A Lagrangian finite volume method for the simulation of flows with moving boundaries
Bibliographic record
Abstract
In this paper a Lagrangian formulation of the Natural Element Method (NEM) is proposed to solve shallow water inviscid flows. NEM is a particle‐based method which revealed its capabilities in handling large distortion problems. Its main advantage is the interpolant character of its shape function and consequently the easiness of imposing Dirichlet boundary conditions.In this paper we use the NEM method in a collocation form and in a Lagrangian kinematic description. This formulation is found to be a finite volume methodology with flux computation on the Voronoï diagram of the standard triangular or quadrilateral meshes. The Shallow‐Water equations are used as the mathematical model. Besides the Lagrangian behavior of the flow which is difficult to capture, these equations have discontinuous solutions. Thus, stabilization issues have been considered. Some inviscid bidimensional flows are used as preliminary benchmark tests. This kind of flows is similar to that of metal casting. Good results were found which promise an interesting future for this method in more complicated applications.
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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".