CVFEM for Multiphase Flow with Disperse and Interface Tracking, and Algorithms Performances
Bibliographic record
Abstract
A Control-Volume Finite-Element Method (CVFEM) is newly formulated within Eulerian and spatial averaging frameworks for effective simulation of disperse transport, deposit distribution and interface tracking. Their algorithms are implemented alongside an existing continuous phase algorithm. Flow terms are newly implemented for a control volume (CV) fixed in a space, and the CVs' equations are assembled based on a finite element method (FEM). Upon impacting stationary and moving boundaries, the disperse phase changes its phase and the solver triggers identification of CVs with excess deposit and their neighboring CVs for its accommodation in front of an interface. The solver then updates boundary conditions on the moving interface as well as domain conditions on the accumulating deposit. Corroboration of the algorithms' performances is conducted on illustrative simulations with novel and existing Eulerian and Lagrangian solutions, such as (-) other, i. e. external methods with analytical and physical experimental formulations, and (-) characteristics internal to CVFEM.
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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".