Bibliographic record
Abstract
Computation of multiphase flows including boiling flows is one of the most challenging problems in CFD.Discontinuities in fluid properties, in addition to flow variables at the interface, lead to challenges in getting an accurate estimate of the gradients at the fluid-fluid interface with reasonable accuracy.Further, with a diffuse approach like VoF (Volume-of-Fluid) or Level-Set, solution accuracy requires a careful choice of reconstruction scheme to limit interface diffusion."Diffuse" approach here refers to interface capturing schemes vs. Lagrangian type schemes like the markerparticle method.Several interface reconstruction schemes like PLIC (Piecewise Linear Interface Construction), HRIC (High-Resolution Interface Capturing Scheme), VoF with height functions exist within the VoF framework that offer different levels of interface capturing accuracy.A one-cell thick moving interface is implemented to model the interface location and orientation using a VoF framework.Since the accuracy of the interface depends on grid resolution, a dynamic octree grid is employed to keep computational cost reasonable.After the interface is advected, volume fraction data is passed to a geo-reconstruct scheme on unity aspect ratio computational cells, which is consistent with the reconstruction algorithm.This approach is applied to several cases including Rayleigh Taylor instability, vortex in a box test and the Enright deformation test to demonstrate both the accuracy and the efficiency of the implementation.It is demonstrated that thin-filaments can be resolved as the Rayleigh Taylor instability grows with time leading to self-similarity.The accuracy of resolving thin filaments for the vortex in the box test case and Enright deformation test are similar to that of Particle-level set method of Fedkiw's group..
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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".