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Record W4402680801 · doi:10.4050/f-0080-2024-1176

Wind Tunnel Testing of X2 Technology Spinning Coaxial Hubs with Aspirated Inlets – Comparison Between Two Wind Tunnel Models and with CFD

2024· article· en· W4402680801 on OpenAlexaff
Dylan Dziuba

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsWind tunnelInletComputational fluid dynamicsCoaxialSpinningMarine engineeringEnvironmental scienceAerospace engineeringEngineeringMechanicsPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

A two-phase wind tunnel test was conducted to evaluate aerodynamic performance on a 1/5th scale model of the Sikorsky/Boeing X2™ technology representative aircraft for Future Vertical Lift (FVL). The test program provided valuable aerodynamic data for two important elements of the design: the faired coaxial hub system and the main inlet flow leading to the engine interface. Studies from previous X2™ technology aircraft have shown that hubs, pylons and sail fairings have strong interactions, and if well integrated can lead to low drag aircraft designs. Rotorcraft main inlets generally have aggressive turns; therefore, this inlet design was investigated for distortion and total pressure loss. Accuracy of modeling these aerodynamic interactions using Computational Fluid Dynamics (CFD) and other forms of computational aerodynamic assessment requires supporting empirical testing for validation. The two wind tunnel facilities used in Phase 1 and 2 offered different and unique advantages compared to each other, which allowed the Sikorsky/Boeing team to generate a large, complementary aerodynamic and propulsion database for comprehension as well as simulation validation.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.289
Teacher spread0.244 · 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 teacher head, not a consensus.

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
Published2024
Admission routes1
Has abstractyes

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