A multiphase lattice Boltzmann method for simulating immiscible liquid-liquid interface dynamics
Bibliographic record
Abstract
The simulation of immiscible liquid–liquid interface dynamics using the lattice Boltzmann method is studied in this work. The capabilities of the proposed model are investigated and validated with the inclusion of an external forcing term, e.g. the force of gravity . Fundamental tests are performed to further validate the performance of the method for computing multiphase flows . Four theoretical test cases are studied: (1) two-phase Poiseuille flow with variable density and viscosity ratios; (2) two-phase flow subject to hydrostatic pressure ; (3) two-dimensional bubble dynamics; and (4) capillary-gravity wave. The four test cases provide clear quantitative results. In particular, the results of the proposed formulation for the test case with two-dimensional bubble dynamics are compared with the results of three different finite element methods . We found that the proposed lattice Boltzmann method is consistent with these standard approaches, and that the relative standard deviation between all codes is less than 1% for several flow quantities. Most of the test cases in this study use real liquid properties for the dimensionless density and viscosity ratios. In this context, the real immiscible liquids are mercury, water, and hexane. In addition, a final application test case is studied, where a hexane bubble under gravity is initially trapped inside a structured pore that is completely water-wet. A methodology using the bisection method to find the critical Bond number for which the transition from a trapped to a non-trapped bubble occurs is proposed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".