NSMB contribution to the 2nd High Lift Prediction Workshop
Bibliographic record
Abstract
A numerical analysis of the flow on the DLR-F11 high lift model in landing configuration is presented within the context of the 2 High Lift Prediction Workshop. The objective is to describe the flow state and characterize the numerical parameters influencing the solution. The NSMB flow solver is used for this purpose, both in steady and unsteady Reynolds-Averaged Navier-Stokes modes. The geometry used is the simplified model (without bracket and bundle). In addition to a grid convergence study, efforts concentrated on the effect of grid size, turbulence model, initialization scheme in the steady flow regime, and to unsteady flow effects. In particular, additional data points to the ones required for the workshop were added in the stall region to further the understanding of the physical phenomena in play. The results show that loss of lift can occur via separate phenomena, one at the wing root, and the other at the wing tip. It also highlights the necessity of performing unsteady flow simulations, since steady flow cannot be achieved for this class of flow problems.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.010 |
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".