Parallel Computing Strategy for a 3D Hybrid Unstructured Navier-Stokes Solver
Bibliographic record
Abstract
A parallel computing strategy for a 3D hybrid unstructured Navier-Stokes solver has been developed. The Navier-Stokes equations are solved by a face based finite volume method which is suitable for arbitrary mesh type. The Spalart-Allmaras one-equation turbulence model is implemented to evaluate the turbulent viscosity. Parallel computation is based on the domain decomposition method and load balance is achieved by using METIS system. The Message Passing Interface (MPI) library routines are utilized to pass information between processors and non-blocking communications are used to minimize the communications overhead. The dynamic allocation feature of FORTRAN 90 is fully exploited to reduce the memory requirement. Finally the parallel code is applied to simulation of viscous flow around the DLR-F6 geometry(wing-body-pylon-nacelle) to validate its accuracy, high parallel performance and the ability to deal with complex geometries.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".