A computational Lagrangian–Eulerian advection remap for free surface flows
Bibliographic record
Abstract
Abstract A VOF‐based algorithm for advecting free surfaces and interfaces across a 2‐D unstructured grid is presented. This algorithm is based on a combination of a Computational Lagrangian–Eulerian Advection Remap and the Volume of the Fluid method (CLEAR‐VOF). A set of geometric tools are used to remap the advected shape of the volume fraction from one cell onto the Eulerian fixed unstructured grid. The geometric remapping is used to compute the fluxes onto a group of neighbouring cells of the mesh. These fluxes are then redistributed and corrected to satisfy the conservation of mass. Here, we present methods for developing identification algorithms for surface cells and incorporating them with CLEAR‐VOF. The CLEAR‐VOF algorithm is then tested for translation of several geometries. It is also incorporated in a finite element based flow solver and tested in a laminar flow over a broad‐crested weir and a turbulent flow over a semi‐circular obstacle. Copyright © 2004 John Wiley & Sons, Ltd.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".