Anisotropic Non-Uniform Block-Based Adaptive Mesh Refinement for Three-Dimensional Inviscid and Viscous Flows
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Bibliographic record
Abstract
A parallel anisotropic block-based adaptive mesh refinement (AMR) algorithm is proposed to describe the solution of physically complex flow problems with disparate spatial and temporal scales exhibiting highly anisotropic features on three-dimensional multi-block body-fitted hexahedral meshes with non-uniform grid blocks. Instead of using a classical uniform treatment for the computational cells of each block within the multi-block grids, the proposed anisotropic AMR scheme adopts a non-uniform representation of the cells within each block. With the former approach, all of the cells for a given block are forced to be at the same resolution, including both interior and ghost cells containing solution information from neighboring blocks. In such a uniform representation, various techniques are required to evaluate the solution in the ghost cells and ensure flux conservation at block interfaces with such a uniform representation. The proposed non-uniform approach directly uses the neighboring cells as the ghost cells, even at a grid resolution change, and this affords a number of computational advantages. A modified upwind finite-volume spatial discretization scheme is applied in conjunction with the AMR scheme to the solution of Euler and Navier-Stokes equations for inviscid and viscous compressible gaseous flow. Steady-state and time-varying flow problems are considered on anisotropic adapted meshes. The potential flexibility and efficiency of this enhanced anisotropic AMR scheme are demonstrated for the simulation of flows of varying complexity.
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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 it