Full Vehicle Helios Model Performance Correlation with SB1 Defiant Flight Test
Bibliographic record
Abstract
Full vehicle CREATE-AV™ Helios model has been developed for SB>1 Defiant®, a Joint-Multi-Role Technology Demonstrator (JMRTD) designed by the Sikorsky-Boeing team utilizing compound design with coaxial rotor and propulsor. The full vehicle model includes coupling with RCAS for elastic blade deformation as well as full vehicle trim in steady level flight condition. The purpose of current study is to assess performance prediction capability of the developed Helios modeling approach for such a complex non-traditional design by correlating with flight test data. To minimize uncertainty in flight test data reduction, correlations were made with the data that were directly measured or requiring minimal derivation. The Helios model showed generally very good correlation in power, component forces, rotor and propulsor efficiencies for wide range of flight test conditions. The model also showed very good correlation in performance sensitivity to trim state and rotor RPM, which demonstrates the modeling approach can be used to find optimal flight trim condition. Significance of geometric details and its aerodynamic interference such as shaft modeling has been demonstrated. Impact of measurement uncertainty to data correlation was also demonstrated.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".