Aerodynamic Computations Using the Convective-Upstream Split-Pressure Scheme with Local Preconditioning
Bibliographic record
Abstract
The implementation of the convective-upstream-split-pressure (CUSP) approach to numerical dissipation is presented for an approximately factored algorithm in conjunction with time-derivative local preconditioning. An inexpensive flux limiter is used to blend the low- and high-order CUSP dissipation to capture shocks without oscillations. The resulting algorithm is applied to several subsonic and transonic turbulent aerodynamic flows and compared with results computed using the matrix dissipation scheme. Grid convergence studies are used to assess global errors. The results show the CUSP scheme to be very effective in providing good shock capturing, low numerical dissipation in boundary layers, and low numerical errors. For the flow regimes studied, accuracy is not significantly compromised when the limiter is based on the pressure variable only, leading to significant savings in computational expense. For freestream Mach numbers below 0.2, the convergence rate and accuracy of the solver are significantly improved by preconditioning the CUSP scheme. Overall, the CUSP scheme provides accuracy similar to that of matrix dissipation at a reduced computational cost.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".