<scp>CFD</scp> analysis of blade coating from a reservoir onto a horizontal substrate using a homogeneous two‐phase model
Bibliographic record
Abstract
Abstract A two‐phase numerical analysis is performed of two‐dimensional, laminar, liquid flow from a reservoir onto a horizontal, rigid, moving substrate. The homogeneous two‐phase model in commercial CFD code CFX is used to model the liquid plus a region containing both liquid and air near the phase interface and downstream of the blade region. Slow convergence due to surface tension modelling required initialization from intermediate results omitting surface tension. Comparisons made with two previous numerical analyses demonstrate the performance of this approach. For a particular upstream reservoir geometry, the effects of changing the substrate speed and the liquid properties from a Newtonian fluid to a Carreau‐Yasuda non‐Newtonian fluid on the pressure field and the downstream film height are studied. The details of the liquid recirculation in the reservoir and the overall pressure distribution are discussed. New results are presented for the meniscus position and contact angle, which are fully predicted by the two‐phase approach. The meniscus position was strongly influenced by substrate speed and liquid properties, whereas the contact angle did not change significantly with changes in substrate speed and dynamic viscosity for the Newtonian fluid nor with changes in the functional parameters for the non‐Newtonian fluid.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".