Simulation of droplet dynamics in an inclined channel considering contact angle hysteresis using the cascade lattice Boltzmann method
Bibliographic record
Abstract
Modeling droplet dynamics on solid surfaces with rough or chemically heterogeneous walls is crucial in various industrial applications. In such cases, the downstream and upstream contact lines of the droplet usually move incongruously, leading to droplet deformation known as the contact angle hysteresis (CAH) phenomenon. In this work, we developed a cascaded multicomponent Shan–Chen lattice Boltzmann method to simulate droplet dynamics considering the CAH. Specifically, the Peng–Robinson equation of state is added to one component to improve the density ratio of the model. By modifying the fluid–fluid interaction force scheme, we achieve thermodynamic consistency and independent adjustment of the surface tension. We also implement the modeling of CAH by applying geometric wetting boundaries with a hysteresis window. Based on this model, we first simulated pinned droplets in inclined channels with different hysteresis windows. We obtain the critical tilt angle of the droplet at the onset of sliding, which agrees with the theoretical result. For sliding droplets in the inclined channel, our results reveal that a slight tilt angle is unfavorable for the upstream portion of the droplet sliding, while a large tilt angle is favorable for the entire droplet sliding. A small receding angle results in a large droplet deformation at the quasi-steady state. Finally, by periodically transitioning between different hysteresis windows, enabling exclusive sliding of the upstream contact line during the first half period and subsequent sliding of the downstream contact line during the second half period, we successfully observed the stick-slip phenomenon of the droplet.
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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".