Hydrodynamics of Gas–Liquid Cocurrent Flows in Micropacked Beds—Wall Visualization Study
Bibliographic record
Abstract
An inverted microscopy technique was implemented to scrutinize the wall-region hydrodynamics of gas–liquid cocurrent flows in micropacked beds. Digital image analysis enabled characterization of two contiguous flow regimes, hysteresis, and transition thereof. Low- and high-interaction regimes featuring, respectively, slow and rapid displacements of gas–liquid boundary were identified. The onset of regime changeover was delineated by distinguishing the fluctuating behavior in time of characteristic lengths extracted from the areas occupied by gas and liquid in the field of view. A Charpentier and Favier flow regime map demarcating low and high interaction regimes in conventional macroscale trickle beds was elaborated for the sake of comparison of micropacked bed transitions for three different gas–liquid systems (air–water, argon–water, and argon–sucrose solution). The flow regime map suggests that micropacked bed transition occurs at considerably lower L / G values. Manifestation of hysteresis in micropacked beds was apprehended via pressure drop measurements and wetting fraction determination both in imbibition and drainage modes. In agreement with macroscale packed bed observations, the drainage branch revealed a larger pressure drop and wetting fraction compared with the imbibition branch for the same set of bed and fluid flow rates.
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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) | 0.000 | 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) | 0.001 | 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".