resulting in a cardioid velocity field. By adjusting the structure of the clamped channels and operating conditions, the tension of the liquid film can be changed, and the velocity distribution of the liquid film can be manipulated. Significantly, under the fluctuating curtain flow, the liquid film coalesces and breaks frequently, which enlarges the surface area of the liquid film and strengthens the surface renewal frequency. Hence, this form of falling film flow can be applied to process intensification of high‐viscosity materials.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".