SB>1 Defiant® Wind Tunnel Test CFD Validation
Bibliographic record
Abstract
Current paper summarizes a correlation study of two flow solvers (CREATETE-AV Helios and Simcenter STAR-CCM+), routinely used at Sikorsky, with multiple model-scale wind-tunnel tests. The Helios modeling approach was aiming for a high-fidelity accurate simulation, whereas the STAR-CCM+ modeling approach was aiming for a fast turn-around time with reasonable solution accuracy with a relatively coarse mesh and simplifications. The two solvers generally agreed well with the test data within reasonable accuracy and captured the airloads and flowfield trends. The calculations presented herein show the impact of the turbulence model on component loads, the aerodynamic interactions among components, and the effect of transition modeling on rotor performance. The Reynolds-Averaged Navier-Stokes CFD model generally delayed separation and resulted in lower drag. By modeling the airframe supporting structure in CFD simulations, an improvement on correlation for inflow on the propeller plane was shown. Additionally, improvements in the rotor system L/De correlation were realized by including a turbulence-transition model, which reduces the rotor drag.
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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 | 0.001 |
| 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 | 0.001 |
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 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".