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Record W4312361286 · doi:10.4050/f-0077-2021-16727

S-97 RAIDER® Wake-Empennage Interaction Fight Data and Correlation

2021· article· en· W4312361286 on OpenAlexaff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsAerodynamicsWakeRotor (electric)Computer scienceAerospace engineeringComputational fluid dynamicsRange (aeronautics)Flight testPropulsionCoaxialSimulationEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

A combination of experimental and analytical methods has been applied to study the aerodynamic interaction of the S-97 RAIDER® coaxial main rotor and its wake on an empennage. The primary goal was to characterize the periodic aerodynamic forcing from the rotor on the horizontal stabilizer over a wide range of flight conditions, and use those data to develop and validate computational fluid dynamics (CFD) methods that can then be applied to optimize future designs. The flight test aircraft was instrumented with 29 unsteady pressure sensors and flown for speed sweeps from 20 to 180 kts as well as a range of maneuvers. The data were processed to provide both unsteady and time-averaged aerodynamic forces and moments. Two CFD codes were then applied: HELIOS/RCAS using discrete main rotor and propulsor blades and STARCCM+ using a recently developed unsteady virtual blade model. Both codes captured the trends of the flight test data and agreed that the vibratory aerodynamic forcing on the empennage was not particularly large. The flight data were also compared with previously acquired powered wind tunnel model data, and showed good agreement. Finally, the Sikorsky GenHel flight dynamics model was applied to level flight and maneuver conditions, and the match was also acceptable. This study has that current state-of-the-art methodology, carefully applied, can capture complex aerodynamic interactions with sufficient accuracy for aircraft design, and that this implementation of X2 Technology™ does not result in unacceptable rotor on empennage interactions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.016
GPT teacher head0.233
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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